Genetic dissection of disease resistance to Phoma medicaginis in Medicago truncatula
This thesis is submitted to Murdoch University for the degree of Doctor of Philosophy
by
Lars Gian Kamphuis MSc
The Australian Centre for Necrotrophic Fungal Pathogens, Division of Health Sciences, SABC, Murdoch University July, 2007
Supervised by: Dr Simon R. Ellwood and Professor Richard P. Oliver
i
Declaration and list of published papers
I declare that this thesis is my own account of my research and contains as its main content work which has not been previously submitted for a degree at any tertiary education institute.
Papers that have been published from the research described in this thesis are:
Ellwood S.R., Kamphuis L.G. and Oliver R. P. (2006). Identification of sources of resistance to Phoma medicaginis isolates in Medicago truncatula SARDI core collection accessions, and multigene differentiation of isolates. Phytopathology 96 1330-1336.
Kamphuis L. G., Williams A.G., D’Souza N.K., Pfaff T, Ellwood S.R., Groves E.J., Singh K.B., Oliver R.P. and Lichtenzveig J. (2007). The Medicago truncatula reference accession A17 has an aberrant chromosomal configuration. New Phytologist 174: 299-303.
Kamphuis L. G., Lichtenzveig J., Oliver R. P. and Ellwood S. R. (2008). Two alternative trait loci correlate with resistance to spring black stem and leaf spot in Medicago truncatula. BMC Plant Biology submitted.
……………………….
Lars Gian Kamphuis
ii ABSTRACT
Phoma medicaginis is a necrotrophic fungal pathogen, commonly found infecting Medicago truncatula and M. sativa in temperate regions of Australia.
To identify, characterize and differentiate eight P. medicaginis isolates from
Western Australia, morphological phenotypes and five gene regions (actin, β- tubulin, calmodulin, internal transcribed spacer, translation elongation factor 1-α) were examined. Sequence comparisons showed that specimens isolated from M. truncatula in Western Australia formed a group that was consistently different from, but closely allied to, a P. medicaginis var. medicaginis type specimen.
Characterization of three P. medicaginis genotypes showed that all exhibited a narrow host range, causing disease only in M. sativa and M. truncatula among eight commonly cultivated legume species sampled. Infection of 85 M. truncatula accessions showed a continuous distribution in disease phenotypes, with the majority of accessions susceptible. Differences in disease phenotypes suggest that M. truncatula harbours specific and diverse sources of resistance to individual P. medicaginis genotypes.
To characterize the genetic basis of resistance to P. medicaginis two F2 populations derived from crosses between the resistant accession SA27063 and the susceptible accessions SA3054 and A17 were phenotyped for disease symptoms. Highly significant recessive QTLs for resistance to P. medicaginis
OMT5 were identified in each mapping population. In SA27063 x A17 a QTL named resistance to the necrotroph Phoma medicaginis one (rnpm1) was identified on the short arm of LG4. In SA27063 x SA3054 a QTL (rnpm2) was identified on the long arm of LG8. Further fine mapping of the areas surrounding the QTLs is underway to identify the genes underlying rnpm1 and rnpm2.
iii Examination of the recombination frequencies between genetic markers on the long arms of chromosomes 4 and 8 in the SA27063 x A17 cross revealed an apparent genetic linkage between these chromosomes. Subsequent analysis of other crosses showed this unexpected linkage relationship is characteristic for genetic maps derived from A17. Furthermore F1 individuals derived from crosses involving A17 showed 50% pollen viability or less. This semisterility and the unexpected linkage relationships provide good evidence for a reciprocal translocation in A17 between chromosomes four and eight. The implications of the distinctive chromosomal rearrangement in A17 on genetic mapping, genome sequencing and comparative mapping are discussed.
The Mt16kOLI1plus microarray was used to identify transcriptional changes in M. truncatula expressed in defence against P. medicaginis. Three- hundred-and-thirty-four differentially expressed transcripts showed a change of two-fold or more in either the resistant or susceptible interaction, and most of the
Phoma-regulated genes could be assigned to functional categories which have been reported to be involved in plant defence responses. RT-qPCR and HPLC-
UV confirmed involvement of the octadecanoid and phenylpropanoid pathways in response to P. medicaginis infection. Faster induction of lipoxygenase genes and constitutively higher levels of certain phenolic metabolites were observed in resistant plants.
iv ABBREVIATIONS
4CL 4-coumarate CoA ligase ACC 1-aminocyclopropanecarboxylic acid synthase BAC bacterial artificial chromosome BGL β-1,3-glucanase bp base pairs CA4H cinnamic acid 4-hydroxylase CCOMT Caffeoyl CoA O-methyltransferase cDNA complementary DNA Chit chitinase CHI chalcone isomerase CHR chalcone reductase CHS chalcone synthase cm centimetre(s) COMT caffeic acid O-methyltransferase
CT theshold cycle DMSO dimethyl sulfoxide DNA deoxyribonucleic acid dNTP deoxyribonucleotides (ie.dATP, dCTP, dGTP, dTTP) EDTA ethylenediaminetetraacetic acid ERF Ethylene Responsive Element Binding Factor EST expressed sequence tag ET ethylene F5H ferulate-5-hydroxylase g gram(s) GOI gene of interest HPLC high performance liquid chromatography hpi hours post infection hr(s) hour(s) HSD honestly significant difference IFMT Isoflavone O-methyl transferase IF2H Isoflavone 2'-hydroxylase IF3H Isoflavone 3'-hydroxylase IFR Isoflavone reductase IFS Isoflavone synthase ITS internal transcribed spacer JA jasmonic acid L litre(s) LOX lipoxygenase MeJA methyl jasmonate γ⎧ microgram(s) mg milligram(s) min minute(s)
v μL microlitre(s) m metre(s) mL milliliter(s) mM millimolar mm millimetre(s) mol mole mRNA messenger RNA MS mass spectrometre ng nanogram(s) nm nanometre(s) OPR 12-oxophytodienoic acid 10, 10-reductase ORF Open Reading Frame o/n over night PAL phenylalanine ammonia lyase PCR polymerase chain reaction PDA potato dextrose agar PDF plant defensin pH potential of hydrogen PIGs Phoma induced genes PR protein pathogenesis related protein PRG Phoma repressed genes RNA ribonucleic acid RNAi RNA interference RNase ribonuclease ROI reactive oxygen intermediates ROS reactive oxygen species RT room temperature RT retention time reverse transcriptase quantitative polymerase chain RT-qPCR reaction SA salicylic acid SAR systemic acquired resistance SDS sodium dodecyl sulfate TC Tentative consensus TE Tris EDTA TF transcription factor UV ultra violet VR vestitone reductase WMA wheat meal agar
vi ACKNOWLEDGEMENTS
I would like to start by thanking Professor Richard Oliver for giving me the opportunity to come over to Perth and commence my PhD with the
Australian Centre for Necrotrophic Fungal Pathogens (ACNFP). I greatly appreciated the constant support, mentoring and guidance throughout my PhD of my two supervisors Prof Richard Oliver and Dr Simon Ellwood. Over the last four years Simon was my partner in crime on the Phoma project and I am positive that our work together will ultimately lead to the cloning of resistance genes to Phoma medicaginis in M. truncatula.
Special thanks to my good friends and colleagues Dr Theo Pfaff and Dr
Judith Lichtenzveig for your support during my PhD. Your opinions and suggestions on my research have proven invaluable and have had a good influence on me as scientist. Wherever your research careers might take you, I am sure we will stay in touch!
I am also grateful to my fellow medic PhD students Nola and Angela and
Dr Huyen Phan for their input, encouragement and ideas on my work and the many laughs we have had in the “medic office”. I would also like to thank Emma and Megan for taking good care of the laboratory and glasshouse, without you two the “medic lab” would not be the same. Without the input of all “medics” the translocation paper (see chapter 6) would not have come together. I would also like to thank the remaining members of the ACNFP, for their help in one way or another. The friendly working environment and Friday afternoon drinks with the group will be missed. I would also like to thank the GRDC for funding this research project.
vii To my sister Esmé, who has always provided me constant love and support, I am forever grateful. To my parents, Anja and Jan, you sacrificed much to provide me with the quality of life and helped me become the scientist and person I am today. This thesis is dedicated to you both with love and thanks for all you have done throughout my life. Your visit to Perth put a smile on my face and I promise that we will regularly visit you in Holland now that I am no longer
“a poor student”.
To my best friend Jeroen Werij, thanks heaps. The many phone conversations and your visit to Perth were greatly appreciated and were welcome distractions from my PhD. We will stay in touch no matter where our science careers will take us!
Finally, I wish to thank my beautiful girlfriend Fiona for taking this journey with me. Your love, humour and patience throughout my PhD helped me through the tough times. I am looking forward to a long and happy future together!
viii TABLE OF CONTENTS
Declaration and list of published papers...... ii
ABSTRACT...... iii
ABBREVIATIONS ...... v
ACKNOWLEDGEMENTS...... vii
TABLE OF CONTENTS...... ix
LIST OF FIGURES ...... xvi
LIST OF TABLES ...... xix
Chapter 1 General introduction ...... 1
1.1 Historical background ...... 1
1.2 Importance of legumes in agriculture ...... 2
1.3 Pathogens and their impact on Australian legume agriculture...... 4
1.4 The host of study: Medicago truncatula Gaertn ...... 5
1.4.1 Medicago truncatula as a model plant ...... 5
1.4.2 Medicago truncatula and comparative mapping ...... 7
1.4.3 Medicago truncatula as a host for fungal pathogens ...... 8
1.5 The pathogen of study: Phoma medicaginis...... 10
1.5.1 Phoma medicaginis causal agent of black stem and leaf spot in
annual Medicago species...... 10
1.5.2 Phoma medicaginis taxonomy ...... 11
1.5.3 The Phoma medicaginis lifecycle...... 11
1.5.4 Advances in Phoma medicaginis research...... 12
1.6 Plant disease-resistance genes ...... 14
ix 1.6.1 Resistance genes to fungal necrotrophs ...... 19
1.7 Plant-pathogen recognition complexes...... 20
1.8 Production of antimicrobial molecules ...... 21
1.9 Plant defence signalling networks ...... 24
1.9.1 The role of salicylic acid in disease resistance ...... 24
1.9.2 The role of jasmonates in disease resistance...... 25
1.9.3 The role of ethylene in disease resistance...... 27
1.9.4 Crosstalk between the signalling pathways in pathogen defence .28
1.10 Regulation of plant defence by transcription factors ...... 30
1.11 Aims of the project...... 32
Chapter 2 General materials and methods...... 34
2.1 General materials...... 34
2.1.1 Plant material ...... 34
2.1.2 Fungal isolates ...... 34
2.2 General methods ...... 35
2.2.1 Plant cultivation ...... 35
2.2.2 Fungal isolation and culture...... 37
Chapter 3 Identification and differentiation of Phoma medicaginis isolates present in Australia based on morphology and sequences from five conserved gene regions ...... 39
3.1 Introduction...... 39
3.2 Material and Methods...... 41
3.2.1 Fungal isolates ...... 41
3.2.3 DNA isolation of fungal isolates...... 41
x 3.2.4 PCR amplification and DNA sequencing of five conserved gene
regions ...... 42
3.2.5 Phylogenetic analyses...... 44
3.2.6 Plant material and growth ...... 45
3.2.7 Plant inoculation to determine host range...... 45
3.3 Results ...... 46
3.3.1 Growth behaviour and morphology in vitro...... 46
3.3.2 DNA sequencing ...... 49
3.3.3 Phylogenetic analyses...... 52
3.3.3 Host-range...... 55
3.4 Discussion...... 55
Chapter 4 Screening of the core Medicago truncatula collection with three different Phoma medicaginis isolates...... 60
4.1 Introduction...... 60
4.2 Material and methods...... 61
4.2.1 Plant material, fungal isolates and inoculum preparation...... 61
4.2.2 Plant inoculations...... 61
4.2.2.1 Whole plant sprays...... 62
4.2.2.2 Whole plant spot inoculation of leaves...... 63
4.2.2.3 Detached leaf assay ...... 66
4.2.3 Statistical analysis of disease score data...... 67
4.3 Results ...... 67
4.3.1 Comparison of the different inoculation methods...... 67
4.3.2 Evaluation of disease resistance to P. medicaginis in the M.
truncatula core collection...... 70
xi 4.4 Discussion...... 77
Chapter 5 Recessive quantitative trait loci confer resistance to spring black stem and leaf spot in Medicago truncatula...... 79
5.1 Introduction...... 79
5.2 Material and Methods...... 81
5.2.1 Mapping populations and growth conditions...... 81
5.2.2 Inoculation procedures and resistance evaluation...... 81
5.2.3 Statistical analysis of the disease resistance data ...... 82
5.2.4 Identification of polymorphic DNA markers ...... 83
5.2.5 Genotyping and linkage analysis ...... 84
5.2.6 Cytology of the M. truncatula-P. medicaginis pathosystem...... 86
5.3 Results ...... 87
5.3.1 Macroscopic phenotype of resistant and susceptible accessions...87
5.3.2 Microscopic disease symptoms of P. medicaginis...... 88
5.3.3 Resistance to Phoma medicaginis OMT5 in accession SA27063 in
two different mapping populations ...... 91
5.3.4 Identification of polymorphisms and genetic linkage mapping....93
5.3.5 QTL mapping of spring black stem and leaf spot resistance in M.
truncatula ...... 99
5.4 Discussion...... 101
Chapter 6 The Medicago truncatula reference accession A17 has an aberrant chromosomal configuration ...... 106
6.1 Introduction...... 106
6.2 Materials and Methods...... 108
xii 6.2.1 Accessions and hybrids...... 108
6.2.2 Pollen viability of intraspecific hybrids ...... 108
6.2.3 Genetic maps...... 109
6.3 Results ...... 110
6.3.1 Hybrids derived from A17 are semi-sterile ...... 110
6.3.2 Genetic maps derived from A17 reveal new linkage relationships
...... 110
6.3.3 Reduced fertility and abnormal seedling phenotypes in SA27063 x
A17 F2 individuals ...... 112
6.4 Discussion...... 116
Chapter 7 Expression profiling of Medicago truncatula infected with Phoma medicaginis reveals involvement of the octadecanoid and phenylpropanoid pathway in defence against this foliar necrotroph...... 119
7.1 Introduction...... 119
7.2 Materials and Methods...... 121
7.2.1 Plant materials and growth conditions ...... 121
7.2.2 Inoculation procedures and resistance evaluation...... 121
7.2.3 RNA isolation...... 122
7.2.4 Cy-labelling of hybridization targets, hybridization and image
acquisition...... 123
7.2.5 Analysis of image data from microarray hybridization ...... 124
7.2.6 cDNA synthesis, primer design and qRT-PCR ...... 125
7.2.7 Metabolite analysis...... 127
7.2.7.1 Chemicals...... 127
7.2.7.2 Metabolite extraction...... 127
xiii 7.2.7.3 HPLC-UV instrumentation...... 128
7.3 Results ...... 129
7.3.1 Microarray analysis of transcriptional changes in foliar tissue
upon infection with P. medicaginis 12 hours post infection...... 134
7.3.2 Induction of genes diagnostic of the salicylic acid and jasmonic
acid defence signalling pathways upon P. medicaginis infection ...... 146
7.3.3 Induction of genes involved in the phenylpropanoid pathway upon
P. medicaginis infection...... 154
7.3.4 Transcriptional changes in the phenylpropanoid pathway upon P.
medicaginis infection lead to an increased abundance of metabolites in
this pathway...... 164
7.4 Discussion...... 174
Chapter 8 General discussion, future directions and conclusion ...... 183
REFERENCES...... 192
APPENDIX ...... 1
Appendix 01 PCR markers used to generate a genetic map of an F2 population between SA27063 and SA3054...... 2
Appendix 02 PCR markers used to generate a genetic map of an F2 population between SA27063 and A17...... 7
Appendix 03 Differentially expressed transcripts showing a ≥ 2-fold activation ratio 12 hours post infection (hpi) with P. medicaginis OMT5 ....10
Appendix 04 Differentially expressed transcripts showing a ≥ 2-fold repression ratio 12 hours post infection (hpi) with P. medicaginis OMT5 ...15
Appendix 05 Genes and primer sequences used for RT-qPCR ...... 20
xiv Appendix 06 Gene families of the phenylpropanoid pathway and their RT- qPCR primer sequences ...... 21
Appendix 07 Expression profiling of genes in the phenylpropanoid pathway in response to Phoma medicaginis OMT5 in resistant (SA27063) and susceptible (SA3054) M. truncatula accessions...... 25
xv LIST OF FIGURES
Figure 1.1 Phylogeny of legumes featuring three major subfamilies and details
about selected (agriculturally important) crop species in the Papilionoideae,
their estimated chromosome number and genome size...... 3
Figure 1.2 Representation, localisation and structure of the five main classes of
disease resistance proteins...... 17
Figure 3.1 Colony morphology of P. medicaginis isolates from M. truncatula, 12
days after plating on ½ PDA...... 48
Figure 3.2 Amplification of EF-1-α PCR products...... 50
Figure 3.3 Alignment of EF-1-α sequence between P. medicaginis var.
medicaginis CBS 316.90 and the Australian Phoma isolates sharing
common intron sequences...... 51
Figure 3.4 Phylogram of one of nine most parsimonious trees based on nuclear
DNA ITS sequence data...... 53
Figure 3.5 Single most parsimonious phylogram of P. medicaginis isolates based
on actin, β-tubulin, and EF-1α sequence data...... 54
Figure 3.6 Macroscopic disease symptoms on M. truncatula and M. sativa 7 dpi
with P. medicaginis...... 56
Figure 4.1 Macroscopic disease symptoms of spray inoculated leaves...... 64
Figure 4.2 Macroscopic disease symptoms of spot inoculated leaves...... 65
Figure 4.3 Position of M. truncatula accessions used for comparing the various
screening methods on relatedness scale...... 69
Figure 4.4 Comparison of three different screening methods to look for
differential responses to P. medicaginis isolates (WAC4736, 4741 and
OMT5) in 10 M. truncatula accessions...... 72
xvi Figure 4.5 Statistical analyses of the phenotype data of the M. truncatula core
accessions...... 73
Figure 4.6 3D-scatter plot of the mean disease scores to three P. medicaginis
genotypes for 85 M. truncatula accessions...... 76
Figure 5.1. Macroscopic disease symptoms of P. medicaginis OMT5...... 89
Figure 5.2 Microscopic analysis of P. medicaginis infection of M. truncatula...90
Figure 5.3. Macroscopic disease symptoms of P. medicaginis OMT5 on F1
hybrids of SA27063 x SA3054...... 92
Figure 5.4 Statistical analyses of the F3 phenotype data...... 94
Figure 5.5 Length polymorphisms are mapped by virtue of their inherent
fragment size differences between the parental alleles...... 95
Figure 5.6a Genetic map of SA27063 x SA3054 population, based on 94 F2
individuals...... 97
Figure 5.6b Genetic map of SA27063 x A17 population, based on 92 F2
individuals...... 98
Figure 5.7 Quantitative trait loci (QTLs) associated with resistance to P.
medicaginis OMT5 in M. truncatula ...... 100
Figure 6.1 Pollen viability of M. truncatula intraspecific hybrids. (a) Proportion
of non-aborted pollen grains...... 111
Figure 6.2 Matrices of neighbourhood frequencies displaying the best marker
order associated with M. truncatula chromosomes 4 or/and 8...... 113
Figure 6.3 Germination phenotypes in F2 individuals derived from SA27063,
SA3054 and A17...... 115
Figure 7.1 Macroscopic disease symptoms of M. truncatula accessions SA27063
and SA3054 ten days post infection with P. medicaginis OMT5...... 130
xvii Figure 7.2 Differential expression of genes representing the salicylic acid or
jasmonic acid/ethylene defence signalling pathway in foliar tissue of mock
inoculated control and Phoma medicaginis inoculated SA27063 and
SA3054 plants...... 131
Figure 7.3 Differentially expressed transcripts showing a ≥ 2-fold change in
abundance 12 hours post infection (hpi) with P. medicaginis OMT5 ...... 136
Figure 7.4 Classification of 191 genes found to be at least 2-fold induced in M.
truncatula upon infection with P. medicaginis OMT5 12 hpi...... 138
Figure 7.5 Classification of 147 genes found to be at least 2-fold repressed in M.
truncatula upon infection with P. medicaginis OMT5 12 hpi...... 145
Figure 7.6 Regulation of genes representing the salicylic acid signalling pathway
upon P. medicaginis OMT5 inoculation of foliar tissue of SA27063 and
SA3054...... 147
Figure 7.7 Schematic illustration of the octadecanoid pathway ...... 150
Figure 7.8 Regulation of genes representing the octadecanoid pathway upon
mock or P. medicaginis OMT5 inoculation of foliar tissue of SA27063 and
SA3054...... 151
Figure 7.9 Schematic illustration of the phenylpropanoid pathway (adapted from
Dixon et al 2002)...... 155
Figure 7.10 Regulation of genes representing the isoflavonoid pathway upon
mock or P. medicaginis OMT5 inoculation of foliar tissue of SA27063 and
SA3054...... 158
Figure 7.11 Abundance of metabolites in M. truncatula accession SA27063 and
SA3054 mock inoculated and inoculated with P. medicaginis OMT5 over a
period of 72 hours...... 167
xviii LIST OF TABLES
Table 1.1 Fungal species and oomycetes causing a differential response among
M. truncatula accessions...... 9
Table 1.2 Recognized families of pathogenesis-related proteins...... 23
Table 2.1 Fungal isolates from legume species used in this thesis...... 36
Table 3.1 Primer name and sequences to study five conserved gene regions in
Phoma species...... 43
Table 3.2 Morphological features of Phoma isolates from M. truncatula and
virulence tests...... 47
Table 4.1. Evaluation of 85 SARDI M. truncatula accessions for resistance to
three genotypes of P. medicaginis...... 74
Table 6.1. Average number of seeds per pod and percentage of abnormal
phenotypes of F2 individuals of seed derived from SA27063 x A17,
A17xSA27063, SA27063 x SA3054 and SA3054 x SA27063...... 114
Table 7.1 Overview of the results obtained from P. medicaginis infection
profiling...... 135
Table 7.2 Genes induced upon infection with P. medicaginis OMT5 of the
ethylene and jasmonic acid biosynthesis pathways and genes where
products have anti-microbial properties...... 139
Table 7.3 Differentially expressed transcription factors upon P. medicaginis
OMT5 infection...... 140
Table 7.4 Genes of the phenylpropanoid pathway induced upon infection with P.
medicaginis OMT5...... 143
Table 7.4 Metabolites of the phenylpropanoid pathway their retention times and
maximum absorbances as identified by HPLC-DAD ...... 165
xix Chapter 1 General introduction
1.1 Historical background
The first traces of agriculture were found in the Middle East and date from 6000
BC, when humans started to cultivate barley and wheat together with the domestication of animals. Compared to hunting and collecting, agriculture was a more reliable way to secure food supplies. However, as described in ancient writings, including the bible, agriculture was affected by all kinds of pests and diseases. It was not until the invention of the light microscope by Anthonie van
Leeuwenhoek that people became aware of the microorganisms causing these diseases. In the early 1700s the first genera of fungi were described (Agrios,
1997). Kuhn wrote the first book on plant pathology, in which he described that plant diseases are caused either by an unfavourable environment or by parasitic organisms such as insects, fungi and parasitic plants (Kuhn, 1858). The first techniques to isolate and grow plant pathogens in a laboratory were described by
Koch and resulted in Koch’s postulates to which a mircoorganism must comply to be classified as the cause of a plant disease. Plant disease resistance breeding originated a century ago, when Biffen applied the Mendel’s laws of inheritance to breed rust resistance in cereal crops (Biffen, 1905).
Over the last few decades the interaction between plants and microbial pathogens through the exchange of signal molecules has been the focus of intensive research. In the following paragraphs legume crops and their diseases will be introduced followed by the host (Medicago truncatula) and pathogen
(Phoma medicaginis) of this study, before an overview of disease resistance to fungal pathogens.
1
1.2 Importance of legumes in agriculture
Legumes (Fabaceae) are a diverse and important family of angiosperms.
With more than 700 genera and 20,000 species, legumes are the third largest family of higher plants, behind orchids (Orchidaceae) and asters (Asteraceae) and the second most important economically. Classically legumes (the family of the Leguminosae) are divided into three subfamilies: Caesalpinioideae,
Mimosoideae and Papilionoideae. Most cultivated legumes are found within the
Papilionoideae (Doyle and Luckow, 2003; Young et al., 2003: Figure 1.1). Seeds of legumes such as peanut, soybeans, chickpeas, and lentils contain from 20 to 50 percent protein, two to three times that of cereal grains and meat. Legumes are also grown since they are a good source of vegetable oil, which is used as cooking and industrial oil. In recent studies, legumes were found to produce secondary compounds, beneficial for human health, providing protection against human cancers and cardiovascular disease (Anderson and Major, 2002; Barnes,
1997; Guillon and Champ, 2002; Madar and Stark, 2002; Mathers, 2002;
Rizkalla et al., 2002). Furthermore, legumes are used as fodder and forage crop for animals.
In 1866 Gregor Mendel published a groundbreaking study of the inheritance of traits in the legume pea (Pisum sativum), now known as the
Mendel’s laws of heredity (Mendel, 1866). Nowadays legumes are perhaps most well-known for their unique capability to enter a nitrogen-fixing endosymbiosis with bacteria of the Rhizobium family (Geurts et al., 2005; Hirsch et al., 2001).
They also form a symbiotic relationship with mycorrhizal fungi and both
2 Figure 1.1 Phylogeny of legumes featuring three major subfamilies and details about selected (agriculturally important) crop species in the Papilionoideae, their estimated chromosome number and genome size. Adapted from Young et al.,
2003.
3 interactions have been studied intensively (Geurts et al., 2005; Harrison, 1998,
2005; Hirsch et al., 2001; Stacey et al., 2006). Thus, legumes are a major source of organic fertilizer and are commonly used in agricultural rotations. Grain legumes are estimated to contribute an additional $600 million per annum in value to the Australian cereal industries through their roles in nitrogen fixation and disease control. Despite their great importance in agriculture, most cultivated legumes are not well suited for genomic analysis due to large and complex genomes. For this reason researchers are increasingly focussing on legume models, such as Medicago truncatula Gaertn.
1.3 Fungal pathogens and their impact on Australian legume agriculture
Cereal, pulse and oilseed production in Australia and world-wide is subject to major losses caused by fungal pathogens. The single most important constraint in Australian legume agriculture is disease caused by necrotrophic fungal pathogens. Fungal necrotrophs induce cell death and maceration of host- tissue and cause losses in broad acre crops in Australia valued at $170 million per annum. The major necrotrophic pathogens in Australian legume agriculture are:
Ascochyta spp., causing blight of chickpea;
Botrytis spp., causing chickpea grey mould and chocolate spot of faba bean;
Colletotrichum gloeosporioides, causing lupin anthracnose;
Colletotrichum trifolii, causing stem anthracnose and crown rot in lucerne;
Fusarium oxysporum, causing Fusarium wilt in chickpea;
Phoma medicaginis, causing spring black stem and leaf spot on Medicago species;
4 Phytophthora medicaginis, causing root rot in chickpea;
Pleiochaeta setosa, causing brown spot of lupin.
Necrotrophic diseases in legumes are generally not well controlled by resistant cultivars, with a few exceptions such as resistance to Ascochyta blight in chickpea (Singh and Reddy, 1996). Resistance to necrotrophs is complex and often dependent on one or a few (quantitative) resistance genes. Necrotrophic pathogens are generally well controlled by modern fungicides, but many consider that chemicals are uneconomic and environmentally undesirable. Therefore, it is quite clear that more resistant cultivars and better control strategies need to be developed.
1.4 The host of study: Medicago truncatula Gaertn
1.4.1 Medicago truncatula as a model plant
Medicago truncatula, also known as the barrel medic, is native to the
Mediterranean basin and has spontaneously naturalised in Australia. In Australia annual medics are grown and bred to improve pastures and as a break crop in rotation with cereals on some 50 million hectares (Crawford et al., 1989).
Medicago lies within the Galegoid group of temperate legumes, which includes the genera Melilotus, Trifolium, Pisum, Vicia, Sesbania and Lotus, and within the
Trifolieae, subfamily Papilionoideae (Doyle, 2001). The first systematic collections of Medicago spp. were made in Australia and the South Australian
Research and Development Institute (SARDI) maintains the largest worldwide collection of Medicago accessions from the Mediterranean basin, with over 5000 accessions, thus being a great source of genetic variability (Ellwood et al.,
5 2006b; Skinner et al., 1999). M. truncatula is an excellent model system for legume biology (Cook, 1999; Frugoli and Harris, 2001; Oldroyd and Geurts,
2001; Young et al., 2003) for the following reasons:
1) M. truncatula is a diploid (2n = 16) with a relatively small genome (~450
Mbp).
2) It reproduces almost exclusively by selfing and therefore shows high homozygosity.
3) It has a fast generation time (from seed-to-seed).
4) Its genome is being sequenced, using a BAC-by-BAC strategy to efficiently sequence the M. truncatula genespace (Cannon et al., 2005; Town, 2006; Young et al., 2005: http://www.medicago.org genome/index.php ).
5) Comprehensive, dense genetic maps have been generated by several laboratories resulting in a composite Medicago map now containing over 2,000
DNA markers (Choi et al., 2004a; Eujayl et al., 2004; Gutierrez et al., 2005;
Mun et al., 2006; Thoquet et al., 2002).
6) M. truncatula has several large public EST databases containing over 250.000
ESTs: TIGR MtGI, (Cannon et al., 2005; Quackenbush et al., 2001; 2000: http://www.tigr.org/tdb/tgi/mtgi), MENS, (Journet et al., 2002: http://www.medicago.toulouse.inra.fr/Mt/EST ) and MtDB, (Lamblin et al.,
2003: http://www.medicago.org:8180/MtDB2/Queries/SimilarityDB2.html).
7) The development of a complete physical map for M. truncatula has been initiated (http://mtgenome.ucdavis.edu/index.html), which has already been proven to be useful for cloning of genes with agricultural importance (Schnabel et al., 2003).
6 8) Efficient mutagenesis protocols have been established for M. truncatula by using ethyl-methyl sulfonate (EMS), Tnt1 transposons or fast neutron bombardment (d'Erfurth et al., 2003; Penmetsa and Cook, 2000; Tadege et al.,
2005) and various transformation methods targeting various organs have been described (Chabaud et al., 2003; 1996; Hoffmann et al., 1997; Kamate et al.,
2000; Limpens et al., 2004; Thomas et al., 1992; Trieu et al., 2000; Trieu and
Harrison, 1996).
10) DNA arrays as tools for expression profiling and gene identification have been established. These macro- and micro-arrays have been used in M. truncatula particularly to study the interaction with beneficial microbes
(Fedorova et al., 2002; Frenzel et al., 2005; Hohnjec et al., 2006; 2005; Kuster et al., 2004; Lohar et al., 2006).
1.4.2 Medicago truncatula and comparative mapping
The use of M. truncatula derived markers that amplify across legume species allows researchers to look for syntenic regions, i.e. regions with the same conserved marker order, containing important traits in other legume species
(Cannon et al., 2003; Choi et al., 2004a; 2004b; Eujayl et al., 2004; Gutierrez et al., 2005; Nelson et al., 2006; Phan et al., 2006; Yan et al., 2003; 2004; Zhu et al., 2005; 2003). Comparative mapping projects have lead to the generation of the Legume Information System (LIS), which is a comparative legume resource that integrates genetic and molecular data from multiple legume species enabling cross-species genomic and transcript comparisons (Gonzales et al., 2005: http://www.comparative-legumes.org ).
7
1.4.3 Medicago truncatula as a host for pathogens
Since the early 1990s, R genes against various pathogens and pests have been cloned in important crop species such as barley, tomato and rice
(Hammond-Kosack and Parker, 2003), although most of the R genes known today are isolated from the model plant Arabidopsis. The cloning of R genes in
Arabidopsis contributed to the identification of homologous disease-resistance loci in complex crop genomes of the Brassica family through comparative mapping (Grant et al., 1998). The genetic tools to clone and characterize R genes are not available in most legumes, making it difficult to study the genetic basis of resistance to legume diseases. M. truncatula, on the contrary, is an excellent model legume and a host for many pathogens (Table 1.1). Various different screening techniques to examine resistance in M. truncatula, against foliar fungal necrotrophs (Tivoli et al., 2006a; 2006b), soil-borne necrotrophs (Infantino et al.,
2006; Tivoli et al., 2006b) and biotrophs (Sillero et al., 2006) have been utilised.
Transciptional profiling studies using a SSH strategy identified 560 ESTs involved in the M. truncatula - Aphanomyces euteiches interaction (Nyamsuren et al., 2003). A proteomics approach studying this interaction showed accumulation of pathogenesis-related proteins of class 10 (PR10 proteins) upon infection (Colditz et al., 2007; 2004). A more detailed study identified changes in regulated proteins of the phenylpropanoid pathway and alcohol dehydrogenases
(Colditz et al., 2005). Torregrosa and colleagues (2004) studied compatible and incompatible interactions between M. truncatula and Colletotrichum trifolii and identified differentially expressed genes through a macroarray experiment.
8 Table 1.1 Fungal species and oomycetes causing significant disease in legumes,
where susceptible and resistant M. truncatula accessions have been identified.
Species Original host Disease name Reference
Aphanomyces Pisum Root rot Nyamsuren et al., euteiches sativum 2003 Ascochyta lentis Lens culinaris Ascochyta blight Pfaff et al., 2006 A. rabiei Cicer Ascochyta blight Pfaff et al., 2006 arietinum Colletotrichum trifolli M. sativa Anthracnose Torregroza et al., 2004 C. coccodes Lupinus albus Anthracnose T. Pfaff, unpublished Erysiphe pisi Pisum Powdery mildew Foster-Hartnett et al., sativum 2007 Fusarium oxysporum M. sativa Fusarium wilt J. Lichtenzveig, et al., 2006 Leptosphaerulina M. truncatula Leaf spot Tivoli et al., 2006 trifolii Mycosphaerella Pisum Black spot Tivoli et al., 2006 pinodes sativum Phoma medicaginis M. truncatula Spring blackstem and Barbetti,, 1987 leaf spot Phytophthora Cicer Root rot D’Souza et al., 2006 medicaginis arietinum Stagonospora meliloti M. sativa Leaf spot and root rot Pfaff et al., 2006 Uromyces striatus M. truncatula Leaf Rust Kemen et al., 2005
9 Foster-Harnett et al. (2004) performed microarray studies to study expression profiles of resistant and susceptible accessions of M. truncatula upon infection with the biotroph Erysiphe pisi and the hemi-biotroph C. trifolii. Since M. truncatula is a natural host for Phoma medicaginis, it is an ideal model system to study legume-fungal necrotroph interactions. Therefore, we chose to study this interaction to gain more insight into legume resistance to fungal necrotrophs and try to identify resistance genes and defence pathways involved in this interaction.
1.5 The pathogen of study: Phoma medicaginis
1.5.1 Phoma medicaginis causal agent of black stem and leaf spot in annual
Medicago species
Phoma medicaginis has a global distribution, and is a notable pathogen on pasture legumes. Spring black stem and leaf spot on lucerne caused by P. medicaginis is a devastating necrotrophic pathogen on Medicago spp in temperate and Mediterranean regions (Graham et al., 1979; Lamprecht and
Knox-Davies, 1984; Smith et al., 1988). Disease symptoms typically include seedling blight, stem canker, and leafspot. Infected leaves undergo chlorosis and defoliate, while stem and petiole lesions may progress causing crown and root rot. In the US alone approximately 9.7 million hectares of alfalfa is grown a year, and yield loss due to foliar necrotrophs like P. medicaginis is estimated to be
10.7 million tons/year (Nutter and Guan, 2002). Dry matter yield in the first harvest of M. sativa as a forage crop can be reduced by 40 to 60% with moderate to severe spring black stem infection. P. medicaginis also causes significant disease on the barrel medic (Medicago truncatula), which is used in Australia as
10 a forage crop and for intercropping as a means to enhance soil nitrogen. In susceptible cultivars, reduction in seed and herbage yield and almost complete defoliation and premature death has been reported (Barbetti, 1983; Barbetti and
Nichols, 1991). Barbetti reported in 1995 that infected Australian Medicago cultivars have an average seed weight loss of 37.3% as opposed to uninfected
Medicago cultivars. When disease is severe, foliar fungicides are recommended and studies using various fungicides show reduction in disease severity but no complete absence of disease (Nutter and Guan, 2002).
1.5.2 Phoma medicaginis taxonomy
Phoma isolates causing disease on Medicago species are normally ascribed to Phoma medicaginis (Malbr. & Roum.) var. medicaginis Boerema
(syn. P. herbarum Westend. var. medicaginis Fckl. and Ascochyta imperfecta
Peck), an ascomycete with no known teleomorph. Phoma medicaginis belongs to the kingdom of the Fungi, phylum Ascomycota, subphylum Pezizomycotina, class Dothideomycetes. The CABI Bioscience world database of fungal names lists P. medicaginis as occupying the group Incertae sedis (of uncertain placement) within the class Dothideomycetidae and subclass Pleosporales.
1.5.3 The Phoma medicaginis lifecycle
P. medicaginis overwinters as mycelium or as small fruiting bodies
(pycnidia) in infected plants, infected seed, in the soil or in plant debris. The pycnidia, which are often embedded in the previous season’s diseased stubble, release their spores (conidia) during periods of cool, wet weather (18-24°C). The conidia ooze from the pycnidia and are splashed onto leaves and stems and
11 infection occurs. The spores germinate and penetrate directly or through stomata and invade the stem- and leaftissue in the form of mycelia. This results in the formation of small, irregular, dark brown to black flecks symptoms on the leaves, petioles and stems. Such lesions expand and increase in numbers and the infected leaves undergo chlorosis and defoliate, while stem and petiole lesions may progress causing crown and root rot. The disease spreads rapidly in the cool and wet conditions, as pycnidia within the lesions are formed to disperse conidia, which will start the secondary infection cycle. Once P. medicaginis has established itself it produces a toxin termed Brefeldin A in dead colonized tissue of infected Medicago species (Weber et al., 2004), which is believed to inhibit growth of saprotrophic fungi competing with P. medicaginis. As the disease spreads through the crop it can colonize the pods containing seeds and survive until the seed is borne to new fields.
1.5.4 Advances in Phoma medicaginis research
Since M. truncatula is a natural host for P. medicaginis, this pathosystem represents a model system to study legume-fungal necrotroph interactions.
Despite this, little is known about the genetic basis of resistance to P. medicaginis. Rapid increases in mRNA levels and enzyme activities of isoflavone reductase, phenylalanine ammonia-lyase and chalcone synthase during the infection of M. sativa leaves suggest the involvement of the isoflavonoid biosysnthetic pathway in defence response to P. medicaginis
(Junghans et al., 1993; Paiva et al., 1994). This hypothesis was given more support when He and Dixon (2000) over-expressed a isoflavone O- methyltransferase (IFMT) gene in alfalfa. Overexpression of IFMT resulted in
12 increased induction of the isoflavonoid pathway gene transcripts after infection but had little effect on basal expression of these genes. IFMT-overexpressing plants had increased amounts of formononetin and medicarpin and displayed enhanced resistance to P. medicaginis (He and Dixon, 2000). Thus, the pterocarpan medicarpin acts as a phytoalexin in this interaction. This was strongly supported by Blount et al. (1992), who found that P. medicaginis growth was strongly inhibited on plates containing 0.5 mM medicarpin. Other agar-plate bioassays indicated that vestitone, trans-resveratrol-3-O-b-D- glucopyranoside (RGluc) and resveratrol greatly inhibit hyphal growth of P medicaginis (Blount et al., 1992; Hipskind and Paiva, 2000). Constitutive expression of a peanut cDNA encoding resveratrol synthase in alfalfa resulted in accumulation of RGluc. These RGluc overexpressing plants showed a significant reduction (relative to control leaves) in the size of necrotic lesions, intensity of adjacent chlorosis and number of pycnidia upon infection with P. medicaginis.
Similarly, alfalfa transformed with a grapevine stilbene-synthase gene driven by the cauliflower mosaic virus 35S promoter, constitutively accumulating resveratrol, also showed reduced fungal development of P. medicaginis (Dixon,
2001). Deavours and Dixon (2005) showed that the overexpression of a M. truncatula isoflavone synthase gene (MtIFS1) in alfalfa resulted in accumulation of the glucosides of genistein, biochanin A, and pratensein. MtIFS1-expressing
M. sativa accumulated additional isoflavones formononetin, daidzein and the phytoalexin medicarpin in response to P. medicaginis.
Metabolites of the isoflavonoid biosynthetic pathway thus play an important role in defence against P. medicaginis and several of these metabolites have antifungal properties. P. medicaginis isolates that have the ability to
13 detoxify these isoflavonoids will be pathogenic. George and VanEtten (2001) identified a cytochrome P450 in a virulent Phoma pinodella isolate, which demethylates (and thus detoxifies) the pea phytoalexin pisatin, a pterocarpan very similar to medicarpin (George and VanEtten, 2001). To date however, no detoxifying enzymes have been reported for P. medicaginis.
1.6 Plant disease-resistance genes
Most plants remain healthy because a mirco-organism has not adapted itself to become pathogenic. This lack of compatibility between the plant and pathogen is referred to as non-host resistance and is a characteristic feature of most interactions between plants and pathogens. A plant species is a non-host to a potential pathogen species when all genotypes of that plant species are fully resistant to all genotypes of that pathogen species (Heath, 2001). Non-host resistance is thought to comprise a variety of distinct mechanisms that may include the production of pre-formed toxins or barriers, or the lack of essential metabolites or signalling molecules required by the pathogen. The detection of microbial-derived molecules termed pathogen-associated molecular patterns
(PAMPs) are an important component of non-host resistance and show similarity to the animal innate immune response (Ingle et al., 2006). The PAMPs are recognised by pattern recognition receptors (PRRs) in plants which lead to signal transduction and the activation of a range of basal defence mechanisms (Ingle et al., 2006; Nurnberger and Brunner, 2002). Plants are also resistant to certain pathogens if they escape or tolerate infection by these pathogens (apparent resistance).
14 Although a pathogen might have all the necessary tools to attack its host, in a natural plant population there will always be some genotypes that are able to recognize and check further development of particular strains of the pathogen.
This type of resistance is known as genotype-specific resistance. Genotype- specific resistance is mostly a dominant or co-dominant trait, which is inherited in a monogenic fashion. Through products of resistance (R) genes, host plants are capable of recognizing specific, pathogen-derived molecules and launch a defence response against the invader. These elicitors of resistance reactions are direct or indirect products of a microbial avirulence (Avr) gene. Both R and Avr genes form the basis of the gene-for-gene hypothesis, stating that for each R gene that confers resistance of the plant, there is a corresponding Avr gene that confers avirulence in the pathogen (Flor, 1946). Lacking or disfunctioning of either R gene or Avr gene results in a compatible interaction. Finally, in the absence of a gene-for-gene recognition system, defences seem to be elicited non-specifically.
This type of defence is known as basal resistance and restricts the development of the disease after pathogen attack.
In the last decade, numerous R genes against viruses, bacteria, fungi, oomycetes, nematodes and aphids have been cloned (reviewed in Hammond-
Kosack and Parker, 2003; Martin et al., 2003; van't Slot and Knogge, 2002).
Although these confer resistance to a variety of different pathogens, the architecture of their products is remarkably similar (Hammond-Kosack and
Jones, 1997). This implies that fundamental modes of recognition and defence signalling have been retained through plant evolution and diversification. R genes encode at least five diverse classes of R proteins (Dangl and Jones, 2001;
Hammond-Kosack and Parker, 2003; Figure 1.2). Most predicted R proteins
15 contain a leucine-rich repeat (LRR) domain, thought to be involved in protein- protein interactions. The R genes can be classified according to whether the LRR domain of the encoded protein is located either inside or outside the cytoplasm.
All R gene-encoded proteins with a cytoplasmic LRR domain also contain a nucleotide-binding site (NBS). These conserved NBS domains are critical in other proteins for ATP or GTP binding and it is therefore believed that the NBS domain functions in signal transduction (Dangl and Jones, 2001). The NBS–LRR class is the largest class of R proteins and can be subdivided into two distinct classes based on the structure of the N terminus of the protein upstream of the
NBS domain. The first class codes for a TIR domain, so called because of sequence homology to the intracellular domain of the Drosophila Toll and mammalian interleukin-1 receptors in the N terminus (Pan et al., 2000a; 2000b).
The second class typically codes for a domain with a predicted coiled-coil
(CC) motif sometimes in the form of a leucine zipper at the N terminus. Variant types with different structures exist in both these classes, but they can generally be classified into the TIR or non-TIR classes based on their NBS-coding sequences (Meyers et al., 2003; 2002). TIR and non-TIR NBS-LRR R genes also appear distinct at the functional level, based on their putative involvement in different signal transduction pathways (Aarts et al., 1998). Less common are the serine/threonine protein kinase class of R proteins (Class III), and the extracellular LRR (eLRR) proteins. These eLLR proteins possess a single transmembrane domain and either a short intracellular C terminus (Class IV) or a cytoplasmic serine/threonine kinase domain (Class V).
16 Figure 1.2 Representation, localisation and structure of the five main classes of disease resistance proteins. Xa21 and Cf-X proteins carry transmembrane domains and extracellular LRRs. The cloned RPW8 gene product carries a putative signal anchor at the N-terminus. The Pto gene encodes a cytoplasmic
Ser/Thr kinase but may be membrane associated through its N-terminal myristoylation site. The largest class of R-proteins, the NB-LRRs, are presumably cytoplasmic and carry distinct N-terminal domains. Figure adapted from Dangl and Jones 2001.
17 Resistance genes and resistance gene analogues (RGAs) are typically clustered in plant genomes (Meyers et al., 2003; Soriano et al., 2005; Zhu et al.,
2002). Clusters of R genes provide a reservoir of genetic variation from which new resistance specificities can evolve. Individual clusters may confer specific resistance to a wide range of different pathogens and pathogen genotypes (van der Vossen et al., 2000). Out of all the classes of R genes, the evolution of NBS-
LRR genes has been studied most thoroughly. Michelmore and Meyers discussed that the NBS-LRR family follows a process of diversifying evolution in a birth- and-death pattern (Michelmore and Meyers, 1998). This was based on phylogenetic analyses indicating that orthologs are more similar than paralogs in several groups of tomato and lettuce resistance genes. Other researchers however showed that gene conversion events lead to new specificities. Mondragon-
Palomino and Gaut (2005) studied gene conversion and unequal crossing-over in the coding and non-coding regions of NBS-LRR, receptor-like kinases (RLK) and receptor-like proteins (RLP) in Arabidopsis thaliana and confirmed gene conversion in clusters for all the three R-gene families (Mondragon-Palomino and Gaut, 2005).
Although Papilionoid legume species seem to share a similar range of
RGA diversity, the phylogenetic relationship between individual RGAs from seven Papilionoid legume species (Pisum sativum, Medicago sativa, Cicer arietinum, Glycine Max, Phaseolus vulgaris, Cajanus cajan and M. truncatula) is closely correlated with the established phylogeny of the species themselves (Zhu et al., 2002). Thus, while the origin of the principal clades of RGAs seems to predate radiation within the Papilionoid legumes, speciation within this group of plants is correlated with divergence of the RGA family (Doyle, 1998; Zhu et al.,
18 2002). Genetic and physical mapping of both TIR and non-TIR NBS-LRR type resistance genes in Medicago truncatula (the host of study in this thesis) revealed that most M. truncatula RGAs are clustered. TIR and non-TIR type RGAs do not occur together in the M. truncatula genome (Zhu et al., 2002).
1.6.1 Resistance genes to fungal necrotrophs
Fungal plant pathogens can be divided into three different classes based on their strategies to obtain nutrients from the plant: biotrophic, hemi-biotrophic and necrotrophic fungal pathogens. Most of the cloned fungal resistance genes confer resistance to biotrophic pathogens, mainly because cultivar specificity and simple genetics were important technical requirements in the cloning strategy. To date only three genes conferring resistance to necrotrophs (Asc-1, Hm1 and Hm2) have been cloned and are structurally distinct from any of the five classes described above (Brandwagt et al., 2000; 1998; Johal and Briggs, 1992). Asc-1 confers resistance to Alternaria alternata f.sp. lycopersici in tomato and Hm1 and Hm2 confer resistance to Cochliocolus carbonum in maize. Plants bearing these R-genes are insensitive to toxins produced by these necrotrophs. Hm1 and
Hm2 encode nitrate reductases which detoxify the C. carbonum HC-toxin
(Walton, 2006). Similarly Asc-1 encodes a gene homologous to the yeast longevity assurance gene LAG1, which detoxifies AAL-toxins of A. alternata f.sp. lycopersici and fumonisin B1 toxin of Fusarium moniliforme (Brandwagt et al., 2000). The AAL toxin kills the host cells in acs-1/acs-1 individuals by inducing programmed cell death (Spassieva et al., 2002).
Other loci conferring resistance (i.e. insensitivity to) host selective toxins of fungal necrotrophs toxin have been identified. For example, in wheat the Tsn1
19 allele confers sensitivity to the Pyrenophora tritici-repentis ToxA (Faris et al.,
1996) and the tsc2 locus confers sensitivity to the P. tritici-repentis ToxB
(Friesen and Faris, 2004; Friesen et al., 2006).
1.7 Plant-pathogen recognition complexes
The simple interpretation of the gene-for-gene-hypothesis implies a receptor–ligand-like interaction between plant R gene products and the corresponding pathogen-derived AVR gene products. However, a lack of evidence for a direct interaction between R proteins and most of their corresponding effectors implies that multiprotein receptor complexes are probably involved in pathogen recognition. In the tomato-Pseudomonas syringae pv. tomato pathosystem the dual requirement of Prf and Pto leads to AvrPto- triggered resistance and was designated as the “guard” hypothesis (Dangl and
Jones, 2001; Van Der Biezen and Jones, 1998). In this model, the effector
(AvrPto) targets a plant protein (Pto) to promote disease and the R protein (Prf) guards against effector attack by recognizing the effector-target complex and activating defence responses. In a compatible interaction, the R protein guard would not be present and the attack of the avirulence product on the host protein would promote disease. Once the effector target-complex is recognised the plant uses a range of signal transduction pathways that lead to the activation of a range of defence mechanisms. R gene mediated resistance is usually accompanied by an oxidative burst that is rapid production of reactive oxygen species (ROS).
ROS production is required for another component of the response called the hypersensitive response (HR). In case of HR, rapid localised cell-death occurs at the site of infection, which is thought to limit the access of the pathogen to water
20 and nutrients (Morel and Dangl, 1997) resulting in no further spread of the pathogen. During HR, the production of reactive oxygen species (ROS: reviewed by Apel and Hirt, 2004) such as hydrogen peroxide and nitric oxide occurs
(Dangl et al., 1996). These chemicals can be directly toxic to the pathogen and can act as a compound involved in the plants defence signalling cascade
(Bindschedler et al., 2006; Durner et al., 1998; Polkowska-Kowalczyk et al.,
2004). The oxidative burst can lead to cell wall fortification and the production of secondary metabolites. During cell wall fortification, lignins, callose and other glycoproteins are produced to form a physical barrier between the pathogens and the internal contents of plant cells (Maor and Shirasu, 2005; Vorwerk et al.,
2004).
R gene mediated resistance is also associated with the activation of salicylic acid (SA)-dependent, jasmonate (JA)-dependent and ethylene (ET)- dependent signalling pathways. These pathways lead to expression of certain pathogenesis-related (PR) proteins and antimicrobial molecules.
1.8 Production of antimicrobial molecules
Following pathogen recognition, the plant produces a range of compounds to combat the pathogen such as large defence related proteins with anti-microbial enzymatic activities and small molecular weight molecules including phytoalexins and phytoanticipints (VanEtten et al., 1994). Phytoalexins are a diverse family of secondary metabolites, which are synthesized upon pathogen attack, whereas phytoanticipints can either be found as (in)active compounds in healthy plants or as secreted active compounds into the environment of the plant forming a chemical barrier against certain pathogens
21 (Morrissey and Osbourn, 1999; Osbourn, 1999; VanEtten et al., 1994). These secondary metabolites include phenolics, flavonoids, isoflavonoids, terpenoids, sesquiterpenes and saponins (Dixon, 2001; 2002; Osbourn, 1999). Most of these anti-microbial secondary metabolites have a broad spectrum activity and specificity is often determined by whether or not a pathogen has the enzymatic machinery to detoxify a particular host anti-microbial metabolite (Bouarab et al.,
2002). Disruption of genes that code for the detoxifying enzymes leads to complete loss in pathogenicity (Bowyer et al., 1995) or reduced virulence of the fungus (Enkerli et al., 1998). Saponin-deficient mutants of oats are compromised in resistance to Gaeumannomyces graminis var. tritici (Papadopoulou et al.,
1999). Constitutive (over)expression of genes catalysing the enzymatic reaction leading to a phytoalexin, results in increased production of this phytoalexin and a consequent reduced disease severity upon pathogen infection (He and Dixon,
2000; Hipskind and Paiva, 2000).
Another defence response by the plants is the production of a number of antimicrobial proteins. These proteins are generally termed pathogenesis-related proteins (PR) proteins and they have been classified into 17 different families
(Table 1.1: Van Loon et al., 2006; Van Loon and Van Strien, 1999). Most PR genes and PR proteins are induced through the action of signalling compounds salicylic acid, jasmonic acid and ethylene, which are discussed in the next sections.
22 Table 1.2 Recognized families of pathogenesis-related proteins. Adapted from
Van Loon et al., 2006.
Family Type member Properties PR-1 Tobacco PR-1a Unknown PR-2 Tobacco PR-2 β-1,3-glucanase PR-3 Tobacco P, Q Chitinase type I-VII PR-4 Tobacco ‘R’ Chitinase type I, II PR-5 Tobacco S Thaumatin-like PR-6 Tomato Inhibitor I Proteinase-inhibitor PR-7 Tomato P69 Endoproteinase PR-8 Cucumber chitinase Chitinase type III PR-9 Tobacco “lignin-forming peroxidase” Peroxidase PR-10 Parsley “PR1” Ribonuclease-like PR-11 Tobacco “class V” chitinase Chitinase, type I PR-12 Radish Rs-AFP3 Defensin PR-13 Arabidopsis THI2.1 Thionin PR-14 Barley LTP4 Lipid-transfer protein PR-15 Barley OxOa (germin) Oxalate oxidase PR-16 Barley OxOLP Oxalate-oxidase-like PR-17 Tobacco PRp27 Unknown
23 1.9 Plant defence signalling networks
Advances in plant defence signalling research have shown that plants are able to differentially activate broad-spectrum defence mechanisms, depending on the type of pathogen encountered. The plant hormones salicylic acid (SA), jasmonic acid (JA) and ethylene (ET) are main players in the network of defence signalling pathways. Other unknown signalling pathways have been reported to confer disease resistance in an independent manner of SA, JA or ET (Thara et al., 1999). The role of the plant hormone abscisic acid (ABA) for example has been argued to play a role in disease resistance (Mauch-Mani and Mauch, 2005), where enhanced levels of ABA are correlated with increased susceptibility and reduction of ABA below wildtype (WT) levels is correlated with increased resistance. It is still unclear whether there is crosstalk between the ABA pathway and the other defence signalling pathways.
1.9.1 The role of salicylic acid in disease resistance
Salicylic acid (SA) has long been associated with defence induction in plants (Durner et al., 1997). In fact, the induction of systemic acquired resistance
(SAR) coincides with an early increase in endogenously synthesized SA at both the primary infection site and systemically in uninfected tissues. Application of exogenous SA or its functional analog 2, 6-dichloroisonicotinic acid (INA) effectively induces SAR (Kessmann et al., 1994). Plants exposed to SA or INA show enhanced resistance to a range of pathogens (Thomma et al., 1998). When
SA accumulation is defective, as in the Arabidopsis nahG mutant, no induction of SAR is observed and nahG plants display increased susceptibility to a range of pathogens (Delaney et al., 1994). Accumulation of SA triggers the activation of a
24 large number of defence response genes, including the pathogenesis-related (PR) genes (PR1, PR2, PR5), which are commonly used as molecular markers to monitor SAR activation. Evidence of a key role for the SA pathway and the identification of downstream signal targets has come from the analysis of several mutants and transgenic Arabidopsis lines. For example the npr1 mutant is still able to accumulate SA upon pathogen challenge, but fails to induce SAR marker genes (like PR1), indicating NPR1 (also known as NIM1) acts downstream of
SA (Cao et al., 1997). NPR1 seems to function as a positive regulator of SA dependent defence response, where overexpression leads to enhanced resistance to pathogens (Cao et al., 1998). NPR1 is localised in the nucleus where it interacts with TGA transcription factors (see paragraph 1.10). These TGA transcription factors are part of the TGA family (TGACG DNA motif) of basic leucine zipper proteins (bZIP) and several of these TGA transcription factors have been shown to specifically bind an SA-responsive element of the
Arabidopsis thaliana PR1 promoter, indicating that NPR1 regulates defence gene expression by interacting with bZIP transcription factors (Zhang et al., 1999).
Despite the detailed studies on SA and SAR, the molecule responsible for the systemic signal transduction of SAR remains unknown but a lipid-derived signalling molecule has been proposed as a likely candidate (Maldonado et al.,
2002).
1.9.2 The role of jasmonates in disease resistance
Jasmonic acid (JA) and its derivatives, collectively called jasmonates
(JAs), are ubiquitous plant regulators. JAs can act as signals in plant cellular responses to different abiotic and biotic stresses. The role of JAs in plant defence
25 against insects and during wounding has been well documented (Gatehouse,
2002; Schilmiller and Howe, 2005). In Arabidopsis it has also been shown that the JA signalling pathway is involved in the defence response to necrotrophic fungi such as Alternaria brassicicola and Botrytis cinerea (Penninckx et al.,
1998; Thomma et al., 1998; 1999). JA-dependant defence responses, which are not associated with cell death, are considered to provide an alternative defence against necrotrophs (McDowell and Dangl, 2000). Application of exogenous methyl jasmonates to Arabidopsis has been shown to increase resistance against fungal necrotrophs (Thomma et al., 2000; 1998). Convincing evidence for the role of JAs in basal resistance comes from genetic analysis of mutant plants that are affected in the biosynthesis or perception of JAs (Berger, 2002). For example, the coi1 and jar1 mutants display enhanced susceptibility to necrotrophic fungi and bacteria (Pieterse et al., 1998; Thomma et al., 1998).
JAs are derived from linolenic acid. In subsequent enzymatic reactions, lipoxygenase (LOX), allene oxide synthase (AOS), allene oxide cyclase (AOC) and OPDA reductase (OPR) turn linolenic acid into 12-oxophytoenoic acid.
Finally, three β-oxidation steps shorten the carboxyl chain and result in the formation of jasmonic acid. The fad3fad7fad8 triple mutant of A. thaliana is deficient in the production of linolenic acid and exhibits susceptibility to the normally non-pathogenic soil-borne Pythium species (Staswick et al., 1998;
Vijayan et al., 1998). This indicates that JA also plays a role in non-host resistance against some fungal pathogens. The only defence regulator gene cloned in this pathway is COI1, which encodes an F-box protein that might bind negative regulators of the JA response (Xie et al., 1998). Induced systemic resistance (ISR) signalling requires JA (and ET) and is completely independent
26 of the SA-signalling pathway. Arabidopsis mutants impaired in their ability to respond to JA and ET are unable to express ISR (Van Loon et al., 1998).
Although the mechanism of JA biosynthesis is fully unravelled, the perception and subsequent signal transduction of JA is still not fully understood.
1.9.3 The role of ethylene in disease resistance
Ethylene (ET) is a gaseous plant hormone with many functions. It plays a role in plant growth regulation including germination, flower and leaf senescence, fruit ripening and leaf abscission (Bleecker and Kende, 2000;
Johnson and Ecker, 1998). It has also been reported to be involved in nodulation, programmed cell death and responsiveness to stress and pathogen attack
(Bleecker and Kende, 2000; Broekaert et al., 2006; McDowell and Dangl, 2000).
ET synthesis is well understood: it is synthesized from S-adenosyl-L-methionine via 1-aminocyclopropane-1-carboxylic acid (ACC). The enzymes catalysing the two reactions in this pathway are ACC synthase and ACC oxidase. Recent findings show that the role of ET in plant resistance is somewhat ambiguous. In some cases it is involved in disease resistance, whereas in others it is associated with disease symptom development. For instance, several ET-insensitive mutants of Arabidopsis exhibit enhanced susceptibility to Botrytis cinerea (Thomma et al., 1999) and Pseudomonas syringae pv. tomato (Pieterse et al., 1998). These findings indicate that ET-dependant defences contribute to basal resistance against pathogens. When a tobacco transformant lacking the ET receptor gene etr1 was challenged with the normally non-pathogenic Pythium sylvaticum, it displayed susceptibility to this oomycete (Knoester et al., 1998). This indicates that ET also plays a role in non-host resistance. In other cases, reduced ET
27 sensitivity was associated with disease tolerance. ET-insensitive tomato genotypes and the ET-insensitive ein2 mutant of Arabidopsis showed wildtype levels of growth of P. syringae pv. tomato and Xanthomonas campestris pathovars but developed less-severe symptoms of disease, eg showing increased tolerance to these virulent strains (Bent et al., 1992; Ciardi et al., 2000; Lund et al., 1998). This indicates that ET can be involved in symptom development rather than disease resistance.
1.9.4 Crosstalk between the signalling pathways in pathogen defence
SA, JA and ET play important roles in the regulation of plant defence responses and genetic engineering of the corresponding signalling pathways can effectively enhance disease resistance. There is ample evidence however that
SA-, JA-, and ET-dependent defence pathways interact, either positively or negatively (Bostock, 2005; Felton and Korth, 2000; Feys et al., 2001; Feys and
Parker, 2000; Kunkel and Brooks, 2002; Pieterse et al., 1998; Schenk et al.,
2000).
Several studies have shown positive interactions between the JA and ET signalling pathways (Xu et al., 1994). They are both required for the expression of defence related genes PDF1.2, HEL and CHIB in Arabidopsis in response to various pathogens (Norman-Setterblad et al., 2000; Penninckx et al., 1998). In a microarray study performed in A. thaliana it was demonstrated that nearly half of the genes induced by ET were also induced by JA, indicating that JA and ET co- ordinately regulate many defence-related genes (Schenk et al., 2000). This study also revealed that JA and ET independently regulate different sets of genes.
28 There is little evidence of both synergistic and antagonistic regulatory interactions between the SA and ET signalling pathways. However, in both tomato and Arabidopsis, the accumulation of SA upon infection with
Xanthomonas species is dependent on ET synthesis (O'Donnell et al., 2001;
2003a; 2003b). An A. thaliana microarray study also suggests that SA and ET may act together to induce several defence-related genes (Schenk et al., 2000).
The interaction between SA and JA signalling appears to be complex and these pathways have been shown to interact both positively and negatively.
However, the main interaction between these two signalling pathways seems to be mutual antagonism (Kunkel and Brooks, 2002). For instance, SA suppresses
JA-dependent defence gene expression possibly through the inhibition of the JA biosynthesis and/or JA-responsive gene expression (Clarke et al., 2000; Doares et al., 1995; Gupta et al., 2000). Preston et al. (1999) showed that Tobacco
Mosaic Virus (TMV) infected tobacco plants expressing SAR are not capable of developing JA-mediated wound responses (upon grazing by tobacco hornworm) due to the inhibition of JA-signalling by an increase in levels of SA resulting from TMV infection. This negative regulation of SA signalling has also been reported in Arabidopsis (Kloek et al., 2001). Conversely, JA has also been reported to repress SA signalling in tobacco (Niki et al., 1998).
Finally, SA dependent and JA dependent induced resistance have been reported to be expressed simultaneously (Clarke et al., 2000; Van Wees et al.,
2000). In Arabidopsis, SA dependent SAR and JA/ET dependent ISR were triggered simultaneously upon P. syringae pv. tomato infection showing an additive effect for the level of resistance to this pathogen (Van Wees et al.,
2000). This demonstrated that the SAR and ISR pathways are compatible and
29 there is no significant crosstalk between these pathways. Thus, combining SAR and ISR could improve disease control in important agricultural crops. Other evidence that SA and JA can act synergistically or co-ordinately induce defence associated genes was shown in the Arabidopsis microarray study by Schenk and colleagues (2000). They revealed that more than 50 defence related genes are co- induced by JA and SA. Additionally, experiments in tobacco showed that SA and
JA act synergistically to induce PR1b expression (Xu et al., 1994).
1.10 Regulation of plant defence by transcription factors
Plant defence responses are associated with the transcriptional activation of a large number of host plant genes after pathogen infection (Rushton and
Somssich, 1998). Transcriptional regulation of gene expression is largely mediated by the specific recognition of cis-acting promoter elements by trans- acting sequence-specific DNA binding transcription factors. Numerous defence associated transcription factors (TF) and their cis acting elements have been identified (Eulgem, 2005). TFs play an important role in the transmission of pathogen-derived defence signals to either activate or suppress downstream defence gene expression. However, the functional requirement for these proteins in defence response is largely unknown (Eulgem, 2005; Rushton and Somssich,
1998). TFs can be divided into different families based on similarities in their binding domains.
AP2/EREBP TFs (or AP2/ERF TFs) bind to the so-called GCC box in the promoters of genes (Ohme-Takagi and Shinshi, 1995). In Arabidopsis, the ethylene response factor 1 (ERF1) was shown to bind to the GCC box (Hao et al
1998). These GCC cis motifs are found in the promoters of many ET/JA
30 regulated PR genes, including PR3, PR4 and PDF1.2 (Ohme-Takagi and Shinshi,
1995) and therefore suggest a potential role of the ERF subfamily of these TFs in plant defence. Overexpression of AtERF2 showed activated transcription of
PDF1.2, Thi2.1 and PR4 genes (Brown et al., 2003). The expression of ERF1 can be activated rapidly by ethylene or jasmonate and can be activated synergistically by both hormones (Lorenzo et al., 2003). ERF genes are induced upon infection with fungal necrotrophs and oomycetes (Berrocal-Lobo and
Molina, 2004; Berrocal-Lobo et al., 2002; Onate-Sanchez and Singh, 2002).
Overexpression of ERF1 increases the tolerance of Arabidopsis to some necrotrophs (B. cinerea and P. cucumerina), but not to others (P. syringae pv. tomato; Berrocal-Lobo et al., 2002; Onate-Sanchez and Singh, 2002).
WRKY TFs are plant specific members that belong to the zinc finger superfamily and are able to bind the W box (Eulgem et al., 2000). The W box is found in promoters of many pathogenesis related genes, like PR1 and NPR1
(Heise et al., 2002; Maleck et al., 2000; Robatzek and Somssich, 2002; Xu et al.,
2006; Yu et al., 2001). Upon pathogen infection and treatment with pathogen elicitors or SA, a rapid induction of WRKY genes has been reported (Chen and
Chen, 2000; Dong et al., 2003; Li et al., 2006; Turck et al., 2004; Xu et al.,
2006). A number of studies have shown that these WRKY proteins specifically recognize the W box sequences of defence-related genes and are necessary for the inducible expression of these genes (Chen and Chen, 2000; Dong et al., 2003;
Li et al., 2006; Turck et al., 2004; Xu et al., 2006).
bZIP transcription factors such as the TGA transcription factor class of
TF have been shown to specifically bind the activation sequence-1 (as-1) element, which regulates the expression of defence related genes such as PR1
31 and GST6 (Glutathione S-transferase) promoters (Lebel et al 1998; Chen and
Singh, 1999; Zhang et al 1999). TGA TF also interact with NPR1, a key component of the SA defence signalling pathway (Zhang et al., 1999). A direct interaction between NPR1 and TGA2 occurs in planta. This direct interaction is predominantly localized to the nucleus and induced by SA (Fan and Dong,
2002), suggesting TGA TFs play a crucial role in SA dependent defence responses.
Other TF families such as MYB family (Kranz et al., 1998; Lee et al.,
2001; Mengiste et al., 2003; Raffaele et al., 2006; Vailleau et al., 2002), basic helix-loop-helix (bHLH) family (Anderson et al., 2004; Boter et al., 2004;
Lorenzo and Solano, 2005; Nickstadt et al., 2004) and the Whirly family (2002;
2000; Desveaux et al., 2005; 2004) have also been shown to be involved in the defence response.
1.11 Aims of the project
It is clear that fungal necrotrophs cause serious yield losses in Australian legume agriculture. The fungal necrotroph P. medicaginis predominantly causes losses in alfalfa and the barrel medic. In this PhD thesis, the model legume
Medicago truncatula, a natural host for Phoma medicaginis is used to investigate legume-fungal necrotroph interactions. This involved a combination of genetic mapping and genomic approaches to identify loci, genes and pathways involved in resistance to P. medicaginis in M. truncatula. The long-term impact of this
Medicago research will be to clone and characterize valuable genes involved in disease resistance, ultimately facilitating the development of improved legume varieties with increased resistance to fungal necrotrophs.
32 The aims of this PhD project were to:
1. identify, characterize and differentiate the Phoma species commonly
found in Australia (Chapter3).
2. setup a reliable and reproducible screening method to measure resistance
to P. medicaginis in M. truncatula accessions (Chapter 4)
3. identify the major loci conferring resistance to P. medicaginis in different
M. truncatula mapping populations (Chapter 5)
4. identify genes, metabolites or pathways involved in compatible and
incompatible interactions between P. medicaginis and M. truncatula
(Chapter 7).
During this research we coincidentially found strong evidence for a reciprocal translocation in the M. truncatula accession A17, which is a key accession in Medicago research. The consequences of this chromosomal rearrangement on the genome sequencing, genetic mapping, synteny studies and cloning of genes are addressed in chapter 6.
33 Chapter 2 General materials and methods
2.1 General materials
The preparation of agarose and polyacrylamide gels, general buffers and solutions were prepared as described by Sambrook et al. (1989). Fungal growth media, potato dextrose agar, wheat meal agar and tap water agar were prepared as described by Ellwood and colleagues (2006a).
2.1.1 Plant material
The majority of M. truncatula accessions used in this study were acquired from the Genetic Resource Centre, SARDI (South Australian Research and
Development Institute, GPO Box 397, Adelaide, South Australia 5001).
Accessions DZ315 and DZ045 were obtained from the Institut National de la
Recherche Agronomique (INRA), Montpellier, France. M. sativa accessions
SA35043, SA36325, and SA38082 were obtained from SARDI. Lupinus albus cv. Kiev Mutant was obtained from the Department of Agriculture and Food
Western Australia (DAFWA, 3 Baron Hay Court, South Perth, Western Australia
6151).
2.1.2 Fungal isolates
All available Phoma medicaginis isolates recovered from Medicago truncatula in Western Australia (WAC4736, WAC4738, WAC4741, WAC7977, and WAC7980) were obtained from DAFWA (3 Baron Hay Court, South Perth,
Western Australia 6151). Isolates OMT1 and OMT5 were isolated from naturally infected M. truncatula in Perth, Western Australia. P. medicaginis var.
34 medicaginis CBS316.90 and P. pinodella CBS318.90 standard reference cultures were acquired from Centraalbureau voor Schimmelcultures (P.O. Box 85167,
3508 AD Utrecht, The Netherlands). Other species used in this study were obtained from DAFWA and included Leptosphaerulina trifolii WAC6693, P. pinodella WAC7978, P. exigua WAC7988, and Ascochyta lentis SATAL. The host, location and original identification for each isolate is presented in Table
2.1. Representative cultures of OMT1 and OMT5 have been deposited with
DAFWA.
2.2 General methods
2.2.1 Plant cultivation
The M. truncatula seeds are stored in pods. After the pods have been harvested they were kept at 37 °C for a week to dry out the pods. After one week the intact pods were stored at room temperature and low humidity, either in paper envelopes or screw cap plastic jars with holes in their lids to allow air circulation.
Seeds were removed from their pods by using a corrugated rubber mat and plasterers hawk with handle. The pods disintegrate as they were rubbed between the rubber mat and the plasterers hawk. Seeds fall in the grooves of the rubber mat and remain undamaged. The seeds were scarified using fine river sand in a mortar and pestle, and then transferred to a Petri dish lined with Whatmann blotting paper and irrigated with sterile water. The seeds were kept at 4oC for at least 48 hours and germinated at room temperature overnight. This generally
35 Table 2.1 Fungal isolates from legume species used in this thesis.
Original Isolate Host Date; Collector; Location identification
SAT AL Lens culinaris 1998; Sweetingham, M; Ascochyta lentis Merredin, WA CBS316.90 M. sativa 1990; Noordeloos, M; P. medicaginis var. Czechoslovakia medicaginis CBS318.90 Pisum sativum 1990; Noordeloos, M; Phoma pinodella Netherlands OMT1 M. truncatula 2000; Oliver, R; Perth WA P. medicaginis OMT5 M. truncatula 2000; Oliver, R; Perth WA P. medicaginis WAC4736 M. truncatula 1986; Barbetti, M; P. medicaginis Gnowangerup, WA WAC4738 M. truncatula 1986; Barbetti, M; P. medicaginis Gnowangerup, WA WAC4741 M. truncatula 1986; Barbetti, M; P. medicaginis Gnowangerup, WA WAC6693 Medicago 1992; Barbetti, M; Leptosphaerulina polymorpha Avondale, WA trifolii WAC7977 M. truncatula 1981; Barbetti, M; Perth, P. medicaginis WA WAC7978 M. truncatula 1981; Barbetti, M; Perth, P. medicaginis WA WAC7980 M. truncatula 1981; Barbetti, M; Perth, P. medicaginis WA WAC7988 M. sativa 1981; Barbetti, M; Harvey, P. medicaginis WA
36 resulted in 90-100% germination rate with seedlings having a radical length of 5-
10 mm.
The seedlings were either planted in pasteurised composted pine bark fines (Richgro Garden Products, Jandakot, Western Australia 6164) or in vermiculite and grown under natural light in a temperature controlled greenhouse
(22oC day, 18oC night). The plants grown in vermiculite were fertilized twice a week using optigrow fertilizer (Growth Technology, O’Connor, Western
Australia 6163). Once M. truncatula accessions reached the fourth trifoliate stage they were infected with P. medicaginis. When large amounts of seeds were needed, M. truncatula plants were transplanted to larger pots containing pasteurised composted pine bark fines, after six weeks growth in small ports.
Plants were bagged with “onion-nets” once the first pods started to turn a grey colour.
2.2.2 Fungal isolation and culture
Pathogens were isolated by surface sterilisation of diseased material from the field (5% ethanol, 1% sodium hypochlorite), followed by three washes in sterile water and plating onto tap water agar with benzimidazole (50 ppm).
Where bacteria were a persistent problem, filter sterilised ampicillin, neomycin,
−1 −1 and streptomycin were added to the agar to give 50 mg. L , 50 mg. L , and 30
−1 mg. L respectively. Similarly isolates obtained from DAFWA were plated onto tapwater agar with 50ppm benzimidazole. The plates were incubated at 22oC for
24–48 hours, and the leading edge of colonies subcultured onto wheat meal agar
(WMA, 12 g ground wheat meal, 12 g agar, and 1 litre of distilled water).
Conidia were harvested at 14 days, and a serial dilution of spores was plated onto
37 water agar (12 g agar and litre of distilled water) to produce single spore cultures to ensure homogeneity. Conidia were harvested after four to six weeks to make glycerol stocks (1 x 107 spores/mL in 25% glycerol). Glycerol stocks of the fungal isolates were stored at -80 °C. As pathogenic fungi can loose their virulence when subcultured in vitro, the fungal cultures were not subcultured, but reisolated from infected host tissue periodically.
For infection, the isolates were grown on WMA plates for four to six weeks. The conidia were harvested by rinsing the plates with sterile milliQ
Water. To release the conidia from the pycnidia, plates were incubated in sterile milliQ water for up to 20 minutes. Conidia were then filtered through a sterile glasswool syringe and counted using a haemocytometer. The conidia concentrations used for spot and spray inoculations are 1 x 106 and 2 x 106 respectively. Tween 20 was added to 0.05% as a surfactant.
38 Chapter 3 Identification and differentiation of Phoma medicaginis isolates present in Australia based on morphology and sequences from five conserved gene regions
3.1 Introduction
In Australia, annual medics are grown to improve pastures and as a break crop in rotation with wheat on some 50 million hectares (Crawford et al., 1989).
M. truncatula is one of the most widely grown of these species (Pearson et al.,
1997). In the field Medicago species are attacked by a range of foliar necrotrophic pathogens, such as Leptosphaerulina trifolii, Colletotrichum trifolii,
Stagonospora meliloti, Cercospora medicaginis, Pseudopeziza medicaginis and
Phoma medicaginis (Tivoli et al., 2006b). These foliar necrotrophs cause serious yield losses in legume agriculture and show very similar disease phenotypes on infected Medicago tissue, which makes them hard to differentiate. Development of effective crop disease management depends on the rapid detection and precise identification of a pathogen. The diagnosis of these foliar pathogens is mostly based on micro- and macro-morphological characteristics such as cultural morphologies including colony and colour characteristics on specific culture media, size, shape, and development of sexual and asexual spores and spore- forming structures and/or physiological characteristics such as the ability to utilize various compounds such as nitrogen and carbon sources. These methods of identification are often time-consuming and do not differentiate isolates from the same genus.
In recent years, DNA-based molecular detection of fungal plant pathogens has emerged as a suit of rapid and reliable diagnostic tool (Levesque,
39 2001; Lievens and Thomma, 2005; Louws et al., 1999; Martin et al., 2000). This involves polymerase chain reaction (PCR) of conserved (gene) regions, in particular the nuclear ribosomal DNA (rDNA). Fungal rDNA occurs as a structured unit consisting of three ribosomal RNA subunit genes that are separated by internal transcribed spacers (ITS). This ITS region is an area which contains alternating areas of high conservation and high variability and allows classification over a wide range of taxonomic levels (White et al., 1990). The
ITS region does not always result in sufficient sequence variation to discriminate between particular isolates/species and therefore other regions including actin
(Weiland and Sundsbak, 2000), β-tubulin (Fraaije et al., 1999) and elongation factor one-alpha (Kristensen et al., 2005) are becoming more intensively studied.
Other molecular diagnostic methods screen random parts of a fungal genome to find diagnostic sequences and successful techniques used include restriction fragment length polymorphisms (RFLP, Donaldson et al., 1995;
Zhang et al., 1997), random amplified polymorphic DNA (RAPD, Jana et al.,
2003) and amplified length polymorphism (AFLP, Gonzalez et al., 1998; Majer et al., 1996). Molecular techniques now allow us to differentiate genera, species, subspecies, races and strains of fungi.
This chapter describes the characterisation and differentiation of Phoma medicaginis isolates collected in Western Australia. This includes colony morphology of the isolates in vitro, their host range and symptoms on M. truncatula. To distinguish the isolates five conserved gene regions were compared: actin, β-tubulin, calmodulin, translation elongation factor 1-α (EF1-
α) and the internal transcribed spacer (ITS).
40 3.2 Material and Methods
3.2.1 Fungal isolation and culture
The Phoma medicaginis isolates used in this chapter were obtained form various sources (paragraph 2.1.2; Table 2.1). Pathogens were isolated and grown as desribed in paragraph 2.2.2. Additionally, a single colony was subcultured onto ½ potato dextrose agar (½ PDA; Becton Dickinson, Franklin Lakes, NJ,
USA) to study colony and colour characteristics. Conidia were harvested after four to six weeks to study conidia size and shape, using a light microscope.
3.2.3 DNA isolation of fungal isolates
Isolates were grown in 10 mL ½ potato dextrose (Becton Dickinson,
Franklin Lakes, NJ, USA) at 22oC for 48 hours. Mycelial mats were blotted to remove excess medium. 0.1 - 0.2 g of fungal material was ground in liquid nitrogen, homogenised in 500 μl DNA extraction buffer (50 mM Tris pH8.0, 25 mM EDTA pH 8.0, 100 mM NaCl and 1% SDS), combined with 20 μl 2.5 mg/mL proteinase K (Sigma, St Louis, MO, USA), and incubated at 65oC for 1 hr. The samples extracted with an equal volume of phenol / chloroform / isoamyl alcohol (25:24:1 v/v). DNA was precipitated with 1/10 volume 3M sodium acetate (pH 6), 0.7 volume isopropanol and pelleted at 20,000g for 15 min. The samples were washed with 80% ethanol, resuspended in 100 μl TE (10 mM Tris,
1 mM EDTA, pH8), and treated with 1 μl RNAase (10 mg/mL, 1 hr. at 37 oC).
DNA concentration was measured on a Perkin-Elmer Lambda 25 spectrophotometer (Perkin-Elmer, Norwalk, CT, USA).
41 3.2.4 PCR amplification and DNA sequencing of five conserved gene regions
Primers ITS1 and ITS4 (White et al., 1990) were used to amplify ITS1,
5.8s subunit, and ITS2 of the rDNA gene cluster. The β-tubulin gene regions were amplified using the Bt2A-F and Bt2B-R primers described by Glass and
Donaldson (1995). Calmodulin gene regions were amplified using the primer set described by Carbone and Kohn (1999). Actin primers (Table 3.2) were designed to conserved regions of the Act1 gene in Septoria tritici (GenBank AJ300310),
Cercospora beticola (AF443281), Botryotinia fuckeliana (AJ000335)
Cladosporium herbarum (AJ300320), and Colletotrichum gloeosporioides
(AF112537), using Vector NTI Suite 9.0 (Invitrogen, Carlsbad, CA, USA). The primers amplify a 400 bp intron spanning fragment. The universal primers described by Carbone and Kohn (1999) to translation elongation factor 1-α (EF-
1-α) amplified all isolates tested but gave poor sequencing results with Phoma isolates WAC4736, 4738, 4741, 7977 and 7980, due to G-C rich stretches.
Therefore nested primers specific to these Phoma isolates were designed, using
Vector NTI Suite 9.0 (Table 3.1).
Temperature gradient PCR was used to identify the optimum annealing temperature for each primer pair, using standard PCR protocol: 100 ng of genomic DNA template, 1 x PCR reaction buffer, 2 mM MgCl2, 0.25 mM of each dNTP, 5 pmol of each primer and 1 unit of Taq polymerase. The thermocycling conditions were: 5 minutes initial denaturation step followed by
37 cycles of 94°C for 30 sec, marker-specific annealing temperatures for 30 sec, and 72°C for 60 sec, then a final extension step of 5 min at 72°C. PCR-products were purified with Mo Bio’s UltraClean™ PCR clean up kit (Mo Bio
42 Table 3.1 Primer name and sequences to study five conserved gene regions in Phoma species. Gene Primer region name Primer sequence Reference
Actin1 Act1-F TTGACCGACTACCTCATGAAGT Ellwood et al., Act1-R AGATACCTGGGTACATGGTGGT 2006 β-tubulin Bt2A-F GGTAACCAAATCGGTGCTGCTTTC Glass and Bt2B-R AACCTCAGTGTAGTGACCCTTGGC Donaldson, 1995 calmodulin Cal-F CAGTTCAAGGAGGCCTTCTCCC Carbone and Cal-R CATCTTTCTGGCCATCATGG Kohn, 1999 EF-1-α EF1a-F CATCGAGAAGTTCGAGAAGG Carbone and EF1a-R TACTTGAAGGAACCCTTACC Kohn, 1999 EF-1-α EF1aN-F CACACCACCATGCCCACA Ellwood et al., (nested) EF1aN-R TTAGCATCTTGTCTTGAAACCT 2006 ITS ITS1 CGTAGGTGAACCTGCGG White et al., 1990 ITS4 CCACCGCTTATTGATATGC
43 Laboratories Inc. Solana Beach, CA, USA). Purified products were direct sequenced with a BigDye 3.1 Terminator Cycle Sequencing Ready Reaction Mix
(Applied Biosystems [AB], Foster City, CA, USA) and an AB Prism 3730 DNA sequencer. The sequences for each gene region were aligned using Vector NTI
Suite 9.0.
3.2.5 Phylogenetic analyses
To compare P. medicaginis isolates from M. truncatula with related species, ITS sequence data from the six additional species sequenced in this study (see Fungal isolates) and ITS sequences from the 9 closest GenBank ITS species were assembled. The Genbank species included Colletotrichum truncatum AF451907, Didymella applanata DAP428170, D. bryoniae
AF297228, D. pinodes AF362064, Epicoccum nigrum AF455455, Phoma glomerata PGL428533, and P. herbarum AY293803. Leptosphaeria maculans
L07735 and Phaeosphaeria nodorum PNU77362 were selected as distant
Dothideomycetes.
Alignments were generated using the ClustalW algorithm in BioEdit v
5.0.9 (Hall, 1999). Gaps were treated as a fifth character and all ambiguous characters and parsimony uninformative characters were excluded prior to analysis. Partition homogeneity tests (Huelsenbeck and Ronquist, 2001) were conducted using PAUP* version 4.0b10 (Swofford, 2001) to determine whether the sequence data from different gene regions were congruent. Phylogenetic analysis based on parsimony was performed on separate and combined data sets in PAUP. The most parsimonious trees were obtained by using heuristic searches with random stepwise addition in 100 replicates, with the tree bisection-
44 reconnection branch-swapping option on and the steepest-descent option off.
Maxtrees were unlimited, branches of zero length were collapsed and all multiple equally most parsimonious trees were saved. Estimated levels of homoplasy and phylogenetic signal (retention and consistency indices) were determined (Hillis and Huelsenbeck, 1992). In the initial analyses all characters were unweighted and unordered; thereafter characters were reweighted according to the consistency index. Branch and branch node supports were determined using 1000 bootstrap replicates (Felsenstein, 1985) and characters were sampled with equal probability (but weights were applied). The phylogenic analysis described in this paragraph was performed by Dr Simon Ellwood.
3.2.6 Plant material and growth
The M. truncatula accessions A17, Borung, DZ315, DZ045, SA8618,
SA11734, SA15951, SA24968, SA27063 and SA30199, M. sativa accessions
SA35043, SA36325, and SA38082 and Lupinus albus cv. Kiev mutant were single seeded for three generations to ensure homogeneity. Seed for other cultivars were commercially sourced. These included: Cicer arietinum cv. Sona;
Lens culinaris cv. Digger; Lupinus angustifolius cvs. Unicrop, Belara, and
Quinlock; Pisum sativum cv. Parafield; M. sativa cv. Sceptre; and Vicia faba cv.
Fiord. All seeds were germinated and plants were grown as desribed in paragraph
2.2.1.
3.2.7 Plant inoculation to determine host range
Inoculum was prepared by growing fungal isolates on WMA at 22oC for
28-35 days under U/V light. Conidia were harvested by incubating plates with 10
45 mL distilled water for 20 min. The suspension was filtered through glasswool, adjusted to 2 x 106 spores/mL, and Tween 20 added to 0.05%. Inoculation of
Medicago accessions was performed at the fourth trefoil stage, or at between three and four weeks of age for species of other legume genera. The pathogenicity and host range tests were performed by spraying with an artists airbrush to runoff, using a rotating platform to ensure an even distribution over plant surfaces. To ensure high humidity to stimulate conidia germination, plants were placed in sealed propagator trays for 48 h.
3.3 Results
3.3.1 Growth behaviour and morphology in vitro
The obtained isolates listed in Table 2.1 were all single spored and plated on ½ PDA to determine the colony characteristics (Figure 3.1; Table 3.2). The shape and size of the harvested conidia were examined under a light microscope and the results are summarised in Table 3.2. These results confirmed the original identification (Table 2.1) of Australian isolates with the exceptions of WAC7978 and WAC7988. Both WAC7978 and WAC7988 were designated as P. medicaginis and produce oblong to ellipsoid, aseptate conidia. However, both isolates have distinctive colony morphologies (Figure 3.1; Table 3.2). The spores of WAC7988 are typically smaller than P. medicaginis, while WAC7978 also produces uniseptate as well as aseptate conidia.
46 Table 3.2 Morphological features of Phoma isolates from M. truncatula and virulence tests.
Isolate Colony Conidia Conidia size Pathogenicity on characteristics range (μm; n = M. truncatula 30) OMT5 Greenish brown Aseptate, ellipsoid 4.0-8.1 (±1.1) x Virulent with radial to oblong, hyaline 1.8-2.6 (±0.3) sectoring WAC4736 Yellowish brown Aseptate, ellipsoid 5.3-7.5 (±0.9) x Virulent with woolly white to oblong, hyaline 1.8-2.9 (±0.4) mycelium in centre WAC4738 Yellowish brown Aseptate, ellipsoid 4.2-4.8 (±0.2) x Virulent with woolly white to oblong, hyaline 1.3-2.0 (±0.2) mycelium in centre WAC4741 Greenish brown, Aseptate, 4.0-7.0 (±1.1) x Virulent sparse aerial occasionally 1.3-1.8 (±0.1) mycelium uniseptate, hyaline, ellipsoid to oblong WAC7977 Grey-brown, Aseptate, ellipsoid 4.5-7.8 (±0.9) x Virulent moderate aerial to oblong, hyaline 1.5-2.4 (±0.3) mycelium WAC7978 Orange-brown, Aseptate and Aseptate: 3.1- Moderate felty, sparse white uniseptate (ratio 5.7 (±0.8) x 1.5- aerial mycelium 5:1). 2.2 (±0.2) Ellipsoid to oblong, Uniseptate: 6.2- hyaline 6.6 (±0.2) x 1.8- 2.4 (±0.3) WAC7980 Greenish brown, Aseptate, ellipsoid 4.4-8.8 (±1.0) x Virulent sparse aerial to oblong, hyaline 1.8-2.4 (±0.2) mycelium WAC7988 Brown, no aerial Aseptate, ellipsoid 3.5-5.1 (±0.5) x Non-pathogenic mycelium, slow to oblong, hyaline 1.2-2.2 (±0.3) growing with abundant pycnidia
47
Figure 3.1 Colony morphology of P. medicaginis isolates from M. truncatula, 12 days after plating on ½ PDA.
WAC4736 WAC4738 WAC4741
WAC7977 WAC7980 OMT5
WAC7978 WAC7988
48 3.3.2 DNA sequencing
Sequences of five gene regions (ITS, actin, β-tubulin, calmodulin and EF-
1-α) were amplified in P. medicaginis isolates and their closely related genera, with the exception of calmodulin in Leptosphaerulina trifolii WAC6693. This is presumably due to loss or alteration of a primer binding site in L. trifolii
WAC6693. The universal primers described by Carbone and Kohn (1999) to translation elongation factor 1-α (EF-1-α) amplified all isolates tested but gave poor sequencing results with Phoma isolates WAC4736, WAC4738, WAC4741,
WAC7977 and WAC7980. The elongation factor introns in these isolates contain
G-C rich stretches resulting in polymerase slippage and abrupt sequencing signal reduction. Therefore nested, P. medicaginis-specific intron-targeted primers were designed to characterise the intervening sequence. All DNA sequences have been deposited in GenBank, under accession numbers AY131200, AY131201, and
AY831507-AY831563.
WAC4736, WAC4738, WAC4741, WAC7977, WAC7980, and OMT5 exhibited a 97.2–97.4% identity in nucleotide composition compared to P. medicaginis v. medicaginis CBS 316.90 across the five gene regions. This suggests these isolates are closely allied to, but different from, this reference culture. The majority of nucleotide differences between isolates were accounted for by high polymorphisms in EF-1α (Figure 3.3). Including P. medicaginis v. medicaginis CBS 316.90, EF-1α resolved four genotypes. EF-1α amplicons for
P. medicaginis isolates ranged in size from 6–800bp (Figure 3.2), twice the expected length found among other Dothideomycetes. Examination of the nested intron sequences showed the existence of a 55bp unit repeated five consecutive times in each isolate.
49
Figure 3.2 Amplification of EF-1-α PCR products. Amplicons of P. medicaginis
CBS316.90 and the other P. medicaginis isolates show a size range from 6-800 bp, at least twice the length of other Dothideomycetes representatives, which are all marginally greater than 300bp. The DNA ladder starts with 1.5 kb fragment followed by a 1.0 kb fragment to 100 bp fragment declining in size by 100 bp increments.
50 Figure 3.3 Alignment of EF-1-α sequence between P. medicaginis var. medicaginis CBS 316.90 and the Australian Phoma isolates (OMT5, WAC4736 and WAC4741). Primers used were EF-1-αN-F (5´-CACACCACCATGCCCACA-
3´) and EF-1-αN-R (5´-TTAGCATCTTGTCTTGAAACCT-3´).
1 45 EF1a CBS 316.90 (1) CACAACACCATGCCCACAGCGTATTTTGCACCCTCCAGTGTGTTG EF1a OMT5 (1) CACAACACCATGCCCACAGCGTATTTTGCACCCTCCAGTGCGTTG EF1a WAC4736 (1) CACAACACCATGCCCACAGCGTATTTTGCACCCTCCAGTGCGTTG EF1a WAC4741 (1) CACAACACCATGCCCACAGCGTATTTTGCACCCTCCAGTGCGTTG Consensus (1) CACAACACCATGCCCACAGCGTATTTTGCACCCTCCAGTGCGTTG 46 90 EF1a CBS 316.90 (46) CACCGCGAGCTTTTCGACCTTGGTCAAAAGCCGCGACACCCTCCA EF1a OMT5 (46) CACCGCGAGCTTTTCGACCTCGGTCAAAAATCGCGACACCCTCCA EF1a WAC4736 (46) CACCGCGAGCTTTTCGACCTCGGTCAAAAATCGCGACACCCTCCA EF1a WAC4741 (46) CACCGCGAGCTTTTCGACCTCGGTCAAAAATCGCGACACCCTCCA Consensus (46) CACCGCGAGCTTTTCGACCTCGGTCAAAAATCGCGACACCCTCCA 91 135 EF1a CBS 316.90 (91) CGCCTCCTTGCACCGCGAGCTTTTCGACTTCGGTCAAAAGCCGCG EF1a OMT5 (91) CACCTCCTTCCATCACGAGCCTCTTGACGTCTGTCAAAAATCGCG EF1a WAC4736 (91) CACCTCCTTCCATCACGAGCCTTTTGACCTCTGTCAAAAATCGTG EF1a WAC4741 (91) CACCTCCTTCCATCACGAGCCTTTTGACCTCTGTCAAAAATCGTG Consensus (91) CACCTCCTTCCATCACGAGCCTTTTGACCTCTGTCAAAAATCGTG 136 180 EF1a CBS 316.90 (136) ACACCCTCCACACCTCCTTGCACCGTGAGCTTTTCGACTTCGGTC EF1a OMT5 (136) ACACCCTCCACACCTCCTTCCATCACGCGCTTTTTGACCTCTGTC EF1a WAC4736 (136) ACACCCTCCACACCTCCTTGCACCGCGAGCTTTTCGACCTTGGCC EF1a WAC4741 (136) ACACCCTCCACACCTCCTTGCACCGCGAGCTTTTCGATCTCGGTC Consensus (136) ACACCCTCCACACCTCCTTGCACCGCGAGCTTTTCGACCTCGGTC 181 225 EF1a CBS 316.90 (181) AAAAGCCGCGACACCCTCCACACCTCGT-TCCATCGCGAGCTTTT EF1a OMT5 (181) AAAAATCGTGACACCCTCCACACCTCCT-TGCACCGCGAGCTTTT EF1a WAC4736 (181) GAAAGTCGCGACACCCTCCACACCCCCTCTTCACCGCGAGCTTTT EF1a WAC4741 (181) AAAAGCCGCGACACCCTCCACACCCCCTCTTCACCGCGAGCTTTT Consensus (181) AAAAGTCGCGACACCCTCCACACCTCCTCTTCACCGCGAGCTTTT 226 270 EF1a CBS 316.90 (225) CGATCTCAGTCAAAAGCCGCGACACCCTCCACAC-CTCCTTGCAC EF1a OMT5 (225) TGACCTTGGCCAAAAGTCGCGACACCCTCCACAC-CTCCTTGCAC EF1a WAC4736 (226) CGATCTCGGTCAAAAGCCGTGACACCCTCCACACCCCCTCTTCAC EF1a WAC4741 (226) CGATCTCGGTCAAAAGCCGCGACACCCTCCACACTCTCCTTCCAT Consensus (226) CGATCTCGGTCAAAAGCCGCGACACCCTCCACAC CTCCTTGCAC 271 315 EF1a CBS 316.90 (269) CGCGAGCTTTTCGACCTTGGTCAAAAGCCGCGACACCCTCCACAC EF1a OMT5 (269) CGCGAGCTTTTCGATCTTGGTCAAAAGCCGCGACACCCTCCACAC EF1a WAC4736 (271) CGCGAGCTTTTCGATCTCGGTCAAAAGCCGCGACACCCTCCACAC EF1a WAC4741 (271) CGCGAGCTTTTCGATTTCAGTCAAAAGCCGCGACACCCTCCAGCG Consensus (271) CGCGAGCTTTTCGATCTTGGTCAAAAGCCGCGACACCCTCCACAC 316 337 EF1a CBS 316.90 (314) -CTCCTTGCATCGCGAGCTTTT EF1a OMT5 (314) -CTCCTTGCACCGCGAGCTTTT EF1a WAC4736 (316) TCTCCTTCCATCGCGAGCTTTT EF1a WAC4741 (316) TATC-TTGCATCGCGAGCTTTT Consensus (316) TCTCCTTGCATCGCGAGCTTTT
51 3.3.3 Phylogenetic analyses
The P. medicaginis isolates in this study were initially compared with closely related species using ITS sequence data alone, as for most species only this data was available in GenBank. The aligned data set consisted of 601 characters of which 80 were parsimony informative. The data set contained significant phylogenetic signal compared to 1000 random trees (P<0.01, g1 = -
0.91), and initial heuristic searches resulted in nine most parsimonious trees of
167 steps (CI = 0.65, RI = 0.77).
One of nine most parsimonious trees (Figure 3.4) shows P. medicaginis v. medicaginis CBS316.90 is closer to P. medicaginis isolates from M. truncatula than to other species. The tree also shows no clear association between genus designation and clade, with reasonable bootstrap support for A. lentis grouping with P. herbarum and strong bootstrap support for D. pinodes grouping with E. nigrum, and D. Bryoniae with P. exigua. EF-1α showed substantial differences in length and sequence between P. medicaginis isolates and other species. The dissimilarity prevented sequence alignments with other species and phylogenetic analyses using combined gene regions were conducted among P. medicaginis isolates only. ITS and calmodulin sequence data were excluded from the analyses because the ITS had no informative regions, while a partition homogeneity test was significant (P = 0.001) that EF-1α and calmodulin data were in conflict. The aligned data set of actin, β-tubulin, and EF-1α consisted of 1056 characters of which 46 were parsimony informative. The data set contained significant phylogenetic signal compared to 1000 random trees (P<0.01, g1 = -1.21), and heuristic searches resulted in a single most parsimonious tree of 52 steps (CI =
52 Figure 3.4 Phylogram of one of nine most parsimonious trees based on nuclear
DNA ITS sequence data. P. medicaginis isolates obtained from M. truncatula in
Western Australia are in bold. Branch support (bootstrap values) is given above branches based on 1000 bootstrap replicates. The tree is rooted to Phaeosphaeria nodorum.
100 P. nodorum PNU77362 L. maculans L07735 Ascochyta lentis SAT AL
P. herbarum AY293803 60 C. truncatum AF451907 OMT1 OMT5 WAC4736 WAC4738 WAC4741 100 WAC7977 WAC7980 P. medicaginis CBS316.90 L. trifolii WAC6693 D. applanata DAP428170
96 D. pinodes AF362064 E. nigrum AF455455 P. glomerata PGL428533
90 WAC7978 P. pinodella CBS318
91 D. bryoniae AF297228 P. exigua WAC7988
5 changes
53 Figure 3.5 Single most parsimonious phylogram of P. medicaginis isolates based on actin, β-tubulin, and EF-1α sequence data. Branch support (bootstrap values) is given above branches based on 1000 bootstrap replicates.
P. medicaginis CBS316.90
100 WAC4736 WAC4738 98 WAC4741 100 WAC7977 WAC7980
100 OMT1 OMT5 5 changes
54 0.98, RI = 0.99, Figure 3). Isolates WAC4736, WAC4741, and OMT5 were selected as representatives of each of the three genotypic groups of P. medicaginis isolates from M. truncatula for infection experiments.
3.3.3 Host-range
The P. medicaginis isolates were all virulent on M. truncatula, producing necrotic lesions within 2 days of inoculation and pycnidia by 10-14 days.
Inoculations with WAC7988 showed the isolate to be non-pathogenic on M. truncatula, while WAC7978 exhibited fewer, smaller lesions compared to P. medicaginis isolates. P. medicaginis isolates WAC4736, WAC4741, and OMT5, representatives of each clade (Figure 3.5), were then used to infect a wider range of legume species. These isolates showed no disease symptoms on the legume species tested, with the exceptions of M. sativa and M. truncatula. M. sativa accessions showed levels of disease equivalent to M. truncatula (Figure 3.6).
3.4 Discussion
The importance of the isolates in this study lies in their pathogenicity on
M. truncatula. As a model legume, we are interested harnessing the genetic resources available to gain an understanding of the genetic basis of resistance to necrotrophic fungi. A prerequisite to understanding isolate specificity and host resistance lies in resolving relationships with allied species and between isolates.
It is therefore essential that that isolates are correctly identified.
Based on colony morphology (Figure 3.1) and conidia size and shape
(Table 3.2) the isolates WAC4736, WAC4738, WAC4741, WAC7977,
55 Figure 3.6 Macroscopic disease symptoms on M. truncatula and M. sativa 7 dpi with P. medicaginis. (A) Necrotic lesions on a trifoliate leaf of M. sativa
SA35043 caused by P. medicaginis OMT5. (B) Stem and leaf lesions on M. truncatula SA3054 infected with P. medicaginis WAC4736.
A B
56 WAC7980, OMT1 and OMT5 showed the morphological characteristics of P. medicaginis. They were all pathogenic on M. truncatula. In contrast, WAC7988 produced significantly smaller conidia uncharacteristic for P. medicaginis and furthermore was incapable of infecting M. truncatula (Table 3.2). Out of all the species used in this study, the ITS sequence of WAC7988 was most similar to
Didymella bryoniae AF297228 (Figure 3.4). However recent BLASTN against
Genbank (Altschul et al 1997) revealed only a 1 bp difference to the ITS sequence of Phoma exigua isolate (AJ608976). P. exigua produces smaller conidia than P. medicaginis (Boerema et al 2004) and has not been reported to cause disease on M. truncatula. Therefore the isolate was re-named Phoma exigua WAC7988.
In contrast to P. exigua WAC7988, isolate WAC7978 was pathogenic on
M. truncatula and produces uniseptate as well as aseptate conidia which is uncharacteristic for P. medicaginis. The ITS and EF-1α sequences of WAC7978 each had a 1bp difference to the ITS and EF-1α sequences of Phoma pinodella
CBS318.90. Both P. pinodella CBS318.90 and WAC7978 lack the P. medicaginis EF-1α 55 bp repeat unit, clearly discriminating them from P. medicaginis isolates. Therefore WAC7978 was concluded to be a Phoma pinodella isolate and not a Phoma medicaginis isolate.
The Australian P. medicaginis isolates were compared to the most genetically similar species in GenBank. Twenty, predominantly North American,
P. medicaginis ITS sequences available in Genbank (AF079775, AY504634,
DQ092494, DQ096581-93, DQ100417, DQ109958-60) and the P. medicaginis v. medicaginis CBS316.90 reference culture examined here share the same single nucleotide difference with the isolates in this study. This suggests the P.
57 medicaginis isolates from M. truncatula in Western Australia form a group closely related to all other isolates examined to date, but that isolates other than these form a distinct taxon, as depicted in the ITS tree (Figure 3.4) and supported in the combined analysis tree (Figure 3.5).
Maximum parisimony showed no support for monophyletic groups of species, but rather strong support for polyphyly among Phoma and Didymella.
The number of nucleotide differences indicates Leptosphaerulina species should be assigned to different genera, or conversely Phoma expanded to incorporate
Ascochyta, Epicoccum, and Phoma. Faris-Mokaiesh et al. (1996) and Reddy et al. (1998) found similar phylogenetic conflicts among Phoma and Didymella, whereby two organisms from different genera were more similar than two organisms of the same genera.
The highly polymorphic P. medicaginis EF-1α 55 bp repeat unit enabled isolate genotypes to be clearly distinguished. The separation of the isolates was consistent with the sum differences from the ITS, actin and β-tubulin, gene regions, other features such as colony morphology (Figure 3.1), and discrimination comparable to randomly amplified polymorphic DNA analysis
(Ellwood et al., unpublished data). The repeat was not present among the other species sequenced, and shows no homology to sequences or motifs in GenBank.
The nested primers designed to EF-1α amplify within an intron, where duplication of non-coding DNA provides an explanation for the hyper-variable nature of this gene region. The EF-1α intron region therefore provides a specific means of rapidly distinguishing closely related strains. Despite being in conflict with EF-1α, the calmodulin gene region further differentiated WAC7977 from
58 WAC4741 and WAC7980, since WAC7977 had 5 bp changes to WAC4741 and
WAC7980 and was identical to the OMT5 calmodulin gene region.
Both OMT1 and OMT5 were collected from the same location and were identical in all the five gene regions sequenced and morphological characters studied. Similarly, WAC4736 and WAC4738 were collected from the same location in the same year and showed no morphological differences and had identical sequences for the gene regions studied. Both could perhaps be identical
P. medicaginis isolates but further studies are needed to confirm this.
P. medicaginis isolates from M. truncatula failed to induce both compatible or incompatible disease phenotypes in legumes other than M. truncatula and the closely related M. sativa. This contrasts with previous reports documenting a wide host range (Kinsey, 2002) among the Papilionaceae but also within the Cruciferae and Solanaceae. Many such reports require verification but suggest P. medicaginis v. medicaginis may be a less discriminating pathogen and underlines the need for characterisation of the population structure, genetic diversity and host specificity of this species.
In conclusion, we correctly identified seven P. medicaginis isolates, based on both morphological characteristics and sequence data of five conserved gene regions. Based on the EF-1α sequence data we could group them into three different clades. A representative of each clade was next used to screen a large number of M. truncatula accessions to examine isolate specificity and genetic variation in disease resistance to P. medicaginis.
59 Chapter 4 Screening of the core Medicago truncatula collection with three different Phoma medicaginis isolates
4.1 Introduction
In Australia, annual medics are used in legume-ley-farming systems
(Crawford et al., 1989) and are estimated to be grown on over 4.5 million hectares (Hill and Donald, 1998). The increased interest in the use of M. truncatula in Australian agriculture contributed towards the conservation of annual Medicago germplasm. Over a period of 58 years the South Australian
Research and Development Institute has developed a M. truncatula collection with a total of 5509 accessions from 40 countries (Nair et al., 2006). Besides the
Australian collection, there are three other stock centres with a M. truncatula germplasm collection (USDA ARS National Plant Germplasm System, INRA
France, and the Noble Foundation). In 1999 Skinner and colleagues developed a core collection of Medicago species of which 231 were M. truncatula accessions.
A core collection is a subset of accessions representing the genetic variability in the whole collection, which enables the variation in large collections to be more efficiently utilised. The M. truncatula accessions of this core collection are highly diverse, with an average of 25 microsatellite alleles per locus among 192 different accession individuals sampled (Ellwood et al., 2006b).
The objectives in this chapter are firstly to develop screening techniques to evaluate the SARDI core accessions for sources of resistance to three different
Australian P. medicaginis isolates and secondly to examine the interaction between pathogen genotype and host resistance.
60 4.2 Material and methods
4.2.1 Plant material, fungal isolates and inoculum preparation
The M. truncatula core collection accessions were grown as described in paragraph 2.2.1. To ensure genetic homozygosity, a single randomly sampled individual from each accession was single seeded for two generations.
Phoma medicaginis isolates WAC4736 and WAC4741 were obtained from Department of Agriculture and Food (DAFWA), Western Australia, and isolate OMT5 was isolated from naturally infected M. truncatula in Perth,
Western Australia. All three isolates were single spored to ensure homogeneity as described in paragraph 3.2.2. Inoculum for the various methods was prepared by growing fungal isolates on WMA at 22oC for 28-35 days under U/V. Conidia were harvested by incubating plates with 10 mL distilled water for 20 min. The suspension was filtered through glasswool, adjusted to appropriate concentrations (either 1-2 x 106 spores/mL, and Tween 20 added to 0.05%) using a light microscope and a haemocytometer.
4.2.2 Plant inoculations
Three different screening methods were designed to screen a subset of M. truncatula accessions and the results compared so that one or two methods could be chosen to screen a larger set of M. truncatula accessions. The subset of M. truncatula accessions consisted of: A17, Borung, DZ315, DZ045, SA8618,
SA11734, SA15951, SA24968, SA27063, and SA30199 and were and were selected as a genetically diverse set of M. truncatula accessions based on the
61 genetic diversity study performed by Ellwood et al., 2006 using six microsatellite regions (Figure 4.3).
4.2.2.1 Whole plant sprays
All M. truncatula accessions were germinated and grown as described in paragraph 2.2.1. Inoculation of M. truncatula accessions was performed at the fourth trifoliate stage. Plants were randomised in trays containing 18 pots per tray, three plants per pot and three biological replicates per accession. Plants were infected with 2 x 106 spores/mL (0.05% Tween 20), using an artist airbrush until runoff. To ensure an even distribution of the conidia over plant surfaces they were sprayed on a rotating platform. The trays were sealed with a transparent covers for 48 hours to ensure high humidity to stimulate conidia germination. Plants were macroscopically evaluated for disease phenotype at ten days post inoculation (dpi), and rescored at 14 dpi to confirm more resistant disease reactions. Disease resistance of the M. truncatula accessions to the three isolates was evaluated on an adjusted 1-5 scale devised by Salter and Leath
(1992), with an additional class, 0, for complete absence of symptoms. This disease rating is very similar to the scale used to screen the American annual
Medicago spp. core germplasm collection for P. medicaginis resistance (O'Neill et al., 2003) and is rated as followed (Figure 4.1A-F):
0 – complete absence of disease symptoms;
1 – healthy, almost symptom free, small ( 2 – small (<2mm), brown or black lesions or flecks; no defoliation; 62 3 – larger (2 to 3mm), discrete lesions; lesions may be on leaves and petioles; usually no chlorosis or defoliation; 4 – large (>3mm) lesions; no defoliation; petiole lesions; 5 – lesions >3mm, fruiting; dead leaves or defoliation. 4.2.2.2 Whole plant spot inoculation of leaves Plants were grown in the glasshouse as described in paragraph 2.2.1. Plants at the fourth trifoliate stage were randomised in trays containing 15 pots per tray, three plants per pot and three biological replicates per accession. Plants were infected with 10 μL droplets of a 1 x 106 spores/mL (0.05% Tween 20) spore suspension on five leaves per plant. These were the unifoliate leaf, the middle and one lateral leaflet of the first trifoliate leaf and the middle and one lateral leaflet of the second trifoliate leaf. This method was developed because M. truncatula accessions of the SARDI core are highly variable in their growth habit, leaf architecture and surface characteristics i.e. presence or absence of leaf hairs, which affect the volume of inoculum adhering to the leaf surface. To ensure high humidity to stimulate conidia germination, plants were placed in sealed propagator trays for 48 hours. Plants were macroscopically evaluated for disease phenotype at seven days post inoculation (dpi), and rescored at 10 dpi to confirm more resistant disease reactions. Spot inoculated plants were rated on a related scale from 0-5 (Ellwood et al., 2006c: Figure 4.2A-F) and as follows: 0 - no disease reaction; 63 Figure 4.1 Macroscopic disease symptoms of spray inoculated leaves (A) absence of disease symptoms (B) healthy, almost symptom free, small ( A B C D E F 64 Figure 4.2 Macroscopic disease symptoms of spot inoculated leaves (A) no disease reaction (B) small brown or black flecks at the inoculation site (typically 3mm in diameter) (C) large lesions spreading beyond the inoculation site, chlorosis limited to a 1 mm margin around the lesion (D) necrotic lesion and chlorosis covering up to 1/3 of the leaf area (E) necrotic lesion and chlorosis covering up to 4/5 of the leaf area (F) necrotic lesion, entire leaf chlorotic or dead A B C D E F 65 1 - small brown or black flecks at the inoculation site (typically 3mm in diameter); 2 - large lesions spreading beyond the inoculation site, chlorosis limited to a 1 mm margin around the lesion; 3 - necrotic lesion and chlorosis covering up to 1/3 of the leaf area; 4 - necrotic lesion and chlorosis covering up to 4/5 of the leaf area; 5 - necrotic lesion, entire leaf chlorotic or dead. 4.2.2.3 Detached leaf assay Plants were grown in the glasshouse as described in paragraph 4.2.2.1. The unifoliate leaf and the first and second trifoliate leaf were cut-off at the stem and transferred to 0.15% benzimidazol plates with the ends of the leaves embedded into the agar. The leaves were spot inoculated with 10 μL droplets of a 1 x 106 spores/mL (0.05% Tween 20) spore suspension. The plates were wrapped in parafilm and incubated at 20 °C in a 12 hour day/night cycle. This method was based on detached leaf assays successfully applied in the Stagonospora nodorum – wheat interaction (Solomon et al., 2003). The detached leaves were macroscopically evaluated for disease phenotype at 7 dpi using a disease score scale similar to whole plant spot inoculation of leaves (Figure 4.2A-F): 0 - no disease reaction; 1 - small brown or black flecks at the inoculation site (typically 3mm in diameter); 2 - large lesions spreading beyond the inoculation site, chlorosis limited to a 1 mm margin around the lesion; 3 - necrotic lesion and chlorosis covering up to 1/3 of the leaf area; 4 - necrotic lesion and chlorosis covering up to 4/5 of the leaf area; 66 5 - necrotic lesion, entire leaf chlorotic or dead. 4.2.3 Statistical analysis of disease score data Two-way ANOVA and Tukey-Kramer honetly significant difference test at P ≤ 0.05 were used to compare the means for disease resistance scores for each of the isolates tested. Departure from normality for the distribution of disease scores was tested using the W test of Shapiro and Wilk (Lynch and Walsh, 1997). All statistical analysis was carried out using the software package JMP IN 5.1 (SAS Institute, Cary, USA). 4.3 Results 4.3.1 Comparison of the different inoculation methods A subset of ten M. truncatula accessions (A17, Borung, DZ045, DZ315, SA8618, SA11734, SA15951, SA24968, SA27063, and SA30199) were selected as a genetically diverse set of M. truncatula accessions based on the genetic diversity study performed by Ellwood et al., 2006 using six microsatellite regions (Figure 4.3). Each of the accessions is a representative of a different clade in the Neighbour-joining tree. Ten accessions were challenged with three different P. medicaginis isolates (WAC4736, WAC4741 and OMT5). All accessions were grown in a temperature controlled glasshouse until they reached the fourth trifoliate stage and were then infected with the various isolates in three different ways. The first screening method uses an artist airbrush to spray inoculate the Medicago accessions and is a screening technique commonly used to assess P. medicaginis resistance (O'Neill et al., 2003; Salter and Leath, 1992). 67 Following inoculation, contrasting phenotypes were observed among the ten accessions at 10 and 14 dpi respectively. Severe black stem and leaf spots were observed in accession SA11734 upon infection with the three P. medicaginis isolates (Figure 4.1 E, F) with chlorotic tissue appearing in infected leaves at 7dpi followed by pycnidia formation as early as 10 dpi. In contrast accession SA27063 and DZ045 exhibited healthy, almost symptom free leaves with the occasional small (< 1mm) black lesion when spray inoculated with P. medicaginis OMT5 and WAC4736 (Figure 4.1 A, B). The second method also infects intact plants, but leaves were spot inoculated as opposed to spray inoculation. The P. medicaginis symptoms appear as early as three dpi and chlorosis around the original infection site as early as 5 dpi in susceptible accessions. In susceptible interactions, the fungus successfully penetrated the plant cells and spreads beyond the inoculation site. A halo of chlorosis spread ahead of the initial infection zone. After 7-10 days post infection the entire infected leaves are chlorotic or necrotic and the fungus has formed pycnidia (Figure 4.2E, F). In resistant accessions however, the fungus was not able to spread outside the inoculation site and no chlorosis or necrosis was observed 7-10 days post infection (Figure 4.2A, B). No spread of the fungus was observed in the later stages of infections, until chlorosis naturally occurred due to ageing of the leaves. 68 Figure 4.3 Position of M. truncatula accessions used for comparing the various screening methods on relatedness scale. (Neighbour-joining in Mega 2.1; picture adapted from Ellwood et al., 2006). 2715u 2729u 9866 14688 21892t M. truncatula var 18395u 10962t 17498t 10964t 12564t 22922t 28645t tricycla 8642 29620 29867 2826 3536 4818 A17 Jester 774 A17 775 15951 1306 1326 1335 SA15951 3569 4480 3648 27774 8105 3047 14829 15268 8625 10406 3713 11954 31438 9675 9888 28339l 24576 8638 25654 2806 8619 29625 8623 31443 6088 28889 18242t 25669 31442 Cyprus 8618 25664 10481 SA8618 F83005 27882 1562 4327 4330 18346 9693 9700 4456 12451 25941 3308 30199 12455 9720 SA30199 9642 9649 8601 9728 9876 9456 Borung 27784 Mogul Borung 9141 25898l 4087 9710 Caliph 8916 9140 9707 9856 21302I 8604l 9048 9820 8454 9138 3054 24968t 3116l 19995 SA24968 3562 14163 4303 17777 3749 2203 11734 2748 8871 SA11734 A20 21560 3919 9121 9295 21590 2162 9062 30203 4947 3573 27176l 2841 1516 2109 25926 9137 18532 2193 9670 2084 24714 27138 2168 27062 27137 28097 2204 8935 9944 18543 17590 30740 25915l 1499 1502t 10419u Sephi 1316 3537 8626 22323 9851 395 2820 9434 28375l 21932 9119 DZA045 9970 28064 11753l DZA045 18935t 21362 28712 7749 27185l DZA315 27192l 14161 DZA315 9356 9357 19957 396 22322 31376 9712 9715 17645 4586l 8496 9596 25226 2840 1489 2218 19998 3363 17562 28089 9049 28099 3916 19964 28110 21819 27063 28890 SA27063 69 A third method, the detached leaf assay (DLA), was developed to be able to control temperature, day length and humidity. The DLA method provided continously high humidity, which seemed to favour the P. medicaginis infection. The P. medicaginis disease symptoms were similar to the ones observed when spot inoculating intact plants, but the disease progression was faster with initial disease symptoms appearing as early as 2 dpi and chlorosis spreading ahead of the infection site as early as 3 dpi. When the mean disease scores of the different screening methods were compared a significant correlation for the disease score for spot inoculation and spray inoculation was observed for all ten accessions tested with the three isolates (Tukey Kramer HSD-test P ≤ 0.05; Figure 4.4). In most cases the DLA disease scores for isolate WAC4736 were significantly different from the disease scores observed when spray and spot inoculating (Tukey Kramer HSD-test P ≤ 0.05; Figure 4.4). These findings were also observed in some cases for isolates WAC4741 and OMT5 (Table 4.1), where most disease scores for the spray and spot inoculations correlate. The spot inoculation of intact plants was chosen to evaluate the SARDI core collection of since this gave the most reproducible results with little variation among individual replicates (Figure 4.4). This is most likely due to the fact the inoculum dose was consistent and was not affected by growth habit, leaf architecture and leaf characteristics. 4.3.2 Evaluation of disease resistance to P. medicaginis in the M. truncatula core collection A set of 85 M. truncatula accessions obtained from SARDI were spot inoculated with three P. medicaginis isolates, WAC4736, WAC4741 and OMT5. 70 Most of the 85 accessions in the M. truncatula core collection were susceptible to P. medicaginis disease (Table 4.1). A normal distribution of disease scores was observed for all three isolates (P < 0.0001 by Shapiro and Wilk W test) with mean disease scores ranging from 2.63-3.18 between the isolates, with WAC4741 the most virulent (Figure 4.5). Over 19% of accessions, SA2193, SA2715, SA3054, SA8618, SA9062, SA9357, SA9596, SA10964, SA11734, SA14829, SA17498, SA17562, SA27774, SA27784, SA28089, and SA28645 were susceptible to all three isolates, with a score of 3 or greater (Figure 4.6). Resistance to all isolates was not observed, with the exception of SA1489 and SA8623 with a disease score of 2 or less (Figure 4.6). Rather, resistance in accessions exhibiting a score of 1.5 or less was observed against individual isolates. Firstly, accessions SA396, SA1306, SA1502, SA8604, SA9456, SA21302, and SA24576 showed isolate specific resistance to WAC4736. Secondly, accessions SA3047, SA9710 and SA11753 showed isolate specific resistance to WAC4741 (Figure 4.6; Table 4.1). Thirdly, accessions SA9866, SA11954, SA18346 and SA27063 showed isolate specific resistance to OMT5. The accessions SA9707, SA12451, SA23859 and SA28064 showed resistance to P. medicaginis isolates WAC4736 and OMT5 with a disease score of 1.5 or less, and were susceptible to P. medicaginis isolates WAC4741 with disease scores ranging from 2.6-4.32 (Figure 4.6; Table 4.1). 71 Figure 4.4 Comparison of three different screening methods to look for differential responses to P. medicaginis isolates (WAC4736, 4741 and OMT5) in 10 M. truncatula accessions. Mean disease score was based on three biological replicates and two independent experiments, using the scales described in paragraph 4.2.2.1-3 for each respective screening method. The mean disease scores for each P. medicaginis isolate not sharing a letter are significantly different by Tukey Kramer-HSD test (P ≤ 0.05). A17 Borung 6.00 6.00 a a a a a a 5.00 a a 5.00 b b a a a 4.00 4.00 b b 3.00 b 3.00 b 2.00 2.00 a 1.00 1.00 Mean disease score Mean disease score 0.00 0.00 WAC4736 WAC4741 OMT5 WAC4736 WAC4741 OMT5 DZA045 DZA315 6.00 6.00 a a a a 5.00 5.00 b b a 4.00 b 4.00 a a b b b a a a 3.00 b b 3.00 2.00 2.00 1.00 1.00 Mean disease score Mean disease score 0.00 0.00 WAC4736 WAC4741 OMT5 WAC4736 WAC4741 OMT5 SA11734 SA15951 6.00 a ab a b 6.00 a a a b 5.00 b 5.00 a 4.00 a 4.00 a b b a a 3.00 3.00 a a 2.00 2.00 1.00 1.00 Mean disease score Mean disease score 0.00 0.00 WAC4736 WAC4741 OMT5 WAC4736 WAC4741 OMT5 SA24968 SA27063 6.00 6.00 a a b 5.00 a 5.00 b a a 4.00 4.00 b a b a a a 3.00 b 3.00 a b a a 2.00 2.00 1.00 1.00 Mean disease score Mean disease score 0.00 0.00 WAC4736 WAC4741 OMT5 WAC4736 WAC4741 OMT5 SA30199 SA8618 a a a a 6.00 a a 5.00 a a a a 5.00 a b b 4.00 a a 4.00 a b b 3.00 3.00 2.00 2.00 1.00 1.00 Mean disease score Mean disease score 0.00 0.00 WAC4736 WAC4741 OMT5 WAC4736 WAC4741 OMT5 DLA Spot Spray 72 Figure 4.5 Statistical analyses of the phenotype data of the M. truncatula core accessions. Distribution of disease scores for the 85 M. truncatula accessions infected with P. medicaginis WAC4736, WAC4741 and OMT5 seven days post infection. The white arrow indicates the mean disease score. The disease scores fit a normal distribution (indicated with the red line) by Shapiro and Wilk W test (P< 0.0001: Lynch and Walsh, 1997). WAC4736 75 Shapiro-Wilk W test 50 Isolate W Prob < W WAC4736 0.963 < 0.0001 25 # of individuals# WAC4741 0.967 < 0.0001 OMT5 0.974 < 0.0001 1 2 3 4 5 Disease Score WAC4741 OMT5 60 60 40 40 20 20 # of individuals # of individuals # 1 2 3 4 5 1 2 3 4 5 Disease Score Disease Score 73 Table 4.1. Evaluation of 85 SARDI M. truncatula accessions for resistance to three genotypes of P. medicaginis. Disease resistance scorea Disease resistance scorea Accession WAC4736 WAC4741 OMT5 Accession WAC4736 WAC4741 OMT5 SA396 1.27 2.08 2.82 SA11954 2.90 4.12 1.33 SA1306 1.40 3.03 1.93 SA12451 1.23 3.22 1.20 SA1316 2.28 4.40 2.90 SA12455 1.93 3.33 1.93 SA1489 1.07 1.28 1.57 SA14829 3.73 3.97 4.13 SA1502 1.00 3.30 3.00 SA15951 3.26 2.40 1.70 SA1516 1.64 1.57 4.00 SA17498 3.10 3.00 4.27 SA2193 3.60 3.26 4.70 SA17562 3.83 4.30 3.52 SA2203 1.88 4.06 2.83 SA17590 3.56 2.64 1.43 SA2715 3.85 3.08 3.48 SA18346 2.57 1.94 1.10 SA2729 3.53 2.80 4.04 SA18395 4.62 2.88 1.87 SA2841 2.58 4.08 1.76 SA18532 3.20 3.25 1.87 SA3047 2.33 1.25 1.72 SA18543 2.84 4.40 1.92 SA3054 4.43 3.98 4.53 SA19957 3.32 4.57 1.96 SA3536 2.00 3.09 2.63 SA19995 3.10 2.61 2.22 SA3569 1.84 1.79 2.97 SA19998 1.92 4.54 2.57 SA3749 1.93 3.25 3.62 SA21302 1.40 3.17 2.14 SA3919 4.28 1.61 4.55 SA21362 1.93 2.75 3.67 SA4327 1.63 3.30 3.44 SA23859 1.47 3.83 1.22 SA4480 1.70 3.27 3.33 SA24576 1.47 4.22 2.33 SA4586 3.00 3.27 2.48 SA24968 2.50 3.89 2.38 SA7749 1.60 4.61 4.70 SA25654 1.76 3.92 1.95 SA8454 1.64 2.40 2.26 SA25915 2.80 2.93 3.20 SA8604 1.43 1.94 4.27 SA25941 3.33 3.20 1.55 SA8618 3.60 3.58 3.67 SA27063 3.20 2.33 1.42 SA8623 1.52 1.50 1.52 SA27192 2.13 2.64 2.50 SA8871 3.25 2.03 2.95 SA27774 4.47 4.77 3.32 SA9062 3.63 3.87 4.10 SA27784 3.20 3.47 3.06 SA9119 2.60 1.64 2.06 SA28064 1.28 2.60 1.48 SA9141 3.73 2.14 2.73 SA28089 3.97 4.22 3.20 SA9295 3.64 2.35 1.40 SA28375 3.40 3.90 1.88 SA9357 4.00 3.64 3.45 SA28645 4.23 4.23 4.93 SA9456 1.00 3.83 2.43 SA28889 1.70 3.93 2.72 SA9596 3.93 4.17 3.12 SA30199 2.23 3.93 3.98 SA9670 3.06 3.10 2.20 SA30203 3.47 4.62 2.27 SA9707 1.20 4.32 1.20 SA30740 4.20 2.90 3.10 SA9710 2.48 1.39 2.60 SA31438 2.76 4.28 3.08 SA9715 1.72 3.28 1.63 A17 2.27 4.00 4.10 SA9856 2.27 1.53 2.33 A20 2.43 2.94 3.15 SA9866 2.24 2.79 1.37 Borung 1.97 2.58 3.28 SA9888 2.43 3.47 2.76 DZ045 1.97 1.81 2.19 SA10481 1.70 3.14 2.93 DZ315 1.92 4.14 3.07 SA10964 3.52 4.23 4.68 SA11734 4.13 4.11 3.67 Range 1-4.62 1.25-4.77 1.1-4.93 SA11753 3.08 1.39 2.22 Mean 2.64 3.2 2.7 LSDb 1.16 1.26 1.11 74 a Disease severity based on a minimum of three replicates composed of three plants per replicate and five leaves per plant. Scores range from 1 (resistant) to 5 (fully susceptible). See Figure 4.2 legend for a complete description of scoring categories. b Least significant difference (LSD) was calculated using the Tukey-Kramer HSD test at P ≤ 0.05. 75 Figure 4.6 3D-scatter plot of the mean disease scores to three P. medicaginis genotypes for 85 M. truncatula accessions. Disease scores are an average of three biological replicates. See Figure 4.2 legend for a complete description of the scoring categories. Mean disease scores for each M. truncatula accessions are listed in Table 4.1. To view and rotate the 3D-scatter plot, download the file 3D- scatter plot.grs from http://wwwacnfp.murdoch.edu.au/Links.htm and follow the instructions on the webpage. 76 4.4 Discussion Three different screening methods were developed to look for differential responses to Phoma disease in the SARDI M. truncatula accessions of the core collection. The spray inoculation method seems a reliable, reproducible and most importantly an efficient method to screen a large number of plants. Not surprisingly, this type of method is routinely by researchers used to screen for resistance to fungal necrotrophs in Medicago species (Barbetti, 1987, 1990; Kinsey, 2002; Mackie et al., 2007; Mackie et al., 2003; Musial et al., 2007; O'Neill et al., 2003; Salter and Leath, 1992; Tivoli et al., 2006a). The dose of spores per plant however is not highly controlled due to various growth habits, the leaf architecture and leaf characteristic of a particular M. truncatula accession. Therefore, the spot inoculation method was developed which controls the dosage of spores. A similar method was developed for the Colletotrichum trifolii-M. truncatula pathosystem which identified that resistance to this hemi- biotroph is dominant and probably due to one major resistance gene (Torregrosa et al., 2004). We used the spot inoculation method to screen the core collection and this revealed a continuous distribution and wide range in disease phenotypes among 85 accessions screened. Previous studies in the P. medicaginis-M. truncatula pathosytem have found comparably wide ranges in disease symptoms between accessions (Barbetti, 1995; Kinsey, 2002). However, this is the first study using genotyped monospore sources of inoculum and single seeded accessions. The results presented in this chapter suggest M. truncatula harbours specific and diverse sources of resistance to individual pathogen genotypes, with several isolate-specific resistant accessions showing pronounced susceptibility to a second isolate with a disease score greater than four. In one accession, SA2841, 77 tissue specificity was observed with complete resistance in the unifoliate leaf to WAC4736, but not in the trifoliate leaves. Two accessions, SA1489 and SA8623, showed resistance to all three isolates. Whether broad spectrum resistance confers these phenotypes cannot be determined until the genes responsible have been mapped or isolated. The identification of new sources of resistance in this diverse collection of M. truncatula accessions offers the opportunity to characterise new forms of resistance since M. truncatula is a genetically tractable model legume. Such disease resistance traits could be utilized in medic breeding programmes to increase the level of resistance to various necrotrophic diseases available in current commercial cultivars. 78 Chapter 5 Recessive quantitative trait loci confer resistance to spring black stem and leaf spot in Medicago truncatula 5.1 Introduction In chapter 4 we have demonstrated that P. medicaginis can cause significant disease on the barrel Medic (Medicago truncatula). Since the 1980s various reports revealed that significant reductions in seed and herbage yield and defoliation and premature death was caused by P. medicaginis isolates in various Medicago cultivars (Barbetti, 1983, 1995; Barbetti and Nichols, 1991). Chemical and cultural control of foliar necrotrophs (such as P. medicaginis) has proved to be expensive and inefficient (Nutter and Guan, 2002) and it is therefore important to generate new resistant cultivars in both M. truncatula and alfalfa or more efficient antifungal control agents. M. truncatula is increasingly being dissected for the genetic basis of resistance to necrotrophic diseases and to identify new sources of resistance that may not be available in other legume crops, for example against Aphanomyces euteiches (Pilet-Nayel et al., 2005), Ascochyta lentis, Colletotrichum coccodes (Pfaff et al., 2006), Colletotrichum trifolii (Torregrosa et al., 2004), Mycosphaerella pinodes (Tivoli et al., 2005) Phoma medicaginis (Ellwood et al., 2006c), Phytophthora medicaginis (de Haan et al., 2002, 1996; D'Souza et al., 2005, 2006), Fusarium oxysporum (Lichtenzveig et al., 2006a) and Stagonospora meliloti (Pfaff et al., 2006). Accessions from the SARDI core collection showed a wide range of disease phenotypes for the three different P. medicaginis isolates tested (Chapter 79 4), in common with previous studies that showed comparably wide ranges in disease symptoms (Barbetti, 1995; O'Neill et al., 2003). Map-based cloning approaches have opened the door for cloning of many crop-specific agronomic traits located in the gene-rich regions of various important crops, which contribute towards improved crop varieties. The major strength of this approach is the ability to tap into a resource of natural genetic variation without prior assumptions or knowledge of specific genes. Most of the map-based cloning strategies resulted in the isolation of genes responsible for Mendelian trait differences. However, in recent studies various QTLs have been cloned in plants species using map-based methods (Frary et al., 2000; Fridman et al., 2000; Shen et al., 2006; Yano et al., 2000). In map-based cloning, the marker interval containing the gene is refined by genetic mapping to a region small enough to be physically mapped, by scoring the phenotypes of individuals that are recombinant between flanking markers. Additional markers in the interval of interest are usually derived from a physical map and used to delimit the recombination breakpoints. Once narrowed down to a small genetic interval, the physical (BAC) contig spanning the interval is identified, and known or predicted candidate genes within the region are tested using complementation or other methods. In contrast to the rapidly increasing knowledge on monogenic resistance to biotrophs (Dangl and Jones, 2001), little is known about the molecular basis of resistance to necrotrophs, which is typically quantitative and multigenic. To study such traits QTL analysis is used. QTL mapping allows the roles of specific R-loci to be described, race-specificity of partial resistance genes can be assessed, and interactions between resistance genes, plant development and the 80 environment can be analysed (Young, 1996). QTL mapping also aids discovery of markers for marker assisted selection of complex disease resistance traits (Quirin et al., 2005; Shen et al., 2006) and the positional (map-based) cloning of R-loci (Shen et al., 2006; Young, 1996). The aims in this chapter are to characterise and validate the P. medicaginis-M. truncatula pathosytem, to examine the responses of resistant and susceptible accessions both macroscopically and cytologically and to determine genetic map positions for resistance loci. 5.2 Material and Methods 5.2.1 Mapping populations and growth conditions Parental M. truncatula accessions SA27063, SA3054 and A17 were identified from the disease phenotype screens described in chapter 4 as being either resistant (SA27063) or susceptible (SA3054 and A17) to P. medicaginis OMT5. Reciprocal crosses between SA27063 and A17, and SA27063 and SA3054 were obtained by a manual crossing procedure (Thoquet et al., 2002). Subsequently seeds were collected and cross-fertilisation was confirmed for F1 individuals with molecular markers polymorphic between the parental accessions. F2 seed was collected from F1 hybrids after self-fertilisation. The germination and growth conditions are desribed in paragraph 2.2.1. 5.2.2 Inoculation procedures and resistance evaluation P. medicaginis OMT5 inoculation of Medicago accessions was performed at the fourth trefoil stage. Two methods of inoculation were used: 81 spraying with an artists airbrush to runoff, using a rotating platform to ensure an even distribution over plant surfaces and spot inoculation with 10 µl droplets of spore suspension (1 x 106 spores/mL) on five leaves per plant. These were the unifoliate, the first trifoliate, and the second trifoliate. To ensure high humidity to stimulate conidia germination, plants were placed in sealed propagator trays for 48 hours. F2 individuals were spot inoculated and macroscopically evaluated at 7 days post inoculation (dpi), and rescored at 10 dpi to confirm more resistant disease reactions, as desribed paragraph 4.2.2.2. Spray inoculations were performed on a minimum of 16 F3 individuals per F3 family and evaluated at 10 dpi, according to the 1-5 scale devised by Salter and Leath (1992), with an additional class, 0, for complete absence of symptoms, described in paragraph 4.2.2.1. 5.2.3 Statistical analysis of the disease resistance data Departure from normality for the distribution of disease scores was tested using the W test of Shapiro and Wilk (Lynch and Walsh, 1997). A Fain test was used see if resistance to P. medicaginis can be attributed to one (or a few) major genes (Lynch and Walsh, 1997). This test is based on means and variances (for resistance) of the F3 families and assumes that if resistance is determined by one or a few genes with a large effect, that families possessing the most extreme phenotypes are likely to be homozygous, exhibiting low variance within the family. Families with intermediate phenotypes are more likely to be heterozygous, exhibiting large variances (for resistance) within each family. Accordingly the relationship between families can be described using a quadratic 82 equation, where a significant value (P of /t/ < 0.05) indicates the presence of one (or a few) major genes. All the statistical analysis of the data described above was carried out using JMP-IN 5.1 software (SAS Institute, Cary, NC). 5.2.4 Identification of polymorphic DNA markers Polymorphic PCR markers were identified from several sources: 1) One hundred and forty-four M. truncatula PCR markers (Choi et al., 2004a; 2004b). 2) A set of 89 primer pairs from M. truncatula genomic sequences containing short repetitive motifs in the intron (Gutierrez et al., 2005). 3) One hundred and nineteen microsatellite markers (Baquerizo-Audiot et al., 2001; Mun et al., 2006: http://medicago.org/genome/downloads/ Mt_markers_jan06.txt). Temperature gradient PCR was used to identify the optimum annealing temperature for each primer pair using the standard reference accession M. truncatula A17 as a positive control. The following basic PCR protocol was used with minor variations: 50-100 ng of genomic DNA template, 1 x PCR reaction buffer, 2 mM MgCl2, 0.25 mM of each dNTP, 10 pmol of each primer and 1 unit of Taq DNA polymerase. The thermocycling conditions (with minor variations) were: 5 minutes initial denaturation step followed by 37 cycles of 94°C for 30 sec, marker-specific annealing temperatures for 30 sec, and 72°C for 60 sec, then a final extension step of 5 min at 72°C. Where no length or published restriction enzyme polymorphisms were available, PCR products with a single amplicon were direct sequenced as follows: PCR products were purified by using Mo Bio’s UltraClean™ PCR clean up kit (Mo Bio Laboratories Inc. Solana Beach, CA). 83 Sequencing reactionswere performed using BigDye 3.1 Terminator Cycle Sequencing Ready Reaction Mix (Applied Biosystems [AB], Foster City, California) and the products run on an AB Prism 3730 DNA sequencer. Polymorphisms in the DNA sequences were identified by aligning the sequences in Vector NTI Suite 9.0 (Invitrogen, Carlsbad, California). Where restriction enzymes recognising differences in DNA sequence were available, markers were run as CAPS (Cleaves Amplified Polymorphic Sites: Konieczny and Ausubel, 1993). Single Nucleotide Polymorphisms (SNPs) for which no restriction enzyme was available were detected using the SNaPshot kit (AB) and analysed on an AB Prism 3730 capillary sequencer. Large fragment size polymorphisms and CAPS markers were resolved by agarose gel electrophoresis and visualised using ethidium bromide staining. Small fragment size polymorphisms were resolved by native polyacrylamide gel electrophoresis or by AB Prism 3730 capillary sequencer using fluorescently labelled primers and GeneScan™ 500 LIZ® Size Standard (AB). 5.2.5 Genotyping and linkage analysis Genomic DNA from the parents and F2 individuals were extracted as described previously (Ellwood et al., 2006b) and polymorphic markers were genotyped on the populations SA27063 x SA3054 and SA27063 x A17 as described above. A Pearson Chi-square analysis was applied to test the observed segregation ratio of parental alleles against the expected Mendelian segregation ratio for co-dominant inheritance in a F2 population, 1:2:1, to remove highly distorted markers. Marker order and map distances were calculated with Multipoint v1.2 software (Institute of Evolotion, Haifa University, Haifa, Israel; 84 http://www.multiqtl.com) using a maximum recombination fraction (rf) of 0.210 and a Kosambi mapping function. To test the stability of the order of markers for each linkage group (LG) a Jackknife resampling approach was used with 5000 iterations. Markers that violated monotonic increase of rfs (i.e., deviation from the expected increase of rf between a marker and its subsequent neighbours) were detected and removed using the control of monotony function. Marker orders were accepted if the probability was greater than 0.90. Removed markers were re-attached to the genetic map in the interval of most probable fit (e.g. minimum increase in the number of recombination events). The QTL (Quantitative Trait Loci) analysis was performed with the software-package MultiQTL v2.5 (Institute of Evolution, Haifa University, Haifa, Israel; http://www.multiqtl.com) using the general interval mapping for a F2 population as described by (Lichtenzveig et al., 2006b). The hypotheses that a single locus or two linked loci have an effect on resistance to P. medicaginis were evaluated. Firstly, 5000 permutation tests were performed on the hypothesis that one locus on a chromosome has an effect on the disease resistance (H1) versus the null hypothesis (H0) that the locus has no effect on the disease resistance. Secondly, 3000 permutation tests were run on the hypothesis that a single locus has an effect on disease resistance versus two linked loci. The model with the highest LOD score was fitted to the QTL and when the models did not differ significantly the simpler model was chosen (‘one locus–one trait’). 5000 bootstrap samples were then run to assess the estimates and the standard deviation (SD) of the main parameters: locus effect, its chromosomal position, its LOD score and the proportion of explained variability (PEV). 85 5.2.6 Cytology of the M. truncatula-P. medicaginis pathosystem Three different staining methods were used to study the M. truncatula – P. medicaginis interaction microscopically: 1) Superficial fungal growth was observed by staining with fluorescent dye 3’3-dihexyloxacarbocyanin iodide (DiOC6(3)). Whole or part-leaf samples were immersed in fresh aqueous solutions of the fluorescent dye 3 DiOC6(3) at 50 -1 -1 mg mL , prepared from DiOC6(3) stock solution in ethanol (0.5 mg mL , stored at -20ºC as described by Duckett and Read (1991). Between 2-3 minutes of exposure normally gave an adequate level of stain absorption. The samples were then placed on slides and the excess stain solution drawn off gently from the edges with tissue. The samples were examined under UV with a light fluorescent Olympus BH-2 microscope fitted with a epifluorescence filter B2A (450-490 nm excitation filter and a 520 nm barrier filter). Hyphae stained bright yellow, conidiospores stained bright green to yellow with increasing age, plant cells exhibiting a hypersensitive response were dark brown or dark green, and healthy cells appeared a deep red colour due to the autofluorescence of intact chloroplasts. Yellow autofluorescence of phenolic compounds can also be observed under UV-light. 2) Superficial fungal growth was also observed using trypan blue staining. Leaves were fixed in Farmers Fluid (acetic acid/ethanol/chloroform, 1:6:3 by volume) until completely cleared. The cleared leaves were immersed in a 0.03% trypan blue stain concentrate mixed with equal volume of 100% ethanol 86 for 30 minutes (to visualize fungal hyphae dark blue), then destained in 2.5 g/mL chloral hydrate and examined under a Olympus BH-2 light-microscope. 3) To visualize production of H2O2 in response to P. medicaginis penetration, a DAB (Diaminobenzidine-tetrahydrochloride) staining solution was used (Huckelhoven et al., 1999). The stems of the leaves were placed in the DAB staining solution (1mg DAB/mL H2O pH 3.8, Sigma) for 48 hours. The leaves were fixed and cleared in a solution of ethanol: chloroform (v/v 4:1) and 0.15% TCA for 2-3 hours. After DAB staining leaves were stained with Trypan Blue staining solution for 5-10 minutes. The stained leaves were examined under an Olympus BH-2 light-microscope. 5.3 Results 5.3.1 Macroscopic phenotype of resistant and susceptible accessions M. truncatula SARDI core collection accessions were previously screened for their response to three P. medicaginis isolates (Chapter 4). Accession SA27063 was resistant to P. medicaginis OMT5, whereas A17 and SA3054 were susceptible. When three-week-old resistant accessions were spot inoculated, the fungus was not able to spread outside the inoculation site and no chlorosis or necrosis was observed 7-10 days post infection (Figure 5.1a). In susceptible interactions the fungus successfully penetrated the plant cells and spread beyond the inoculation site, accompanied by a halo of chlorosis ahead of the infection zone. Seven to ten days post infection the entire infected leaves were chlorotic or totally necrotic and the fungus formed pycnidia (Figure 5.1b, e). When spray inoculated small microscopic “hypersensitive response” like 87 lesions and no chlorosis of the leaves was observed in resistant interactions (10- 14 dpi; Figure 5.1c). In the susceptible interactions disease symptoms were visible to the naked eye at seven days post infection. After successfully penetrating plant cells, P. medicaginis colonized the surrounding plant tissue, resulting in macroscopic necrotic spots on both leaves and stems. Around the infection sites chlorosis occured as the pathogens spread throughout the foliar tissue (10-14 dpi; Figure 5.1d). As early as 10 days after infection P. medicaginis starts to produce asexual spore producing structures known as pycnidia (Figure 5.1e). Pycnidia released their spores and spread through the canopy of the susceptible accessions by splash dispersal, initiating a secondary infection cycle. 5.3.2 Microscopic disease symptoms of P. medicaginis Histological analyses were performed to monitor the manner of tissue colonisation by isolate OMT5. Fungal structures in inoculated leaves were revealed by trypan blue or DiOC6 staining (Figure 5.2a-f). Spores germinated on the leaf surface and successful penetration of the plant tissue was observed as early as six hours post inoculation. Penetration of the plant tissue by P. medicaginis was observed in three different ways: firstly, directly through the epidermal cells (Figure 5.2c); secondly in between epidermal cells (Figure5.2d) and thirdly through stomata followed by penetration of the underlying mesophyll cells (Figure 5.2a). Following penetration, fungal colonisation proceeded rapidly in the susceptible accessions SA3054 and A17, whereas fungal development in the resistant accession SA27063 was limited and mostly restricted to individual epidermal cells. Diaminobenzidine-tetrahydrochloride (DAB) was used to detect endogenous H2O2 production in inoculated leaves. In the resistant accession SA27063, the penetrated plant cell stained a reddish-brown colour indicating the 88 Figure 5.1. Macroscopic disease symptoms of P. medicaginis OMT5. (A) SA27063 spray inoculated 10 days post inoculation (dpi) (B) SA3054 spray inoculated 10 dpi (C) SA27063 spot inoculated 7dpi (D) SA3054 spot inoculated 7dpi (E) Pycnidia of P.medicaginis on A17 infected leaf 14 dpi. A B C D E 89 Figure 5.2 Microscopic analysis of P. medicaginis infection of M. truncatula. Leaves were spot inoculated with P. medicaginis OMT5 and hyphae were visualised with trypan blue (A-C) or DiOC6 (D, E). (A) P. medicaginis entereing a stomata of SA3054, 48 h post infection. (B,C) build-up of H2O2 around the sites of penetration in SA27063. (D, E) Autofluorescence of potential defence related compounds around the infection site in both SA27063 (D) and SA3054 (E). H2O2 = hydrogen peroxide; ifh = infection hyphae; p = point of penetration; sp = spore; st = stomata. ifh ifh H2O2 H2O2 p st A B C p sp sp sp ifh p D p E 90 accumulation of H2O2 at the infection site (Figure 5.2b, c). No further spread of the fungus was observed. In the susceptible interaction the accumulation of H2O2 at the infection site was also observed, but was less common. Around the site of infection autofluorescence was observed, perhaps indicating the build up of plant defence related compounds (Figure 5.2d, e). In SA27063 infected leaves autofluorescence was more common and abundant than in the susceptible leaves, 72 and 96 hours post infection (Figure 5.2d, e). The HR-like symptoms, the abundance of production of H2O2 and (autofluorescent) phenolic compounds may play essential roles in restricting P. medicaginis colonisation. 5.3.3 Resistance to Phoma medicaginis OMT5 in accession SA27063 in two different mapping populations The resistant accession SA27063 was crossed with susceptible accessions A17 and SA3054 to create two different F2 populations. The response to P. medicaginis OMT5 was assessed on the F1 individuals. The F1 individuals of both crosses showed P. medicaginis symptoms equivalent to the susceptible parents, when either spray or spot inoculated (Figure 5.3a, b), indicating that the resistance to P. medicaginis OMT5 is recessive. The F2 individuals of the two mapping populations SA27063 x A17 (n=92) and SA27063 x SA3054 (n=94) were inoculated with P. medicaginis OMT5. SA27063 x SA3054 F3 families (n F3 individuals per family ≥ 16) were also screened for their resistance to confirm the F2 individual phenotypes. F3 families of the A17 cross were not assayed for their disease resistance to P. medicaginis OMT5, due to the presence of a reciprocal translocation in the accession A17 and a large proportion of aberrant F2 individuals (see Chapter 6). 91 Figure 5.3. Macroscopic disease symptoms of P. medicaginis OMT5 on F1 hybrids of SA27063 x SA3054. (A) F1 hybrid of SA27063 x SA3054 spray inoculated 10 days post inoculation (dpi) showing similar disease severity as the susceptible parent SA3054 (see Figure 4.1e-f). (B) F1 hybrids of SA27063 x SA3054 spot inoculated 7dpi showing similar disease severity as the susceptible parent SA3054 (see Figure 4.2e-f). A B 92 The distributions of the average disease scores within the F3 families were plotted using a 1 = resistant to 5 =susceptible scale (Figure. 5.4a). A platykurtic distribution of disease scores (showing a negative kurtosis value Kur = -1.25) was observed not following a normal distribution (P< 0.0001 by Shapiro and Wilk test) with a mean disease score of 2.45 (Figure 5.4a). The Fain’s test predicts a pattern of maximum variability in intermediate families whenever a major quantitative trait locus (or few) is involved (Lichtenzveig et al., 2002). Analysis of the F3 family disease scores using the Fain’s test revealed that the quadratic term is highly significant (P of /t/ = 0.0027) in the SA27063 x SA3054 population, indicating one or a few “major genes” are involved in resistance to P. medicaginis (Figure 5.4b). 5.3.4 Genetic linkage mapping Framework genetic maps for the SA27063 x SA3054 and SA27063 x A17 crosses were created using both gene-based and microsatellite markers. Markers were selected to form evenly distributed markers over each of the linkage groups and were selected from various sources (Baquerizo-Audiot et al., 2001; Choi et al., 2004a; 2004b; Gutierrez et al., 2005; Mun et al., 2006). A total of 123 and 78 markers were charachterized for the SA27063 x SA3054 (n= 94) and SA27063 x A17 (n= 92) mapping populations. Of these 77 length polymorphisms were characterized for SA27063 x SA3054 and 18 length polymorphisms for SA27063 x A17. These length polymorphisms could be mapped by virtue of their inherent fragment size differences between the parental alleles (Figure 5.5). 93 Figure 5.4 Statistical analyses of the F3 phenotype data. (A) Distribution of disease scores for F3 families of cross SA27063 x SA3054 infected with P. medicaginis OMT5 7dpi. (B) Variance within a family (Vi) as a quadratic function of its mean response (Mi) of a segregating population (SA27063 x SA3054) of M. truncatula to P. medicaginis expressed as the mean F3 family disease score. 0.4 V = 0.088 + 0.050 M –0.043 (M-2.45)2 0.35 i i i A P= 0.0027 B 0.30 15 0.15 0.25 10 0.10 0.20 Number of F3 families F3 of 0.15 Probability 5.0 0.05 Std Err (DiseaseScore) 0.10 0.05 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Mean Disease Score F3 Family Mean (Disease Score) 94 Figure 5.5 Length polymorphisms are mapped by virtue of their inherent fragment size differences between the parental alleles. 2% agarose gel with PCR product of marker MTIC82. SA3054 and SA27063 indicate fragment size of the parental alleles. S S A A 3 F1 2 F2 individuals 0 7 5 0 6 F2 individuals 95 The remaining 46 and 58 for SA27063 x SA3054 and SA2706 x A17 respectively, were single nucleotide polymorphisms (SNPs) between the parental alleles. The majority of these SNPs, were converted to CAPS markers (Konieczny and Ausubel, 1993). SNPs that could not be converted were run with fluorescently labelled primers on a capillary sequencer (see Appendix 01 and Appendix 02). In total 53% of markers were polymorphic between SA27063 and A17 and 35% were polymorphic between SA27063 and SA3054. The genetic maps for SA27063 x SA3054 and SA27063 x A17 are shown in Figure 5.6a and 5.6b. As expected, the SA27063 x SA3054 map included eight linkage groups, in accordance with the basic number of chromosomes in M. truncatula (x = 8). The 123 genetic markers in SA27063 x SA3054 span a total of 488.3 centimorgans (cM) with an average distance between markers of 4.0 cM. Very few markers known to be on the lower half of linkage group 2 (Choi et al., 2004a; Mun et al., 2006) were polymorphic between alleles of SA27063 and SA3054. In contrast to the SA27063 x SA3054 map, the SA27063 x A17 map was organized in seven linkage groups, with LG4 and LG8 forming a single linkage group (Figure 5.6b). These linkage groups have previously been reported as single linkage groups (Choi et al., 2004a; Mun et al., 2006; Thoquet et al., 2002). The establishment of new linkage relationships between LG4 and LG8 combined with observations of semisterility in hybrids involving A17 (see Chapter 6) provides strong evidence that A17 bears a reciprocal translocation, which differentiates it from other M. truncatula accessions. This reciprocal translocation involves the lower arm of chromosome 4 and the lower arm of chromosome 8. 96 Figure 5.6a Genetic map of SA27063 x SA3054 population, based on 94 F2 individuals. The genetic map comprises 123 markers and spans 488.3 cM with an average distance of 4.0 cM between the markers. LG1 LG2 LG3 LG4 MtB157 0.0 MTIC019 0.0 DK501R 0.0 MAA660456 0.0 MTIC033 0.0 MTIC43 1.8 MtB26 0.0 MTIC354 0.5 AW256637 4.5 ACCO 2.3 TC90233 5.6 ENOD8 7.4 MTIC74 4.0 EPS 7.4 UNK3, MtB27 MTIC361 4.5 UNK16 8.0 MtB220 10.2 MTIC452 8.4 DK258L 11.9 MtB61 14.3 MTIC236 15.4 MDH2 17.5 QORlik 17.4 MtB344 18.5 MTIC235 31.7 h2_87i13a 32.5 DK419R 33.7 DK417L 34.3 h2_77p14a 36.0 DK379L 39.6 MTIC051 38.8 DK381L 39.6 MTIC249 42.3 DK473L 45.9 47.0 MtB118 EST400 MtB290 47.8 MtB172 48.2 DK313L 49.8 h2_8c19d CDC2 50.8 CysPR1 50.9 DK024R 50.9 52.5 MtB300 MtB160 54.8 MtB43 56.6 h2_33J22 57.0 TUP MtB223 57.7 SQEX MtB286 57.6 58.8 MTIC279 60.9 ATP2 58.8 MtB4 59.2 MTIC065 62.0 MTIC297 63.6 BiPA 64.1 MtB248 64.7 MtB193 64.6 41O18L 64.7 LG5 LG6 LG7 LG8 MTR52 0.0 OXG 0.0 MtB213 0.0 AW257033 0.0 FENR 0.6 MAA538 1.8 PGDH 2.3 GLUT 2.4 UDPGD 4.0 MtB293 4.1 CrS 6.2 7.6 DK322L 8.0 MtB247 Ms/U141 8.8 DK455L 10.0 DK242R 13.8 36N1L 14.5 h2_8a13a 14.6 48N18L 17.4 DK505R 20.7 NTRB1 21.3 SDP1 25.3 h2_15m24a 28.4 30.6 MtB32 31.1 MtB59 MTIC153 39.1 MTIC82 41.8 MTIC243 47.4 REP 46.7 MTSA5 47.4 MTIC238 46.4 PAE 49.0 MtB276 48.6 VR 48.0 MtB294 54.3 MtB217 58.1 MtB55 50.8 h2_24j8b 58.1 MTIC48 53.1 TE001 55.6 MtB3 58.1 FAL 53.7 MTIC014 56.1 MtB174 59.7 MtB262 61.9 MTIC268 56.1 CAK 57.0 h2_28c12a 61.9 CA4H MtB139 62.5 58.2 ENOL 59.1 h2_9d1a 62.5 MtB96 59.9 MtB124 60.2 h2_35l19b 62.5 PTSB 61.6 MtB295 62.5 CPOX2 64.1 MTIC58 64.4 EIF5A 64.1 MTSA6 68.9 97 Figure 5.6b Genetic map of SA27063 x A17 population, based on 92 F2 individuals. The genetic map comprises 78 markers and spans 497.8 cM with an average distance of 6.6 cM between the markers. LG1 LG2 LG3 LG4-8 ENOD8 0.0 PFK 0.0 DK501R 0.0 MAA660456 0.0 MTIC033 0.0 TE016 4.1 AW256637 7.0 DK258L 10.1 EPS 8.6 MtB99 9.2 MDH2 15.0 UNK3 TE011 9.8 QORlik MtB344 16.1 SAMS 21.8 MtB169 27.2 ACL 33.7 DK132L 33.2 Ms/U131 35.1 EST763 39.3 DK381L 36.7 MTR58 41.6 DK417L 41.2 DK293R 43.6 DK024R 47.6 UNK27 51.2 TUP 53.8 SAT 61.4 GLNA 61.4 41O18L 61.4 DK045R 65.6 DK473L 70.7 MTIC297 68.1 MAAP, MPP, CPOX2, EIF-5A, FIS1, PAE, EST400 74.0 CP450 71.5 SQEX, MTIC279, DK353L, DNABP, HYPTE3 NPAC 75.1 DK313L 76.8 CysPr1 79.6 LG5 LG6 LG7a SDP1 84.1 MAA660538 0.0 CrS 0.0 DK225L 0.0 UDPGD 0.6 UNK7 1.7 DK505R 92.9 PGDH 6.4 DK009R 11.5 DK322L 13.9 48N18L 15.3 CNCG4 106.0 ENOD40 18.8 36N1L 18.9 Ms/U336 110.5 DK242R 26.2 LG7b MtU04 39.1 AW257033 128.9 PROF 46.4 MTSA5 0.0 DK287R 2.9 DK321L 47.0 CAK 6.4 ENOL 11.7 FAL 59.1 TE001 59.5 MTSA6 75.5 DK006R 77.2 98 All markers publicly available to date in the middle of LG7 were monomorphic and LG7 was therefore split into two small linkage groups named LG7a and LG7b. The 78 genetic markers in SA27063 x A17 span a total of 497.8 cM with an average distance between markers of 6.4 cM. The linkage groups of the genetic maps present herein were similar in length to the previously published maps (Choi et al., 2004a; Mun et al., 2006) with the exception of LG3. In SA27063 x SA3054 the distance between DK501R and CysPR1 was 50.9 cM, whereas in SA27063 x A17 this distance was 79.6 cM. 5.3.5 QTL mapping of spring black stem and leaf spot resistance in M. truncatula QTL analysis was carried out using the mean disease scores of the F3 families of SA27063 x SA3054 and the F2 disease scores of SA27063 x A17. By applying a general interval mapping method with the software-package MultiQTL two highly significant QTLs for resistance to P. medicaginis OMT5 were identified, one in each mapping population. In SA27063 x A17, one highly significant QTL (LOD= 6.96; α = 0.00001) named resistance to the necrotroph Phoma medicaginis one (rnpm1), was located on LG4 (Figure 5.7a). rnpm1 explains 32.1% of the phenotypic variance for resistance to P. medicaginis OMT5 and is is tightly linked to AW256637. The second highly significant QTL (LOD= 6.79; α = 0.00001) named resistance to the necrotroph Phoma medicaginis two (rnpm2) was located on LG8 in the population SA27063 x SA3054 (Figure 5.7b). rnpm2 explains 29.6% of the phenotypic variance for resistance to P. medicaginis OMT5 and is tightly linked to marker MtB262. 99 Figure 5.7 Quantitative trait loci (QTLs) associated with resistance to P. medicaginis OMT5 in M. truncatula (A) rnpm1 for resistance to the necrotroph P. medicaginis OMT5 identified on an intraspecific genetic linkage map from the cross of SA27063 x A17. rnpm1 is located on the short arm of chromosome 4 and explains 29.6 of the phenotypic variance (B) rnpm2 for resistance to the necrotroph P. medicaginis OMT5 identified on an intraspecific genetic linkage map from the cross of SA27063 x SA3054. rnpm2 is located on the long arm of chromosome eight and explains 32.1% of the phenotypic variance for resistance to P. medicaginis OMT5. The estimated location of the QTLs is shown by the position of the wide bar, while the narrow bars flanking it represent the standard deviation of the location. The parameter estimates for a given locus, i.e., the locus effect, its LOD score and the proportion of explained phenotypic variation (PEV) are noted in the respective boxes which were derived from a ‘one locus– one trait analyses’. 100 5.4 Discussion The main purpose of this section was to analyse the genetic basis of resistance to P. medicaginis in M. truncatula. To achieve this, M. truncatula accessions from the SARDI core collection were screened (Chapter 4) with three different P. medicaginis isolates. Among the accessions tested SA27063 was shown to be resistant to P. medicaginis OMT5, whereas A17 and SA3054 were highly susceptible. Therefore, these accessions were selected for further investigation. The resistant phenotype was characterized macroscopically by the presence of small necrotic spots, whereas susceptible accessions showed typical stem and leaf spots, within which fruiting bodies, or the pycnidia, formed. Presence of the pycnidia proves that the fungus is able to complete its life cycle on susceptible M. truncatula accessions and the M. truncatula-P. medicaginis interaction thus represent a natural pathosystem to study necrotroph resistance. This is of great importance since the model plant Arabidopsis thaliana is not a natural host for most necrotrophic fungal pathogens. Microscopically no differences were observed in penetration capabilities on resistant and susceptible accessions. In both interactions the fungus penetrated directly through or in between epidermal cells or hyphae grew into the stomata and the underlying mesophyll cells. In the resistant interaction fungal growth seemed to be restricted to the penetrated plant cell, where accumulation of H2O2 and autofluorescence around the infection site was observed. H2O2 has been reported to play an important role in the resistance of hypersensitive disease resistance (Huckelhoven et al., 2001; 1999). Production of H2O2 was observed in SA27063 infected leaves and was also detectable in SA3054 and A17, but to a lesser degree. Torregrosa et al., (2004) observed H2O2 production, when infecting resistant M. truncatula accessions with the fungal necrotroph 101 Colletotrichum trifolii. Their gene expression study also showed upregulation of glutathione methyl transferase in resistant accessions supporting their hypothesis that production of reactive oxygen species (ROS) played a role in resistance to C. trifolii. Build up of reactive oxygen species is generally observed following penetration by fungi with a biotrophic lifestyle (Glazebrook, 2005) and subsequently leads to resistance against such fungi. Necrotrophic pathogens are believed to stimulate ROS production in the infected tissue to induce cell death that facilitates subsequent infection (Torres et al., 2006). It remains unclear whether the observed ROS production aids P. medicaginis or M. truncatula in this interaction. Examination of inoculated leaf tissue showed that autofluorescent phenolic compounds accumulated around the infection site. The accumulation of these phenolic compounds was more abundant in the resistant accession SA27063. Phenolic compounds are believed to play an important role in plant defence (Dixon, 2001; Dixon et al., 2002) and gene expression and metabolic profiling can help to identify these compounds. Changes in pathogenic and environmental conditions can significantly influence the disease progression. Infections were carried under temperature controlled glasshouse conditions. When individual F3 families were re-inoculated between experiments, mean disease scores did not significantly differ showing this method is reliable and reproducible method to phenotype resistance to P. medicaginis. QTL analysis of the F2 disease scores in mapping population SA27063 x A17 revealed a highly significant QTL for P. medicaginis resistance (rnpm1) and QTL analysis of the F3 disease scores in mapping population SA27063 x SA3054 revealed a second highly significant QTL for P. medicaginis resistance (rnmp2). 102 Both QTLs explain a small amount of the total variance for this trait indicating that resistance to P. medicaginis is complex and controlled by other loci with small effects. QTL analysis of resistance to P. medicaginis in the SA27063 x SA3054 population revealed one such minor QTL (LOD= 2.4; α = 0.04) on linkage group one explaining 14.3% of the variance. No other significant QTLs could be detected but by increasing the population size, one would be able to reveal other minor loci involved. In addition to reliable phenotypic characterisation, precision and accuracy of QTL analysis based on segregating populations largely depend on map quality and population size. The two maps comprised 123 and 75 SSR and gene-based markers and had population sizes of 94 and 92 for SA27063 x SA3054 and SA27063 x A17 respectively. In total 53% of markers were polymorphic between SA27063 and A17, whereas only 35% of markers were polymorphic between SA27063 and SA3054. This indicates that SA27063 x SA3054 is a narrower cross than SA27063 x A17. The total map length for SA27063 x SA3054 (488.3 cM) was lower than previously reported genetic maps (Thoquet et al 2002; Choi et al 2004; Mun et al 2006). The observed genetic distance between markers DK501R and CysPR1 on LG3 in the SA27063 x SA3054 cross was notably smaller compared to previously published maps and the SA27063 x A17 map presented. LG3 corresponds with chromosome 3, the largest chromosome of M. truncatula (Kulikova et al., 2001) and it is surprising to see a lack of recombination between the markers mapped on LG3 in the SA27063 x SA3054 population. One explanation for this phenomenon could be that the accessions SA27063 and SA3054 are sympatric (Ellwood et al., 2006b) and may 103 share long stretches of homology in chromosome 3, resulting in a lack of recombination. All the previously published genetic maps have accession A17 as one of the parental lines. As described in chapter 6, accession A17 bears a reciprocal translocation, involving chromosomes four and eight. The SA27063 x SA3054 genetic map is the first map produced in M. truncatula not involving A17 as a parental line and is therefore useful in identifying the correct position of ambiguously placed markers in A17-derived genetic maps. The reciprocal translocation could perhaps explain why we were not able to detect the QTL identified in SA27063 x SA3054 population in the SA27063 x A17 population ot that genotype-specific susceptibility loci interact with P. medicaginis. The former hypothesis can only be confirmed with a population derived from a cross with A17 and a M. truncatula SA27063-like resistance with an A17-like reciprocal translocation. The simplest explanation remains that A17 and SA27063 are monomorphic for the QTL in question. Comparative studies of genetic map positions between QTLs for resistance and R genes may provide evidence for possible genomic and functional relationships between genes underlying monogenic and quantitative resistance. In many cases, the map positions of QTLs for resistance to pathogens overlap with major resistance genes, RGAs, or general plant defence genes (Faris et al., 1999; Geffroy et al., 2000; Pan et al., 2000a; Pflieger et al., 2001a; 2001b; Rouppe van der Voort et al., 1998). In the common bean a QTL conferring resistance to the necrotroph Colletotrichum lindemuthianum is located in an area with RGAs and defence related genes (Geffroy et al., 2000). Similarly the map 104 position of rnpm1 seems to overlap with a cluster of TIR (toll and interleukin-1 receptors) and non-TIR resistance genes (Zhu et al., 2002). Host plant resistance mechanisms to necrotrophs appear to function by interfering with the ability of the pathogen to suppress defences through toxins, for example the race-specific Hm1 gene in maize (Johal and Briggs, 1992), and the race-specific Pyrenophora tritici-repentis ToxA-insensitivity QTL tsn1 and ToxB-insensitivity QTL tsc2 in wheat (Faris et al., 1996; Friesen and Faris, 2004; Friesen et al., 2006). Apart from Hm1 all these detoxifying enzymes are recessive in nature, like QTLs rnpm1 and rnpm2. Whether rnpm1 and rnpm2 are also detoxifying genes is focus of further research involving toxin analysis in P. medicaginis isolates as described by Liu and colleagues (2004) and further fine mapping and cloning of rnpm2 locus. 105 Chapter 6 The Medicago truncatula reference accession A17 has an aberrant chromosomal configuration 6.1 Introduction Map-based cloning, synteny studies and some genome sequencing strategies all have a common approach in relying on genetic linkage maps to represent the genome of a given species/accession. For example, one of the strategies to efficiently sequence plant genomes is the anchored clone-by-clone strategy (Sasaki et al., 2005; Udvardi et al., 2005; Wu et al., 2004; Young et al., 2005) where genomic segments are sequenced and positioned following the order of the segments’ markers on a genetic map. The extent to which the genetic map is a good representation of the genome depends on whether the parental lines from which the maps derive share a common chromosomal configuration. Several of the crosses made in the course of this study involved the accession A17, a single-seed descendant line from the cultivar Jemalong. This accession was one of the parental lines used for the primary M. truncatula genetic map (Choi et al., 2004a; Mun et al., 2006) and its genome is being sequenced (Young et al., 2005). Limited information is available on the cytogenetics of the species; fluorescent in situ hybridization (FISH) studies have been conducted with only two M. truncatula accessions: cv. Jemalong, lines A17 and J5, and R108-1 (Cerbah et al., 1999; Choi et al., 2004a; Falistocco and Falcinelli, 2003; Kulikova et al., 2004; Kulikova et al., 2001; Young et al., 2005). A reciprocal translocation between chromosome 4 and 8 has been suggested as a distinctive feature between the parents of the primary mapping population derived from a 106 cross between A17 and A20 (Cannon et al., 2005; Choi et al., 2004a; Young et al., 2005). During the course of this research markers on the long arms of chromosome 4 and 8 in mapping population derived from a cross between SA27063 and A17 were linked, forming one linkage group for chromosomes four and eight (see Figure 5.6a). The observed new linkage relationship suggests evidence for a reciprocal translocation. However, evidence for such translocation in either of these populations had not been published and there was no clear indication which of the two parental accessions had the idiosyncratic chromosomal arrangement. Pollen viability is a good indicator of chromosomal aberrations (Griffiths et al., 1996). Heterozygotes for chromosomal rearrangements such as deletions, inversions and translocations show significant reductions in fertility due to the presence of non-functional gametes. The meiotic products of a reciprocal translocation in plants are 50% unbalanced at the gametic (pollen) stage and half of the gametes will be non-functional (eg. infertile pollen) and this is termed semi-sterility. The aims of this chapter were to provide evidence that A17 bears a reciprocal translocation involving chromosomes 4 and 8 by studying pollen viability and performing linkage analysis of F2 populations derived from A17. Observed poor fertility in various crosses involving A17 and the “coincidence” of a possible translocation in mapping populations derived from A17, were reasons for further investigation of the reciprocal translocation. This information is critical given the status of A17 as the reference genotype for M. truncatula. 107 6.2 Materials and Methods 6.2.1 Accessions and hybrids The M. truncatula accessions A17, A20, Borung, Cyprus, SA1499, SA3054, SA8616, SA10419, SA11734, SA18395, SA23859, SA25654, SA27063, SA27192 and SA30199 were acquired from the Genetic Resource Centre, SARDI (South Australian Research and Development Institute, GPO Box 397 Adelaide, South Australia 5001). Accession DZ315.16 was obtained from the Institut National de la Recherche Agronomique (INRA) Montpellier, France. The hybrids described in this chapter were obtained by a manual crossing procedure (Thoquet et al., 2002) and their nature confirmed by PCR using DNA markers polymorphic between the parental lines. The F1 hybrids A17 x A20, A17 x Borung, Borung x A17, SA8618 x Borung, SA30199 x SA8618 and SA8618 x SA30199 were generated by Ms Nola D’Souza. The F1 hybrids SA25654 x A17, DZA315.16 x SA27192 and SA18395 x SA10419 were generated by Dr Theo Pfaff. The F1 hybrids SA10419 x A17, A17 x SA10419, A17 x DZA315.16 and Cyprus x SA1499 were generated by Dr Judith Lichtenzveig. A17 x SA27192, A17 x SA23859 and A17 x SA27063 were generated by Dr Simon Ellwood. The F1 hybrids SA3054 x SA27063, SA11734 x SA27063, SA27063 x SA3054 and SA27063 x SA11734 were generated by both Dr Simon Ellwood and myself. 6.2.2 Pollen viability of intraspecific hybrids Several crosses between M. truncatula accessions, representative of the large genetic variation within the germplasm collection (Ellwood et al., 2006b; Skinner et al., 1999), were generated for genetic studies. Pollen viability of the 108 hybrids and their parental lines was scored under the light microscope; spreads of 100-500 fresh pollen grains were stained with Alexander’s stain (Alexander, 1969); aborted pollen stains pale turquoise blue and non-aborted pollen stains dark blue or purple (Fig. 7.1b,c). At least 3 flowers from 1-6 F1 plants were scored per cross combination. Pollen counts were done by Ms Angela Williams, Ms Nola D’Souza and myself. 6.2.3 Genetic maps For comparison, three genetic maps involving A17 and one genetic map not involving A17 were constructed. The F2 populations SA27063 x SA3054 (n = 94), SA27063 x A17 (n = 92) and A17 x Borung (n = 99) were genotyped using primer pairs designed by the Medicago genome sequencing project (http://w.w.w.medicago.org/genome/). Genotypes for the A17 x A20 F2 population (n = 69) - used as a reference for the allocation of BACs in the sequencing project - were obtained from the file UMN_marker_genotypes_2005- 03-14.xls available at http://www.medicago.org/genome/downloads.php#marker- seqs. To avoid false positive linkage a large number of markers were excluded from the A17 x A20 analysis due to high levels of segregation distortion (Choi et al., 2004a). Linkage analyses were performed using the MultiPoint v1.2 software (http://www.multiqtl.com; Institute of Evolution, Haifa University, Israel). Multilocus ordering was conducted using the sum of recombination rates along consecutive pairs of adjacent markers and a Jackknife re-sampling technique (5000 iterations) for verification of the obtained order (Mester et al., 2003). Stable map segments are revealed with neighbour probabilities higher than a threshold (e.g. P = 0.9). 109 6.3 Results 6.3.1 Hybrids derived from A17 are semi-sterile Pollen grains from a sample of the hybrids and parental lines were evaluated and the proportion of non-aborted pollen grains was estimated (Alexander, 1969). The parental lines had 94-100% non-aborted pollen grains; A17 had in average 98.2% pollen viability (SE = 0.3, n = 10 plants; Figure 6.1c). All F1 individuals showed approximately 100% pollen viability with the exception of those derived from crosses involving A17, which showed 50% non- aborted pollen or less (Figure 6.1a,b). A 50% reduction in viable gametes (semi- sterility) is characteristic of heterozygotes for a reciprocal translocation (Griffiths et al., 1996). Further reductions in pollen viability, such as those observed in the A17 x SA27192 and A17 x A20 hybrids, may be a result of additional chromosomal re-arrangements between the parents. 6.3.2 Genetic maps derived from A17 reveal new linkage relationships The formation of new linkage relationships is further evidence for the segregation of a reciprocal translocation (Griffiths et al., 1996). Linkage analyses were performed using F2 populations derived from A17 and from the SA27063 x SA3054 hybrid. As expected, the SA27063 x SA3054 map was composed of eight linkage groups corresponding to the haploid chromosome number. In contrast, seven linkage groups emerged from the analysis of the SA27063 x A17 and A17 x Borung populations. Re-evaluation of the genotype data available for the A17 x A20 population, used as a reference in the Medicago genome 110 Figure 6.1 Pollen viability of M. truncatula intraspecific hybrids. (a) Proportion of non-aborted pollen grains. Bars indicate standard errors of the flowers scores mean. (b) Anther from an A17 x SA27063 hybrid containing aborted (pale turquoise blue) and non-aborted (dark blue or purple) pollen grains. (c) Anther from A17 containing non-aborted pollen grains. 100 (c) 80 60 40 20 Non-aborted pollen (%) Non-aborted 0 A17 x A20 Borung x A17 A17 x Borung x A17 A17 x SA10419 SA10419 x A17 SA10419 SA25654 x A17 SA25654 x SA27063 A17 A17 x SA23859 A17 A17 x SA27192 x A17 Cyprus x SA1499 Cyprus A17 xDZA315.16 A17 x Borung SA8618 SA30199 x SA8618 SA30199 x SA30199 SA8618 SA27063 x SA3054 (a) x SA3054 SA27063 SA11734 x SA11734 SA27063 x SA18395 SA10419 SA27063 x SA27063 SA11734 (b) DZA315.16 x SA27192 DZA315.16 111 sequencing project, revealed that markers originally assigned to either LG4 or LG8 were clustered in a single linkage group (Figure 6.2e). By taking sub- samples of the initial genotype data, one can build repeated maps and test whether the marker order remains the same. Using this Jackknife re-sampling technique the probablility of the marker order was determined for all linkage groups resulting in a matrix of probabilities for the marker order (Figure 6.2). The relatively low neighbourhood frequencies (i.e. probabilities) observed in the SA27063 x A17 and A17 x Borung matrices (Figure 6.2c,d) exposed markers with several putative neighbours making the allocation of markers in a certain order statistically unjustifiable. In the A17 x A20 matrix (Figure 6.2e), high recombination frequencies outlines the most probable order of these tightly linked markers. In contrast, data from the SA27063 x SA3054 population provided unequivocal marker order and resulted into two distinctive linkage groups (Figure 6.2a, b). 6.3.3 Reduced fertility and abnormal seedling phenotypes in SA27063 x A17 F2 individuals Two-hundred F2s per F1 hybrid were analysed for any abnormalties (Table 6.1). A large difference in the average number of seeds per pod was observed between the F2 populations of SA27063 x A17 and SA27063 x SA3054 and their reciprocal crosses (Table 6.1). The SA27063 x A17 F1 individuals and their reciprocal counterparts averaged 3.33 seeds per pod, whereas F1 individuals derived from SA27063 x SA3054 and the reciprocal cross averaged 8.33 seeds per pod. Differences in number of seeds per pod for different M. truncatula accessions are not uncommon. However, the parental accessions SA27063, 112 Figure 6.2 Matrices of neighbourhood frequencies displaying the best marker order associated with M. truncatula chromosomes 4 or/and 8. The linkage group (LG) to which the markers where originally assigned in the Medicago genome sequencing project are indicated for c-e; in a-b, LG indicates the marker assignment resulting from the analysis presented herein. (a) (b) (c) (d) (e) 113 Table 6.1. Average number of seeds per pod and percentage of abnormal phenotypes of F2 individuals of seed derived from SA27063 x A17, A17xSA27063, SA27063 x SA3054 and SA3054 x SA27063. SA27063 x A17 and reciprocal F2s SA27063 x SA3054 and reciprocal (n= 200 per cross) F2s (n=200 per cross) Average Number of 3.33 8.33 Seeds per Pod Albinos 6.20% 0 Abnormal radicals 11.80% 0 Slow germination 4.90% 0 Dwarves 19.3% 0 114 Figure 6.3 Germination phenotypes in F2 individuals derived from SA27063, SA3054 and A17. (A) F2 seedlings derived from hybrids of SA27063 and SA3054. (B) Albinism in F2 seedlings derived from hybrids of SA27063 and A17 (C) Abnormal root formations in F2 seedlings derived from hybrids of SA27063 and A17 (D) non-germinating F2 individuals derived from SA27063 and SA3054 and SA27063 and A17, one week of vernalisation (E) Dwarf F2 individual derived from SA27063 and A17, grown under glasshouse conditions for three weeks. (F) Healthy F2 individual derived from SA27063 and A17, grown under glasshouse conditions for three weeks. Percentages of phenotypes are listed in table 6.1. C A D F B E 115 SA3054 and A17 averaged 7.63, 9.10 and 9.86 seeds per pod. The average number of seeds per pod was significantly different for F1s derived from the SA27063 and A17 compared to the parental lines and F1s derived from SA27063 and SA3054 (P ≤ 0.05, Tukey-Kramer HSD-test). On average 90% of F2 seed germinated from the SA27063 x SA3054 cross (Figure 6.3a), whereas only 65% of F2 seed derived from the SA27063 x A17 cross germinated. A number of lethal abnormal germination phenotypes was also observed (Table 6.1). 6.2% of the F2 seedlings were albinos (Figure 6.3b) and 11.2% showed abnormal root formation (Figure 6.3c). Another 4.9% of the seeds only germinated after two weeks at room temperature following normal germination procedures (Figure 6.3d). 19.3% of germinated F2 seed showed abnormal growth behaviour resulting in a dwarf phenotype (Figure 6.3e). No altered germination phenotypes were observed in F2 individuals derived from SA27063 and SA3054 and none of the F2 individuals showed a dwarf phenotype. 6.4 Discussion The pollen viability tests and the establishment of new linkage relationships together provide strong evidence that A17 bears a reciprocal translocation that distinguishes it from other M. truncatula accessions. The reciprocal translocation involves the long arms of chromosomes 4 and 8 (Figures 5.6 and 6.2). Detailed cytological studies of hybrids derived from A17 are needed to determine the exact breakpoints of the translocation event. Cytogenetic studies are well developed in M. truncatula. Thus far, they have been conducted in two inbred lines - cv. Jemalong, lines A17 and J5, and acc. R108-1 (Cerbah et al., 1999; Choi et al., 2004a; Falistocco and Falcinelli, 2003; Kulikova et al., 2004; 2001). We suggest that denser genetic maps, cytological studies or 116 sequence information from other accessions might provide enough evidence for the exact position of the translocation. The genetic map derived from the cross between Jemalong line J6 and the Algerian accession DZA315.16 (Thoquet et al., 2002) shows no obvious evidence of segregation of a reciprocal translocation. To date, no phenotypic or genotypic differences have been observed between the Jemalong lines A17, J6 and J5 which were considered to be genetically identical (Thoquet et al., 2002). However, hybrids derived from the cross between A17 and DZA315.16 consistently show about 50% pollen viability (Figure 6.1). Whether A17 and J6 differ in their chromosomal configuration needs to be determined. Since all the F1s derived from crosses not involving A17 showed approximately 100% non-abortive pollen (Figure 6.1) it seems that these accessions share a common chromosomal arrangement. Linkage maps derived from such crosses (SA27063 x SA3054; Figures 5.6a and 6.2a, b) are therefore valuable tools to provide insights into the M. truncatula intraspecific genomic organization and evolution. The distinctive chromosomal arrangement in A17 has significant implications on genetic studies that involve out-crosses. Semi-sterile F1s and further selection of F2 individuals through low germination rates and albinism (Table 6.1, Figure 6.3), can lead to biased selection of certain gene combinations causing skewed genetic analyses. The implications of the aberrant chromosomal configuration on the sequencing project are minor but noteworthy. An anchored clone-by-clone strategy was chosen to efficiently sequence the M. truncatula gene-space (Young 117 et al., 2005). Clones are initially ordered according to the position of selected markers in a genetic map derived from a A17 x A20 F2 population. The translocation accounts for the consistently poor scoring and ambiguous mapping of some markers (Cannon et al., 2005; Zhu et al., 2002) and subsequently the mis-allocation of the respective clones. For example, the gene based marker SQEX derived from BAC clone AC124214 has been mapped to LG8 (Choi et al., 2004a; 2004b) whereas the BAC clone is physically mapped to chromosome 4 (http://www.medicago.org/genome/cvit_bacs.php). These are small obstacles in the genome sequencing effort. However, special caution should be taken in using the genome configuration of M. truncatula A17 (i.e. the physical map) for comparative studies between accessions or between species, as this would disguise the detection of synteny among species. However, if the comparison is by means of linkage maps (Choi et al., 2004b) the chromosomal rearrangements will have a significant impact on the inferred synteny relationships if the accessions from which the map derives both share that peculiar chromosomal rearrangement. Otherwise, such as in the case of the M. truncatula primary linkage map, the map does not necessarily show the physical chromosomal composition of A17 or A20 but rather a combination of the two genomes. Therefore, the syntenic relationships between M. truncatula and the other legumes are largely conserved with the exception of ambiguously allocated markers resulting in biased observations (e.g. SQEX in MtLG8 and in PsLGVII: Choi et al., 2004b). 118 Chapter 7 Expression profiling of Medicago truncatula infected with Phoma medicaginis reveals involvement of the octadecanoid and phenylpropanoid pathway in defence against this foliar necrotroph 7.1 Introduction Although plants are continuously challenged by pathogenic microorganisms, the development of disease is a relatively rare event. It is clear, therefore, that plants possess efficient defence systems. Effective induction of the defence response requires pathogen recognition followed by a network of signal transduction processes resulting in the rapid activation of defence gene expression. Research in Arabidopsis has helped our understanding of the resistance response to a range of fungal pathogens. Most of these studies involved pathogens with a biotrophic lifestyle. Although defence responses triggered by biotrophs and necrotrophs in Arabidopsis show a significant degree of overlap, generally salicylic acid (SA)-mediated responses are associated with resistance to biotrophic pathogens, whereas jasmonate (JA) and ethylene (ET) mediated responses are associated with resistance to necrotrophic pathogens (Oliver and Ipcho, 2004). The model legume M. truncatula is a natural host to several fungal necrotrophs (Table 1.1: Infantino et al., 2006; Tivoli et al., 2006a; Tivoli et al., 2006b). Resistance to fungal necrotrophs in legumes is still poorly understood and in particular the defence signalling pathways that operate during necrotroph- legume interactions. Recently, there has been an increased research focus on 119 fungal necrotrophs and hemi-biotrophs using M. truncatula (Colditz et al., 2007; Pilet-Nayel et al., 2005; Tivoli et al., 2005; Torregrosa et al., 2004). Chemical defences against pathogenic microorganisms in leguminosae include the production of alkaloids, coumarins, stilbenes and especially isoflavonoid derivatives. Isoflavonoids possessing pterocarpan and isoflavan skeletons are the most frequently found secondary compounds of legumes with anit-microbial activity (Liu et al., 2003). Although isoflavonoids phytoalexins exhibit antimicrobial activity in vitro (Blount et al., 1992; Hipskind and Paiva, 2000) and are produced at potentially antimicrobial concentrations in Medicago tissue upon infection (He and Dixon, 2000; Paiva et al., 1994), there is no evidence of their direct function as resistance factors in vivo. There is ample evidence of correlation between accumulation of isoflavonoids and resistance to pathogens in Medicago species (Barbetti, 1995; Barbetti, 2007; Deavours and Dixon, 2005; Deavours et al., 2006; Dixon et al., 2002; He and Dixon, 2000; Liu et al., 2003). Interactions between M. truncatula and beneficial microbes have been studied intensively using macro- and microarrays to identify the pathways involved (Frenzel et al., 2005; Hohnjec et al., 2006; Hohnjec et al., 2005; Kuster et al., 2004). However, only a few expression profiling studies have been carried out in M. truncatula infected with fungi (Foster-Hartnett et al., 2007; Foster- Hartnett et al., 2004; Samac et al., 2005; Torregrosa et al., 2004). The aim in this chapter is to utilize expression profiling techniques to examine the M. truncatula defence response to P. medicaginis infection in both resistant and susceptible accessions. Over 300 genes were identified as at least two-fold differentially expressed in plants infected with P. medicaginis relative to mock-inoculated 120 plants 12 hours post infection, using a small scale microarray experiment. Subsequently reverse transcriptase quantitative polymerase chain reaction (RT- qPCR) was used to analyse the expression of a subset of these transcripts in both the susceptible and resistant M. truncatula–P. medicaginis interactions over the course of infection. These genes represented various signalling pathways or showed relatively high abundance in cDNA libraries from various abiotic or biotic stress treatments in M. truncatula. HPLC-UV was employed to identify secondary metabolites involved in the defence response to P. medicaginis. The identification and characterisation of genes, metabolites and pathways involved in the defence response to P. medicaginis are described and their potential for enhanced resistance in Medicago cultivars is discussed in this chapter. 7.2 Materials and Methods 7.2.1 Plant materials and growth conditions The M. truncatula accessions SA27063 and SA3054 were used in this chapter. Plants were grown as desribed in paragraph 2.2.1. 7.2.2 Inoculation procedures and resistance evaluation P. medicaginis OMT5 inoculum was prepared by growing the isolate on wheat meal agar plates (WMA, 12 g ground wheat meal, 12 g agar, and 1 litre of distilled water). The plates were incubated at 22oC for 28-35 days under U/V. Conidia were harvested by incubating plates with 10 mL milliQ water for 20 min. The suspension was filtered through a glasswool syringe, adjusted to 2 x 106 spores/mL, and Tween 20 added to 0.05%. Inoculation of Medicago accessions 121 was performed at the fourth trefoil stage. M. truncatula accessions were inoculated by spraying with an artists airbrush to runoff, using a rotating platform to ensure an even distribution over plant surfaces. To ensure high humidity to stimulate conidia germination, plants were placed in sealed propagator trays for 48 hours. Three biological replicates of infected and control plants (mock inoculated with 0.05% Tween 20 solution) were harvested at 0, 9, 12, 24, 48 and 72 hours post infection. The remaining plants were phenotyped for their resistance to P. medicaginis OMT5 ten days post inoculation as described by Salter and Leath (1992), to determine the success of the infection. 7.2.3 RNA isolation Approximately 150 mg of plant material was ground to a fine powder under a stream of liquid nitrogen. The ground powder was homogenised in 1.5 mL Eppendorf tubes using two times 500 μL TRIzol reagent (Invitrogen Corp., Carlsbad, CA) followed by a 15 minute incubation period at room temperature (RT). After centrifugation at 12000g and 4°C for 10 minutes the supernatant was mixed with 200 μL chloroform, followed by another centrifugation step at 12000g and 4°C for 15 minutes. The upper phase was mixed with 300 μL of high salt precipitation buffer (0.8 M sodium citrate/1.2 M NaCl) and 300 μL of isopropanol and incubated on ice for at least ten minutes to selectively precipitate total RNA. Precipitated RNA was centrifuged (10 minutes 12000 g and 4°C) and washed twice in 75% ethanol. RNA was dissolved in diethylpyrocarbonate (DEPC) treated water. The resulting RNA preparations were adjusted to 1.25 μg/μL using Microcon-30 columns (Millipore, Schwalbach, Germany) and stored 122 at -80°C until further use. The integrity of the total RNA was checked on 1% agarose gels and the quantity and purity was determined spectrophotometrically. 7.2.4 Cy-labelling of hybridization targets, hybridization and image acquisition Twenty micrograms of total RNA was used to synthesize Cy3- or Cy5 labelled cDNA targets according to Kuster et al. (2004) using a mixture of of 2.5 mg of double-anchored oligo(dT)15VN primers and 5 mg of random hexamers. Labelled cDNA was purified using CyScribe GFX columns (Amersham Biosciences, Freiburg, Germany). The labelling efficiency was checked by separating 1/30 (v/v) of the combined targets on 1% agarose gels, that were subsequently scanned for Cy3 and Cy5 fluorescence on a Tyfoon phosphorimager (Amersham Biosciences, Freiburg, Germany) (Kuster et al., 2004). Mt16kOLI1plus microarray slides contained 160086 70mer oligonucleotides representing all TCs from the TIGR M. truncatula Gene Index version 5 (http://www.operon.com/arrays/omad.php) with replicate spots for each TC on the slide. Prior to hybridisation the Mt16kOLI1plus microarray slides were rinsed for 5 minutes in 0.1% Triton X-100, followed twice by 2 minutes in 250 mL MilliQ water containing 29 mL 32% (v/v) HCl, then 10 minutes in 0.1 M KCl, and 1 minute in MilliQ water (at 20 °C each). Slides were blocked for 15 min at 50 °C in 200 mL 13 QMT (Quantifoil) solution containing 46 mL 32% (v/v) HCl. Subsequently, slides were rinsed in MilliQ water (20 °C, 1 minute) and dried by centrifugation (185g, 5 minutes, 20 °C). 123 Hybridization was performed in an ASP hybridization station (Amersham Biosciences) in a sample volume of 250 mL DIG EasyHyb solution (Roche, Mannheim, Germany) supplemented with 15 mg sonicated salmon sperm DNA (Amersham Biosciences). Immediately before injection, samples were denatured for 5 minutes at 65 °C. After 16 hours of hybridization at 42 °C, microarrays were washed once in 2x SSC, 0.2% SDS (1 minute, 42 °C), twice in 0.2x SSC, 0.1% SDS (1 minute, 20 °C), twice in 0.2x SSC (1 minute, 20 °C), and once in 0.1x SSC (1 minute, 18 °C). Slides were dried by centrifugation (185g, 5 minute, 20 °C) and scanned with a resolution of 10 mm using the ScanArray 4000 (PerkinElmer, Boston, USA). 7.2.5 Analysis of image data from microarray hybridization Image processing was performed using the ImaGene 6.0 software (Bio- Discovery, Los Angeles, USA). The mean intensities of signal pixels and the mean intensities of local background pixels were calculated for each spot in both channels and spots were flagged ‘‘empty’’ in the case of R ≤ 0.5 for both channels. The R ≤ 0.5 threshold resulted in the removal of signals corresponding to negative controls and empty wells. Data files were imported into the EMMA2.0 array analysis software (Dondrup et al., 2003) and flagged spots were discarded during import. Subsequent to Lowess normalization with a floor value of 20, regulated genes were identified using a t-statistic. Each sample type (SA27063 control, SA27063 infected, SA3054 control, SA3054 infected) had three biological replicates and two technical dye-swap replicates resulting in twelve data-points (n=12) for each unigene represented on the array. Genes were 124 regarded as significantly differentially expressed if P ≤ 0.01, M ≥ 1 and n ≥ 10 or if P ≤ 0.01, M ≤ -1 and n ≥ 10 with M specifying a log2 expression ratio. 7.2.6 cDNA synthesis, primer design and qRT-PCR In order to follow the levels of expression on differentially expressed genes throughout the interaction in resistant and susceptible accessions three biological replicates per treatment (infected/mock) were collected and cDNA synthesized. cDNA was synthesised, using the iScript cDNA Synthesis Kit (Biorad Laboratories, Hercules, USA), according to manufactures descriptions and as follows: 1 μg of total RNA was added to 4 μL 5x iScript Reaction Mix and 1 μL iScript Reverse Transcriptase and nuclease free water was added to a total volume of 20 μL. cDNA synthesis reactions were incubated for 5 minutes at 25 °C, followed by 30 minutes at 42 °C and 5 minutes at 85 °C. The newly synthesized cDNA was diluted to a total volume of 400 μL. Conventional PCR using intron spanning actin primers was performed to check for contamination of the cDNA samples with genomic DNA. The RT-qPCR primers were designed using the primer3 software (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi) as described by Gao et al. (2007) with minor variations: the product size range was set between 100- 300 bp and primer Tm between 58 °C and 63 °C with an optimum of 60 °C. Furthermore the maximum allowable local alignment score when testing a single primer for (local) self-complementarity was set to five and the maximum allowable 3’ alignment score was set to three. RT-qPCR conditions, such as annealing temperature and primer concentration were optimized for all primer 125 pairs. Once optimized all primer pairs showed a similar amplification efficiency in cDNA derived from both SA27063 and SA3054. RT-qPCR analysis was carried out on a Rotorgene 3000 (Corbett Research, Sydney, Australia) using iQ SYBR Green Supermix (Biorad, Hercules, California). Each reaction contained 10 μL of iQ SYBR Green Supermix, 1 μL each of 5μM forward and reverse primer, 5 μL cDNA, and nuclease free water was added to a total volume of 20 μL. Thermal cycling conditions consisted of 2 minutes at 94 °C and 45 cycles of 30 seconds at 94 °C, 30 seconds at 60 °C; 1 minute at 72 °C. Controls with no added template were conducted for each primer pair to ensure primer dimer was not interfering with amplification detection. The RT-qPCR results were captured and analyzed using the Rotorgene 6.0.14 software (Corbett Research, Sydney, Australia). After real-time PCR, amplification products for each primer set were subjected to melt-curve analysis to ensure that the fluorescence resulted from a single PCR product and did not represent primer dimer or non-specific products. This was conducted by measuring fluorescence over an 11 minute thermal gradient from 72-94 °C and data analysis using the Rotorgene 6.0.14 software. All PCRs were validated in this way by the presence of a single peak in the meltcurve and amplification of a single specific product was further confirmed by electrophoresis on a 2% agarose gel. To compare data from different runs or cDNA samples the threshold cycle (CT) values for all genes were normalised to the reference gene β-actin (TC107326 or TC106785), whose expression did not significantly differ (e.g. remained constant) among the various mock and inoculated samples. The level of transcript abundance relative to reference gene (termed ΔCT) was determined by 126 subtraction of the CT for reference gene from the candidate gene CT according to -ΔΔC the function ΔCT = CT (GOI) - CT (actin). Using the 2 T method (Livak and Schmittgen, 2001) expression data are presented as fold change in gene expression normalised to actin and relative to the untreated control (0 hours). The significant differences in relative transcript abundance for a gene of interest (GOI) at each timepoint was analysed by two-way ANOVA and compared using a Tukey-Kramer HSD test (P < 0.05) with the statistical software package JMP IN 5.1 (SAS Institute, Cary, USA). 7.2.7 Metabolite analysis 7.2.7.1 Chemicals The standards 2’4’4-trihydroxychalcone, 3’5-dimethoxy-4-hydroxy- cinnamic acid, 5’7-dihydroxy-4-methoxy flavone, apigenin, p-coumaric acid, coumestrol, ferulic acid, genistein, genistin, isoquercetin, kaempferol, luteolin, naringin, quercetin, rhoifolin and vanillin were kindly provided by Dr. Ulirke Mathesius. Biochanin A, daidzein, formononetin, liquiritigenin, medicarpin and naringenin were purchased from Indofine (Somerville, NJ, USA). The standards were first dissolved in methanol and those that did not dissolve were dissolved in either acetonitrile or DMSO. All solvents and standards used were HPLC-grade. 7.2.7.2 Metabolite extraction Metabolites of the phenylpropanoid pathway were extracted according to a modified protocol described by Farag et al. (2006). The foliar tissue was ground to a fine powder under a stream of liquid nitrogen, using a mortar and 127 pestle and subsequently freeze dried. 20 mg (± 0.08) of freeze dried tissue were extracted with 1.8 mL aqueous 80% methanol overnight using an orbital shaker in the dark. Extracts were centrifuged at 3000 g for 60 minutes and 1.4 mL of the supernatant was transferred to a new tube and evaporated under nitrogen until dry. The residue was dissolved in phosphate citrate buffer containing 25 units of β-glucosidase o/n at 37 °C to cleave glucoside groups. The aglycones were then partitioned from the aqueous phase into ethyl acetate (2 x 1 mL). The ethyl acetate fractions were evaporated to dryness under nitrogen and residues were resuspended in 100 μL methanol. 7.2.7.3 HPLC-UV instrumentation Twenty-five μL of sample was analysed using an Agilent 1100 series II HPLC system (Hewlett-Packard, Palo Alto, CA, USA), equipped with a photodiode array detector to identify (iso)flavonoids involved in defence against P. medicaginis. UV spectra were obtained by scanning from 200-600 nm. A reverse phase, C18, 5 μm, 4.6, 250 mm column (J.T.Baker, Phililsburg, NJ, USA) and a linear gradient of 5-90% eluent B over 70 minutes, followed by 90- 100% eluent B over 5 minutes and 10 minutes of 100% eluent B were used for separations. The mobile phase consisted of eluent A (0.1% aqueous acetic acid) and eluent B (acetonitrile). The flow rate was 0.8 mL per minute and the temperature of the column was maintained at 28 °C. The area under the peak for a given metabolite was normalised to the dry weight of a sample. The significant differences in metabolite abundance at given timepoint was analysed by two-way ANOVA and compared using a Tukey-Kramer HSD test (P < 0.05) with the statistical software package JMP IN 5.1 (SAS Institute, Cary, USA). 128 7.3 Results To identify genes in M. truncatula that are expressed in defence against the legume necrotroph Phoma medicaginis, resistant (SA27063) and susceptible (SA3054) accessions were infected and sampled at timepoints 0, 12, 24 and 48 hours post infection. Several biological replicates were phenotyped for their disease score as described in paragraph 4.2.2.1 at 7 dpi and 10 dpi (Figure 7.1). RT-qPCR of defence-related homologues in each of the main defence signalling pathways (SA, JA and ET) was used to determine the timing of maximal gene expression for subsequent array experiments (Figure 7.2 A-F). SA responsive genes such as β-1,3-glucanase (TC94670, Figure7.2A) and PR1 (TC105889, Figure 7.2B) were induced in both resistant and susceptible plants upon infection with P. medicaginis OMT5. Similarly JA/ET signalling related genes chitinase (Chit, TC106842) and chalcone synthase (CHS, TC106536) were upregulated in both resistant and susceptible interactions (Figure 7.2D, F). The induction of these genes was significantly higher (by Tukey Kramer HSD-test, P < 0.05) in the resistant interaction at both 12 and 24 hpi. The ethylene response factor 1 gene (ERF1; TC94867) and plant defensin gene (PDF2.1; TC107866), were not induced upon infection with P. medicaginis (Figure 7.2C, E). Highest transcription of defence related genes was observed 12 hours post infection with maximum relative transcript abundances varying between 50.9 and 181.0 (Figure 7.2). This timepoint was therefore chosen for the hybridisation experiments using the Mt16kOLI1plus microarray to identify key genes and pathways in the M. truncatula-P. medicaginis interaction. 129 Figure 7.1 Macroscopic disease symptoms of M. truncatula accessions SA27063 (A) and SA3054 (B) ten days post infection with P. medicaginis OMT5. The pictures represent average disease symptoms among six replicates. The mean disease score for SA27063 and SA3054 were 1.25 and 4.08 respectively. A B 130 Figure 7.2 Differential expression of genes representing the salicylic acid or jasmonic acid/ethylene defence signalling pathway in foliar tissue of mock inoculated control and Phoma medicaginis inoculated SA27063 and SA3054 plants. Transcript abundances with different letters are significantly different by Tukey-Kramer HSD (P < 0.05). (A) β-1,3-glucanase TC94670 (BGL2.1) (B) Pathogenesis related protein 1 TC105889 (PR1); (C) Plant Defensin TC107866 (PDF1.2); (D) Chalcone synthase TC 106636(CHS); (E) Ethylene response factor TC94867 (ERF1); (F) Chitinase TC106842 (Chit). Primer sequences for each of the genes are listed in Appendix 11. A β-1,3-glucanase TC94670 200 a 150 100 b b levels a a 50 c b b Relative transcript 0 0122448 Time (hours) B Pathogenesis related protein 1 TC105889 100 a a 80 60 a 40 levels 20 b b b b b Relative transcript 0 0122448 Time (hours) 131 Defensin C TC107866 3.5 3 2.5 2 1.5 levels 1 0.5 Relative transcript 0 0 122448 Time (hours) Chalcone synthase D TC106536 60 a 50 40 30 b levels 20 a c c a a 10 b b b b ab Relative transcript 0 0122448 Time (hours) Ethylene response factor E TC94867 2 1.5 1 levels 0.5 Relative transcript 0 0 122448 Time (hours) 132 Chitinase F TC106842 200 a 150 100 b levels a 50 c c b b b Relative transcript 0 0122448 Time (hours) SA27063 Mock SA3054 Mock SA27063 Phoma SA3054 Phoma 133 7.3.1 Microarray analysis of transcriptional changes in foliar tissue upon infection with P. medicaginis 12 hours post infection Three biological replicates from independent experiments identified transcriptional changes in several thousand genes 12 hpi with P. medicaginis (P ≤ 0.01, n ≥ 10). Three-hundred-and-thirty-four transcripts showed a change in abundance of 2-fold or more in either the resistant or susceptible interaction (compared to uninfected plants; P ≤ 0.01, M ≥ 1 and n ≥ 10 or if P ≤ 0.01, M ≤ -1 and n ≥ 10 with M specifying the log2 expression ratio; Table 7.1). Of 334 genes, 191 were induced at least 2-fold or more in either the resistant or the susceptible interaction (Figure 7.3A). 65 transcripts were ≥ 2-fold induced upon infection in both interactions. 106 transcripts were ≥ 2-fold induced in infected resistant SA27063 of which 48 only showed minor increase in transcript abundance in infected SA3054 (< 2-fold) and 58 had no significant changes in transcript abundance in SA3054 (P ≤ 0.01; Figure 7.3A; Appendix 03). Furthermore, another 20 transcripts were ≥ 2-fold induced in infected susceptible SA3054 of which 11 showed minor changes in transcript abundance in infected SA27063 (< 2-fold), and 9 had no significant changes in transcript abundance in infected SA27063 (P ≤ 0.01; Figure 7.3A; Appendix 03). Another 147 genes were repressed 2-fold or more upon infection with P. medicaginis in at least one of the interactions (Figure 7.3B; Appendix 04). Of these 51 transcripts were repressed 2-fold or more in both SA27063 and SA3054 (Figure 7.3B; Appendix 04). 73 TCs were ≥ 2-fold repressed infected SA27063 of which 48 only showed minor changes in transcript abundance in infected SA3054 (< 2-fold) and 58 showed no significant change in transcript abundance 134 Table 7.1 Overview of the results obtained from P. medicaginis infection profiling. The table lists the number of probes with a log2 activation or repression ratio M larger than 1 or smaller than -1 (2-fold induction or repression) respectively, of inoculated samples in relation to non-inoculated reference samples 12 hours after treatment (mock or P. medicaginis OMT5). For each interaction three biological replicates were studied. The values are based on probes in which at least 10-12 replicate spots (n) remained after flagging for empty and poor spots and in which associated P-values were < 0.01. Samples Induced probes Repressed probes M >1 Max. M M< -1 Max. M M. truncatula SA27063 12hpi 171 3.75 124 -3.83 with P. medicaginis OMT5 M. truncatula SA3054 12hpi 84 3.11 71 -2.82 with P. medicaginis OMT5 135 Figure 7.3 Differentially expressed transcripts showing a ≥ 2-fold change in abundance 12 hours post infection (hpi) with P. medicaginis OMT5 (A) Differentially expressed transcripts of SA3054 (left circle) and SA27063 (right circle) showing ≥ 2-fold activation ratio (B) Differentially expressed transcripts of SA3054 (left circle) and SA27063 (right circle) showing a ≥ 2-fold repression ratio. Numbers in brackets represent minor (less than 2-fold), but differentially expressed transcript changes in the opposite M. truncatula accession. (A) ≥ 2-fold upregulation of transcripts 12 hpi (B) ≥ 2-fold downregulation of transcripts 12 with P. medicaginis OMT5 hpi with P. medicaginis OMT5 20 106 19 73 SA3054 65 SA27063 SA3054 51 SA27063 Infected (11) (48) Infected Infected (11) (37) Infected 136 in infected SA3054 (P ≤ 0.01; Figure 7.3B; Appendix 04). Furthermore another 19 transcripts were ≥ 2-fold repressed in infected SA3054 of which 11 showed minor changes in transcript abundance in infected SA27063 (< 2-fold) and eight showed no significant change in transcript abundance in infected SA27063 (P ≤ 0.01; Figure 7.3B; Appendix 04). To identify genes involved in various plant processes or metabolic pathways, the sequences of differentially expressed transcripts showing at least a 2-fold change in abundance were annotated and assigned to different functional categories. To achieve this, Phoma-induced genes (PIGs) and Phoma-repressed genes (PRGs) were searched by BLASTN and TBLASTX against Genbank (14th of June 2005) using Seqtools v8.0 software (Rasmussen, 2002). Blast results were compared to the TIGR-MtGI7 annotation. In most cases the best hit to Genbank was identical to the TIGR-MtGI7 annotation. For some PIGs and PRGs however, a better identity was found and a new annotation given. Functional categories of the P. medicaginis induced and repressed genes are shown in Figures 7.4 and 7.5. Significant changes were observed in PIGs related to oxidative burst, cell wall strengthening and lipid metabolism (Appendix 03). These are all processes which have been reported to play a role in plant defence against pathogens and seem to be induced in a similar fashion in both the resistant and susceptible interaction. A few genes with homology to R-genes (TC86207, TC86208 and TC92969) were also induced upon infection in both resistant and susceptible plants (Appendix03). Precursors of the ET and JA pathway were also among the PIGs (Figure 7.4). Various lipoxygenases (LOX), an 12-oxophytodienoic acid 10, 10-reductase (OPR), methyljasmonate esterase and 1-. 137 Figure 7.4 Classification of 191 genes found to be at least 2-fold induced in M. truncatula upon infection with P. medicaginis OMT5 12 hpi. The number of genes allocated to each functional category is indicated. Unknown Other pathways Isoflavanoid biosynthesis 3 11 27 Anti-microbial 16 Oxidative burst 6 7 Transcription factors 8 36 General phenyl propanoid pathway JA/ET biosynthesis 14 Transporters 15 26 Cell wall modification 21 Pathogen perception Lipid metabolism 138 Table 7.2 Genes induced upon infection with P. medicaginis OMT5 of the ethylene and jasmonic acid biosynthesis pathways and genes where products have anti-microbial properties. MtGI* Annotation SA270631 SA30542 Antimicrobial TC76640 Similar to Pprg2 protein (Alfalfa) 2.98 1.79 BM815404 Class PR10-1 protein 2.91 2.32 TC77137 Similar to pathogenesis related protein (Chickpea) 2.88 2.73 TC76511 Class PR10-1 protein 2.87 2.38 TC76641 Similar to Pprg2 protein (Alfalfa) 2.61 TC76643 Similar to Pprg2 protein (Alfalfa) 2.59 1.66 TC76642 Similar to Pprg2 protein (Alfalfa) 2.51 1.47 TC76518 Similar to disease resistance response protein Pi49 2.47 2.10 (PR10)(Garden pea) TC77138 Similar to pathogenesis related protein (Chickpea) 2.39 2.54 TC76638 Similar to Pprg2 protein (Alfalfa) 2.28 -§ TC86847 Similar to osmotin-like protein (Grapevine) 1.94 1.14 TC78899 Sinilar to Glucan endo-1 3-beta-d-glucosidase (Chickpea) 1.88 - BG452227 Homologue to pathogenesis-related protein 4A (Pea) 1.55 - TC84433 Similar to Beta-1,3-glucanase (Soybean) 1.50 - TC85874 Homologue to Beta-1,3-glucanase (Alfalfa) 1.46 - TC86735 Similar to pseudo-hevein (Rubber tree) 1.27 1.37 TC87236 Homologue to pathogenesis-related protein 4A (Garden 1.20 - pea) TC76694 Homologue to thaumatin-like protein PR-5b (Chickpea) 1.15 - TC88905 Class PR10-1 protein 1.07 1.21 TC77149 Similar to thaumatin-like protein precursor Mdtl1 (Apple) 1.03 - TC90394 Class IV chitinase precursor - 1.13 ET/JA pathway TC85808 Similar to 12-oxophytodienoate reductase (Arabidopsis) 1.96 0.75 TC76875 Similar to methyljasmonate esterase (Alfalfa) 1.37 0.85 TC79124 1-aminocyclopropanecarboxylic acid synthase 1.04 0.97 TC85168 Similar to Lipoxygenase (Garden pea) 1.04 - TC91892 Similar to Lipoxygenase (Almond) 0.96 1.13 TC85618 Similar to Lipoxygenase (CPRD46, Cowpea) 0.64 1.24 * Medicago truncatula Gene Index tentative consensus (TC) numbers for the 70- mer oligonucleotides on the microarray (http://compbio.dfci.harvard.edu/tgi/cgi- bin/tgi/gimain.pl?gudb=medicago). 1 log2 expression ratio inoculated/ control SA27063 (resistant) 12 hpi with P. medicaginis OMT5. 2 log2 expression ratio inoculated/ control SA3054 (susceptible) 12 hpi with P. medicaginis OMT5. § Dash (-) indicates that the TC is not significantly differentially expressed (P ≤ 0.01, M ≥ 1 and n ≥ 10). 139 Table 7.3 Differentially expressed transcription factors upon P. medicaginis OMT5 infection MtGI* Annotation SA270631 SA30542 Transcription factors (induced) TC88711 Similar to homeobox-leucine zipper protein (Soybean) 1.03 -§ Similar to ethylene reponse factor-like AP2 domain TC88951 transcription factor (Arabidopsis) 2.08 1.08 Similar to CCAAT-box-binding transcription factor TC79960 (Arabidopsis) 2.05 1.89 Similar to homeodomain-leucine zipper protein 56 TC85738 (Soybean) 1.34 1.04 TC86558 Similar to ERF-like protein (Melon) 1.24 - TC78267 Weakly similar to MYB transcription factor (Arabidopsis) 1.22 - TC84988 Similar to Zinc finger protein (Garden pea) 1.22 0.74 TC79325 Zinc finger, C3HC4 type (M. truncatula) 1.12 - TC86084 Similar to WRKY transcription factor 11 (Arabidopsis) 1.07 - TC86292 Similar to putative WRKY transcription factor 30 (Grape) - 1.04 TC83033 Similar to WRKY8 transcription factor (Rice) - 1.02 TC87393 Similar to CCCH-type zinc finger protein (Arabidopsis) 0.90 1.08 Similar to putative bZIP family transcription factor TC86453 (Arabidopsis) 1.06 - Similar to putative WRKY family transcription factor TC84187 (Arabidopsis) 1.10 0.66 Transcription factors (repressed) TC82271 Similar to DNA binding transcription factor (Arabidopsis) - -1.24 TC81746 Similar to DNA binding transcription factor (Arabidopsis) -1.33 -1.17 TC88924 Similar to DNA binding transcription factor (Arabidopsis) -1.22 -1.11 TC83285 Similar to elicitor induced McWRKY1 (Camomile) - -1.07 TC87781 Similar to transcription factor TINY (Arabidopsis) -0.77 -1.02 Similar to putative bHLH transcription factor TC77495 (Arabidopsis) -1.06 -0.94 TC79195 Zinc finger, TAZ-type; BTB/POZ (M. truncatula) -1.24 -0.98 Similar to light-induced protein CPRF-2 (bZip like) TC86844 (Parsley) -1.09 -0.83 TC77080 Similar to BTB and TAZ domain protein 1 (Arabidopsis) -0.99 -1.54 TC89819 Similar to RING-domain containing protein (Capsicum) -1.29 -1.01 TC78797 Similar to homeobox protein (Arabidopsis) - -1.21 * Medicago truncatula Gene Index tentative consensus (TC) numbers for the 70- mer oligonucleotides on the microarray (http://compbio.dfci.harvard.edu/tgi/cgi- bin/tgi/gimain.pl?gudb=medicago). 1 log2 expression ratio inoculated/ control SA27063 (resistant) 12 hpi with P. medicaginis OMT5. 2 log2 expression ratio inoculated/ control SA3054 (susceptible) 12 hpi with P. medicaginis OMT5. § Dash (-) indicates that the TC is not significantly differentially expressed (P ≤ 0.01, M ≥ 1 or M< -1 and n ≥ 10). 140 aminocyclopropanecarboxylic acid synthase (ACC) were strongly induced in the resistant interaction and to a lesser degree in the susceptible interaction (Table 7.2). The activation of the ET, JA and SA defence signalling pathway leads to the expression of certain pathogenesis related proteins (PR-proteins) with anti- microbial activity. These were also found to be strongly induced upon P. medicaginis infection (Table 7.2). Most PR-proteins upregulated upon infection with P. medicaginis were Pr10-like and showed similar induction in the resistant and susceptible accessions (Table 7.2). Other SA-regulated PR-proteins: Pr2-like (β-1,3-glucanase), Pr4-like (chitinase) and Pr5-like (thaumatin) proteins were strongly induced in the resistant interaction, but no significant change in expression was observed in the susceptible interaction. Pr3 (hevein-like), Pr4 and Pr12 (plant defensins) are JA and ET inducible antimicrobial proteins. One hevein-like protein was induced in both interactions but Pr4-like genes solely in the resistant interaction (Table 7.3). Increased transcript abundances were observed in PIGS with homology to functionally characterised genes belonging to various other pathways other than the ones described in Figure 7.4 (Appendix 03). Increased transcript levels were also observed in PIGs with no homology to functionally characterised genes, but most of the PIGs encode proteins that function in plant secondary metabolic pathway derived from L-phenylalanine, termed the phenylpropanoid pathway (Figure 7.4; Table 7.4; Appendix 03). In the general phenylpropanoid pathway, the phenylalanine ammonia lyase (PAL) genes were equally abundant in the resistant and susceptible interaction. However the trans-cinnamate 4- monooxygenase (CA4H) unigene and the 4-coumarate:CoA ligase (4CL) genes showed a strong induction only in the resistant interaction. 4CL converts 141 coumaric acid into 4-coumaroyl-CoA, which can feed into the lignin biosynthetic pathway, the flavonoid biosynthetic pathway and the isoflavonoid biosynthetic pathway. Besides genes involved in lignin biosynthesis, genes involved in isoflavonoid biosynthesis were strongly induced upon infection in both the resistant and susceptible interaction (Table 7.4). Genes that lead to the production of flavonoids, flavonols, anthocyanins and tannins were not induced 12 hpi with P. medicaginis. In the last 20 years, the role of transcription factors in plant defence has become apparent (see paragraph 1.10). Upon infection with P. medicaginis we observed both induction and repression of several transcription factors (Table 7.3). The induced transcription factors (TF) included ERF, WRKY, bZIP and Zinc finger proteins which were similarly induced in the resistant and susceptible accessions. The exceptions were TC88711, TC86558, TC78267, TC79325, TC86084 and TC86453 which were induced in SA27063 and not in SA3054. Two WRKY-like TF (TC86292 and TC83033) showed abundant transcript levels in the susceptible accession and not in the resistant accession. Among repressed TFs were basic DNA binding transcription factors (TC82271, TC81764 and TC88924) with strong homology with myb-like transcription factors of rice, myb-like genes, a WRKY type, a bHLH type and an ERF-like TF. Most of the repressed TFs, except TC82271 and TC83285, were repressed in a similar fashion in both the resistant and susceptible interactions. Among the 147 genes that were at least 2-fold repressed in either the resistant or the susceptible interaction, most genes were involved in the synthesis of sugars or amino acids (Figure 7.5) and in both SA27063 and SA3054 they were repressed in similar fashion (Appendix 04). Furthermore, various genes 142 Table 7.4 Genes of the phenylpropanoid pathway induced upon infection with P. medicaginis OMT5 MtGI* Annotation SA270631 SA30542 General phenylpropanoid pathway TC85502 Phenylalanine ammonia lyase (M. truncatula) 2.27 1.82 TC85506 Similar to phenylalanine ammonia lyase (Rubus idaeus) 1.29 1.45 TC85501 Homologue to Phenylalanine ammonia lyase (Stylosanthes 1.69 1.44 humilis) TC85505 Phenylalanine ammonia lyase (M. truncatula) 1.64 1.60 TC76780 Trans-cinnamate 4-monooxygenase (M. truncatula) 1.35 - § TC77196 Similar to 4-coumarate:CoA ligase (Amorpha fruticosa) 1.80 - TC77196 Similar to 4-coumarate:CoA ligase (Amorpha fruticosa) 1.19 - TC77753 Similar to 4-coumarate:CoA ligase (Soybean) 1.12 - Isoflavonoid biosynthesis TC76770 Homologue to chalcone synthase 2 (Alfalfa) 3.38 2.75 TC85138 Homologue to chalcone synthase 8 (Alfalfa) 3.30 2.80 TC85146 Homologue to chalcone synthase 2 (Alfalfa) 3.09 2.63 TC76765 Homologue to chalcone synthase 2 (Alfalfa) 3.02 3.11 TC76769 Homologue to chalcone synthase 4 (Alfalfa) 2.31 2.12 TC85174 Homologue to chalcone synthase 4 (Alfalfa) 2.25 1.82 TC85150 Homologue to chalcone synthase 9 (Alfalfa) 2.75 2.57 TC76767 Homologue to chalcone synthase 2 (Alfalfa) 1.98 1.95 TC85174 Homologue to chalcone synthase 4 (Alfalfa) 0.55 1.16 TC85186 Homologue to chalcone synthase 4 (Alfalfa) 1.98 1.94 TC76766 Homologue to chalcone synthase 2 (Alfalfa) 2.01 2.48 TC85521 Homologue to chalcone reductase (Alfalfa) 2.86 2.11 TC76884 Similar to chalcone reductase (Chickpea) 2.24 1.43 TC85521 Homologue to chalcone reductase (Alfalfa) 2.86 2.07 TC85519 Homologue to chalcone reductase (Alfalfa) 2.46 2.15 TC85633 Homologue to chalcone-flavonone isomerase 1 (Alfalfa) 2.01 1.03 TC76950 Similar to chalcone-flavonone isomerase (Arabidopsis) 1.58 0.99 TC77996 Similar to isoflavone-7-O-methytransferase 9 (Alfalfa) 1.40 1.46 TC85608 Isoflavone 2'-hydroxylase (M. truncatula) 1.23 - TC85478 Isoflavone reductase (M. truncatula) 3.75 2.54 TC85477 Isoflavone reductase (M. truncatula) 2.90 2.44 TC86455 Similar to isoflavone reductase homologue (Lupin albus) 1.58 1.20 TC86358 Homologue to 6a-hydroxymaackiain methyltransferase 1.49 1.46 (Garden pea) TC77308 Vestitone reductase (Alfalfa) 1.67 1.62 TC87730 Weakly similar to UDP-glycose:flavonoid 1.75 1.36 glycosyltransferase (Soybean) TC78077 Similar to UDP-glycose:flavonoid glycosyltransferase 1.62 - (Mungbean) Lignin Biosynthesis TC85611 Caffeoyl-CoA O-methyltransferase (Alfalfa) 2.48 1.73 TC85611 Caffeoyl-CoA O-methyltransferase (Alfalfa) 1.84 1.39 TC85981 Similar to Caffeic acid 3-O-methyltransferase 1 (Alfalfa) 1.35 1.63 TC85550 Homologue to caffeic acid 3-O-methyltransferase (Alfalfa) 1.05 0.51 143 MtGI* Annotation SA270631 SA30542 TC92066 Homologue to caffeic acid 3-O-methyltransferase (Alfalfa) 1.05 - TC91631 Weakly similar to putative cinnamyl alcohol 1.06 - dehydrogenase (Apple) TC85789 Similar to peroxidase 3 (Common bean) 1.61 1.33 TC85974 Peroxidase 2 precursor (Alfalfa) 1.34 1.10 TC86423 Homologue to peroxidase precursor (Alfalfa) 1.31 0.67 TC77974 Similar to peroxidase (Soybean) 1.04 - TC85172 Weakly similar to peroxidase 3 (Scutellaria baicalensis) 0.68 1.17 * Medicago truncatula Gene Index tentative consensus (TC) numbers for the 70- mer oligonucleotides on the microarray (http://compbio.dfci.harvard.edu/tgi/cgi- bin/tgi/gimain.pl?gudb=medicago). 1 log2 expression ratio inoculated/ control SA27063 (resistant) 12 hpi with P. medicaginis OMT5. 2 log2 expression ratio inoculated/ control SA3054 (susceptible) 12 hpi with P. medicaginis OMT5. § Dash (-) indicates that the TC is not significantly differentially expressed (P ≤ 0.01, M ≥ 1 and n ≥ 10) 144 Figure 7.5 Classification of 147 genes found to be at least 2-fold repressed in M. truncatula upon infection with P. medicaginis OMT5 12 hpi. The number of genes allocated to each functional category is indicated. Amino Acid Biosynthesis Circadian rhythm 40 Inositol metabolism Pathogen perception 40 14 Sugar metabolism Transcription factors 5 Transporters 5 6 1 Unknown 12 24 Other 145 associated with circadian rhythm, inositol metabolism and transporters were repressed 12 hpi with no significant observed differences between the resistant and susceptible accessions (Appendix 04). The bulk of repressed genes belong to the category ‘unknowns’ with no functional annotation, but with similarity to unknown expressed Arabidopsis sequences (Appendix 04). 7.3.2 Induction of genes diagnostic of the salicylic acid and jasmonic acid defence signalling pathways upon P. medicaginis infection The SA-signalling pathway in plants regulates defence against many pathogens, in particular biotrophs, whereas the JA-signalling pathway regulates defence against predominantly necrotrophs (Glazebrook, 2005). To investigate this diagnostic SA and JA-signalling pathways related genes were studied using RT-qPCR. The SA responsive genes studied upon infection with P. medicaginis in this paragraph have been shown to be induced upon treatment with SA in M. truncatula (Gao et al., 2007). The SA responsive genes were β-1,3-glucanase, PR5 and PR10 and showed no significant transcript accumulation in mock inoculated plants (Figure 7.6). A small but significant increase in transcript abundance was observed for β-1,3-glucanase transcript levels in infected SA3054 compared to both their mocks and SA27063 plants at 9 hpi (Figure 7.6a). The β- 1,3-glucanase transcript levels declined and returned to their basal levels by 24 hours. In susceptible plants following infection, an increase in transcript abundance of PR5 was seen at 9 hours, reaching a peak at 12 hours with significantly higher levels of expression observed throughout the later stages of the infection (Figure 7.6b). In contrast, a slight but significant increase in PR5 transcript abundance was seen at 24 hours post infection in resistant plants, 146 Figure 7.6 Regulation of genes representing the salicylic acid signalling pathway upon P. medicaginis OMT5 inoculation of foliar tissue of SA27063 and SA3054. The relative transcript abundance is shown as a ratio of the relative gene expression for each sample to that in the untreated SA27063 or SA3054 and values are the mean of three biological replicates. Different letters for a given timepoint indicate significant difference in transcript abundance by Tukey Kramer HSD- test (P < 0.05)and a white star () indicates significant difference in transcript abundance between treatments (control vs Phoma) for a given timepoint (P < 0.05). Primer sequences for the genes are listed in Appendix05. β-1,3-glucanase A TC98780 25 20 15 a 10 ab abundance 5 ab b Relative transcript 0 0 122436486072 Time (hours) B PR5 TC100682 25 20 15 a a 10 a b b a abundance 5 b b b b b b Relative transcript 0 b b 0 122436486072 Time (hours) 147 C PR10 TC94219 700 a a 600 500 400 300 b b 200 abundance 100 c c Relative transcript 0 c c 0 122436486072 Time (hours) SA27063 Mock SA3054 Mock SA27063 Phoma SA3054 Phoma 148 which returned to basal levels by 48 hours (Figure 7.6b). Minor changes in transcript abundance were observed for resistant plants upon infection for either β-1,3-glucanase or PR5 (Figure 7.6a, b). In stark contrast, transcript levels of PR10 increased strongly upon P. medicaginis infection in both SA27063 and SA3054 (Figure 7.6c). For PR10, following infection, an increase in transcript level was seen at 9 hours and reached a peak at 24 hours in resistant plants, whereas in susceptible plants the increase started at 9 hours and reached a peak at 48 hours (Figure 7.6c). Various genes of the octadecanoid acid pathway (Figure 7.7) leading to MeJA biosynthesis were studied over the course of the infection. These genes have been shown to be induced upon treatment with MeJA in M. truncatula (Gao et al., 2007; http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/tc_report.pl). Genes of the octadecanoid pathway were induced in resistant and susceptible accessions following P. medicaginis infection, but differences in the kinetics and magnitude of induction were observed (Figure 7.8). For the lipoxygenases a significant increase in transcript abundance was observed at 9 and 12 hours, which returned to basal levels by 24 hours (Figure 7.8a-c). In all cases, significantly higher lipoxygenase transcript abundances were observed for infected resistant plants at 9 hours compared to their mock inoculated counterparts (Figure 7.8a-c). Similarly, higher lipoxygenase transcript abundances were observed for infected susceptible plants at 12 hours compared to their mock inoculated counterparts (Figure 7.8a-c). The lipoxygenase transcript abundance thus accumulates faster upon infection in resistant plants than in susceptible plants. Allene oxide synthase (AOS) is the second enzyme in the octadeconoid pathway. Of the two known AOS genes in M. truncatula (TC101097 and 149 Figure 7.7 Schematic illustration of the octadecanoid pathway (adapted from Gao et al., 2007). Figure legend: LOX = Lipoxygenase, AOS = allene oxide synthase, OPR = 12- OPDA reductase, DES = divinyl ether synthase and HPL = hydroperoxide lyase. 150 Figure 7.8 Regulation of genes representing the octadecanoid pathway upon mock or P. medicaginis OMT5 inoculation of foliar tissue of SA27063 and SA3054. The relative transcript abundance is shown as a ratio of the relative gene expression for each sample to that in the untreated SA27063 or SA3054 and values are the mean of three biological replicates. Different letters for a given timepoint indicate significant difference in transcript abundance by Tukey Kramer HSD- test (P < 0.05) and a white star () indicates significant difference in transcript abundance between treatments (control vs Phoma) for a given timepoint by (P < 0.05). Primer sequences for the genes are listed in Appendix05. A Lipoxygenase TC100514 25 a 20 a 15 ab ab 10 ab b b abundance 5 b Relative transcript 0 0 122436486072 Time (hours) B Lipoxygenase TC100155 25 20 a a 15 ab 10 b ab b b abundance 5 b Relative transcript 0 0 122436486072 Time (hours) 151 C Lipoxygenase TC100513 40 a 30 a ab 20 b b 10 b b abundance b Relative transcript 0 0 122436486072 Time (hours) D Allene oxide synthase TC101097 10 a a 8 6 b ab 4 c ab abundance 2 c b Relative transcript 0 0 122436486072 Time (hours) E Allene oxide synthase TC110784 25 20 a 15 b 10 abundance 5 c c Relative transcript 0 0 122436486072 Time (hours) 152 F 12-OPDA reductase TC94406 35 30 25 20 15 10 abundance 5 Relative transcript 0 0 122436486072 Time (hours) 12-OPDA reductase G TC94407 35 a 30 25 20 ab a 15 10 b b abundance b 5 b b Relative transcript 0 0 122436486072 Time (hours) SA27063 Mock SA3054 Mock SA27063 Phoma SA3054 Phoma 153 TC101097), one (TC101097) showed a small change in transcript abundance in infected tissue at 12 hours (Figure 7.8d). The second AOS gene however had significantly higher transcript abundances in mock and inoculated resistant plants than in mock and inoculated susceptible plants 24 hours post treatment (Figure 7.8e). No other significant differences in transcript abundance were observed for the AOS genes (Figure 7.8d, e). The 12-OPDA reductase genes were induced in both resistant and susceptible plants following P. medicaginis inoculation (Figure 7.8f, g). The increase in gene transcript occurred as early as 9 hours and was significantly different from mock inoculated plants at 12, 24 and 48 hours (Figure 7.8f, g). 7.3.3 Induction of genes involved in the phenylpropanoid pathway upon P. medicaginis infection Various genes in the phenylpropanoid pathway (Figure 7.9) showed differences in transcript abundance on the Mt16kOLI1plus array upon P. medicaginis infection in both the resistant and susceptible interactions. Certain genes for example, isoflavone 2’-hydroxylase (TC85608), were only significantly induced in the resistant M. truncatula accession (Table 7.4) at 12 hours post infection. To see whether the differences in transcript abundance were a consistent response, these genes were also studied over the course of infection, by RT-qPCR. Gene specific primers were tested by conventional PCR and sequencing to see if a single gene product was amplified. In case of the large chalcone synthase gene family multiple products (e.g. multiple CHS genes) were amplified and thus not used in the transcription profiling. The main focus hence remained on genes from small gene families or unigenes. An overview of the 154 Figure 7.9 Schematic illustration of the phenylpropanoid pathway (adapted from Dixon et al 2002). Legend: BA = benzoic acid; BA2H = benzoic acid 2-hydroxylase; t-CA = trans - cinnamic acid; 4-CA = 4-coumaric acid; CA2H = cinnamate 2-hydroxylase; Calc = coniferyl alcohol; Cald = coniferaldehyde; CafCoA = caffeoyl CoA; 4-CCoA = 4-coumaroyl CoA; CGA = chlorogenic acid; C3H = coumarate (coumaroyl quinate/shikimate) 3-hydroxylase; C4H = cinnamate 4-hydroxylase; ChA = chorismic acid; i-ChA = isochorismic acid; 4-CL = 4-coumarate:CoA ligase; 155 CHR = chalcone reductase; CHS = chalcone synthase; COMT = caffeic acid O methyltransferase; Csh = 4-coumaroyl shikimate; Daid = daidzein; FerA = ferulic acid; FerCoA = feruloyl CoA; Gen = genistein; 5-HCald = 5- hydroxyconiferaldehyde; HQT = hydroxycinnamoyl-CoA:quinate hydroxycinnamoyl transferase; ICS = isochorismate synthase; IFR = isoflavone reductase; IFS = isoflavone synthase; Il = isoliquiritigenin; IOMT = isoflavone O -methyltransferase; Liq = liquiritigenin; MCoA = malonyl CoA; Med = medicarpin; Nar = naringenin; Nc = naringenin chalcone = PAL = L – phenylalanine ammonia-lyase; L-phe = L -phenylalanine; PL = pyruvate lyase; SA = salicylic acid; Salc = sinapyl alcohol; Sald = sinapaldehyde; ShA = shikimic acid; Van = vanillin; VR = vestitone reductase. Note that the pathways are, in several places, over-simplified.Reactions not designated with an enzyme name may be catalysed by more than one enzyme. 156 gene families of the phenylpropanoid pathway and the corresponding primers amplifying a single gene PCR product are listed Appendix 06. Genes in the phenylpropanoid pathway showed no significant differences in transcript abundance over the course of the experiment in controls (Figure 7.10, Appendix 07). In infected plants genes involved in the synthesis of isoflavonoids were induced in both resistant and susceptible plants where differences in the kinetics and magnitude of induction were observed (Figure 7.10; Appendix 07). For chalcone isomerase (CHI) and isoflavone synthase (IFS) a significant increase in transcript abundance was observed in infected resistant and susceptible plants at 12 hpi (Figure 7.10a, b). CHI had its highest transcript abundance at 12 hpi, whereas the IFS maximum was at 48 hpi. A similar transcript abundance pattern was observed for isoflavone 3’-hydroxylase (Figure 7.10h), but the magnitude of transcript abundance was larger compared to IFS. Differences in isoflavone O-methyltransferase (IFMT) transcript abundance were observed in resistant and susceptible plants upon P. medicaginis infection (Figure 7.10c-f). In resistant plants, the highest IFMT transcript levels were observed at 12 hpi, similar to those in infected susceptible plants. Significantly higher IFMT transcript levels were observed in infected susceptible plants throughout the later stages of the infection, which could either be prolonged or a second induction in transcript abundance (Figure 7.10c-f). Three isoflavone hydroxylase genes (TC94324, TC95424 and TC100787) were studied over the course of infection. No significant changes in transcript abundance were observed for the isoflavone 3’-hydroxylase (IF3H) TC100787 (Appendix 07); whereas IF3H homologue TC95424 was strongly induced in the susceptible interaction from 12 hpi reaching maximum transcript abundance at 48 hpi 157 Figure 7.10 Regulation of genes representing the isoflavonoid pathway upon mock or P. medicaginis OMT5 inoculation of foliar tissue of SA27063 and SA3054. The relative transcript abundance is shown as a ratio of the relative gene expression for each sample to that in the untreated SA27063 or SA3054 and values are the mean of three biological replicates. Different letters for a given timepoint indicate significant difference in transcript abundance by Tukey Kramer HSD- test (P < 0.05) and a white star () indicates significant difference in transcript abundance between treatments (Mock vs Phoma) for a given timepoint (P < 0.05). Primer sequences for each gene are listed in Appendix 05 and Appendix 06. A Chalcone Isomerase TC100522 25 20 15 10 a ab abundance 5 b 0 b Relative transcript transcript Relative 0 122436486072 Time (hours) Isoflavone synthase B TC106939 40 a 30 20 b 10 abundance c Relative transcript 0 0 122436486072 Time (hours) 158 C Isoflavone O -methyl-transferase TC101335 25 20 15 a 10 ab abundance 5 b Relative transcript 0 0 122436486072 Time (hours) D Isoflavone O -methyl-transferase TC101336/7 30 a 25 20 15 10 abundance 5 b b Relative transcript 0 0 122436486072 Time (hours) Isoflavone O -methyl-transferase E TC95934 50 a 40 a 30 20 b a abundance 10 b b b Relative transcript 0 b b b 0 122436486072 Time (hours) 159 Isoflavone O -methyl-transferase F TC100926 30 a 25 20 15 a b 10 abundance b c 5 c c Relative transcript transcript Relative c 0 0 122436486072 Time (hours) G Isoflavone 2'-hydroxylase TC94324 10 a 8 6 4 ab abundance b 2 b Relative transcript 0 0 122436486072 Time (hours) Isoflavone 3'-hydroxylase H TC95424 100 a 80 a 60 40 b abundance 20 a b 0 b c c Relative transcriptRelative b c c 0 122436486072 Time (hours) 160 Isoflavone reductase I TC96312 300 250 a 200 a 150 b 100 a abundance 50 a b b b c c c Relative transcript 0 b c c 0 122436486072 Time (hours) J Isoflavone reductase TC85477 300 a 250 200 150 b a 100 a abundance 50 b b b c c Relative transcript 0 b c 0 122436486072 Time (hours) Vestitone reductase K TC100886 25 20 15 10 a abundance 5 ab ab Relative transcript 0 b 0 122436486072 Time (hours) 161 L Caffeic acid O -methyltransferase TC100776 2000 a a 1500 1000 a a b ab 500 abundance b b b b c b b Relative transcript 0 c b 0 122436486072 Time (hours) Ferulate-5-hydroxylase M TC111608 10 8 a 6 ab 4 b abundance 2 b Relative transcript 0 0 122436486072 Time (hours) SA27063 Mock SA3054 Mock SA27063 Phoma SA3054 Phoma 162 (Figure 7.10h). An increase in transcript abundance for this gene was also observed in the resistant interaction from 48 hpi, and was significantly smaller than the transcript abundance observed in susceptible infected plants (Figure 7.10 h). In contrast to any of the isoflavonoid pathways genes isoflavone 2’- hydroxylase (IF2H), the enzyme responsible for converting formononetin into 2’- hydroxyformononetin, showed stronger transcript abundance upon infection in resistant plants than in susceptible plants in particularly at 24 hours post infection (Figure 7.10g). In the subsequent enzymatic step in the pathway isoflavone reductase genes (IFR) convert 2’-hydroxyformononetin into vestitone reductase (Figure 7.9). IFR transcript was strongly induced upon P. medicaginis infection and reached its peak at 12 hpi, where susceptible plants showed significantly higher transcript abundance than resistant plants (Figure 7.10i, j), particularly at 9 hpi. Throughout the later stages of the infection, significantly higher transcript abundances were observed in infected plants than in uninfected plants (Figure 7.10i, j). Similarly increased transcript abundances were observed for vestitone reductase upon infection, as early as 9 hpi, reaching maximum transcript abundance at 12 hpi and remaining induced in the later stages of the infection (24-72 hours; Figure 7.8k). This one of two enzymes involved in the conversion of vestitone into the phytoalexin medicarpin (Guo et al., 1994: Figure 7.9). The array data showed that the lignin biosynthesis genes caffeoyl CoA O- methyltransferase (CCOMT) and caffeic acid acid O-methyl transferase (COMT) were induced more than two fold at 12 hpi. Therefore, a subset of lignin biosynthesis genes was further investigated. For the CCOMT gene TC94321 and COMT TC106629, no significant changes were observed over the course of 163 infection (Appendix 07), whereas COMT TC100776 was strongly induced over the course of the experiment in both mock and inoculated plants (Figure 7.10l; Appendix 07). A swift response upon infection with P. medicaginis was observed in resistant plants, with significantly higher transcript abundances at 9- 24 hpi reaching maximal transcript abundance at 24 hpi. Susceptible infected plants reached similar maximum transcript abundance to resistant plants at 48 hours, thus showing a similar yet delayed response (Figure 7.10l). The subsequent enzyme in the synthesis of monolignols is ferulate-5-hydroxylase (F5H) which also showed a significant increase in transcript abundance upon P. medicaginis infection in the resistant plants compared to infected susceptible plants (Figure 7.10m). 7.3.4 Transcriptional changes in the phenylpropanoid pathway upon P. medicaginis infection lead to an increased abundance of metabolites in this pathway As transcript levels phenylpropanoid pathway genes do not necessary reflect enzyme activity, HPLC-UV was employed to differentiate, identify and quantify the major (iso)flavonoids involved in the defense response to P. medicaginis. The method of choice reported here has been used to profile (iso)flavonoids in red and white clover (Lin et al., 2000; Wu et al., 2003) and M. truncatula (Farag et al., 2006). The UV spectra (200-600 nm) and retention times were recorded for 22 (iso)flavonoid standards and are listed in Table 7.4. The photodiode array detection provided an overview of the main flavonoid constituents in M. truncatula foliar tissue. Using the linear gradient described in paragraph 7.2.7.3 a total of 62 peaks could be resolved. In uninfected tissue p- 164 Table 7.4 Metabolites of the phenylpropanoid pathway their retention times and maximum absorbances as identified by HPLC-DAD described in paragraph 7.2.7.3. Absorbance Retention time maxima (min) Identification λmax (nm) 22.6 Isoquercetin 246,340 22.6 Vanillin 206,231,280,310 23.0 p-coumaric acid 237,278,325 23.5 Genistin (genistein-7-glucoside) 260,330 23.6 Naringin 214,225,283,330 23.7 Ferulic acid (4-hydroxy-3-methoxy cinnamic acid) 240,325 23.8 Rhoifolin 200,267,338 23.8 Sinapic acid (3’5’dimethoxy-4-hydroxy-cinnamic acid) 237,325 30.6 Daidzein (7, 4'dihydroxyisoflavone) 215,324 31.5 Liquirtigenin 217,231,275,312 32.1 Luteolin 210,250,270,347 32.5 Quercetin dihydrate 255,370 35.9 Naringenin (5,7,4'-trihydroxyflavonone) 200,214,226,289 36.5 Apigenin 230,265,335 36.5 Genistein (5,7,4'-trihydroxyisoflavone) 260 37.1 Coumestrol 207,244,343 37.2 Kaempferol 200,228,265,367 39.8 2'4'4-trihydroxy chalcone 205,240,345,387 40.3 Formononetin 249, 305 43.9 Medicarpin 233, 286 46.4 5’7-dihydroxy-4-methoxy flavone 212,268,330 47.0 Biochanin A 261,330 165 coumaric acid, daidzein, liquirtigenin, naringenin, coumestrol, formononetin and medicarpin were identified, based on their retention time and absorbance spectra to authentic standards. The compound(s) that eluted at retention times 36.5 showed a similar yet not identical absorbance spectra to apigenin, indicating that perhaps multiple compounds elute at this retention time. Apigenin is the most prevalent flavonoid in M. sativa (iso)flavonoid extractions of untreated plants (Deavours and Dixon, 2005) which would suggest that the most prevalent compound(s) eluting at 36.5 contain apigenin. A possible co-eluent is genistein (Table 7.4). None of the other standards were detected in either in infected or uninfected tissue. To identify which of the eluted compounds showed significant differences in metabolite abundance upon infection, the 62 metabolites were subjected to a three-way ANOVA and compared by a Tukey-Kramer HSD-test (P < 0.05). Forty-six metabolites, including daidzein (Figure 7.11a), liquiritigenin (Figure 7.11b) and p-coumaric acid (Figure 7.11c) did not show significant changes in abundance upon infection. However, individual time points showed occasional significant differences in abundance between accessions. For example,a significantly higher abundance of p-coumaric acid was observed in the susceptible accession compared to the resistant accession at twelve hours post treatment (infected or mock) which restored to similar levels during the remainder of the experiment (Figure 7.11c). In the case of daidzein, a significantly lower amount was present in infected tissue (for both SA27063 and SA3054) compared to uninfected tissue at the 12 hour time point. A higher level of daidzein was observed at 48 hours post infection of SA27063 compared to all other plants tested (Figure 7.11b). 166 Figure 7.11 Abundance of metabolites in M. truncatula accession SA27063 and SA3054 mock inoculated and inoculated with P. medicaginis OMT5 over a period of 72 hours. Metabolite abundances are the mean of three biological replicates. Different letters for a given timepoint indicate significant difference in transcript abundance by Tukey Kramer HSD- test (P < 0.05), a white star () indicates significant difference in transcript abundance between treatments (Mock vs Phoma) for a given timepoint (P < 0.05) and a black star () indicates significant difference in transcript abundance between accessions (SA27063 vs SA3054) for a given timepoint (P < 0.05). A RT = 30.6 (Daidzein) 700 600 a 500 400 b 300 b the Peak 200 b 100 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) B RT = 31.6 (Liquiritigenin) 400 a 350 300 ab 250 200 ab 150 the Peak b 100 50 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) 167 C RT = 23.0 (p-Coumaric Acid) 1600 1400 1200 1000 800 600 the Peak 400 200 0 Normalised Area under 0 122436486072 Time (hours) D RT = 37.1 (Coumestrol) 250 a 200 ab 150 b Peak 100 50 c Normalised Area under the the under Area Normalised 0 0 122436486072 Time (hours) E RT = 35.2 200 a 150 a 100 ab the Peak 50 b 0 Normalised Areaunder 0 122436486072 Time (hours) 168 F RT = 36.5 1600 1400 1200 1000 a 800 600 b the Peak 400 bc 200 c 0 Normalised Areaunder 0 122436486072 Time (hours) G RT = 42.3 500 a a 400 300 b b 200 c c the Peak 100 c c 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) H RT = 42.7 400 350 300 a 250 a 200 ab 150 the Peak 100 b 50 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) 169 I RT = 35.8 (Naringenin) 200 150 a 100 b the Peak 50 c c 0 Normalised Area under 0 122436486072 Time (hours) J RT = 40.3 (Formononetin) 300 a 250 a b 200 a 150 b the Peak 100 b c c 50 c c c c 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) K RT = 39.4 120 100 a a 80 b 60 b the Peak 40 bc 20 c 0 c c Normalised Area under under Area Normalised 0 122436486072 Time (hours) 170 L RT = 40.9 100 80 60 40 the Peak 20 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) M RT = 32.0 350 300 250 200 a 150 a the Peak 100 b 50 b b 0 b b Normalised Area under under Area Normalised 0 122436486072 Time (hours) N RT = 28.9 500 a 400 300 200 a the Peak b 100 ab b b b 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) 171 O RT = 31.0 500 a 400 a a 300 b b 200 b the Peak 100 c c 0 Normalised Area under 0 122436486072 Time (hours) P RT = 44.0 (Medicarpin) 120 100 80 60 the Peak 40 20 0 Normalised Area under under Area Normalised 0 122436486072 Time (hours) SA27063 Mock SA3054 Mock SA27063 Phoma SA3054 Phoma 172 Sixteen metabolites showed a significant change in metabolite abundance upon P. medicaginis infection. Five compounds showed constitutively higher metabolite abundance in the resistant accession SA27063, compared to the susceptible accession SA3054, irrelevant of the treatment (Figure 7.11d-h). These were coumestrol (RT = 37.1) and the unidentified metabolites at retention times of 35.2, 36.5, 42.3 and 42.7 (Figure 7.11d-h). Coumestrol and RT 35.2 showed an increased abundance 72 hpi in the susceptible accession SA3054, which is similar to the levels in SA27063 at 72 hours (Figure 7.11d, e). From 24 hpi onwards naringenin, formononetin and RT 32.0, RT 39.4 and RT 40.9 showed increased levels in both infected plants compared to mocks (Figure 7.11 i-m). Naringenin and formononetin are metabolites that can feed into the synthesis of the pterocarpan medicarpin (Figure 7.10). Medicarpin production was significantly increased in infected plants compared to their mock inoculated controls from 48 hours post treatment (Figure 7.11p). The metabolites at retention times 28.3 and 31.0 showed an increased abundance upon infection with P. medicaginis, with SA27063 showing a significant increase from 48 hpi and SA3054 at 72 hpi (figure 7.11n, o). The metabolite at retention time 32.0 showed a rapid increase from 24 hpi onwards, whereas in SA3054 an increased abundance was first observed at 48 hpi (Figure 7.11m). These three unknown metabolites thus accumulate faster upon P. medicaginis infection in resistant plants than in susceptible plants. 173 7.4 Discussion The main purpose of this chapter was to analyse the molecular components of Medicago resistance to this fungal necrotroph. To achieve this two M. truncatula accessions with resistant and susceptible disease responses to P. medicaginis OMT5 from the SARDI core collection of M. truncatula accessions (Ellwood et al., 2006c) were examined. Transcriptional profiling at 12 hpi using the Mt16kOLI1plus microarray resulted in the identification of 191 gene transcripts induced upon P. medicaginis infection, belonging to various components of pathogen defence (Figure 7.4). A large proportion of these genes were strongly induced in SA27063 and a small proportion in SA3054 (Figure 7.3). Although these gene transcripts will have to be studied over the course of an infection, the findings here fit well with the widely accepted concept that defence responses are delayed and less intense in susceptible plants than in resistant ones. Interactions between plants and pathogens induce a series of plant defence responses, such as the production of signalling compounds (reactive oxygen intermediates, salicylic acid, nitric oxide, ethylene and jasmonic acid) leading to the activation of many downstream responses such as the synthesis of antimicrobial peptides, phenolics, (iso)flavonoids and other potential phytoalexin compounds (Hammond-Kosack and Jones, 1997). Significant changes were observed in PIGs related to oxidative burst, cell wall strengthening and lipid metabolism (Appendix 03). Within minutes of contact between a host plant and a 2- pathogen, ROIs such as O and H2O2 are produced in an oxidative burst. The oxidative burst is usually a result of R-gene mediated resistance. A few such disease resistance-like genes (TC86207, TC86208 and TC92969) were induced upon infection. These disease resistance-like genes, peroxidases and alternate 174 oxidases were induced in both the resistant and susceptible interaction (Appendix 03). According to Glazebrook (2005), gene-for-gene resistance is not expected to be observed in interactions with necrotrophs, as host cell death is not predicted to limit pathogen growth (Glazebrook, 2005). In fact, there are no examples of Avr- gene-for-R-gene resistance against Alternaria brassicicola and Botrytus cinerea in Arabidopsis (Glazebrook, 2005). However, necrotrophic pathogens are believed to stimulate ROS production in the infected tissue to induce cell death that facilitates subsequent infection (Torres et al., 2006). In a detailed study in barley ROIs were observed in the early stages of the infection by necrotrophic pathogens in both resistant and susceptible interactions (Able, 2003). In the later stages of the infection a susceptible-specific second burst of ROIs was observed (Able, 2003). This would suggest an early role for ROIs in defence signalling against necrotrophs. In Arabidopsis there is evidence that HO2•/O2- production may still be essential to limit the size of lesions through the induction of ET or JA in plants challenged with Botrytis cinerea (Thomma et al., 2000; 1999). In this pathosystem there is an induction of genes involved in ROS upon infection, but whether this aids the plant or the necrotrophs remains to be answered. During P. medicaginis infection of M. truncatula we observed an increased abundance of genes involved in monolignol biosynthesis (Appendix 03). In particular the COMT and F5H were rapidly induced upon infection in resistant plants (Figure 7.10l, m). The susceptible plants showed a slower response in COMT transcript abundance and no significant increase in F5H transcript was observed. Lignin, a major component of secondary cell walls, is a phenolic polymer made by oxidative polymerisation of monolignols (Boerjan et al., 2003), achieved by peroxidase activity and H2O2 in the cell wall. From 175 various Arabidopsis pathosystems it became apparent that lignin and lignin-like compounds accumulate around the site of pathogen infection, changing the rigidity and digestibility of the cell walls. A swift response in monolignol synthesis and generation of H2O2 helps to prevent the pathogen from spreading to neighbouring cells. One could thus hypothesize that a rapid response of monolignol biosynthesis in M. truncatula contributes to the resistance response to P. medicaginis. Not all PAL, CCOMT and COMT genes were induced upon infection and M. truncatula thus seems to stimulate selective expression of particular members of these gene families upon infection with P. medicaginis. The PAL (TC85501, TC85502 and TC85505) and CCOMT (TC85611) genes strongly induced upon P. medicaginis infection were also most abundantly induced upon C. trifolii infection of M. truncatula (Dixon et al., 2002). These genes were not induced in three M. truncatula accessions infected with the biotroph E. pisi (Foster-Hartnett et al., 2007). M. truncatula thus utilises distinct members of gene families of the monolignol biosynthesis pathway which are responsive to necrotrophs a not to biotrophs. The Mt16kOLI1plus array identified genes of the octadecanoid pathway to be induced upon infection with P. medicaginis at 12 hpi (Table 7.2). A major output of the octadecanoid pathway is the production of JA, but there are branch points that lead to the production of other compounds (Figure 7.7). The key enzymes at these branch points (hydroperoxide lyases and divinyl ether synthases) did not show any significant changes in transcript abundance 12 hours post infection. Furthermore, a gene with strong homology to an alfalfa methyl jasmonate esterase (TC76875) was strongly induced 12 hpi. Using RT-qPCR we confirmed strong induction of octadecanoid pathway genes leading to JA 176 synthesis (Figure 7.8a-g). The lipoxygenase genes showed swift response upon P. medicaginis infection, with resistant plants and susceptible plants showing strongest transcript abundance at 9 hpi and 12 hpi respectively. The subsequent allene oxide synthase and 12-OPDA reductase genes were also induced upon infection in both resistant and susceptible plants. These results suggest a strong case for the involvement of the octadecanoid pathway in the defence response to P. medicaginis. The observed induction of the octadecanoid pathway does not seem to be R-gene mediated, since it is induced in both resistant and susceptible M. truncatula plants (Figure 7.8a-g). This differs from the response of M. truncatula to C. trifolii, where six lipoxygenase genes were induced in resistant interaction and only two in the susceptible interaction (Torregrosa et al., 2004), where the authors suggest resistance in incompatible interactions might be mediated through the octadecanoid pathway. The activation of the defence signalling pathways such as JA and SA lead to the expression of certain pathogenesis related proteins with anti-microbial activity. Most pathogenesis related proteins upregulated upon infection with P. medicaginis were Pr10-like proteins and were strongly induced in both the resistant and susceptible interactions (Table 7.2). These Pr10 genes are also strongly induced upon infection of M. truncatula with the pathogens Aphanomyces euteiches (Colditz et al., 2005; 2007), C. trifolii (Torregrosa et al., 2004), E. pisi (Foster-Hartnett et al., 2007) and various other biotic stresses. Some Pr2-like (β-1,3-glucanase) and Pr5-like (thaumatin) proteins were also induced. Exogenous application of SA in Arabidopsis leads to induction of Pr1, Pr2 and Pr5 mRNAs (Van Loon et al., 2006), but in M. truncatula only a few Pr-gene homologues have actually been demonstrated to be SA responsive (Gao 177 et al., 2007). SA regulated defence related proteins were assumed to be primarily directed against pathogens with a biotrophic lifestyle, as shown in the E. pisi- M. truncatula pathosystem (Foster-Hartnett et al., 2007). In this study induction of these genes occurs upon infection with a necrotroph. Infection of M. truncatula with the hemi-biotroph C. trifolii results in induction of various SA-regulated Pr genes (Torregrosa et al., 2004). Confirmation of increased transcript abundance of SA regulated Pr genes using RT-qPCR revealed only minor induction of the SA regulated Pr2 and Pr5 genes (Figure 7.6a, b), whereas PR10 expression was strongly induced upon P. medicaginis infection. Pr3 (hevein-like), Pr4 and Pr12 (plant defensins) are JA and ET inducible antimicrobial proteins of Arabidopsis. In this study, a hevein-like protein is induced in both resistant and susceptible interactions, but Pr4-like genes solely in the resistant interaction (Table 7.3). In Arabidopsis a distinction between the SA-inducible Pr-proteins and the JA/ET- inducible Pr-proteins seems clear (Thomma et al., 2001). In tobacco it has been demonstrated that different members within the same protein family are differentially regulated by SA and JA/ET (Niki et al., 1998; Seo et al., 2001). In tomato, Thaler et al. (2004) found that the JA response reduces damage by a range of pathogens with biotrophic and necrotrophic lifestyles contrasting the hypothesis developed from observations in Arabidopsis. The Arabidopsis model might not apply to M. truncatula when it comes to its response to fungal necrotrophs and hemi-biotrophs. Not only in the case of the P. medicaginis interaction, but also in the C. trifolii interaction chitinases, thaumatin-like and β- 1,3-glucanase genes are strongly induced upon infection in M. truncatula (Torregrosa et al., 2004). This suggests that there might be a fine interplay of various defence signalling pathways leading to a resistance response. 178 Many transcription factors play a regulatory role in the SA, JA and ET signalling pathways in Arabidopsis (Desveaux et al., 2005; 2004; Dong et al., 2003; Kalde et al., 2004; Lorenzo et al., 2003; 2005). Furthermore WRKY, Myb, and ERF factors have all been reported to play role either directly or indirectly in Arabidopsis defence against both biotrophs and necrotrophs (Berrocal-Lobo and Molina, 2004; Berrocal-Lobo et al., 2002; Mengiste et al., 2003; Xu et al., 2006; Zheng et al., 2006). Upon infection with P. medicaginis we observed both induction and repression of several transcription factors (Table 7.3). Most induced and repressed TF showed similar levels of induction/repression in both resistant and susceptible plants. However, some WRKYs showed differential transcript abundances in resistant and susceptible interactions (Table 7.3). WRKY TC86292 and TC83033 showed abundant transcript levels in the susceptible interaction and not in the resistant interaction whereas WRKY TC84187 and TC86084 showed abundant transcript levels in the resistant interaction and not in the susceptible interaction. WRKY gene TC86084 shows strong sequence homology to the Arabidopsis WRKY11 and WRKY17 genes. In Arabidopsis these TF act as negative regulators of basal defence against the biotroph P. syringae pv. tomato (Journot-Catalino et al., 2006). WRKY11 and WRKY17 also act as positive regulators of JA responsive genes like LOX2 and AOS (Journot-Catalino et al., 2006). The observed induction of WRKY11-like gene upon infection in resistant plants could explain an earlier induction of LOX genes in resistant plants compared to susceptible plants upon P. medicaginis infection. Furthermore, the repressed WRKY gene TC83285 showed weak homology to the A. thaliana WRKY70 gene, which is not only negatively regulated by JA (Li et al., 2006; Li et al., 2004), but also negatively regulated by 179 WRKY11 and WRKY17 (Journot-Catalino et al., 2006). The development of various gene knockout systems including RNAi (Limpens et al., 2004) and insertional mutagenesis approaches like Tnt1-transposons (d'Erfurth et al., 2003) and gene TILLING (Tadege et al., 2005) in M. truncatula can help determine whether the M. truncatula WRKY genes described above regulate JA biosynthesis and JA responsive genes upon P. medicaginis infection. Most PIGs encoded proteins that function in the plant secondary metabolic pathway leading to the synthesis of isoflavonoids (Figure 7.4; Table 7.4) and mRNA induction upon P. medicaginis infection was confirmed using RT-qPCR (Figure 7.10; Appendix 07). Isoflavonoids are predominantly found in the subfamily Papilionoideae of the Leguminosae and can act as signalling molecules mediating bacterial or fungal symbiosis and as antimicrobial phytoalexins during plant-pathogen defence responses (Dixon et al., 2002). The data presented in this chapter revealed that the phenylpropanoid pathway is triggered in both susceptible and resistant accessions of M. truncatula and is a general defence response not associated with resistance. In most cases, higher transcript abundances were observed in the susceptible interaction. One explanation for this would be that more cells were successfully penetrated by P. medicaginis in the susceptible interaction than in the resistant interaction resulting in higher isoflavonoid transcript levels (Figure 7.10). This is supported by the immunolocalisation studies in alfalfa which showed that IFR and VR proteins specifically accumulate in leaf cells surrounding P. medicaginis lesions (Lopez-Meyer and Paiva, 2002). The possible “second induction” in transcript abundance observed in susceptible SA3054 at 48 hpi for CHI, IFMT, IFR and VR (Figure 7.10a, c-f, i-k), which is absent in resistant SA27063, could be a 180 consequence of P. medicaginis being able to colonize cells surrounding the initial infection zone. In contrast to the expression data, the higher transcript abundance of phenylpropanoid genes in the susceptible plants did not result in a significantly higher accumulation of isoflavonoids compared to the resistant plants (Figure 7.11). In both resistant and susceptible interaction we observed accumulation of naringenin and formononetin (Figure 7.11i, j) leading to the synthesis of the phytoalexin medicarpin. Medicarpin was significantly more abundant in infected than in uninfected plants (Figure7.11p). This is in accordance with the findings of Deavours and Dixon (2005) in alfalfa where liquiritigenin, formononetin and medicarpin accumulate upon infection of the susceptible cultivar Regen SY. In this cultivar, dihydroxyflavone, isoliquiritigenin and afromosin were also more abundant when infected with P. medicaginis. Once standards for these compounds have been obtained these might elucidate whether they are one of the unidentified peaks of interest (Figure 7.11e-h, k-o). No differences were observed between resistant and susceptible plants in abundance of naringenin, formononetin and medicarpin when infected with P. medicaginis. However, subtle differences between the resistant and susceptible accessions were observed (Figure 7.11). A total of five metabolites with (iso)flavonoid-like properties, including coumestrol, showed a naturally higher abundance in the resistant plants than the susceptible plants (Figure 7.11d- h). Upon P. medicaginis infection of susceptible plants two of these compounds were able to accumulate to similar (basal) levels observed in the resistant plants at 72 hpi (Figure 7.11d, e). Coumestrol was one of these compounds and its production has been reported to be stimulated in annual medics when diseased with fungal necrotrophs (Barbetti, 2007; Barbetti and Nichols, 1991; Saunders 181 and O' Neill, 2004). Whether the resistance observed in M. truncatula accessions described in chapter three correlate with constitutively higher levels of coumestrol or the other four (iso)flavonoid-like compounds needs to be addressed. Besides obtaining more (iso)flavonoid standards, to identify our Phoma responsive compounds, other avenues can be explored. HPLC-UV-MS, HPLC-MS-MS and HPLC-UV-ESI-MS have been successfully applied for metabolic profiling and systematic identification of flavonoids and isoflavonoids in root and cell cultures of M. truncatula (Farag et al., 2006). The two major findings were the induction of the octadecanoid and phenylpropanoid pathway in M. truncatula upon P. medicagnis infection. In M. truncatula cell suspensions entry point enzymes into the phenylpropanoid and (iso)flavonoid pathways, PAL and CHS respectively, were not induced nor repressed by MeJA (Suzuki et al., 2005). This would suggest that at least two independent defence mechanisms being triggered upon P. medicaginis infection, where a faster induction of lipoxygenase genes and a constitutively higher abundance of metabolites with phenolic properties is observed in resistant plants. 182 Chapter 8 General discussion, future directions and conclusion Australian farming systems commonly rely on legume-based pastures to provide nitrogen for the following season’s crop, which is predominantly wheat (Crawford et al., 1989). Lucerne (M. sativa) and the barrel medic (M. truncatula) are major components of this crop rotation in temperate regions of Australia (Dear et al., 2003; Loi et al., 2005). In Western Australia, Phoma black stem and leaf spot disease can be found in most medic stands after the first year of establishment and cause significant herbage and seed yield losses in susceptible varieties (Barbetti, 1995). Hence, disease management relies heavily on using disease-resistant varieties and employing sound agronomic practices. M. truncatula has been adopted as a model for legume research. In this study, M. truncatula genetic resources have been employed to gain an understanding of the genetic basis of resistance to necrotrophic fungi. Furthermore, gene expression profiling and metabolomic techniques have been used to identify pathways involved in the M. truncatula defence response to P. medicaginis. Data from the research presented will contribute to the understanding of defence mechanisms and the generation of more resistant Medicago cultivars and identification of antifungal compounds. A prerequisite to understanding isolate specificity and host resistance lies in resolving relationships with allied species and between isolates. It is therefore essential that that isolates are correctly identified. Using a combination of classical morphological taxonomy and modern molecular taxonomy of five phylogenetically informative gene regions, Western Australian P. medicaginis isolates were identified, characterized and differentiated. EF-1α contained a 183 hypervariable 55-bp repeat unit, forming the basis of a rapid polymerase chain reaction-based method of reliably distinguishing isolates. All the Australian P. medicaginis isolates share the same one nucleotide difference in their ITS sequence compared to the reference culture CBS316.90 and all deposited ITS sequences for P. medicaginis in GenBank. Furthermore, the Australian P. medicaginis isolates studied failed to induce both compatible or incompatible disease phenotypes in legumes other than M. truncatula and the closely related M. sativa. This contrasts with previous reports documenting a wide host range (Kinsey, 2002) which detailed disease principally among the Papilionaceae, but also within the Cruciferae and Solanaceae. The Australian isolates thus may be different to P. medicaginis isolates reported to date and could therefore be placed in a different taxon. It is likely that the P. medicaginis isolates described in this thesis have locally adapted to Medicago species (i.e. allopatric speciation). The sequencing of four Dothideomycetes genomes (Alternaria brassicola, Mycosphaerella graminicola, Pyrenophora tritici-repentis and Stagnospora nodorum) will provide tools to analyse and dissect the genetic basis pathogenicity of P. medicaginis. The importance of the isolates in this study lies in their pathogenicity on M. truncatula. Two reliable and reproducible screening techniques (spray and spot inoculation) were developed to evaluate the SARDI core M. truncatula accessions for sources of resistance to P. medicaginis. Spot inoculation of 85 single seeded accessions (for three generations) with a monospore source of inoculum for three P. medicaginis genotypes showed a continuous distribution and wide range in disease phenotypes. This study revealed that M. truncatula harbours specific and diverse sources of resistance to individual pathogen 184 genotypes with several isolate-specific resistant accessions showing pronounced susceptibility to a second isolate. The identification of new sources of resistance in the diverse collection of SARDI M. truncatula core collection accessions offers the opportunity to characterise new forms of resistance. Given the status of M. truncatula as a model legume (Young et al., 2005), it provides the opportunity to study defence against P. medicaginis at physiological, biochemical and molecular levels. As P. medicaginis is an important pathogen especially on alfalfa, such disease resistance sources could be utilized directly in medic breeding programmes to increase levels of resistance in current commercial cultivars. The accessions SA3054 and the reference accession A17 were found to be highly susceptible, whereas the accession SA27063 was found to be highly resistant allowing us to compare compatible and incompatible interactions. Two F2 mapping populations were genotyped to unravel the genetic basis of resistance to P. medicaginis. Framework genetic maps were constructed using CAPS, SNP and SSR markers, and comprised 123 and 78 evenly distributed SSR and gene- based markers for SA27063 x SA3054 (n = 94) and SA27063 x A17 (n = 92) respectively. The percentage of polymorphic markers between SA27063 and A17 (53%) was significantly higher than the percentage between SA27063 and SA3054 (35%), indicating that SA27063 x SA3054 is a narrower cross than SA27063 x A17 and confirms previously published SSR results (Ellwood et al., 2006b). Mapping populations involving the reference accession A17 showed a consistent anomaly in the F1 pollen viability and in genetic maps constructed of their F2 progeny linkage groups four and eight formed a single linkage group. 185 These findings provide strong evidence for the presence of a reciprocal translocation in the accession A17 involving the long arms of chromosomes four and eight. Furthermore, albinism, dwarfism and low germination rates were consistently observed in F2 progeny derived from a cross with accession A17. The semi-sterility of F1s and further selection of F2 individuals through low germination rates, albinism and dwarfism provide a natural selection of certain gene combinations leading to subsequent biased observations in genetic studies. This can provide difficulties when attempting to map-base clone loci, particularly those linked to the translocation breakpoints. Another finding has been that an F1 derived from a cross between accessions DZA315.16 and A17 showed a reduction in pollen viability of about 50%, whereas the genetic map derived from the cross between Jemalong line J6 and accession DZA315.16 (Thoquet et al., 2002) has shown no evidence of segregation of a reciprocal translocation. This suggests that the genetically identical Jemalong derived lines J6 and A17 (Thoquet et al., 2002) could differ in their chromosomal configuration. This can be confirmed by creating hybrids between various Jemalong derived lines and accession DZA315.16. The genome of A17 in that case is not representative of most M. truncatula genomes. The F2 individuals used to generate the framework genetic maps and their F3 progeny were assayed for their response to P. medicaginis and subsequent QTL analysis identified two highly significant QTLs for resistance to P. medicaginis, one in each mapping population, rnpm1 and rnpm2. rnpm1 is located on the short arm of chromosome four and rnpm2 is located on the long arm of chromosome eight. By increasing the F2 population sizes and marker density in the areas of interest, the positions of rnpm1 and rnpm2 can now be 186 genetically fine mapped and subsequently physically mapped. Alternatively, near-isogenic lines (NILs) that differ only around the QTL could be used to isolate rnpm1 and rnpm2. NILs require a considerable investment in time and effort. As part of this project, we are currently generating recombinant inbred line populations (RILs) for the two populations described. Once at the appropriate inbred level (eg. F7 with 1.5625% heterozygosity), a genetic linkage map can be constructed and the RILs phenotyped for their response to P. medicaginis. Residual heterozygote lines (RHLs) can be generated from a RIL that is heterozygous in the area of the QTL for P. medicaginis resistance. The progeny of such lines would provide discriminating recombinants to separate the QTL as a single genetic factor (Tuinstra et al., 1997). The additional phenotyping may further aid identification of minor QTLs involved in the resistance response, which in their turn can be potentially cloned. Markers tightly linked to (e.g. co-segregating with) the loci of interest can be used in marker assisted selection in current medic breeding programmes to speed up the process of generating M. truncatula cultivars resistant to P. medicaginis. Comparative mapping could identify similar resistance loci in related species such as alfalfa and introgression of these loci may help to improve their resistance to P. medicaginis. To identify the molecular components of M. truncatula involved in the response to P. medicaginis, we used the Mt16kOLI1plus microarray. The number of genes on the array used in this study does not represent all of the predicted genes present in the Medicago genome. Nevertheless, the data generated has resulted in the identification of a number of potential defence- related transcripts that will facilitate the molecular dissection of host responses to 187 P. medicaginis and perhaps other necrotrophic pathogens. To functionally characterize the role of various PIGs, one could “knock out” the PIGs of interest. Recently, large scale insertional mutagenesis approaches using EMS, the tobacco retrotransposon Tnt1, and fast neutron bombardment have generated mutagenised M. truncatula libraries (Nair et al., 2006; Ratet et al., 2006). These libraries offer the potential to identify mutants with phenotypic changes in the defence response against a necrotroph. However, accession A17, which is susceptible to the three P. medicaginis isolates studied here, has been used to generate all the mutagenised populations of M. truncatula. Using mutagenised A17 lines still allows the study of PIGs that increase resistance to P. medicaginis. A number M. truncatula lines mutagenised in genes controlling the expression of the phenylpropanoid pathway could, as an example, be screened for an altered response to P. medicaginis. Although numerous transformation methods have been reported in M. truncatula, no efficient high-throughput stable transformation system has yet been developed, making it difficult to functionally characterize PIGs. To date, the use of plant viruses as vectors for stable protein expression and sequence-specific virus-induced gene silencing (VIGS: Baulcombe, 1999; Waterhouse et al., 2001) has not been developed in M. truncatula. VIGS could be used to generate transient loss-of-function assays in M. truncatula as a rapid alternative to stable transformation. From the array data and the RT-pPCR results, it became evident that both the octadecanoid pathway (Figure 7.7) and the phenylpropanoid pathway (Figure7.9) were associated with the defence response to P. medicaginis (Chapter 7). A major output of the octadecanoid pathway is the production of JA, which in Arabidopsis regulates defence responses to fungal necrotrophs. The observed 188 induction of the octadecanoid pathway does not seem to be R-gene mediated, since it is induced in both resistant and susceptible interactions. This differs from the response of M. truncatula to the hemi-biotroph C. trifolii, where particular lipoxygenases are specifically induced in resistant plants and therefore it was suggested that the octadecanoid pathway mediates resistance in incompatible interactions (Torregrosa et al., 2004). Upon P. medicaginis infection, however, the induction of lipoxygenases in resistant plants took place earlier than in susceptible plants, which could be explained by the induction of a WRKY11-like gene in resistant plants. This WRKY gene has strong sequence homology to WRKY11 and WRKY17 of A. thaliana, which positively regulates the JA- responsive genes LOX2 and AOS (Journot-Catalino et al., 2006). Besides WRKY11 and WRKY17, various other WRKYs have been shown to play an important role in defence against fungal necrotrophs and in regulation of the JA- regulated defence response. This makes the genes of the octadecanoid pathway and WRKY genes induced or repressed upon P. medicaginis infection appropriate candidates to study by reverse genetics. Genes of the phenylpropanoid pathway were induced upon P. medicaginis infection, and no major differences were observed in transcript abundance between resistant and susceptible plants (Figure 7.10). Significant differences in abundance of compounds with (iso)flavonoid properties were observed between resistant and susceptible plants (Figure 7.11). We identified constitutively higher abundances of five compounds with (iso)flavonoid properties, including coumestrol, in the resistant accession SA27063. In susceptible plants, coumestrol and the phenolic compound at retention time 35.2 accumulated to similar (basal) levels found in the resistant plants, 72 189 hpi with P. medicaginis (Figure 7.11d, e). Coumestrol production has been reported to be stimulated in annual medics when diseased with fungal necrotrophs (Barbetti, 2007; Barbetti and Nichols, 1991; Saunders and O' Neill, 2004). The question whether M. truncatula accessions with naturally higher amounts of (iso)flavonoid-like compounds as found in SA27063 are more resistant to P. medicaginis isolates needs to be clarified. Accumulation of naringenin, formononetin and medicarpin upon infection with P. medicaginis was observed in both resistant and susceptible plants. This is in accordance with the findings of Deavours and Dixon (2005) in alfalfa where liquiritigenin, formononetin and medicarpin were found to accumulate upon infection in the susceptible cultivar Regen SY. In Regen SY, dihydroxyflavone, isoliquiritigenin and afromosin were also more abundant when infected with P. medicaginis. Increased levels of formononetin and medicarpin were also observed in IFMT- overexpressed alfalfa plants, which showed enhanced resistance to P. medicaginis (He and Dixon 2000). The overexpression of certain genes of the phenylpropanoid pathway (He and Dixon 2000; Deavours and Dixon, 2005) can lead to enhanced resistance to P. medicaginis but the question whether this results in increased resistance to all P. medicaginis isolates and other foliar necrotrophs of Medicago needs to be addressed. George and VanEtten (2001) identified a cytochrome P450 in a virulent Phoma pinodella isolate, which demethylates (and thus detoxifies) the pea phytoalexin pisatin (a pterocarpan similar to medicarpin). P. medicaginis isolates that have the ability to detoxify certain isoflavonoids and isoflavonoid- like compounds could become pathogenic. It would be interesting see whether M. truncatula accessions all resistant to a specific P. medicaginis isolate share 190 certain isoflavonoid(s) or isoflavonoid-like compound(s) which a P. medicaginis isolate cannot detoxify. The identification of the P. medicaginis responsive compounds and the naturally more abundant compounds in the resistant accession SA27063 is a priority. HPLC-UV-MS, HPLC-MS-MS and HPLC-UV-ESI-MS have been successfully applied to metabolic profiling and systematic identification of flavonoids and isoflavonoids in root and cell cultures of M. truncatula (Farag et al., 2006). These techniques might enable us to identify unknown compounds of interest in resistant and genetically diverse accessions. Fourier transform mass spectrometry (FTMS) would allow us to structurally characterize (e.g. determine the composition of molecules based on accurate mass) of the unknown compounds of interest. In conclusion, metabolites of the isoflavonoid biosynthetic pathway appear to play an important role in defence against P. medicaginis. This work has significantly increased our understanding of the P. medicaginis – M. truncatula pathosystem, where novel sources of resistance and two major loci involved in the resistance response to P. medicaginis have been identified. Furthermore, the phenylpropanoid and octadecanoid pathway were shown to be involved in the defence response to P. medicaginis. The identification of differences in transcript levels and several phenolic compounds more abundant in the resistant accession SA27063 allows the characterisation of genes in R-gene mediated resistance and may lead to the identification of novel antifungal compounds. 191 REFERENCES Aarts N., Metz M., Holub E., Staskawicz B. J., Daniels M. J., and Parker J. E. (1998). 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Plant Physiology, 131, 1018-1026. 219 Appendix 1 Appendix 01 PCR markers used to generate a genetic map of an F2 population between SA27063 and SA3054 Marker Sequenced Putative function Linkage Restriction enzyme/fragment size and Method SA27063 SA3054 Forward primer sequence Reverse primer sequence Reference name amplicon Group SNP primer/Fluorescent primers restriction restriction accession fragment fragment number pattern of pattern of CAPS or CAPS or SNP position SNP position 36N1L Resistance gene analog 6 NA Length 410 950 GAAGCAGCCGGACATTGGACACA TGTTAGTTCAAATGGATCTTCTATGAGGTAT Choi et al 2004 41O18L Resistance gene analog 4 Alu I CAPS 268 167+101 AGATATATCAGAAAAAACTAACCCAACCTT AATACCCTTCCCTTTCCTTCCC Choi et al 2004 48N18L Resistance gene analog 6 NA Length 580 480 TCTTTTCCTCCGATTTCTTGATTCTC AGGCTTGCTTGCTGTTGGTTGTA Choi et al 2004 ACCO 1-ACC oxidase 2 Mnl I CAPS 40 + 250 290 GAAGATGGCGCAAAAAGAAAGT CGATGTGTCGTGTCATCTCGTTAAGTTCCCT Choi et al 2004 ATP2 DX922473 ATP synthase beta chain, 1 Rsa I CAPS 950 + 650 950 + 520 + ATTGCTATGGATGCTACTGAAGGTGTTG TGGTATGGTGCAAGCAGGTCAA Choi et al 2004 DX922532 mito precusor +520 470 + 180 AW256637 Resistance gene analog 4 NA Length 600 525 TTCACCTAATTTCCATCTATACCATCCATGT TATTTGTTAGCTTTAGTGATCGCTGCTACAC Choi et al 2004 AW257033 DX922475 Resistance gene analog 8 Mae III CAPS 314 260 + 54 TGCGTCATTAACCAAAGATGATGTTGTAA CCAACAGTAACATCCCCAAAGACAATATTC Choi et al 2004 DX922533 BiPA DX922476 BiP isoform A 4 Hinf I CAPS 250 +150 400 GAGGAGTCTCACAAAGGATTGC GGTTTTTCATGTTGTAGACATAGGTTTCA Choi et al 2004 DX922534 CA4H DX922477 Cinnamic acid 4- 5 NA Length 712 483 GTTACGGGTGGGAGTCTGAA AGTCCATCATTGCTCGTGGT This paper DX922535 hydroxylase (TC106704) CAK Calcium-dependant protein 7 Apo I CAPS 545+210+110 345 + 200 + TTCAACCCCTCTGCGAACC CATCTATAGCAATTGCTGTTGTCATCT Choi et al 2004 kinase 210 + 110 CDC2 DX922478 Putatice cdc2 kinase 1 Dde I CAPS 490 +330 820 CAACTTTGCAAGGGTGTTGCTTTCT ACTAACACCTGGCCACACATCTTCA Choi et al 2004 DX922536 CPOX2 DX922480 Cationic peroxidase 8 Fluorescent Length 300 294 GATAATGGCCTTGTTATGAATTACTACA GCTCAGACAAGCTTCTTCTTGTGGA Choi et al 2004 DX922537 CrS Cystathionine-gamma- 6 NA Length 950 750 CAAATGGTGCTTTGGAGATTGAT TTAAAAAAGTAGACTGAAGTGTTGACCA Choi et al 2004 synthase precursor CysPR1 DX922481 Cysteine proteinase-like 3 197, GACTGACTGACTGACTGTGG SNP G/59/R C/59/R GAGAATTCAAAGAAGAAATTAAGACAAAGA GAAGAATTCATGGGGAGCAAAGT Choi et al 2004 DX922538 protein CTTCTTATCCCACTAAAAA DK024R DX922483 NA 4 440, TTTTGGGGCCCAAAATATAT SNP A/313/R T/313/R GCCGCGCCATCTTTATTGA GACGATTTTACCCTTTATCTAAGC Choi et al 2004 DX922539 DK242R NA 5 Hinc II CAPS 330 230 + 100 CGTATGTTTAATCCGTTAGTCCGTCTT GCTTGCTTAGATATTTGGCACTTCA Choi et al 2004 DK258L NA 3 Xba I CAPS 100 + 360 470 GTATTCAGGGATTGAGTAAGAAAAAGGA ACAAAATCCGTGGATGTATAAAAGTGTA Choi et al 2004 DK313L NA 3 NA Length 240 265 GCCAAACATAGGCTAAGTGTGAAAAA TGACACATAAATTGTTAGCATCTGAAGG Choi et al 2004 DK322L NA 7 Dde I CAPS 90 + 30 + 145 90 + 175 GGACCGAACTGGGTCAACAAT GCACCGAGATCCACCAACAACTT Choi et al 2004 DK379L DX922485 NA 4 Bsl I CAPS 410 205 + 205 AGCTTGTTGAGGTGGAAGGAAGTC GTGTGTATGAGTGTCGTAAGCCCCT Choi et al 2004 DX922540 DK381L DX922486 NA 4 Mae II CAPS 330 210 + 120 TGTTACAAAAAGAGTTGGTTGTCGTTC GTGCACTTTTCAATTTGTCCATCATA Choi et al 2004 DX922541 DK417L DX922487 NA 3 406, GACTGACTGACTGACTCAT SNP T/353/F A/353/F ACTCGTCGCCTAACAATATCAACCAG GAATTCCATATCCAACACCTTTAGACTTA Choi et al 2004 DX922542 AAGCTAGAAGGTGCCTTAAC DK419R DX922488 NA 3 Hae III CAPS 420 250 + 170 CATCAGAAGTTGCCAAGCTATCAGAG GCTTTGGTGCCGTTGTCAGAAGTA Choi et al 2004 DX922543 DK455L DX922489 NA 8 325, GACTGACTGACTGGATGGT SNP A/97/R G/97/R AAGGTTGTGTTGCAGGCGGTTTTAGT CACATACAGAGTTTCCAGGATTACCATT Choi et al 2004 DX922544 AAAGTCCCTGATTGA DK473L NA 3 Bcl I CAPS 130 + 230 360 AACTGGTTAACTCGCTAATTGCTACATA CAATCCTAAACCTCCCAAAAAGC Choi et al 2004 DK501R NA 3 Apo I CAPS 420 200 + 220 TATTTGGGATGGAAGCTATGTTGATTGG TGCTTTAAAGGAGAAGGTAGATGATGAT Choi et al 2004 2 Marker Sequenced Putative function Linkage Restriction enzyme/fragment size and Method SA27063 SA3054 Forward primer sequence Reverse primer sequence Reference name amplicon Group SNP primer/Fluorescent primers restriction restriction accession fragment fragment number pattern of pattern of CAPS or CAPS or SNP position SNP position DK505R NA 8 Ase I CAPS 380 200 +180 GCCGCCGCTCCCAAACTT CAATTCCCTCCGGCGTCACTT Choi et al 2004 EIF5A DX922490 Eukaryotic initiation factor 8 Fluorescent Length 1052 1038 CGCGCAGAGAAAGCATCAA CACAATTGTGGGACGAAGGAAC Choi et al 2004 DX922545 5A3 ENOD8 Early nodulin 8 1 Dra I CAPS 876 630 + 246 CCATGCCCATTCCTACTTTTCA GTGGATTCCACGGACTTTACTTACT Choi et al 2004 ENOL DX922492 Enolase 7 Taq I CAPS 450 + 1050 1500 TTCCATCAAGGCCCGTCAGA TTGCACCAACCCCATTCATT Choi et al 2004 DX922546 EPS 3-Phospho-shikimate 1- 4 Bgl II CAPS 1050+570 1620 GCTGTTGTGGAAGGCAGTGG ACGACATACGGAACAGAAATCAGT Choi et al 2004 carboxyvinyl transferase EST400 DX922493 NA 3 SfaN I CAPS 500 + 500 1000 GGTGGCTGTCCCACTGATTATGT AAATGCTTGTGTTATGCGGAGAG Choi et al 2004 DX922547 FAL Fructose-1,6-bisphosphate 5 Bcl I CAPS 450 110 +340 TTATCGCCAATGCCGCCTACA ATGATAAGTATGCATGTTCAGAGTCA Choi et al 2004 aldolase FENR DX922494 Ferredoxin NADP reductase 5 729, GACTGACTGACATTCGGCTA SNP T/628/F C/628/F ATGCTTATGCCAAAAGATCCAAATGC CTCACAGCAAAGTCGAGCCTGAAGT Choi et al 2004 DX922548 precursor CAAGCTATGTAGAA GLUT DX922497 Putative glucosyl transferase 8 1067, TCGAAGAGAACCACCATCCT SNP T/274/F C/274/F TACAAGGCAGGGAATCTTAAATCTGCA TTATTCTCCAGACACCAGCAGTTCCA Choi et al 2004 DX922549 h2_15m24a NA 7 NA SSR AAAAACACCACATGGCCCTA GAGGAGGGATCCTTCAAAAA http://medicago.org/genome/ downloads/Mt_markers_jan06 h2_24j8b NA 8 NA SSR GCACATGGTTTTGTTGTTGG GTGAGAGTCACGTTCTGGCA http://medicago.org/genome/ downloads/Mt_markers_jan06 h2_33J22 NA 1 NA SSR GATGGATGAGAAATGGAGAA GAATCAAATCCACCTATCCA Gutierrez et al 2005 h2_35l19b NA 8 NA SSR AATCCAACTTGTGTCGGGAT AAATGACGGAGGGTGAACAG http://medicago.org/genome/ downloads/Mt_markers_jan06 h2_77p14a NA 2 NA SSR TGGCGAAATTGACAACACTG TCACGGTCATCATACTCACTATCC http://medicago.org/genome/ downloads/Mt_markers_jan06 h2_87i13c NA 2 NA SSR TGTGGAGATCCTTCATGCAC TGGCCAAGTGTGTGTTTGAT http://medicago.org/genome/ downloads/Mt_markers_jan06 h2_8a13a NA 8 NA SSR GCACTTTTTGGGCTGACTTT GACAACCGGTCCGAATTTTA http://medicago.org/genome/ downloads/Mt_markers_jan06 h2_8c19d NA 2 NA SSR ACAAGGCCTTTAACACCAGC GGCACTTGTTATCATTTTCCG http://medicago.org/genome/ downloads/Mt_markers_jan06 MAA660456 NA 4 NA SSR GGGTTTTTGATCCAGATCTT AAGGTGGTCATACGAGCTCC Baquerizo-Audiot et al 2001 MAA660538 NA 5 NA SSR ATCAAAGCAGAGCAATTTAA GAAATGCTGTAGGTATCTCC Baquerizo-Audiot et al 2001 MDH2 Malate dehydrogenase 1 Dra I CAPS 70 + 1180 70 + 100 + CTTCCATTTTCGATTCCTTTCATT GCATGCCTCGACAACATCAGT Choi et al 2004 1080 Ms/U141 Hypothetical protein 8 Alu I CAPS 750 530 + 220 TTGATCAGCCACAGAAATATAAACCA GCCTCCCACAAAGTAACAAGTTTC Choi et al 2004 MtB118 NA 3 NA SSR GATGCCATCTTTTCTTCAAT ATCTTTCCGCTAGTGTGTGT Mun et al 2006 MtB124 NA 7 NA SSR CAAGCTTCAATTCCACAAGT TGGTGAATTACATGCTCAGA Mun et al 2006 MtB139 NA 8 NA SSR AATCGCGTAAAATTGGGTTG GCTGATCCTCTTCAGGTTCG Mun et al 2006 MtB157 DX922503 NA 1 223, CACATAATGCCCATCTGAACA SNP T/25/R C/25/R TGATCGATTACACCGCAAAA CGACACATAATGCCCATCTG Mun et al 2006 DX922551 MtB160 NA 1 NA SSR CTGCAATCAACAATTAATGC AATCACGGGAAATAAGAAAA Mun et al 2006 MtB172 NA 3 NA SSR TTGTTGACGCAAATGACGAT ATGCATCACACATGCTAGGG Mun et al 2006 3 Marker Sequenced Putative function Linkage Restriction enzyme/fragment size and Method SA27063 SA3054 Forward primer sequence Reverse primer sequence Reference name amplicon Group SNP primer/Fluorescent primers restriction restriction accession fragment fragment number pattern of pattern of CAPS or CAPS or SNP position SNP position MtB174 NA 8 NA SSR TGTGCAGAGGAATCTATAATGA CCAGCTACTCTTATTGCGTA Mun et al 2006 MtB193 NA 2 Fluorescent SSR CGATTTCCATGATGAGATTT ACCATCACACAACATAATTCAC Mun et al 2006 MtB213 NA 7 NA SSR GTCGATTTTGACTCTCTTGC TGGCCAACTTAGACAAATCT Mun et al 2006 MtB217 NA 8 NA SSR TCGACAGTAATACACGCTCA GTCTGAAAATCATCCAAAGC Mun et al 2006 MtB220 NA 3 NA SSR AAGGTGTCTTCTAGCAAAACTAA TCATAACCCGGATCGTAGTA Mun et al 2006 MtB223 NA 4 NA SSR AACGTGAGCTTGTAGCAGCA ACACCCTTTACCACCACTGC Mun et al 2006 MtB247 NA 8 NA SSR GTGGAAGTTTGATCATTTCG CAAATCTCACACCCACTACA Mun et al 2006 MtB248 NA 4 NA SSR CTGTATCGCCAAATGAATTA TAAACAGAGCCGAACTATCC Mun et al 2006 MtB26 DX922504 NA 2 272, GCTAGGATCGCACTCCCTAA SNP T/57/R C/57/R CGGTTTTGGTGGAGAAGTTG TCTTAATACCCGTGGGAGCA Mun et al 2006 DX922552 MtB262 NA 8 NA SSR AAACGAAGCAAGCAGCTCAT GAAGCAAGAAGAAAAGGAGTGG Mun et al 2006 MtB27 DX922505 NA 4 Hae III CAPS 100 + 100 200 TCCCAACGCTTTTTCATTTC GAACTTGAAGAAGAACGCCG Mun et al 2006 DX922553 MtB276 DX922506 NA 6 Nde I CAPS 110 + 140 250 CCCTCCCTTTCCTTTCAAAC GATGTGCCCCTTTTTCTCAT Mun et al 2006 DX922554 MtB286 NA 1 NA SSR CTCTTCTCACGCTGATGCTG TGGTGGAAGGAACGGTTAAG Mun et al 2006 MtB290 NA 1 Fluorescent SSR TTCAAAACAGTGGGGAAAGC TTGGTTTTGTTCTGCGTCTG Mun et al 2006 MtB293 DX922507 NA 8 Apo I CAPS 220 180 + 40 CAAGCTTCAATTCCACAAGT TGGTGAATTACATGCTCAGA Mun et al 2006 DX922555 MtB294 NA 8 NA SSR AATTTCGGACGTTCATTTCG CCGATTTACAATTTAGACTGCCA Mun et al 2006 MtB295 NA 8 NA SSR AACCTTACGGTGTCGTTTCG TTTCTCAAACCCATCGATCC Mun et al 2006 MtB3 NA 8 NA SSR CACATAACAACCACCACCACA CCCAGGTTGTTGAGGAAGAA Mun et al 2006 MtB300 NA 1 NA SSR ATCTGGTAGGAGATGGTGCG ATGCAGAGGGGTGATTCAAG Mun et al 2006 MtB32 DX922508 NA 5 BsmA I CAPS 610 490 + 120 GGATTCAGGACCAAGAGACT CAAAATGCCACTGTTATAAGG Mun et al 2006 DX922556 MtB344 DX922509 NA 4 198, GACTGACTGACTCCACCGC SNP A/101/F C/101/F ATGGAGAAGATGTTCCGACG GTCACACCAGGTGCACAATC Mun et al 2006 DX922557 TCAAGTTAGTATTTG MtB4 NA 2 NA SSR 420 GCCCTAAGGACTGCATTTTG CCCCTCCTAAACCCTCAATC Mun et al 2006 MtB43 NA 4 NA SSR GCCCTAAGGACTGCATTTTG CCCCTCCTAAACCCTCAATC Mun et al 2006 MtB55 NA 7 Fluorescent SSR TCTGAAAGGGCACCTCCTAA CGCGAAAGGAATGTTGAAGT Mun et al 2006 MtB59 DX922510 NA 7 Mse I CAPS 180 +40 220 CCCTTGACTGAAAGGGACAA TCGGTGTCGAACACCTACAC Mun et al 2006 DX922558 MtB61 NA 2 Fluorescent SSR CGGACAAAACAGATTGTCCTT GAAGGTGCGTTTTAGCAACA Mun et al 2006 MtB96 NA 5 NA SSR TAGCTCAATTGGCATGGACA TGGCAAACGTTACCAAACAA Mun et al 2006 MTIC014 NA 6 NA SSR CAAACAAACAACACAAACATGG CCCATTGATTGGTCAAGGTT Gutierrez et al 2005 4 Marker Sequenced Putative function Linkage Restriction enzyme/fragment size and Method SA27063 SA3054 Forward primer sequence Reverse primer sequence Reference name amplicon Group SNP primer/Fluorescent primers restriction restriction accession fragment fragment number pattern of pattern of CAPS or CAPS or SNP position SNP position MTIC019 NA 2 NA SSR TCTAGAAAAAGCAATGATGTGAGA TGCAACAGAAGAAGCAAAACA Gutierrez et al 2005 MTIC033 NA 4 NA SSR AAAATTAGAAGAACCACGGCTTT AATCGCTTTCCCAATTTCAA Gutierrez et al 2005 MTIC051 NA 3 NA SSR AGTATAGTGATGAAGTGGTAGTGAACA ACAAAAACTCTCCCGGCTTT Gutierrez et al 2005 MTIC065 NA 4 NA SSR ATGCTTGCAAGGGGTCTCTA AATGCATACACCAAACTTAAACATT Gutierrez et al 2005 MTIC153 NA 6 NA SSR TCACAACTATGCAACAAAAGTGG TGGGTCGGTGAATTTTCTGT Gutierrez et al 2005 MTIC235 NA 1 NA SSR CCTTTGGTTGATTCAGTTTC CCAATATGTCACTCCTTGCT Gutierrez et al 2005 MTIC236 NA 1 NA SSR AAGTCATCAGGACCAACAAC TGTTTGACGCAAAGAAAGAT Gutierrez et al 2005 MTIC238 NA 5 NA SSR TTCTTCTTCTAGGAATTTGGAG CCTTAGCCAAGCAAGTAAAA Gutierrez et al 2005 MTIC243 NA 7 NA SSR GGAGGAGGTTATAGGTTTGG TCAGTGCTCAGCATCTATGT Gutierrez et al 2005 MTIC249 NA 4 NA SSR TAGGTCATGGCTATTGCTTC GTGGGTGAGGATGTGTGTAT Gutierrez et al 2005 MTIC268 NA 6 NA SSR GAGGATTCATTCTTCTTCCA ATTGTTCCTAGGTTGGGTTT Gutierrez et al 2005 MTIC279 NA 4 NA SSR GCAGCACAAGATACTCACAA CTTAGACGGTGTTGGTTTTC Gutierrez et al 2005 MTIC297 NA 4 NA SSR CTAAGCTTTGGCCATGTATC TGAAATGAGTTTGACTGAGG Gutierrez et al 2005 MTIC354 NA 2 NA SSR AAGTGCCAAAGAACAGGGTTT AACCTACGCTAGGGTTGCAG Gutierrez et al 2005 MTIC361 NA 2 NA SSR AGCTGAAGTGGAACCACCAG CCCCTAGCTTGAGGAGAGGA Gutierrez et al 2005 MTIC43 NA 1 NA SSR CGTCGTTACTCAAACGACACC GCGTGTTTCTGCTGATTCAT Gutierrez et al 2005 MTIC452 NA 2 NA SSR CTAGTGCCAACACAAAAACA TCACAAAAACTGCATAAAGC Gutierrez et al 2005 MTIC48 NA 5 NA SSR TTTTTGTTAGTTTGATTTTAGGTG GCTACAAAGTCTTCTTCCACA Gutierrez et al 2005 MTIC58 NA 5 NA SSR AGGTGGGCACAACAAAAGAG CTCTCCATTTTCACCGCTTC Gutierrez et al 2005 MTIC74 NA 2 NA SSR GGTGGAAGGAACAACTCTGG CCGGCATGATTAAGACACAC Gutierrez et al 2005 MTIC82 NA 6 NA SSR CACTTTCCACACTCAAACCA GAGAGGATTTCGGTGATGT Gutierrez et al 2005 MTR52 NA 5 Fluorescent SSR AGCGGATGGTGGGGATA ATTCCATTTACTGCTTATCG Baquerizo-Audiot et al 2001 MTSA5 NA 7 NA SSR ACTGTTCCGTCCTTTCAATC TGAGTTCTTGTTCCTTGTTA Baquerizo-Audiot et al 2001 MTSA6 NA 5 NA SSR TCACATTAATTATCTTTTCACAA GGCCAAAACATAAAAATTG Baquerizo-Audiot et al 2001 NTRB1 DX922511 Retino blastoma related 8 Dde I CAPS 560 470 + 90 CACGACTCTGCACGCTTTGTTA ACCCTTGTTGCGAGTCATTTG Choi et al 2004 DX922559 protein\ OXG DX922512 oxygenase 6 Rsa I CAPS 720 390 + 330 AGGTGTAGCAAGATATAACCAATTCAGGA TTTGGTGGTGCATCCCAAACAGAGAAAG Choi et al 2004 DX922560 PAE DX922513 Pectinacetylesterase 8 800, GACTGACTGACTGACTGACTC SNP A/742/F T/742/F CTAAAAGCAGCAGAAGGGGTTAC GATCCGGTCAAGGCAAGTAGTT Choi et al 2004 DX922561 precursor TTTTGTCTTGTAATGATCTTGAGT PGDH Phosphogluconate 7 Bcl I CAPS 460 + 30 490 GAGTTGAAGCTGCAAAGGTCTTTAAATCA TGTATGAGCACCGAAGTAGTCTCGTTGA Choi et al 2004 dehydrogenase 5 Marker Sequenced Putative function Linkage Restriction enzyme/fragment size and Method SA27063 SA3054 Forward primer sequence Reverse primer sequence Reference name amplicon Group SNP primer/Fluorescent primers restriction restriction accession fragment fragment number pattern of pattern of CAPS or CAPS or SNP position SNP position PTSB DX922516 Proteasome beta subunit 5 Fluorescent Length 365 370 ACTAAACAACACGCTAATTGGTCTCCA ATGCCTAGCAGACAAAACCTTCTGCA Choi et al 2004 DX922562 QORlik DX922517 Mt-apy2 4 409, GACTGACTGACTGACTGACTG SNP C/261/F A/261/F GATGGTCTGGCAACTGT AGGGAGGACTTTTCTTAG Choi et al 2004 DX922563 TGTGTATGTATCTCCAAGTCTACT REP DX922518 Poly(A)+ RNA export 8 Mnl I CAPS 300 + 50 + 65 350 + 65 CTCCATTTCCCGTTCGTTCG CACCGGTTGCCCTCCAGAC Choi et al 2004 DX922564 protein SDP1 Seed protein precursor 8 Ssp I CAPS 76+829+62 76+726+103 TGGCTCTAAATCAGGGGAAGAATA TGTGACGGTTGAATATCTGAATGTTT Choi et al 2004 + 62 SQEX DX922521 Squalene mono-oxygenase 4 Xba I CAPS 880 + 190 1070 TGCCGCTATAAAAAGTAAACAAAGAA CAATTCACCCACAATTCTATCAGG Choi et al 2004 DX922565 TC90233 DX922522 RGA-H protein 4 Alu I CAPS 100 + 120 220 CCGATCCAAAGAAGAGAAGG GAACACAGGCAGAACAACCA This paper DX922566 TE001 DX922523 CCCH-type zinc-finger 6 Bcc I CAPS 520 + 380 380 + 440 + CGGCGCCGGAGATTACACTG AATCACAAACCCACCCAACATCTG Choi et al 2004 DX922567 protein 80 TUP Translationally controlled 1 Bcl I CAPS 620 230 + 390 GAATGGGATGCTATGGGAAGTG TGGATCAGTGGCACCATCTTTAT Choi et al 2004 tumor protein UDPGD DX922527 UDP-glucose 6- 7 Mbo II CAPS 825 + 400 + 650 + 400 + CAAAAGCGTTTCATCACTCATCTCT ATCGTCAAGGCCAGGTTCATAG Choi et al 2004 DX922568 dehydrogenase 105 175 + 105 UNK16 DX922528 Hypothetical protein, Ms 4 322, GACTGACAAATCCAGGCATAA SNP C/293/F T/293/F CCTTCCAATATCCCTCCCACAT GAAGAAAATGATGAAAAGCCAAAAG Choi et al 2004 DX922569 AJ410117 CCATCAA UNK3 DX922530 VAMP-associated protein 4 Alu I CAPS 250 + 120 370 CACCGGAAATTCAACAGCAAC GACCTAGGCAACACAACTCCATTA Choi et al 2004 DX922570 VR DX922531 Vestitone reductase 7 Xho I CAPS 800 600+ 300 AAGCTGTTCTTGAATTTGGTGA TCCACGAGTTTCTTCGTGTTT This paper DX922571 (TC100886) 6 Appendix 02 PCR markers used to generate a genetic map of an F2 population between SA27063 and A17 Marker name Sequenced Putative function Linkage Restriction Method SA27063 restriction A17 restriction Forward primer sequence Reverse primer sequence Reference amplicon Group enzyme fragment pattern of fragment pattern of accession CAPS CAPS number 36N1L DX922470 Resistance gene analog 6 Hae III CAPS 410 190 + 220 GAAGCAGCCGGACATTGGACACA TGTTAGTTCAAATGGATCTTCTATGAGGTAT Choi et al 2004 DX922442 41O18L DX922471 Resistance gene analog 4 Mse I CAPS 210 + 72 76 + 134 + 72 AGATATATCAGAAAAAACTAACCCAACCTT AATACCCTTCCCTTTCCTTCCC Choi et al 2004 DX922443 48N18L DX922472 Resistance gene analog 6 Apo I CAPS 450 + 140 590 TCTTTTCCTCCGATTTCTTGATTCTC AGGCTTGCTTGCTGTTGGTTGTA Choi et al 2004 DX922444 ACL ATP citrate lyase 2 Bcl I CAPS 1200 30 + 270 + 900 AAGGTTAAGACCGTATTTATTCCAACA AGTCCAAATTCGTCCCCACTG Choi et al 2004 AW256637 DX922474 Resistance gene analog 4 NA Length 574 524 TTCACCTAATTTCCATCTATACCATCCATGT TATTTGTTAGCTTTAGTGATCGCTGCTACAC Choi et al 2004 DX922445 AW257033 DX922475 Resistance gene analog 8 Nla III CAPS 280 + 40 + 50 +26 320 + 50 + 26 TGCGTCATTAACCAAAGATGATGTTGTAA CCAACAGTAACATCCCCAAAGACAATATTC Choi et al 2004 DX922446 CAK Calcium dependent protein kinase 7 Apo I CAPS 545 + 210 + 110 345 + 200 + 210 + TTCAACCCCTCTGCGAACC CATCTATAGCAATTGCTGTTGTCATCT Choi et al 2004 110 CNCG4 Cyclic nucleotide regulated ion 8 Bsl I CAPS 380 AGAGATGAGAATCAAGAGGAGGGATGCA CATGATGAAGAGCATTTCGTCCACTGGA Choi et al 2004 chanel CP450 DX922479 Cytochrome P450 4 Hae III CAPS 260 + 130 + 75 390 + 75 AGTGTGAGATCAATGGTTATGTGATC CATCATCACCTTTCAATATTTGTCC Choi et al 2004 DX922447 CPOX2 DX922480 Cationic peroxidase 8 Xmn I CAPS 220 + 80 300 GATAATGGCCTTGTTATGAATTACTACA GCTCAGACAAGCTTCTTCTTGTGGA Choi et al 2004 DX922448 CrS Cystathionine-gamma-synthase 6 NA Length 950 750 CAAATGGTGCTTTGGAGATTGAT TTAAAAAAGTAGACTGAAGTGTTGACCA Choi et al 2004 precursor CysPr1 Cysteine proteinase-like protein 3 Acl I CAPS 60 + 170 230 GAGAATTCAAAGAAGAAATTAAGACAAAGA GAAGAATTCATGGGGAGCAAAGT Choi et al 2004 DK006R DX922482 NA 5 Rsa I CAPS 450 405 + 45 GAACATAACCCCGAAGTGGAT GAGTTTGGGAACAAAATTAGTATGAT Choi et al 2004 DX922449 DK009R NA 5 Dra I CAPS 280 + 170 450 TAGCATCATCTTTCCCATACAA GGGCAGGCAGCACCAGATA Choi et al 2004 Dk024R DX922483 NA 4 Bsr I CAPS 440 315 + 135 GCCGCGCCATCTTTATTGA GACGATTTTACCCTTTATCTAAGC Choi et al 2004 DX922450 DK045R DX922484 NA 2 Mlu I CAPS 390 240 + 150 TGGCAATATCCACCAAATCAAA CGAACCCACGACCACAAGG Choi et al 2004 DX922451 DK132L NA 3 Xmn I CAPS 290 + 30 320 TGGACCTAAGACTTCAAAGATTCAGA CCTATTAAGCATATTTGCAGCATGAACAATTT Choi et al 2004 DK225L NA 7 Nco I CAPS 60 + 210 270 TGTCCTTGCTTCTTATCCTTCCTTCA AGCAGCACAACAACTTACAACAACTC Choi et al 2004 DK242R NA 5 Hinc II CAPS 330 230 + 100 CGTATGTTTAATCCGTTAGTCCGTCTT GCTTGCTTAGATATTTGGCACTTCA Choi et al 2004 DK258L NA 3 Xba I CAPS 100 + 360 470 GTATTCAGGGATTGAGTAAGAAAAAGGA ACAAAATCCGTGGATGTATAAAAGTGTA Choi et al 2004 DK287R NA 7 Dde I CAPS 135 + 135 270 AGCCGCCCTCTTGAACCTCC TAGCTGCAACAAAGAAACCAAAACC Choi et al 2004 DK293R NA 2 Dra I CAPS 290 80 + 210 ACTTACAAGGTTAGCGTCATTCTCCATC GCTATCCCACCTTAAAATTTCTTCACAA Choi et al 2004 DK313L NA 3 NA Length 240 265 GCCAAACATAGGCTAAGTGTGAAAAA TGACACATAAATTGTTAGCATCTGAAGG Choi et al 2004 DK321L NA 6 Msl I CAPS 370 120 + 250 GAGCGAGCTCAGGATAGACTTTAGAA TCCCACCTCCAATTTGTAGACGAT Choi et al 2004 DK322L NA 7 Dde I CAPS 90 + 30 + 145 90 + 175 GGACCGAACTGGGTCAACAAT GCACCGAGATCCACCAACAACTT Choi et al 2004 DK381L NA 4 Hinf I CAPS 40 + 210 + 80 250 + 80 TGTTACAAAAAGAGTTGGTTGTCGTTC GTGCACTTTTCAATTTGTCCATCATA Choi et al 2004 DK417L NA 3 Bbv I CAPS 180 + 230 410 ACTCGTCGCCTAACAATATCAACCAG GAATTCCATATCCAACACCTTTAGACTTA Choi et al 2004 7 Marker name Sequenced Putative function Linkage Restriction Method SA27063 restriction A17 restriction Forward primer sequence Reverse primer sequence Reference amplicon Group enzyme fragment pattern of fragment pattern of accession CAPS CAPS number DK473L NA 3 Bcl I CAPS 360 130 + 230 AACTGGTTAACTCGCTAATTGCTACATA CAATCCTAAACCTCCCAAAAAGC Choi et al 2004 DK501R NA 3 Apo I CAPS 420 200 + 220 TATTTGGGATGGAAGCTATGTTGATTGG TGCTTTAAAGGAGAAGGTAGATGATGAT Choi et al 2004 DK505R NA 8 Ase I CAPS 380 200 + 180 GCCGCCGCTCCCAAACTT CAATTCCCTCCGGCGTCACTT Choi et al 2004 DNABP SAR DNA binding protein 4 Afl II CAPS 860 + 260 280 + 580 + 260 CCCTATGAGCTTGGGTTTGTCT CTCATGGCATACGTGTTCAGC Choi et al 2004 EIF5A Eukaryotic initiation factor 5A3 8 Dde I CAPS 360 + 620 980 CGCGCAGAGAAAGCATCAA CACAATTGTGGGACGAAGGAAC Choi et al 2004 ENOD40 Early nodulin 40 5 NA Length 177 136 AACCAATGCCACTTTTCACTTTGCCTCC AGACTCTTGCGAGTGCTACCATTTGACC Choi et al 2004 ENOD8 DX922491 Early nodulin 8 1 Pvu I CAPS 650 + 250 900 CCATGCCCATTCCTACTTTTCA GTGGATTCCACGGACTTTACTTACT Choi et al 2004 DX922452 ENOL DX922492 Enolase 7 Taq I CAPS 450 + 1050 1500 TTCCATCAAGGCCCGTCAGA TTGCACCAACCCCATTCATT Choi et al 2004 DX922453 EPS 3-Phospho-shikimate 1- 4 Bgl II CAPS 1050 + 570 1620 GCTGTTGTGGAAGGCAGTGG ACGACATACGGAACAGAAATCAGT Choi et al 2004 carboxyvinyl transferase EST400 NA 3 Sac I CAPS 1000 500 + 500 GGTGGCTGTCCCACTGATTATGT AAATGCTTGTGTTATGCGGAGAG Choi et al 2004 EST763 Hypothethical protein 1 Hinf I CAPS 155 130 + 25 CACTCTAAAAAGGCCCAGAAGGTTTGACT CTTATGACCAATAGTCTGTTCCACTC Choi et al 2004 FAL Fructose-1,6-bisphosphate aldolase 5 Bcl I CAPS 110 + 340 450 TTATCGCCAATGCCGCCTACA ATGATAAGTATGCATGTTCAGAGTCA Choi et al 2004 FIS1 DX922495 fis1 protein 8 Apo I CAPS 616 + 122 + 90 + 124 488 + 128 + 122 + 90 TCAGTGATTGAGGGTTTTTCTACG CTGTTTCATCAACTTCAGCAACTTT Choi et al 2004 DX922454 + 43 + 124 + 43 GLNA DX922496 Glutamate ammonia ligase 3 HindIII CAPS 540 195 + 345 GAATGGTGCTGGTGCTCACACA TGGTGGTGTCTGCAATCATGGAAG Choi et al 2004 DX922455 HYPTE3 DX922498 Hypothethical protein 4 BsmA I CAPS 180 + 170 350 TCGTCTCATGGTGGAATCGTGATGGT TTCCTCCTTTAAACAAGCAAATTGGA Choi et al 2004 DX922456 MAA660456 NA 4 NA SSR GGGTTTTTGATCCAGATCTT AAGGTGGTCATACGAGCTCC Baquerizo-Audiot et al 2001 MAA660538 NA 5 NA SSR ATCAAAGCAGAGCAATTTAA GAAATGCTGTAGGTATCTCC Baquerizo-Audiot et al 2001 MAAP DX922499 Membrane alanylaminopeptidase 8 Afl III CAPS 990 605 + 385 TACCTAAGACTGCACATGCTATGTAT CATCACCAACACGCTTTACAGTGCGGCT Choi et al 2004 DX922457 MDH2 Malate dehydrogenase 1 Dra I CAPS 70 + 1180 70 + 100 + 1080 CTTCCATTTTCGATTCCTTTCATT GCATGCCTCGACAACATCAGT Choi et al 2004 MPP Mitochondrial processing peptidase 4 BstB I CAPS 440 110 + 330 TCCCCGAAACAATCCTCATCTG GCAAATGTGTAGCCCCAAAAGTTA Choi et al 2004 Ms/U131 DX922500 Hypothethical protein 4 Hinf I CAPS 410 180 + 230 ATGCTATTGGGACTCAACACTCTGA GGAATTGCACTATACAGATGATAGGA Choi et al 2004 DX922458 Ms/U336 DX922502 Phytohemagglutinin 8 Rsa I CAPS 560 280 + 280 AGACGTGGCTAACTTCGAAACACT GAGCTTGAAACATTAGCATTGTTGTTA Choi et al 2004 DX922459 MtB169 NA 1 NA SSR AGGCTGAAAATGGCTTGAAA CCACACAGATGCCACAGACT Mun et al 2006 MtB99 NA 4 NA SSR CTTGGCAAAATGTCAACTCT GGAAAGGGGTTAGGTGAGTA Mun et al 2006 MTIC033 NA 4 NA SSR AAAATTAGAAGAACCACGGCTTT AATCGCTTTCCCAATTTCAA Gutierrez et al 2005 MTR58 NA 1 NA SSR GAAGTGGAAATGGGAAACC GAGTGAGTGAGTGTAAGAGTGC Baquerizo-Audiot et al 2001 MTSA5 NA 7 NA SSR ACTGTTCCGTCCTTTCAATC TGAGTTCTTGTTCCTTGTTA Baquerizo-Audiot et al 2001 MTSA6 NA 5 NA SSR TCACATTAATTATCTTTTCACAA GGCCAAAACATAAAAATTG Baquerizo-Audiot et al 2001 MtU04 Hypothethical protein 5 Nsi I CAPS 1165 310 + 855 ATGGGAAGAGGATTGCTGTGATA AAGCGAACATTTTTGGCATCTAC Choi et al 2004 8 Marker name Sequenced Putative function Linkage Restriction Method SA27063 restriction A17 restriction Forward primer sequence Reverse primer sequence Reference amplicon Group enzyme fragment pattern of fragment pattern of accession CAPS CAPS number NPAC Putative nascent polypeptide 3 Ssp I CAPS 470 + 270 + 500 340 + 130 + 270 + TGGCTCCAGGTCCAGTTATTGA TCGGCTCTTCTTCTCGCTTCT Choi et al 2004 associated protein 500 PAE DX922513 Pectinacetylesterase precursor 8 Ava II CAPS 470 + 330 800 CTAAAAGCAGCAGAAGGGGTTAC GATCCGGTCAAGGCAAGTAGTT Choi et al 2004 DX922460 PFK Ppi-dependent phophofructokinase 2 Ssp I CAPS 80 + 420 500 TCCCACTGCAAATCATGTCAAAAC ACACAAGTGGATATTGATGGTTAGACTAC Choi et al 2004 beta subunit PGDH DX922514 Phosphogluconate dehydrogenase 7 Bcl I CAPS 460 + 30 490 GAGTTGAAGCTGCAAAGGTCTTTAAATCA TGTATGAGCACCGAAGTAGTCTCGTTGA Choi et al 2004 DX922461 PROF DX922515 Profucosidase 6 BsaJ I CAPS 195 + 125 320 AGAAGTCAAAAATGGTCTACCAGTGA CAAATCTTCCAATATCCAAACAAGTAGGA Choi et al 2004 DX922462 QORlik Mt-apy2 4 Rsa I CAPS 409 119 + 209 GATGGTCTGGCAACTGT AGGGAGGACTTTTCTTAG Choi et al 2004 SAMS S-adenosyl-methionine synthase 2 2 BstB I CAPS 525 + 525 1050 CATAGCAAAGCGGGTTCAATCT GTCAGCATCAAGACCAACATCATC Choi et al 2004 SAT DX922519 Sulfate-adenylyl transferase 1 Dde I CAPS 565 + 60 + 195 625 + 195 GTATCATGATGGACTTGATCATTTTCGTC AGCCTTTGCATGCCACTGCACCTCA Choi et al 2004 DX922463 SDP1 DX922520 Seed protein precursor 8 Bcl I CAPS 660 + 350 1100 TGGCTCTAAATCAGGGGAAGAATA TGTGACGGTTGAATATCTGAATGTTT Choi et al 2004 DX922464 SQEX Squalene mono-oxygenase 8 EcoRV CAPS 190 + 620 +260 810 + 260 TGCCGCTATAAAAAGTAAACAAAGAA CAATTCACCCACAATTCTATCAGG Choi et al 2004 TE001 DX922523 CCCH-type zinc-finger protein 6 Ava II CAPS 750 + 250 1000 CGGCGCCGGAGATTACACTG AATCACAAACCCACCCAACATCTG Choi et al 2004 DX922465 TE011 DX922524 SCARECROW gene regulator 4 Hinc II CAPS 1550 1200 + 350 GGAGAGAAACCGGACTGAAGAAACA CAAGAAGAAGCCCTAGTCCTCCATT Choi et al 2004 DX922466 TE016 DX922525 Cyanogenic beta-glucosidase 4 Hinc II CAPS 1950 1530 + 420 TCCCCAGGCCTTACAAGATGATTAT AAACACTCCCACGTCGCACTAAG Choi et al 2004 DX922467 TUP DX922526 Translationally controlled tumor 1 Mnl I CAPS 420 + 200 285 + 135 + 200 GAATGGGATGCTATGGGAAGTG TGGATCAGTGGCACCATCTTTAT Choi et al 2004 DX922468 protein UDPGD UDP-glucose 6-dehydrogenase 7 Mnl I CAPS 230 + 1120 1350 CAAAAGCGTTTCATCACTCATCTCT ATCGTCAAGGCCAGGTTCATAG Choi et al 2004 UNK27 DX922529 dTDP-glucose 4-6-dehydratase 4 Apo I CAPS 350 250 + 100 GGCTTCATCGGTTCTCATCTCTGCGA TGTAATCAGCAGGAGTACAAATTGCAGCCA Choi et al 2004 DX922469 UNK3 VAMP-associated protein 4 Mbo II CAPS 80 + 390 470 CACCGGAAATTCAACAGCAAC GACCTAGGCAACACAACTCCATTA Choi et al 2004 UNK7 Putative protein 5 Xho I CAPS 1420 1250 + 170 AAAAAGCAGCAAGAGAAATGTCAAT GAGAATCTTTCTCCATCGTATCTTACTT Choi et al 2004 9 Appendix 03 Differentially expressed transcripts showing a ≥ 2-fold activation ratio 12 hours post infection (hpi) with P. medicaginis OMT5 MtGI* Annotation SA270631 SA30542 Antimicrobial TC76640 Similar to Pprg2 protein (Alfalfa) 2.98 1.79 BM815404 Class PR10-1 protein 2.91 2.32 TC77137 Similar to pathogenesis related protein (Chickpea) 2.88 2.73 TC76511 Class PR10-1 protein 2.87 2.38 TC76641 Similar to Pprg2 protein (Alfalfa) 2.61 -§ TC76643 Similar to Pprg2 protein (Alfalfa) 2.59 1.66 TC76642 Similar to Pprg2 protein (Alfalfa) 2.51 1.47 TC76518 Similar to disease resistance response protein Pi49 2.47 2.10 (PR10)(Garden pea) TC77138 Similar to pathogenesis related protein (Chickpea) 2.39 2.54 TC76638 Similar to Pprg2 protein (Alfalfa) 2.28 - TC86847 Similar to osmotin-like protein (Grapevine) 1.94 1.14 TC78899 Similar to glucan endo-1 3-beta-d-glucosidase (Chickpea) 1.88 - BG452227 Homologue to pathogenesis-related protein 4A (Pea) 1.55 - TC84433 Similar to Beta-1,3-glucanase (Soybean) 1.50 - TC85874 Homologue to Beta-1,3-glucanase (Alfalfa) 1.46 - TC86735 Similar to pseudo-hevein (Rubber tree) 1.27 1.37 TC87236 Homologue to pathogenesis-related protein 4A (Garden pea) 1.20 - TC76694 Homologue to thaumatin-like protein PR-5b (Chickpea) 1.15 - TC88905 Class PR10-1 protein 1.07 1.21 TC77149 Similar to thaumatin-like protein precursor Mdtl1 (Apple) 1.03 - TC90394 Class IV chitinase precursor - 1.13 Cell wall modification TC85611 Caffeoyl-CoA O-methyltransferase (Alfalfa) 2.48 1.73 TC85611 Caffeoyl-CoA O-methyltransferase (Alfalfa) 1.84 1.39 TC85981 Similar to Caffeic acid 3-O-methyltransferase 1 (Alfalfa) 1.35 1.63 TC85550 Homologue to caffeic acid 3-O-methyltransferase (Alfalfa) 1.05 0.51 TC92066 Homologue to caffeic acid 3-O-methyltransferase (Alfalfa) 1.05 - TC91631 Weakly similar to putative cinnamyl alcohol dehydrogenase 1.06 - (Apple) TC85789 Similar to peroxidase 3 (Common bean) 1.61 1.33 TC85974 Peroxidase 2 precursor (Alfalfa) 1.34 1.10 TC86423 Homologue to peroxidase precursor (Alfalfa) 1.31 0.67 TC77974 Similar to peroxidase (Soybean) 1.04 - TC85172 Weakly similar to peroxidase 3 (Scutellaria baicalensis) 0.68 1.17 TC76722 Homologue to extensin (Garden pea) 1.44 1.06 TC76876 Similar to pectinesterase-like protein (Arabidopsis) 1.39 0.73 TC87122 Weakly similar to UDP-glycosyltransferase (Stevia 1.20 - rebaudiana) TC77216 Similar to putative xyloglucan endotransglycosylase 1.11 0.65 (Arabidopsis) TC77735 Similar to pectinesterase (Arabidopsis) 1.00 - ET/JA pathway TC85808 Similar to 12-oxophytodienoate reductase (Arabidopsis) 1.96 0.75 TC76875 Similar to methyljasmonate esterase (Alfalfa) 1.37 0.85 TC79124 1-aminocyclopropanecarboxylic acid synthase 1.04 0.97 10 MtGI* Annotation SA270631 SA30542 TC85168 Similar to Lipoxygenase (Garden pea) 1.04 - TC91892 Similar to Lipoxygenase (Almond) 0.96 1.13 TC85618 Similar to Lipoxygenase (CPRD46, Cowpea) 0.64 1.24 General phenylpropanoid pathway TC85502 Phenylalanine ammonia lyase (M. truncatula) 2.27 1.82 TC85506 Similar to phenylalanine ammonia lyase(Rubus idaeus) 1.29 1.45 TC85501 Homologue to Phenylalanine ammonia lyase (Stylosanthes 1.69 1.44 humilis) TC85505 Phenylalanine ammonia lyase (M. truncatula) 1.64 1.60 TC76780 Trans-cinnamate 4-monooxygenase (M. truncatula) 1.35 - TC77196 Similar to 4-coumarate:CoA ligase (Amorpha fruticosa) 1.80 - TC77196 Similar to 4-coumarate:CoA ligase (Amorpha fruticosa) 1.19 - TC77753 Similar to 4-coumarate:CoA ligase (Soybean) 1.12 - Isoflavonoid biosynthesis TC85478 Isoflavone reductase (M. truncatula) 3.75 2.54 TC76770 Homologue to chalcone synthase 2 (Alfalfa) 3.38 2.75 TC85138 Homologue to chalcone synthase 8 (Alfalfa) 3.30 2.80 TC85146 Homologue to chalcone synthase 2 (Alfalfa) 3.09 2.63 TC76765 Homologue to chalcone synthase 2 (Alfalfa) 3.02 3.11 TC76769 Homologue to chalcone synthase 4 (Alfalfa) 2.31 2.12 TC85174 Homologue to chalcone synthase 4 (Alfalfa) 2.25 1.82 TC85150 Homologue to chalcone synthase 9 (Alfalfa) 2.75 2.57 TC76767 Homologue to chalcone synthase 2 (Alfalfa) 1.98 1.95 TC85174 Homologue to chalcone synthase 4 (Alfalfa) 0.55 1.16 TC85186 Homologue to chalcone synthase 4 (Alfalfa) 1.98 1.94 TC76766 Homologue to chalcone synthase 2 (Alfalfa) 2.01 2.48 TC85521 Homologue to chalcone reductase (Alfalfa) 2.86 2.11 TC76884 Similar to chalcone reductase (Chickpea) 2.24 1.43 TC85521 Homologue to chalcone reductase (Alfalfa) 2.86 2.07 TC85519 Homologue to chalcone reductase (Alfalfa) 2.46 2.15 TC85633 Homologue to chalcone-flavonone isomerase 1 (Alfalfa) 2.01 1.03 TC76950 Similar to chalcone-flavonone isomerase (Arabidopsis) 1.58 0.99 TC77996 Similar to isoflavone-7-O-methytransferase 9 (Alfalfa) 1.40 1.46 TC85608 Isoflavone 2'-hydroxylase (M. truncatula) 1.23 - TC85477 Isoflavone reductase (M. truncatula) 2.90 2.44 TC86455 Similar to isoflavone reductase homologue (Lupin albus) 1.58 1.20 TC86358 Homologue to 6a-hydroxymaackiain methyltransferase 1.49 1.46 (Garden pea) TC77308 Vestitone reductase (Alfalfa) 1.67 1.62 TC87730 Weakly similar to UDP-glycose:flavonoid 1.75 1.36 glycosyltransferase (Soybean) TC78077 Similar to UDP-glycose:flavonoid glycosyltransferase 1.62 - (Mungbean) Lipid metabolism TC78074 Similar to lipase (Arabidopsis) 1.06 - TC86035 Similar to triacylglycerol lipase like protein (Arabidopsis) 1.02 1.01 TC78074 Similar to lipase (Arabidopsis) 1.11 - TC76844 Similar to patatin-like protein 1 (Tobacco) 2.07 1.55 TC86826 Similar to lipase (Arabidopsis) 1.32 0.93 TC83261 Similar to lysophospholipase (Hyacinthus orientalis) 1.31 0.85 TC77636 Similar to alcohol dehydrogenase (Phaseolus lunatus) 2.88 1.81 11 MtGI* Annotation SA270631 SA30542 BG455041 Similar to short chain alcohol dehydrogenase (Arabidopsis) 1.33 1.27 TC88138 Similar to putative long-chain acyl-CoA synthetase 1.09 - (Arabidopsis) TC85230 Homologue to glyceraldehyde 3-phosphate dehydrogenase 1.03 0.63 (Carrot) TC76591 Similar to Putative NADPH dehydrogenase (Rose) 1.00 - Oxidative burst/stress TC85907 Similar to flutathione S-transferase GST 15 (Soybean) 2.01 1.22 TC82678 Weakly similar to 21 kDa extracellular calmodulin-binding 1.63 1.18 protein (Angelica dahurica) TC87506 Similar to putative Serine/arginine rich protein/SC35-like 1.29 0.55 splicing factor (Arabidopsis) TC80949 Similar to alternative oxidase-related protein IMMUTANS 1.19 - (Arabidopsis) TC86161 Similar to putative blue copper protein (Rice) 1.18 - TC77725 Similar to ubiquinol-cytochrome-c reductase (Potato) 1.17 0.42 TC77162 Similar to chorismate synthase 1 chloroplast precursor 1.12 1.01 (Tomato) TC88539 Weakly similar to blue copper-binding protein-like gene 1.12 - (Arabidopsis) TC87086 Similar to blue copper protein precursor (Garden pea) 1.02 - TC87019 Similar to Avr9/Cf-9 rapidly calcium-binding protein 0.94 1.49 (Tobacco) TC78580 Homologue to alternative oxidase 3 mitochondrial precursor 0.68 1.07 (Soybean) TC78579 Homologue to alternative oxidase 3 mitochondrial precursor - 1.08 (Soybean) TC86393 Weakly similar to UDP-glucosyltransferase HRA25 - 1.05 (Common bean) TC92417 Similar to calmodulin binding protein NPGR1 (Arabidopsis) 1.03 - TC85956 Homologue to 1,4-benzoquinone reductase-like protein 1.22 0.85 (Arabidopsis) Pathogen perception TC86207 Similar to disease resistance response protein (Arabidopsis) 2.20 1.42 TC86208 Similar to disease resistance response protein (Arabidopsis) 1.58 1.06 TC92969 Similar to resistance gene candidate RCa12 (Cassava) - 2.31 Transcription factors (induced) TC88711 Similar to homeobox-leucine zipper protein (Soybean) 1.03 - TC88951 Similar to ethylene response factor-like AP2 domain 2.08 1.08 transcription factor (Arabidopsis) TC79960 Similar to CCAAT-box-binding transcription factor 2.05 1.89 (Arabidopsis) TC85738 Similar to homeodomain-leucine zipper protein 56 (Soybean) 1.34 1.04 TC86558 Similar to ERF-like protein (Melon) 1.24 - TC78267 Weakly similar to MYB transcription factor (Arabidopsis) 1.22 - TC84988 Similar to Zinc finger protein (Garden pea) 1.22 0.74 TC79325 Zinc finger, C3HC4 type (M. truncatula) 1.12 - TC86084 Similar to WRKY transcription factor 11 (Arabidopsis) 1.07 - TC86292 Similar to putative WRKY transcription factor 30 (Grape) - 1.04 TC83033 Similar to WRKY8 transcription factor (Rice) - 1.02 TC87393 Similar to CCCH-type zinc finger protein (Arabidopsis) 0.90 1.08 TC86453 Similar to putative bZIP family transcription factor 1.06 - (Arabidopsis) 12 MtGI* Annotation SA270631 SA30542 TC84187 Similar to putative WRKY family transcription factor 1.10 0.66 (Arabidopsis) Transporters TC89164 Weakly similar to transporter-like protein (Arabidopsis) 1.55 0.96 TC90542 Similar to transporter-like protein (Arabidopsis) 1.25 1.40 TC91345 Similar to nitrate transporter NTL1 (Arabidopsis) 1.19 0.92 TC86470 Similar to glutathione-conjugate transporter AtMRP4 1.11 0.99 (Arabidopsis) TC86206 Similar to PDR-type ABC transporter 2 (Tobacco) 1.07 0.89 TC89611 Similar to potassium-sodium symporter HKT1 (Eucalyptus) 0.74 1.17 Other TC76542 Homologue to cold acclimation responsive protein BudCAR5 1.68 1.76 (Alfalfa) Autointerpro Polygalacturonase inhibitory protein (PGIP) 1.34 1.24 TC79039 Similar to heat shock protein binding / unfolded protein 1.83 1.24 binding (Arabidopsis) TC78258 Similar to polygalacturonase inhibitor protein (Arabidopsis) 1.43 0.82 TC85685 Similar to Kunitz proteinase inhibitor-1 (Chickpea) 1.27 - TC76965 Similar to MtN19-like protein (Garden pea) 1.22 - TC88119 Similar to rev interacting protein mis3-like (Arabidopsis) 1.06 0.60 TC89463 Waekly similar ro small basic membrane integral protein 1.05 0.85 ZmSIP1-1 (Maize) TC78492 Similar to cytochrome P450 82A1 (Garden pea) 1.94 1.22 TC86953 Similar to adenosine 5'-phosphosulfate reductase (Soybean) 1.66 - TC86858 Similar to formate dehydrogenase (Common Oak) 1.46 1.09 TC85513 Homologue to 60S ribosomal protein L10 (Euphorbia esula) 1.45 1.14 TC87629 Similar to putative aspartate aminotransferase (Arabidopsis) 1.28 1.46 BG647615 Similar to IN2-2 protein (Maize) 1.24 - TC77574 Similar to putative pyrophosphate-dependent phosphofructo- 1.23 0.82 1-kinase (Arabidopsis) TC85399 Similar to thiamin biosynthetic enzyme (Soybean) 1.18 - TC91238 Similar to heat shock protein DnaJ (M. truncatula) 1.14 - TC84147 Homologue to spindly (Gibberellin signal transduction 1.12 0.46 protein) (Arabidopsis) TC92053 Similar to phi-1-like protein (Arabidopsis) 1.10 0.86 TC80864 Similar to Cytochrome P450 71D10 (Soybean) 1.07 1.02 TC80272 Similar to RPS6-like protein (Arabidopsis) 1.06 0.78 TC79174 Homologue to beta-adaptin-like protein B (Arabidopsis) 1.06 0.53 TC81620 Similar to cyclin-dependent protein kinase-like (Arabidopsis) 1.04 0.37 TC78347 Similar to glutamate decarboxylase (Rice) 1.04 0.86 TC87529 Similar to 4 5-DOPA dioxygenase extradiol-like protein 1.03 0.51 (Arabidopsis) TC93480 Similar to Nodulin 26-like protein (M. truncatula) 1.03 - TC78643 Similar to serine acetyltransferase 1(Tobacco) 1.02 0.64 TC86202 Homologue to sulfite reductase precursor (Garden Pea) 1.01 0.55 TC80834 Similar to cytochrome P450 monooxygenase (Chickpea) 0.99 1.17 TC84044 Similar to glutamine synthetase I (M. truncatula) 0.84 1.16 TC92218 Similar to beta-carotene hydroxylase (Soybean) 0.84 1.17 TC85876 Homologue to B12D-like protein (Common bean) 1.19 - TC92334 Similar to erythrocyte membrane-associated antigen 1.15 0.68 (Plasmodium falciparum) TC85021 Similar to NADH dehydrogenase subunit I (Common frog) 1.14 1.15 TC89517 Similar to fiber protein Fb19 (Cotton) 1.27 - 13 MtGI* Annotation SA270631 SA30542 TC91790 Similar to GPI inositol-deacylase PGAP1-like protein (Rice) 1.08 - Unknown TC88891 Similar to At2g42750/F7D19.25 (Arabidopsis) 1.16 0.51 TC79576 Similar to unknown protein AAK62372 (Arabidopsis) 1.16 0.91 TC83303 Similar to Hypothetical protein At1g20670 (Arabidopsis) 1.05 0.85 TC91188 Similar to unknown protein AAM51238 (Arabidopsis) 1.68 1.20 TC83249 Weakly similar to hypothetical protein At2g31110 1.63 0.80 (Arabidopsis) TC89112 Expressed M. truncatula sequence with no homology 1.40 0.68 BE204092 Similar to hypothetical protein OSJNBb0013C14.20 (Rice) 1.37 1.20 TC87675 Weakly similar to unknown protein AAO42434 1.36 - (Arabidopsis) TC81002 Expressed M. truncatula sequence with no homology 1.24 - TC87156 Similar to unknown protein AAL85103 (Arabidopsis) 1.24 0.76 TC79898 Similar to unknown protein AAM63792 (Arabidopsis) 1.22 - TC88561 Similar to hypothetical protein At1g19020 (Arabidopsis) 1.20 - TC88331 Similar to OSJNBa0033H08.17 protein (Rice) 1.18 - BE997888 Similar to hypothetical protein CAD29515 (White clover) 1.18 - TC86306 Similar to unknown protein AAM65675 (Arabidopsis) 1.16 0.86 TC80471 Weakly similar to unknown protein BAD31502 (Rice) 1.11 0.40 TC92520 Similar to unknown protein At3g06130/F28L1_7 1.04 0.93 (Arabidopsis) TC81516 Weakly similar to At4g13350 (Arabidopsis) 1.03 - TC90834 Expressed M. truncatula sequence with no homology 1.02 0.90 BE325980 Expressed M. truncatula sequence with no homology 0.71 1.04 TC83645 Expressed M. truncatula sequence with no homology 1.06 - TC77306 Similar to unknown protein AAM13275 (Arabidopsis) 1.05 0.79 TC88299 Weakly similar to unknown protein AAM63493 1.23 0.82 (Arabidopsis) TC92566 Weakly similar to unknown protein AAM51440 1.21 - (Arabidopsis) TC88019 Similar to unknown protein AAM53332 (Arabidopsis) 1.20 - TC90662 Similar to unknown protein AAM91646 (Arabidopsis) 1.15 0.60 TC81177 Similar to unknown protein 47745-45927 (Arabidopsis) 1.08 0.70 * Medicago truncatula Gene Index tentative consensus (TC) numbers for the 70-mer oligonucleotides on the microarray (http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=medicago). 1 log2 expression ratio inoculated/ control SA27063 (resistant) 12 hpi with P. medicaginis OMT5. 2 log2 expression ratio inoculated/ control SA3054 (susceptible) 12 hpi with P. medicaginis OMT5. § Dash (-) indicates that the TC is not significantly differentially expressed (P ≤ 0.01, M ≥ 1 and n ≥ 10) 14 Appendix 04 Differentially expressed transcripts showing a ≥ 2-fold repression ratio 12 hours post infection (hpi) with P. medicaginis OMT5 MtGI* Annotation SA270631 SA30542 Amino Acid Biosynthesis TC85436 Asparagine synthetase (Alfalfa) -1.39 -0.88 TC77613 Similar to putative branched chain alpha-keto acid -1.08 -0.91 dehydrogenase E2 subunit (Rice) TC78680 Similar to branched-chain alpha keto-acid -1.01 -0.69 dehydrogenase E1-alpha subunit (Arabidopsis) TC85288 Homologue to UDP-glucose 4-epimerase (Garden pea) -1.03 -0.62 TC85291 Similar to UDP-glucose 4-epimerase (Garden pea) -1.18 -0.76 TC85458 Homologue to proline dehydrogenase (Alfalfa) -1.08 -0.92 TC85459 Homologue to proline dehydrogenase (Alfalfa) -1.35 -1.21 TC86074 Similar to branched-chain-amino-acid aminotransferase -1.05 -1.48 2 chloroplast precursor (Arabidopsis) TC86153 Similar to fiber protein Fb19 (Cotton) -1.37 -§ TC86377 Homologue to Isovaleryl-CoA Dehydrogenase (Garden -1.02 -0.76 pea) TC86378 Homologue to Isovaleryl-CoA Dehydrogenase (Garden -1.34 -0.85 pea) TC86606 Similar to methylcrotonyl-CoA carboxylase alpha chain -1.13 - mitochondrial precursor (Soybean) TC86756 Similar to proline dehydrogenase (Soybean) -1.23 -1.17 TC90508 Homologue to tyrosine and tryptophan hydroxylase -1.10 -0.72 (fruit fly) Circadian rhythm TC85289 Similar to GIGANTEA protein (Arabidopsis) -1.69 - TC88001 Similar to expansin-like protein (Common Oak) -1.23 -1.62 TC89712 Similar to GIGANTEA protein (Arabidopsis) -2.93 -1.78 TC86792 Similar to pseudo-response regulator 37 (Rice) -1.06 -0.77 TC88177 Homologue to pseudo-repsonse regulator APRR7 -1.05 - (Arabidopsis) Inositol metabolism BG648637 Similar to myo-inositol oxygenase 2 (Arabidopsis) -1.83 -1.56 TC78339 Similar to probable inositol-1 4 5-trisphosphate 5- -0.83 -1.07 phosphatase At5P2 (Arabidopsis) TC86932 Similar to protein kinase-like protein (Arabidopsis) -1.03 - TC87390 Similar to myo-inositol oxygenase 2 (Arabidopsis) -1.78 -1.72 TC89865 Similar to inositol transporter 1 (Arabidopsis -1.15 - Pathogen perception TC83637 Similar to disease resistance protein RPP1-WsB -1.15 - (Arabidopsis) Sugar biosynthesis TC76597 Similar to auxin-induced beta-glucosidase (Red -1.02 - goosefoot) TC76798 Similar to brassinosteroid-regulated protein BRU1 -1.10 -0.81 precursor (Soybean) TC76799 Homologue to brassinosteroid-regulated protein BRU1 -1.02 -0.90 precursor (Soybean) TC77191 Similar to beta-amylase (Apricot) -1.21 -1.35 15 MtGI* Annotation SA270631 SA30542 TC77504 Similar to alkaline alpha-galactosidase seed imbibition -1.63 -1.46 protein (Tomato) TC78936 Similar to probable xyloglucan -2.17 -1.80 endotransglucosylase/hydrolase protein 33 precursor (Arabidopsis) TC79850 Similar to putative xyloglucan endotransglycosylase -3.83 -2.82 (Cucumber) TC82075 Similar to putative cellulose synthase (Arabidopsis) - -1.29 TC83047 Similar to probable trehalose-6-phosphate synthase -1.39 -1.14 (Arabidopsis) TC85920 Homologue to fructose-bisphosphate aldolase -1.72 -1.10 cytoplasmic isozyme 1 (Garden pea) TC86293 Homologue to fructose-1, 6-bisphosphatase (Garden -1.08 - pea) TC86293 Homologue to fructose-1, 6-bisphosphatase (Garden -1.00 - pea) TC86511 Similar to xylose isomerase (Arabidopsis) -1.35 - TC87307 Similar to aspartic peptidase (M. truncatula) -1.54 -0.96 TC87386 Similar to putative mannose-6-phosphate isomerase -1.42 -1.19 (Arabidopsis) TC87856 Similar to raffinose synthase family protein -1.64 -1.48 AT5g20250/F5O24_140 (Arabidopsis) TC87973 Similar to nudix hydrolase 4 AtNUDT4 (ADP-ribose -1.06 -0.91 pyrophosphatase) (Arabidopsis) TC88291 Similar to putative trehalose-6-phosphate synthase -1.30 -0.67 (Arabidopsis) TC88532 Similar to putative raffinose synthase (Rice) -1.84 -1.88 TC88915 Similar to glyoxalase/bleomycin resistance -1.67 -1.82 protein/dioxygenase (M. truncatula) TC89593 Similar to cellulose synthase-like H1 (Rice) -1.82 -1.03 TC92091 Waekly similar to myo-inositol oxygenase (Arabidopsis) -1.59 -1.04 TC93335 Similar to cytosolic fructose-1 6-bisphosphatase -1.08 - (Banana) TC93546 Similar to putative trehalose-6-phosphate synthase -1.13 -0.73 (Arabidopsis) Transcription factors TC82271 Similar to DNA binding transcription factor - -1.24 (Arabidopsis) TC81746 Similar to DNA binding transcription factor -1.33 -1.17 (Arabidopsis) TC88924 Similar to DNA binding transcription factor -1.22 -1.11 (Arabidopsis) TC83285 Similar to WRKY70 transcription factor (Arabidopsis) -0.38 -1.07 TC87781 Similar to transcription factor TINY (Arabidopsis) -0.77 -1.02 TC77495 Similar to putative bHLH transcription factor -1.06 -0.94 (Arabidopsis) TC79195 Zinc finger, TAZ-type; BTB/POZ (M. truncatula) -1.24 -0.98 TC86844 Similar to light-induced protein CPRF-2 (bZip like) -1.09 -0.83 (Parsley) TC77080 Similar to BTB and TAZ domain protein 1 (Arabidopsis) -0.99 -1.54 TC89819 Similar to ring domain containing protein (Capsicum) -1.29 -1.01 TC78797 Similar to homeobox protein (Arabidopsis) - -1.21 Autointerpro Homeobox domain -1.51 - Transporters TC78388 Similar to plasma intrinsic protein 2 2 (English walnut) -1.01 -0.88 16 MtGI* Annotation SA270631 SA30542 TC78672 Similar to sodium-dicarboxylate cotransporter-like -0.91 -1.11 (Arabidopsis) TC78964 Similar to monosaccharide transporter (Soybean) -0.57 -1.17 TC79056 Similar to auxin efflux carrier (M. truncatula) -1.05 -0.57 TC82682 Similar to aluminum-activated malate transporter-like -1.05 - (Rice) TC87421 H(+)/hexose cotransporter (M. truncatula) -0.89 -1.17 Others TC76773 Similar to Phi-1 protein (Tobacco) -1.33 -1.23 TC76774 Similar to putative phi-1-like phosphate-induced protein -1.84 -1.27 (Arabidopsis) TC76774 Similar to putative phi-1-like phosphate-induced protein -1.71 -1.01 (Arabidopsis) TC76776 Similar to putative phi-1-like phosphate-induced protein -1.38 -0.81 (Arabidopsis) TC76869 Similar to glycerophosphodiester phosphodiesterase -1.68 -2.14 SRG3 (Arabidopsis) TC76872 Similar to glycerophosphodiester phosphodiesterase -1.30 -2.05 SRG3 (Arabidopsis) TC77024 Similar to putative extracellular dermal glycoprotein -1.06 - (Chickpea) TC77116 AKIN gamma (M. truncatula) -1.17 - TC77118 AKIN gamma (M. truncatula) -1.15 -1.37 TC78309 Similar to cytochrome P450 monooxygenase -1.05 - (Arabidopsis) TC79831 Similar to ribonucleoprotein F-like protein (Arabidopsis) -1.23 - TC80052 Similar to Hsc70 protein (Tomato) -1.01 - TC81387 Similar to receptor kinase-like protein (Arabidopsis) - -1.75 TC80815 Homologue to MtN20 protein (M. truncatula) -1.20 -0.94 TC81103 Similar to CTP synthase F19I3.12 (Arabidopsis) -0.93 -1.03 TC83536 Similar to putative chromodomain-helicase-DNA- -1.08 - binding protein (Arabidopsis) TC83571 GRAS family protein (M. truncatula) -1.40 - TC85265 Similar to topoisomerase-like protein (Arabidopsis) -1.44 -1.11 TC85650 Similar to DnaJ protein (Arabidopsis) -1.06 - TC85919 Similar to deoxycytidine deaminase (Wild cabbage) -2.07 - TC86283 Similar to Alfin-1 (Alfalfa) -1.25 -1.20 TC86399 Similar to thioredoxin-like 1 (Arabidopsis) -0.95 -1.04 TC86641 Similar to short-chain alcohol dehydrogenase SAD-C -1.98 -0.81 (Garden Pea) TC87585 Similar to lipase-like protein At1g02660/T14P4_9 - -1.32 (Arabidopsis) TC88037 Similar to isoflavone reductase (Soybean) -1.07 -1.07 TC88240 Similar to probable RNA-binding protein (Arabidopsis) -0.78 -1.12 TC93440 Similar to patatin (M. truncatula) -1.28 -0.81 TC77767 Similar to isoprenylated protein FP6 (Soybean) -1.03 -0.98 TC77768 Similar to isoprenylated protein FP6 (Soybean) -1.31 -1.41 TC77769 Similar to isoprenylated protein FP6 (Soybean) -1.13 -1.05 TC79499 Similar to CREG2-protein-like (Rice) -1.08 -0.53 TC80329 Weakly similar to thioredoxin-like 4 (Arabidopsis) -0.90 -1.23 TC80868 Similar to glutaredoxin-like protein (Arabidopsis) -1.75 -0.98 TC81137 Similar to isoprenylated protein FP6 (Soybean) -1.21 -1.03 TC83108 Similar to oxidoreductase At5g04070 (Arabidopsis) -1.06 - TC86666 Similar to Ntdin (Tobacco) -1.32 - 17 MtGI* Annotation SA270631 SA30542 TC86888 Similar to Blue copper-binding protein 15K (Lamin) -1.07 -1.03 (Arabidopsis) TC86956 Similar to thylakoid lumenal 35.8 kDa protein, -1.00 - chloroplast precursor (Arabidopsis) TC89742 Similar to carbonate dehydratase-like protein -1.37 -1.28 (Arabidopsis) Autointerpro Cyclin like F box -1.41 - Unknown TC76385 Weakly similar to unknown protein AAM91530 -1.04 - (Arabidopsis) TC88790 Similar to unknown protein AAM91677 (Arabidopsis) -1.38 - CB891284 Similar to unknown protein AAM92303 (Rice) -1.12 -1.11 TC76647 Expressed M. truncatula sequence with no homology -1.27 -1.11 TC77484 Weakly similar to AT4g32480/F8B4_180 (Arabidopsis) -2.83 -2.05 TC77485 Similar to T4g32480/F8B4_180 (Arabidopsis) -1.93 -1.50 TC77494 Similar to hypothetical protein (rodent malaria parasite) -1.09 -0.78 TC77948 Similar to expressed protein Q7GAD9 (Arabidopsis) -1.54 -1.23 TC77948 Similar to expressed protein Q7GAD9 (Arabidopsis) -1.19 -1.00 TC78853 Expressed M. truncatula sequence with no homology -1.33 - TC78888 Similar to unknown protein NP_200466 (Arabidopsis) -1.15 -0.83 TC78915 homologue to unknown protein AAL79748 (Rice) -1.16 -0.77 TC78929 Similar to unknown protein AAB63076 (Arabidopsis) -1.53 -1.25 TC79055 Weakly similar to unknown protein AAD32907 -0.84 -1.07 (Arabidopsis) TC79105 Similar to unknown protein AAL60032 (Arabidopsis) -1.46 -1.17 TC79183 Similar to unknown protein AAK76703 (Arabidopsis) -2.10 -1.11 TC79339 Similar to unknown protein AAM60835 (Arabidopsis) -1.25 -1.34 TC79485 Similar to hypothetical protein At5g56550 (Arabidopsis) -1.10 - TC79627 Expressed M. truncatula sequence with no homology -0.51 -1.16 TC81235 Similar to unknown protein AAM20264 (Arabidopsis) -1.49 -1.07 TC81753 Similar to At1g72790/F28P22_2 (Arabidopsis) - -1.18 TC82520 Homologue to hypothetical protein CBG12313 -1.17 -1.32 (Caenorhabditis briggsae) TC83210 Weakly similar to unknown protein AAM91187 -1.21 -0.81 (Arabidopsis) TC83346 Similar to unknown protein AAM62635 (Arabidopsis) -1.16 -0.96 TC83863 Similar to unknown protein NP_564914 (Arabidopsis) -1.15 - TC85036 Expressed M. truncatula sequence with no homology -1.21 -0.76 TC87709 Similar to hypothetical protein At1g45150 (Arabidopsis) -1.18 -0.69 TC87803 Expressed M. truncatula sequence with no homology -1.20 -0.56 TC88027 Weakly similar to unknown protein AAP06874 - -1.08 TC88495 Similar to F-box protein ORE9 AtFBL7 (Arabidopsis) -0.69 -1.05 TC89381 Weakly similar to hypothetical protein At5g56550 -1.48 -1.31 (Arabidopsis) TC90110 Similar to putative protein CAB62464 (Arabidopsis) - -1.15 TC91172 Similar to auxin-induced protein-like (Arabidopsis) -0.81 -1.04 TC91945 Similar to hypothetical protein LE51 (Mouse) -1.07 - TC92112 Similar to F21D18.17 (Arabidopsis) -1.28 -1.00 TC92918 Similar to hypothetical protein CNBG0510 -1.15 - (Cryptococcus neoformans) TC93294 Expressed M. truncatula sequence with no homology -2.01 - TC90615 Similat to hypothetical protein At1g77160 (Arabidopsis) -1.17 -1.60 TC80320 Gibberellin regulated protein (M. truncatula) -1.09 -0.71 TC77482 Similar to protein of unknown function DUF506 (M. -2.54 -2.04 18 MtGI* Annotation SA270631 SA30542 truncatula) * Medicago truncatula Gene Index tentative consensus (TC) numbers for the 70-mer oligonucleotides on the microarray (http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=medicago). 1 log2 expression ratio inoculated/ control SA27063 (resistant) 12 hpi with P. medicaginis OMT5. 2 log2 expression ratio inoculated/ control SA3054 (susceptible) 12 hpi with P. medicaginis OMT5. § Dash (-) indicates that the TC is not significantly differentially expressed (P ≤ 0.01, M< -1 and n ≥ 10) 19 Appendix 05 Genes and primer sequences used for RT-qPCR Primer Expression MtGI annotation TC name Sequence data Reference β-1,3-glucanase TC94670 BGL2.1-F CCTGAGTTAGAGAAACATTTTGGAGT Figure 7.2a This thesis BGL2.1 R ATACATAAAGAGAGCAACCTTAATT Pathogenesis related protein 1 (PR1) TC105889 PR1-F AGGGTTATGGTGAAGTGAATGGT Figure 7.2b This thesis PR1-R TTAGCACAACCAAGATGAACAGAA Plant defensin TC107866 PDF2.1-F GTCTTAACACAGGAAACTGCA Figure 7.2c This thesis PDF2.1-R CTTTCACAAAGTTTAGGTTCCA Chalcone synthase TC106536 CHS-F GCTGCACTAATTGTTGGTTCA Figure 7.2d This thesis CHS-R TAAGCACCTCATATAGCGATACTT Ethylene response factor (ERF) TC94867 ERF1-F GAATGAAGTGGGGTTATGCGATGTA Figure 7.2e This thesis ERF1-R AAATAGAAAAGCCAAGGTGGGT Chitinase TC106842 Chit-F ACAGAATCCCAGCAGCACAT Figure 7.2f This thesis Chit-R CGATGGAGTTGAGGAAGAGG Gao et al. β-1,3-glucanase TC98780 BGL1-F CAAATTGGGTCCAAAAATATGTGAC Figure 7.6a 2007 BGL1-R GCACCATCATTGGGTGGATATGAAG PR5 (thaumatin- Gao et al. like protein) TC100682 PR5-F TGCCTTAGCTTTGCATTCCT Figure 7.6b 2007 PR5-R AATTTCCGCTGAGTTCGTTG PR10 TC94219 PR10-F TGTCGAAGATGGTGAAACAAA Figure 7.6c This thesis PR10-R TTGCCATTCTTGAGTTCCTCT Gao et al. Lipoxygenase TC100514 LOX1-F TTCAGACAGCGAATGGGAACTTTTCTTCG Figure 7.7a 2007 LOX1-R CAAAAGCAGCTTTAATCATTGGTTCCTC Gao et al. Lipoxygenase TC100155 LOX3-F CGATGAGATGGTGAAAAGTCCTC Figure 7.7b 2007 LOX3-R GCTTGAACTGCCCTTGTATCAGA Gao et al. Lipoxygenase TC100513 LOX5-F AAAGCTGTGGCTGTGAGTGATG Figure 7.7c 2007 LOX5-R CCACTGATCTATGCGTTTGGTG Allene oxide synthase TC101097 AOS1-F GGACACCGAACTTGGACTTGAC Figure 7.7d This thesis AOS1-R AAACATCCAAACGCTCTGCTTC Allene oxide synthase TC110784 AOS2-F GGCCCATTCATTTCCTCTAACC Figure 7.7e This thesis AOS2-R AGAAGGCGTTTGAGTTGGTCGT 12-OPDA reductase TC94406 OPR1-F CGAAGTTGTGGTGTGAGTGG Figure 7.7f This thesis OPR1-R CCGGTTCTAACGGAGGTCTT 12-OPDA Gao et al. reductase TC94407 OPR-F TGGCACCACTCACAAGACAAAG Figure 7.7g 2007 OPR-R GAACAGCATCCACAATGGGTTT Caffeoyl O- CCOMT1- methyltransferase TC94321 F GCCATTCCTGAAGATGGAAA Appendix This thesis CCOMT1- R GTAATTGTCTTTGTCAGCATCCAC Caffeic acid O- methyltransferase TC100776 COMT1-F TGTTGATGTTGGTGGTGGAA Figure 7.8l This thesis COMT1-R CTGTGGCAGGAAGAGAATCATAG Caffeic acid O- methyltransferase TC106629 COMT2-F GGTGGTGGTACTGGAGCTGT Appendix This thesis COMT2-R TGGTAGTGCTTCATAGCAGTTCTT Ferulate-5- hydroxylase TC111608 F5H-F TCAACTCTCATCACCCAACAAC Figure7.8m This thesis F5H-R CCAGGTGGATATGGTGCTCT 20 Appendix 06 Gene families of the phenylpropanoid pathway and their RT-qPCR primer sequences Enzyme name Forward Forward primer sequence Reverse primer Reverse primer sequence Product primer name name size Phenylalanine ammonia-lyase (PAL) TC101026 PAL3-F GCAACCTAAAGAAGGTTTAGCAC PAL3-R GCAGCCTTACCATAATAACTTCC 252 bp TC102823 TC103174 TC106667/TC106671 (TC85501/TC85506) PAL1-F GAAGCGTATGGTGGAGGAGT PAL1-R CGGTGAGAAGTAGCACCAAA 228 bp TC106668 TC106669 (TC85502) PAL2-F AAGAGGTTGAAAGTGCAAGGA PAL2-R CCCAAGCATTCAAGAAGAGG 223 bp TC106670 (TC85505) Cinnamate 4-hydroxylase (CA4H) TC106704 (TC76780) CA4H-F GTTACGGGTGGGAGTCTGAA CA4H-R AGTCCATCATTGCTCGTGGT 388 bp 4-Coumarate:coenzyme A ligase (4CL) TC94566 (TC77196) 4CL1-F CGCCAATCCCTTCTTCACT 4CL1-R TATGGCAATGCAACCACATC 249 bp TC95093 (TC77753) 4CL2-F AGCATTGTTGATTGCTCATCC 4CL2-R GGCGGCTTTAGGAATTGTTT 211 bp TC95226 TC98074 TC99584 TC99926 TC103345 TC104410 TC108579 TC111254 TC111271 Chalcone synthase (CHS) TC95902 TC97724 TC102579 TC105903 21 Enzyme name Forward Forward primer sequence Reverse primer Reverse primer sequence Product primer name name size TC106536 (TC85138) TC106537 (TC76765 and TC76766) TC106538 TC106539 (TC85146) TC106544 (TC85150) TC106549 (TC76767) TC106550 (TC76767) TC106552 (TC85169) TC106554 (TC85174) TC106555 (TC76769) TC106559 (TC76770) TC106561 (TC85186) Chalcone reductase (CHR) TC94042 TC94161 TC98216 TC100398 (TC85521 and TC85519) CHR3-F GCAGATGCACATGGAAAGTC CHR3-R TTCAAAGCTCGAAAGAAACAAG 322 bp TC100399 (TC76884) TC100400 (TC85521 and TC85519) TC100401 (TC85521 and TC85519) CHR2-F GCAGATGCACATGGAAAGTC CHR2-R AACAAGGGTAATCCTAAGCTCAAA 328 bp TC100402 (TC85521) CHR1-F GCAGATGCACATGGAAAGTC CHR1-R CCAAGCTCAAGCAACAAGAA 320 bp Chalcone isomerase (CHI) TC100522 (TC85633) CHI1-F GGGAATTGAGTGGTCCTGAGT CHI1-R CTGCTGATGAAACTGCCTTG 264 bp TC100603 TC100604 (TC76950) TC100605 (TC76950) TC107065 TC107882 22 Enzyme name Forward Forward primer sequence Reverse primer Reverse primer sequence Product primer name name size TC112171 Isoflavone synthase (IFS) TC106938 TC106939 IFS1-F TGGAATTTCGTCCAGAGAGG IFS1-R CCAGGTCTCTCATCCATGCT 281 bp TC106940 TC110872 Isoflavone 7-O-methyl-transferase (IFMT) TC94971 TC95934 TC101280 TC101281 TC101335 (TC77996) IFMT1-F ATTATCTACAATCATGGCAAACCAA IFMT1-R TTTAGGATCAAGAACACACTCAACC 252 bp TC101336/TC101337 IFMT2-F ATCCACAATCATGGCAAACC IFMT2-R TGTTGGATCAAGAACACACTCAAC 249 bp TC100926 (TC86358) 6HMM-F GAGGGTTTGGAGTCTCTTGTTG 6HMM-R TGTGAAATAGCTTCTTTGCTGTTC 273 bp TC108558 Isoflavone 2'-hydroxylase (IFOH) TC94324 CYP81E7-F ATAATTGGCAACCTCCACCA CYP81E7-R ACCGAAACCTTCAGAGACGA 387 bp Isoflavone 3'-hydroxylase (IFOH) TC95424 (TC85608) CYP81E9-F TCCACCAGGTCCAACTTCTC CYP81E9-R CGAAGGTTACGCCAGTGTTC 288 bp TC96856 TC100787 (TC77891) CYP81E8-F TTCTCGTCTCGTCGTTGTTG CYP81E8-R TCCACTTCGGTGAAACCATT 297 bp TC105563 Isoflavone reductase (IFR) TC94281 (TC85477) IFR2-F AACATTTCCGGGATGACAAA IFR2-R AAGCAGCAAATGATCCCAAC 347bp TC95666 TC96039 TC96312 (TC85478) IFR1-F TCCCAGGAAGACAAACTTAGACA IFR1-R AAGCAGCAAATGATCCCAAC 342bp TC100786 23 Enzyme name Forward Forward primer sequence Reverse primer Reverse primer sequence Product primer name name size TC107101 TC107320 (TC86455) TC109045 Vestitone Reductase (VR) TC100886 (TC77308) VR-F AAGCTGTTCTTGAATTTGGTGA VR-R TCCACGAGTTTCTTCGTGTTT 382 bp 24 Appendix 07 Expression profiling of genes in the phenylpropanoid pathway in response to Phoma medicaginis OMT5 in resistant (SA27063) and susceptible (SA3054) M. truncatula accessions SA27063 (Resistant) 09 h 12 h 24 h 48 h 72 h Enzyme name Mock Phoma Mock Phoma Mock Phoma Mock Phoma Mock Phoma Cinnamate 4-hydroxylate TC106704 (CA4H) 0.34 (0.01) 0.19 (0.02) 0.19 (0.04) 0.45 (0.15) 1.80 (0.33) 2.33 (0.53) 1.62 (0.47) 2.66 (1.14) 2.01 (0.78) 2.11 (1.05) 4-Coumarate CoA ligase TC94566 (4CL1) 0.41 (0.04) 0.42 (0.11) 0.53 (0.04) 1.02 (0.25) 1.51 (0.27) 1.25 (0.26) 1.17 (0.25) 1.02 (0.29) 0.91 (0.09) 1.13 (0.36) TC95093 (4CL2) 0.42 (0.05) 0.23 (0.04) 0.24 (0.09) 0.24 (0.06) 0.95 (0.34) 1.04 (0.17) 1.19 (0.56) 1.12 (0.62) 0.65 (0.24) 0.67 (0.38) Chalcone isomerase TC100522 (CHI) 4.9 (1.86) 5.8 (0.76) 3.06 (0.47) 13.78 (2.18) 3.25 (2.53) 4.36 (0.44) 1.48 (0.61) 5.30 (0.92) 1.08 (0.18) 4.15 (1.47) Isoflavone synthase TC106939 (IFS) 1.86 (0.46) 0.88 (0.32) 0.95 (0.29) 2.58 (0.72) 2.35 (1.07) 4.83 (0.85) 0.49 (0.14) 9.71 (2.68) 0.47 (0.24) 12.1 (4.77) Isoflavone O -methyltransferase TC101335 (IFMT1) 1.47 (0.67) 3.51 (1.12) 1.57 (0.33) 9.64 (2.19) 0.85 (0.63) 7.72 (2.32) 0.36 (0.11) 5.8 (2.86) 0.49 (0.21) 4.41 (1.91) TC101336/7 (IFMT2) 1.90 (1.46) 4.26 (2.34) 1.63 (0.21) 13.61 (2.84) 2.37 (0.38) 4.22 (1.74) 0.33 (0.04) 4.02 (0.27) 0.70 (0.53) 4.67 (2.21) TC95934 (IFMT3) 1.87 (0.87) 5.93 (3.45) 3.07 (1.35) 12.34 (3.57) 1.12 (0.63) 9.92 (3.28) § 0.56 (0.01) 3.82 (2.28) 0.29 (0.06) 2.30 (0.82) TC100926 (6hmm) 1.86 (0.83) 1.87 (0.17) 1.03 (0.62) 11.00 (2.88) 1.17 (0.54) 4.41 (0.06) 0.87 (0.45) 10.15 (3.58) 0.45 (0.21) 11.59 (4.57) Isoflavone 2'-hydroxylase TC94324 (CYP81E07) 2.39 (1.39) 1.16 (0.35) 0.76 (0.27) 1.42 (0.56) 1.93 (0.60) 8.68 (3.88) § 2.16 (0.36) 4.36 (0.22) 1.50 (0.24) 1.66 (1.01) Isoflavone 3'-hydroxylase TC100787 (CYP81E08) 1.05 (0.12) 1.92 (0.79) 1.10 (0.30) 3.75 (1.74) 0.60 (0.39) 2.13 (0.68) 0.71 (0.23) 1.93 (1.56) 1.03 (0.27) 0.68 (0.15) TC95424 (CYP81E09) 2.61 (0.37) 2.33 (0.72) 1.48 (0.76) 5.98 (3.63) 1.41 (0.23) 6.94 (0.69) 1.36 (0.09) 15.11 (3.79) 1.11 (0.42) 17.79 (6.28) Isoflavone reductase TC96312 (IFR1) 5.11 (4.49) 12.50 (2.29) 2.99 (1.61) 84.32 (46.14) 1.93 (0.23) 25.78 (7.46) 1.53 (0.23) 34.67 (11.53) 1.00 (0.65) 38.07 (10.02) TC85477 (IFR2) 5.02 (0.45) 30.28 (6.02) 8.94 (4.88) 139.23 (56.03) 3.22 (0.21) 28.41 (2.87) 1.84 (0.71) 41.37 (12.38) 1.71 (0.68) 45.21 (21.30) Vestitone reductase TC100886 (VR) 2.77 (1.86) 7.07 (3.68) 2.40 (1.14) 13.00 (7.07) 2.32 (1.21) 7.12 (2.99) 1.62 (0.92) 9.30 (3.59) 1.21 (0.32) 7.48 (2.38) Caffeoyl CoA O -methyltransferase TC94321 (CCOMT1) 0.18 (0.05) 0.45 (0.07) 0.63 (0.12) 0.90 (0.09) 1.94 (0.07) 1.51 (0.25) 1.66 (0.29) 1.47 (0.51) 1.13 (0.06) 1.07 (0.36) Caffeic acid O -methyltransferase TC100776 (COMT1) 123.28 (177.69) 705.04 (134.32) § 55.41 (24.51) 713.10 (121.85) § 161.85 (247.78) 1487.66 (308.74) § 22.78 (5.04) 636.01 (176.88) 25.41 (13.85) 334.61 (183.65) TC106629 (COMT2) 0.45 (0.23) 0.33 (0.06) 0.74 (0.42) 0.62 (0.280 1.90 (0.42) 1.81 (0.34) 2.35 (1.76) 1.96 (1.21) 1.35 (0.35) 1.02 (0.38) Ferulate-5-hydroxylase TC111806 (F5H) 3.02 (2.08) 5.19 (1.35) 4.73 (1.03) 7.89 (3.09) § 1.30 (0.48) 1.15 (0.26) 0.88 (0.75) 1.01 (0.17) 1.17 (0.96) 0.93 (0.68) 25 SA3054 (Susceptible) 09 h 12 h 24 h 48 h 72 h Enzyme name Mock Phoma Mock Phoma Mock Phoma Mock Phoma Mock Phoma Cinnamate 4-hydroxylate TC106704 (CA4H) 0.84 (0.38) 0.43 (0.15) 0.28 (0.05) 0.68 (0.09) 1.58 (0.38) 3.17 (0.96) 3.04 (0.79) 4.99 (2.25) 2.97 (1.47) 2.13 (0.54) 4-Coumarate CoA ligase TC94566 (4CL1) 0.54 (0.19) 0.53 (0.070 0.48 (0.12) 1.19 (0.30) 0.88 (0.17) 1.05 (0.38) 1.16 (0.21) 1.11 (0.30) 1.07 (0.52) 1.26 (0.57) TC95093 (4CL2) 0.98 (0.37) 0.43 (0.08) 0.41 (0.12) 0.43 (0.04) 1.38 (0.65) 0.77 (0.22) 2.65 (0.77) 1.96 (0.89) 1.31 (0.59) 1.07 (0.54) Chalcone isomerase TC100522 (CHI) 4.86 (1.88) 7.16 (0.25) 3.28 (0.50) 18.57 (3.74) 1.23 (0.31) 3.94 (0.68) 2.05 (0.37) 9.70 (3.45) 1.69 (0.71) 4.63 (1.38) Isoflavone synthase TC106939 (IFS) 2.54 (1.60) 3.16 (0.24) 1.09 (0.23) 6.13 (0.73) 0.40 (0.10) 4.97 (1.50) 1.16 (0.51) 30.91 (5.07) § 0.51 (0.31) 15.75 (6.36) Isoflavone O -methyltransferase TC101335 (IFMT1) 4.01 (3.27) 8.33 (3.92) 1.35 (0.14) 16.59 (5.63) 1.49 (0.14) 6.76 (1.44) 1.58 (0.57) 21.43 (8.15) 1.62 (1.03) 10.25 (5.48) TC101336/7 (IFMT2) 4.70 (3.76) 8.90 (5.20) 1.19 (0.64) 19.57 (6.39) 0.98 (0.40) 5.01 (2.73) 1.14 (0.59) 27.64 (10.95) § 0.99 (0.37) 10.96 (6.11) TC95934 (IFMT3) 7.56 (5.69) 11.21 (9.59) 1.18 (0.48) 38.99 (12.29) § 1.14 (0.07) 4.62 (1.23) 2.53 (1.88) 30.32 (16.98) § 1.61 (1.24) 5.61 (3.47) TC100926 (6hmm) 1.62 (1.12) 4.47 (0.51) 1.41 (0.99) 23.18 (11.12) 0.47 (0.18) 6.78 (0.62) § 1.42 (0.440 27.38 (7.15) § 0.77 (0.37) 17.15 (5.93) Isoflavone 2'-hydroxylase TC94324 (CYP81E07) 2.99 (1.76) 0.97 (0.27) 0.38 (0.06) 2.80 (1.78) 2.62 (2.01) 2.88 (0.93) 2.05 (1.06) 3.89 (1.43) 1.87 (1.08) 1.13 (0.53) Isoflavone 3'-hydroxylase TC100787 (CYP81E08) 2.32 (0.060 4.8 (2.29) 1.74 (0.14) 4.35 (1.10) 0.87 (0.26) 3.51 (1.53) 1.58 (0.41) 2.94 (2.41) 1.91(0.58) 1.27 (0.47) TC95424 (CYP81E09) 6.17 (5.67) 11.96 (6.61) 1.40 (0.28) 17.11 (5.65) § 1.09 (0.35) 7.42 (1.34) 3.12 (1.23) 86.39 (16.71) § 1.90 (0.82) 54.58 (26.51) § Isoflavone reductase TC96312 (IFR1) 4.75 (1.80) 44.19 (12.80) 2.31 (0.17) 221.90 (98.91) § 0.71 (0.30) 71.03 (28.98) § 4.60 (3.06) 135.59 (43.10) § 2.67 (2.56) 53.31 (23.19) TC85477 (IFR2) 9.73 (3.43) 101.51 (34.75) § 13.20 (11.46) 261.70 (97.38) § 0.48 (0.22) 36.87 (19.33) 4.60 (3.44) 138.45 (28.79) § 2.51 (2.46) 70.90 (28.80) Vestitone reductase TC100886 (VR) 2.75 (1.51) 9.35 (2.04) 1.82 (0.55) 20.93 (9.44) 1.00 (0.19) 5.58 (1.15) 1.78 (0.24) 16.61 (5.16) 2.09 (0.89) 7.38 (3.22) Caffeoyl CoA O -methyltransferase TC94321 (CCOMT1) 0.71 (0.330 0.82 (0.64) 0.54 (0.07) 1.32 (0.37) 1.35 (0.33) 1.21 (0.07) 2.69 (0.95) 2.62 (1.14) 2.08 (1.20) 1.37 (0.71) Caffeic acid O -methyltransferase TC100776 (COMT1) 50.90 (3.95) 223.42 (101.44) 8.64 (6.93) 333.48 (73.33) 6.56 (2.92) 494.57 (125.99) 24.84 (9.94) 1470.43 (885.62) 28.98 (26.23) 411.44 (352.88) TC106629 (COMT2) 2.05 (1.07) 0.93 (0.67) 0.54 (0.13) 1.03 (0.19) 1.93 (1.26) 2.24 (0.51) 4.46 (1.87) 5.14 (4.19) 3.53 (2.02) 3.49 (1.80) Ferulate-5-hydroxylase TC111806 (F5H) 2.41 (0.71) 1.94 (1.27) 1.30 (0.67) 2.59 (1.41) 0.22 (0.03) 0.11 (0.10) 0.63 (0.38) 0.76 (0.36) 0.68 (0.39) 0.40 (0.28) Fold induction was determined as described in paragraph 7.2.6. Values in bold indicate that the relative transcript abundance was significantly different from that of mock inoculated plants of the same accession at a given timepoint (P < 0.05). § indicates that the relative transcript abundance was significantly different between resistant and susceptible plants upon Phoma medicaginis infection at a given timepoint (P < 0.05). Colour scale 26