Exploring and Mapping Genetic Variation in Wild Barley, Hordeum Spontaneum

Exploring and mapping genetic variation in wild barley, Hordeum spontaneum

Tytti Kaarina Vanhala

Promotor: Prof. Dr. Ir. P. Stam Hoogleraar in de plantenveredeling

Samenstelling promotiecomissie:

Prof. Dr. P.H. van Tienderen (Universiteit van Amsterdam) Prof. Dr. R.F Hoekstra (Wageningen Universiteit) Dr. H. Poorter (Universiteit Utrecht) Prof. Dr. Ir. P.C. Struik (Wageningen Universiteit)

Dit onderzoek is uitgevoerd binnen de onderzoekschool Production Ecology and Resource Conservation

Tytti Kaarina Vanhala

Exploring and mapping genetic variation in wild barley, Hordeum spontaneum

Proefschrift ter verkrijging van de graad van doctor op gezag van de rector magnificus van Wageningen Universiteit, Prof. Dr. Ir. L. Speelman, in het openbaar te verdedigen op vrijdag 10 september 2004 des namiddags te half twee in de Aula

Tytti Kaarina Vanhala (2004)

Exploring and mapping genetic variation in wild barley, Hordeum spontaneum Vanhala, T.K. –[S.1.:s.n.].Ill. PhD Thesis Wageningen University. –With ref.- With summaries in English, Dutch and Finnish

ISBN : 90-8504-043-4

Contents

Abstract 1

Chapter 1 General Introduction 3

Chapter 2 A genetic linkage map of wild barley (Hordeum spontaneum) 11

Chapter 3 Environmental, phenotypic and genetic variation of wild barley (Hordeum spontaneum) from Israel 25

Chapter 4 Association of AFLP markers with growth related traits in Hordeum spontaneum 43

Chapter 5 Quantitative trait loci for seed dormancy in wild barley (Hordeum spontaneum) 63

Chapter 6 Summarising discussion 75

Samenvatting 81

Tiivistelmä 87

References 95

Addresses of co-authors 107

Acknowledgements 108

Curriculum vitae 111

Abstract

Wild barley represents an important genetic resource for cultivated barley, which has a narrowed gene pool due to intensive breeding. Therefore, it is imperative to study the genetics of different traits in wild barley, if it is to be used for cultivar improvement. This thesis describes studies of different aspects of diversity, as well as linkage, QTL and association mapping in wild barley. The natural populations that were studied were collected in environmentally diverse Israel. Using a cross between genotypes from contrasting habitats, a linkage map was produced. Due to unexpectedly high heterozygosity of one of the parents the map covered approximately 45% of the barley genome. This map was subsequently utilised in all other studies in this thesis. Genetic diversity was estimated within and between 21 populations. This was correlated with phenotypic and environmental diversities of the same populations. Genetic diversity was loosely connected with environmental diversity. In general, phenotypic diversity did not correlate with either one. Some markers were ecotype-specific; some of these were mapped and correlated significantly not only with environmental but also with phenotypic traits. Using the same populations, correlations between mapped markers and phenotypic traits were calculated. The significant associations were then compared with QTL found in an earlier study. Many of these associations mapped to the same regions as the QTL and therefore these two approaches of mapping traits complemented each other. Lastly, the map was used to locate QTL for dormancy in wild barley. Five QTL were found of which three map to regions where dormancy QTL has been found earlier in cultivated barley. For further research, another cross should be made to produce a map with larger coverage of the genome. The results of this thesis add to the characterisation of the diverse wild barley populations from Israel, which is important to the future improvement of cultivated barley.

Chapter 1

Many years have passed since those summer days Among the fields of barley See the children run as the sun goes down Among the fields of gold You'll remember me when the west wind moves Upon the fields of barley You can tell the sun in his jealous sky When we walked in the fields of gold

Sting – Fields of gold

General Introduction

Hordeum spontaneum, wild in Southwest Asia across a wide range of barley climates and soils. It is particularly Hordeum spontaneum (wild barley) is the common in the Near East Fertile Crescent ancestor of cultivated barley. It belongs (Zohary 1969). In general, wild barley is to the Poaceae- family of grasses and not tolerant to extreme low temperatures within it to the Triticeae-tribe. Triticeae is and is rarely found above 1500 m a temperate plant group mainly altitude. However, it is more drought concentrated around Central and resistant than the wild wheat and Southeastern Asia, although the species penetrates relatively deeply into the warm belonging to it are distributed around the steppes and deserts (Zohary & Hopf world. Triticeae includes many 1988). economically important cultivated cereals Wild barley and cultivated 2-rowed and forages but also about 350 wild barley have quite similar morphology. The species. The wild species are of great most notable differences are wild barley’s interest as potential gene donors for brittle rachis and its hulled grain. Six- commercial breeding. rowed barley has evolved during The genus Hordeum includes 30 domestication, the trait being controlled species (Von Bothmer 1992), both by a single gene on chromosome 2 annuals and perennials. Wild barley can (Komatsuda et al. 1999; Tanno et al. be winter or summer annual depending 2002). Wild barley is the only wild on the local climate. It is diploid (2n=14) Hordeum species that can produce fully and mainly inbreeding, although some fertile hybrids (with normal chromosome populations have a higher rate of pairing and segregation in meiosis) when outcrossing. On average this is 1.6%, crossed with cultivated barley. Hybrids varying from 0 to 9.6%, depending on can also be formed in nature when these the environment; it is significantly higher two occur at the same location (Asfaw & in the mesic than in the xeric regions Von Bothmer 1990). (Brown et al. 1978a). The collection of wild barley from The wild annual Hordeum species Israel was obtained between 1974 and grow in open habitats with comparatively 1976 (Nevo et al. 1979). During that low competition from other species (Von period over a thousand different Bothmer 1992). Wild barley is distributed accessions were collected from the whole over the eastern Mediterranean area and of Israel. Sampling was done from various habitats like road and mountainsides,

4 fields and deserts. Latitude, longitude, (PCR) to amplify DNA, many different altitude and different rainfall and types of molecular markers have been temperature variables were reported from developed. Wild barley from Israel has the nearby weather stations. This also been studied utilising several of these collection has been maintained in the PCR-based methods: RAPDs (Baum et al. Institute of Evolution, Haifa, Israel by 1997; Owuor et al. 1997, 1999), AFLPs prof. E. Nevo and his co-workers. During (Pakniyat et al. 1997, Turpeinen et al. successive years, more samples were 2003) and SSRs (Turpeinen et al. 2001). added to the collection; populations from RFLPs (Chalmers et al. 1992), Tabigha (Nevo et al. 1986a) and retrotransposon copy numbers (Kalendar Evolution Canyon (Nevo 1995). et al. 2000) and genome size (Turpeinen Accessions from this collection in Haifa et al. 1999) were also used in studying have been distributed around the world. wild barley diversity within Israel. However, because of the high number of Studies with wild and cultivated accessions available, there is hardly any barley have shown that there is more overlap on the material used in the variation within the wild than in the different studies. Because these samples cultivated barley (e.g. Saghai Maroof et have been collected from widely diverse al. 1995), although in some cases the habitats, the collection represents a rich opposite has been reported for some source of phenotypic and genetic isozymes and mitochondrial DNA (Nevo, variation, which can be used to study 1992). The larger genetic variation within ecophysiological issues both at the wild barley gives the opportunity to use phenotypic and genotypic level. In this variation for breeding purposes. addition, the wild barley accessions of The genetic diversity of wild this collection are a potential source of barley is correlated with its geographic variation to be tapped by plant breeders distribution on a large scale, between for the improvement of cultivated barley. countries. But it is not evident on the micro-geographic scale within Israel. For example, Song & Henry (1995) found that Variation in wild barley from some of the accessions that were identical Israel genetically were geographically widely The genetic variability of wild barley has scattered and of contrasting habitat. been described in many studies. So far, Resistance to biotic and abiotic the only research including all the stresses has been the main area of study collected accessions from Israel has been on the phenotypic variation in wild barley, conducted by using isozymes (Brown et as these are important targets for al. 1978b; Nevo et al. 1979). After the improvement in barley breeding (Ellis et invention of polymerase chain reaction al. 2000). Wild barley accessions from Israel have been screened for resistance

5 to several plant pathogens (e.g. marker alleles arises from linkage Moseman et al. 1983, 1990; Ordon et al. between marker loci and loci controlling 1997). Several lines were resistant to the trait. By identifying these Erysiphe graminis and Puccinia hordei as associations, the method allows the well as soil-borne mosaic-inducing viruses location of genomic regions on a marker (Moseman et al. 1983, 1990; Ordon et al. linkage map that most likely contain 1997). Other agronomically interesting genes involved in the trait (the QTL). The traits include a range of physiological and results of QTL mapping provide the most chemical traits (e.g. Ellis et al. 1993; likely position of the QTL, together with Forster et al. 1994; Nevo et al. 1993a, an estimate of the allele substitution 1992, 1985), abiotic stress tolerance effects (the additive effect) and so called (e.g. Nevo et al. 1993b, Pakniyat et al. ‘supportive intervals’ that roughly 1997, Robinson et al. 2000) and correspond to confidence intervals for the morphological characters (e.g. Gutterman QTL map positions. The precision that can et al. 1996, Nevo et al. 1984, Giles be attained in QTL mapping, both with 1990). respect to positioning on the map and the estimated substitution effect, depends largely on two factors, i.e. the size of the Quantitative trait loci (QTL) mapping population and the genetic mapping and wild barley variation that is attributable to a Linking genetic information with particular QTL. In general, using a phenotypic measurements is vital if wild mapping population of size below 400, barley is to be used for barley confidence intervals for QTL positions improvement. This can be done either by cover map distances as large as 20 to 60 mapping quantitative trait loci (QTL centimorgans. More precise location (fine mapping), association mapping or both. mapping) of QTL requires different Both of these methods are based on approaches, such as the construction of associations between quantitative traits backcross inbred lines, containing small and marker alleles, which is due to introgressed ‘donor’ genome fragments in linkage disequilibrium between the alleles a homogeneous recipient genetic at marker loci and trait controlling loci; background. From a breeding perspective both have their advantages and a potential disadvantage of QTL detection disadvantages. in mapping populations is that the results QTL mapping requires the obtained from a particular cross cannot a construction of a linkage map using a priori be extrapolated to other crosses cross between phenotypically divergent because the magnitude of QTL effects and accessions. In the offspring of such a the detectability of QTL depends on the cross, association between a trait and genetic background. Nonetheless, several studies have shown that certain QTL

6 regions may be common to several that have taken place during a single or a crosses. Interspecific crosses between few meioses following the cross between wild and cultivated barley have been the parents, whereas in a germ plasm made (Graner et al. 1991, Pillen et al. collection linkage disequilibrium reflects 2000, Ramsay et al. 2000) and some QTL the recombination events that have studies have been conducted using such accumulated during the history of the an interspecific cross (Ellis et al. 1997, germ plasm. Usually this history traces Huang et al. 2001, Backes et al. 2003, back to an unknown point in time. For Baum et al. 2003). these reasons the amount of LD that can Another way of screening and be encountered depends on the history of locating useful traits in wild barley the germ plasm, its population structure populations is to look for associations and its mating system (outbreeding between the traits and previously versus inbreeding). In addition to linkage, mapped markers among the wild associations in a germ plasm collection populations (e.g. Nevo et al. 1984, may also arise by chance (i.e. admixture, Pakniyat et al. 1997). The advantages are outcrossing events etc.), resulting in LD notable as the development of mapping between the alleles of unlinked or loosely populations is not required and the study linked loci. Therefore, observed is not limited to a single cross between associations between traits and marker two individual parent lines that might not alleles in a population survey should be express sufficient variation in the traits of interpreted with care. It is helpful when interest. In contrast to QTL mapping, in the markers used in an association study which the difference between the two have been mapped previously, so that the parental genotypes is analysed, map distance over which significant association mapping (also referred to as linkage disequilibrium between markers linkage disequilibrium (LD) mapping) extends, can be estimated. Combining relies on the association between traits and comparing the results of association and marker alleles across a large set of studies with those obtained from QTL populations or accessions. Associations mapping may then lead to a better and between the alleles of markers and QTL more reliable identification of the genomic in a germ plasm collection may arise in regions that contain the trait-controlling various ways. First, identity by descent of genes. From a plant breeding perspective, the alleles of tightly linked loci may be an obvious advantage of association the cause. It is this type of association, or mapping over QTL mapping exercises is linkage disequilibrium, that association that the observed associations are not mapping tries to uncover. In a classical confined to a particular cross, but hold mapping population the degree of linkage over a wild range of a crop’s germ plasm. disequilibrium between linked loci An additional advantage of association depends on the recombination events mapping is the potential high precision of

7 QTL location, as compared to QTL conducted to unravel the genetic basis of mapping. This is because in a germ plasm relative growth rate (Elberse, 2002; survey, significant associations between Poorter et al. 2004; Verhoeven et al. the alleles of linked loci usually do not 2004a). The overall aim of this program extend beyond a few centimorgans was to unravel the genetic basis of the (Kraakman et al., 2004); in outbreeders slow versus fast growing ‘syndrome’ in the distance over which linkage wild barley and to investigate how the disequilibrium extends may be even various physiological components of much smaller (see Rafalski & Morgante relative growth rate respond to a change 2004 for a recent overview). So, if a trait in environmental conditions, both natural is associated with a few closely linked and controlled. A hypothesis to be tested markers that cover a tiny chromosomal was the existence of a ‘major switch’, segment, but markers outside that possibly controlled by a single gene, segment do not show association with the which determines whether a genotype is trait, one can infer that the hypothesised slow or fast growing; such a switch might QTL is within that small segment. control several components underlying relative growth rate. Briefly, the results, obtained by QTL analyses in various Outline of this thesis environments, showed that growth rate is As well as exploring the genetics of wild influenced by several genes, some of barley from Israel, this thesis forms the which have an effect on more than one genetic backbone of a bigger research component of growth rate and that the program, which was set up to study size of the QTL effects may be relative growth rate and its components environmentally dependent thus leading in wild barley from Israel. The other parts to QTL by environment interaction. The of the research program included overall picture, however, indicated that physiological research done at the the direction of the QTL effects does not Utrecht University (Van Rijn, 2001), change between environments that are plasticity under different nutrient characterised by different levels of conditions (Elberse, 2002) and selection nutrient availability. and adaptation (Verhoeven, 2003). Both The objectives of the present latter studies were conducted at the thesis were Netherlands Institute of Ecology, Heteren, 1. to assess the genetic with some of the field work taking place diversity between and within wild barley in Israel. The resulting marker data and populations, linkage map from this thesis were shared 2. to study, at the population with all of these subprojects and QTL level, the associations between studies for a broad array of traits were physiological traits and DNA markers and to see to what extend these are in

8 accordance with the results of earlier QTL producing numerous crosses and studies, and recombinant inbred lines for QTL 3. to study the genetics of mapping. The most promising and dormancy in wild barley by means of a interesting accessions can thereafter be QTL mapping approach. crossed so that high quality QTL mapping Because several of these issues, populations can be produced for fine as well as the QTL studies performed in mapping of QTL, and possibly, cloning of the other projects of the program, require the underlying genes. a linkage map, a molecular marker Seed dormancy is extremely linkage map, based on an intraspecific important for the survival of wild species wild barley cross, has been constructed. as germinating during ‘wrong’ season can Such a linkage map is also vital for future be fatal. It is just as important in identification of agronomically relevant cultivated barley, as too dormant cultivars genes that are present in this germ will require after-ripening storage before plasm, especially because wild barley is germination can occur, and completely far more variable than cultivated barley. non-dormant cultivars might germinate As there was no previous detailed before harvesting, thus significantly genetic background information of the decreasing the quality and value of the particular accessions that were used in harvested crop. So far, several QTL for this and the other theses, it was of major dormancy have been identified in importance to estimate the variation cultivated barley and their variation and within and between all the studied expression has been studied in minute populations. This undertaking has greatly detail (e.g. Romagosa et al. 1999, Gao et enlarged the understanding of these al. 2003). Additional dormancy QTL from populations and given new views for wild barley will aid the designing of an further research and has provided the optimally dormant cultivar in providing basis for the choice of the parents to be more genetic variation to work with. crossed for linkage and QTL mapping. Chapter 2 presents the first wild From a breeding perspective it is barley genetic linkage map. The linkage equally important to screen all the map was constructed using an F2 populations for agronomically important population from a single pair cross traits and identify the genomic regions between two accessions from divergent that harbour the underlying genes. populations. Studies that uncover associations In Chapter 3, the genetic variation between traits and DNA markers at the in 21 wild barley populations from Israel level of germ plasm collection provide a is estimated using AFLP markers. gateway toward efficient tapping of this Phenotypic and environmental data were genetic resource for breeding purposes. also used to establish the general pattern This type of screening is much faster than of variation within and among these

9 populations. Correlations between these In Chapter 5, the genetic basis of three different levels of variation were seed dormancy in wild barley is studied. studied as well as associations between The experimental work was performed individual mapped markers and using F4 lines derived from F2 plants of the phenotypic and environmental variables. above-mentioned cross (Chapter 2). In Chapter 4, map-based AFLP Chapter 6 gives a summarising markers were associated with the discussion on the most important variation in growth traits in the 21 wild conclusions from the previous chapters. barley populations and compared with the QTL reported by Poorter et al. (2004).

Chapter 2

Do you remember the Shire, Mr. Frodo? It’ll be spring soon, and the orchards will be in blossom, and the birds will be nesting in the hazel thicket. And the whistle in the summer barley in the lower fields. And eating the first of the strawberries with cream. Do you remember the taste of strawberries?

J.R.R. Tolkien – The Return of the King

A GENETIC LINKAGE MAP OF WILD BARLEY (Hordeum spontaneum)

Tytti K. Vanhala & Piet Stam

Abstract A molecular marker map of wild barley (Hordeum spontaneum) was constructed using an

F2 population derived from the cross ‘Ashkelon’ x ‘Mehola’. Thirteen SSR markers and 22 AFLP primer combinations were used, yielding 384 polymorphic markers of which 202 were eventually mapped to 11 linkage groups. The map coverage was 445 cM, corresponding to an average distance of 2.2 cM between adjacent markers. To assign the linkage groups to known barley chromosomes, 33 AFLP markers, which were previously mapped in four different cultivated barley crosses and the SSRs were used as chromosome-specific markers. Due to heterozygosity of one of the parental plants used in this cross the map is estimated to cover approximately 45% of the wild barley genome. This map is the first intraspecific molecular linkage map of wild barley.

Introduction barley (Zohary 1969). Interspecific hybrids between wild and cultivated Wild relatives of crop plants are barley are fully fertile. This and the important resources for crop diversity of wild barley make it attractive improvement (e.g. Tanksley & Mc Couch for the genetic improvement of barley 1997). Intraspecific crosses are important cultivars. Wild barley is diploid (2n = 14) for detection and mapping of quantitative and although some outcrossing has been trait loci (QTL) controlling agronomic detected in the field, it is a predominantly traits within wild species. Crosses self-fertilising plant species (Brown et al. between wild and cultivated species are 1978a). important for transferring desired QTL Linkage maps are important for alleles to cultivars and/or advanced various purposes such as the detection breeding lines. and localisation of quantitative trait loci. Wild barley (Hordeum Linkage maps based on several crosses of spontaneum) is the ancestor of cultivated cultivated barley have been published

12 over the years (e.g. Becker et al. 1995, Co-dominant markers such as Qi et al. 1998, Yin et al. 1999). Also microsatellites (SSRs), as well as co- crosses between cultivated and wild dominantly scored AFLP markers can be barley have been used to construct used as anchors to integrate maternal linkage maps (Graner et al. 1991, Laurie and paternal linkage maps. et al. 1993, Pillen et al. 2000, Ramsay et In this study we have al. 2000). Even though wild barley has constructed the first linkage map from an been extensively studied, up to now no intraspecific wild barley cross using AFLP linkage map has been constructed based and SSR markers. on an intraspecific cross. The AFLP method (Vos et al. 1995) has become a popular tool for Material and methods linkage mapping. The markers obtained using this method are easily obtainable in Plant material large numbers, thus giving a genome A cross was made between a plant from wide coverage of markers within a accession 28-77 (‘Ashkelon’) and a plant relatively short time period. Their from accession 22-28 (‘Mehola’) of wild disadvantage is that they are mainly barley. The accessions were selected on dominant. This may cause problems in basis of their growth characteristics as assembling a linkage map if the well as their habitat locations in Israel population used is an F2. The problem (Van Rijn et al. 2000); Ashkelon is with mapping dominant markers in an F2 situated in the Mediterranean cost arises with markers that are in repulsion whereas Mehola is located in the Jordan phase. First, the recombination frequency Valley (Brown et al. 1978b; Figure 1 in of repulsion phase markers is estimated Chapter 3). Because of differences in with less precision than from coupling their environmental conditions, the two phase markers. Secondly, the maximum accessions were expected to differ likelihood (ML) estimator for repulsion considerably both phenotypically and phase markers is substantially biased genotypically. downwards whereas the ML estimator for The linkage map from this cross coupling phase markers is virtually was constructed to enable the mapping of unbiased. A detailed account of the QTL underlying a suite of growth-related problems with mapping dominant traits including RGR (initial relative markers in an F2 is given by Knapp et al. growth rate), SLA (specific leaf area), (1995) and Maliepaard et al. (1997). LAR (leaf area ratio) and photosynthesis These problems usually result in two rate. separate maps, a paternal and a maternal Eight F1 plants were self- one, each containing markers in coupling fertilised to obtain eight F2 sub-families. phase only.

13 To prevent outcrossing, which in E38M54 (Qi & Lindhout 1997) were ‘Ashkelon’ was observed to range from genotyped co-dominantly by Keygene 0.1% to 10.0% and in ‘Mehola’ from 0% B.V., Wageningen, The Netherlands. to 7.4% (Brown et al. 1978a), all spikes A set of 13 SSR markers were were bagged in paper bags at anthesis. A used (Ramsay et al. 2000; Liu et al. total of 233 F2 plants were grown and 1996). The primers were labeled with used as a mapping population. Because either IRD700 or IRD800 for Licor the structure of this mapping population sequencer (Li-Cor Inc., Lincoln, NE, was kept track of, F1 plants that were U.S.A.). Approximately 20 ng of template homozygous for any marker could easily DNA was used in PCR reactions which be traced and the F2 data could be consisted further of 1 x PCR buffer, 0.5 U corrected as appropriate (see ‘Data of AmpliTaq polymerase (Perkin Elmer Analysis’). Inc., Wellesley, MA, U.S.A.), 200µM DNA was isolated from two week dNTPs and 1 pmol of forward and reverse old leaves using the CTAB method primer. The reaction volume was 10µl. (Ausubel et al. 1999). Four different PCR programs were used for amplification as described by Ramsay et al. (2000). AFLP and SSR markers Seventeen primer combinations were selected: E33M54, E33M61, E35M48, Data analysis E35M54, E35M61, E38M55, E38M58, The AFLP markers from 17 primer E42M51 and E45M55 (Qi & Lindhout combinations were scored dominantly as 1997), E37M32, E37M33, E40M38, the absence or presence of an E41M32, E41M40, E42M32, E42M40 amplification product. The scoring was (Becker et al. 1995) and E31M55 (Table done by eye with the help of the program 1). The AFLP protocol was essentially as Cross Checker (Buntjer 1999). The described in Vos et al. (1995), with the markers from five primer combinations exception of diluting the secondary generated and scored by Keygene B.V. template only 10 times. The DNA was were scored co-dominantly using the double digested with the restriction QuantarTMPro software enzymes EcoRI and MseI. The EcoRI (http://www.keygene- specific primers were labeled with either products.com/html/index_products.htm), 700 or 800 nm infrared dye (IRD700, which enables a distinction between IRD800) for detection with a Licor heterozygous and homozygous state automated laser sequencer (Li-Cor Inc., based on band intensity. The AFLP Lincoln, NE, U.S.A.). In addition, markers marker names were designated from the generated by the primer combinations primer combination and size of the E32M61, E33M55, E39M61, E42M48 and

14 Table 1. List of primers and adapters useda.

Primers/adapters Sequences MseI adapter 5’-GACGATGAGTCCTGAG-3’ 3’-TACTCAGGACTCAT-5’ M00 (universal primer) 5’-GATGAGTCCATGAGTAA-3’ MseI +1 primer M02 M00 + C MseI +3 primers M32 M00 + AAA M33 M00 + AAG M38 M00 + ACT M40 M00 + AGC M48 M00 + CAC M51 M00 + CCA M54 M00 + CCT M55 M00 + CGA M58 M00 + CGT M61 M00 + CTG

EcoRI adapter 5’-CTCGTAGACTGCGTACC-3’ 3’-CTGACGCATGGTTAA-5’ E00 (universal primer) 5’-GACTGCGTACCAATTC-3’ EcoRI +1 primer E01 E00 + A EcoRI +3 primers E31 E00 + AAA E33 E00 + AAG E35 E00 + ACA E37 E00 + ACG E38 E00 + ACT E40 E00 + AGC E41 E00 + AGG E42 E00 + AGT E45 E00 + ATG a Full listing of primer nomenclature and sequences are to be found from: http://www.keygene.nl/html/nomenclature.htm

amplification product. SSRs were scored parental F1 plant was homozygous for that co-dominantly. particular marker. From this observation,

Inspection of the overall i.e. some F1 plants being homozygous and segregation data revealed that a large some being heterozygous for a particular proportion (36%) of the markers showed marker, we concluded that one of the significant distortion from their expected parents of our cross must have been segregation ratios. Many of these skewed heterozygous at such a marker locus. The markers yielded suspect estimates of consequence of neglecting this recombination frequency (ranging from heterogeneity of F1 plants would be 0.70 to 0.95) with non-distorted markers. twofold, i.e. (1) a severe distortion of A closer inspection of the data revealed segregation, and (2) a serious over- that some of the eight F2 sub-families did estimation of the recombination frequency not segregate for the majority of these between distorted and non-distorted severely distorted markers. A non- makers (Stam, unpublished results). This segregating F2 subfamily indicates that the is exactly what we observed in the overall,

15 complete, data set. distances. Before ordering the markers Having observed the above within each of the linkage groups, the data feature of the data and being aware of its were split into three sub-sets, i.e. (1) the consequences, we corrected the raw data dominant ‘Ashkelon’-specific markers, (2) as follows. Each marker was checked for the dominant ‘Mehola’- specific markers its segregation in each of the eight F2 sub- and (3) the co-dominant markers. For families. If a marker was non-segregating each of these sub-sets an ordering was in a particular sub-family, all the data for calculated within linkage groups, which that marker in that sub-family were could be used as a so-called ‘fixed order’ removed (set to “missing”). As a result of in the final merged data set. The reason to this correction, for many markers the first establish the marker order within majority of the data points were lost, paternal and maternal maps as well as for leaving insufficient linkage information to the anchor co-dominant markers is that reliably map them. Another consequence these sub-sets represent the most reliable of the correction is that some data were part of the linkage information in the data. removed not because of genuine non- The marker order in the merged map segregation, but because of non- should not be in conflict with the ordering segregation that occurred just by chance. in these constituent maps. Sub-family size ranged from 14 to 50 To assign the linkage groups to (average 29.1) so it is expected that in known barley chromosomes, SSR loci some small sub-families the observed (Ramsay et al. 2000) as well as AFLP non-segregation has been the result of markers in common with earlier maps genetic sampling rather than from several cultivated barley populations homozygosity of the parental F1 plant. L94 x Vada’ (Qi et al. 1998), ‘L94 x 115-6’ Because the correction described above (Lindhout, personal communication), also influences any genuine skewness of ‘Apex x Prisma’ (Yin et al. 1999) and segregation, such as might arise through ‘Proctor x Nudinka’ (Becker et al. 1995) some pre- or post-zygotic selection were used. mechanism, the corrected data leave little room for sensible interpretation of the remaining distorted segregation ratios. Results and discussion With the corrected data set a linkage map was constructed using the By using 22 primer combinations we algorithm described by Stam (1993), as obtained 348 polymorphic AFLP markers, implemented in the JoinMap 3.0 software of which 151 (43%) were scored co- package (Van Ooijen and Voorrips 2000). dominantly. The 13 SSRs were all Linkage groups were assigned using a LOD informative without further adjustment of threshold of 5.0. Kosambi’s mapping the original PCR conditions. However, only function was used to calculate map

16 five from the 13 could be scored without distributed over 11 linkage groups. Except problems. Two null alleles were for linkage group U1, each linkage group encountered as well as four alleles for contains both dominant and co-dominant which amplification was repressed by one markers. The co-dominant markers or two other alleles. Six SSRs were provided sufficient anchors to enable heterozygous in the Ashkelon and two in integration of the parental maps. The total the Mehola parent. map length equals 445 cM. This makes an The adjustment of the raw data average of 18 markers per linkage group, (see ‘Data Analysis’) revealed that the the range being from two to 36. The ‘Ashkelon’ parent must have been highly average distance between two markers heterozygous; 59% of the ‘Ashkelon’- was 2.2 cM. No gaps larger than 20 cM specific markers did not segregate in at between two adjacent markers were least one F2 sub-family. Heterozygosity observed. was less prominent in the ‘Mehola’ parent; The assignment of linkage groups 7% of the ‘Mehola’-specific markers did to barley chromosomes is based on AFLPs not segregate in at least one F2 sub- and SSRs that are in common with other family. linkage maps of cultivated barley (see After adjustment, 202 markers Table 2). Seven of the eleven linkage (56%) could be mapped without problems. groups could unambiguously be assigned The remaining ones (159) could not be to known barley chromosomes. Three mapped, mainly because they would not (groups 2A, U1 and U2) did not contain link to any other marker, as a result of the any common markers and one (group 6) large proportion of missing genotype contained markers that mapped to scores. Therefore, due to the different chromosomes in other mapping heterozygosity in at least one of the populations. Groups 2A and 6 were parents of this cross, about 45% of the tentatively assigned to chromosomes markers contained no useful linkage based on weak linkage of some markers information. that were eventually not mapped in our The linkage map is shown in population, but have been mapped in at Figure 1. It contains 202 markers least one of the other populations.

Figure 1. The linkage map of wild barley, Hordeum spontaneum. Assignment of linkage groups to barley chromosomes 1H to 7H as described in the text. Linkage groups U1 and U2 are unassigned. AFLP marker identifiers are composed of primer combinations and estimated length of the amplification product. Co-dominant markers are indicated in boldface, and markers used in identification of chromosomes are indicated in italics. Clusters of markers mapping to the same position (within 1 cM) are indicated by vertical bars to the left of clusters.

11 13 14 15 16 20 19 21 22 23 25 27 30 31 35 37 42 45 0 3 6

E42M40-299 E33M54-112 E31M55-130 E35M48-221 E35M48-473 E35M48-326 E38M55-380 E37M32-374 E42M51-280 E38M54-368 E38M54-368 E33M61-362 E33M61-362 E42M48-93 E37M33-409 E38M54-374 E38M54-374 E31M55-262 E35M48-563 E38M54-183 E38M54-183

E31M55-238 E38M54-655 E33M54-235 E38M58-84 E33M61-123

E33M54-203 E33M54-568 E39M61-116 E39M61-116 E42M48-174 E42M48-174 E42M51-220 E35M54-528

14 26 27 28 30 31 32 33 34 35 40 42

43 45 46 63 64 66 0 2

2A E33M55-418 E33M55-418 E42M48-282 E42M48-282 E45M55-115 E33M54-126 E38M54-486 E38M54-486 E33M54-518 E42M48-210 E42M48-210 E42M32-350 E33M55-436 E33M55-436 E33M54-326 E45M55-275 E32M61-382 E32M61-382 E38M54-169 E38M54-169 E45M55-465 E41M40-110 E35M61-129 E42M48-329 E42M48-329 E37M32-270 E38M54-71 E38M54-71 E39M61-315 E38M54-72 E38M54-72

E37M33-208 E38M54-371 E38M54-371 E38M54-107 E38M54-107 E33M61-180

12 16 23 28 31 33 37 46 51 0 9

2B E42M48-374 E42M48-374 E38M54-294 E38M54-294 E38M55-251 E38M55-251 E38M54-293 E38M54-293 E38M54-470 E38M54-470 E31M55-84 E35M48-91 E35M48-91 E33M55-157 E33M55-157 E33M55-156 E33M55-156 E42M32-335 E42M32-186

18 12 40 37 35 34 29 26 25 48 45 44 43 51 49 47 67 61 59 56 55 53 52 50 65 0 7

E42M48-171 E38M54-221 E38M58-160 E42M51-130 E38M54-236 E38M55-433 E39M61-238 E35M61-177 E41M32-450 E42M40-238 E38M58-142 E33M55-392 E38M55-510 E35M61-466 E42M48-120 E35M61-118 E33M55-140 E33M55-368 E33M55-235 E33M55-152 E35M54-370 E42M48-366 E33M55-346 E33M55-591 E41M40-445 E33M61-450 E42M51-245 E33M61-232

E33M61-340 E39M61-159 E33M55-372 E33M55-296

13 12 11 20 16 14 7 0 8

E42M48-261 E35M48-246 E33M61-469 Bmac0018 E45M55-417 E42M48-302 E33M55-294 E39M61-252 E38M54-349 E38M54-307

E42M48-301 E42M51-497 E42M32-484

14 18 16 15 13 12 10 27 24 20 36

7 4 2 0

E38M58-500 E35M48-513 E35M48-170 E33M61-370 E38M54-239 E33M55-290 E39M61-255 E33M61-221 E35M48-391 E33M55-537 E40M38-212 E40M38-445 E35M48-422 E42M32-196 E35M61-498 E42M40-411

E32M61-155 E39M61-228 E41M40-375

12 0 U1 E42M48-276 E39M61-232 9 5 3 0 U2 E33M55-338 E39M61-272 E38M54-335 E35M54-582 E39M61-271 E38M54-375

20 Table 2. The linkage groups, respective chromosomes, number of markers in linkage group, length of linkage group, the maps in which the chromosomes were based on and common markers linking the map of ‘Ashkelon’ x ‘Mehola’ to the other maps.

Linkage Hordeum No. of Length Assignment No. of group chromosome markers (cM) based on common markers 1 1 (7H) 28 45 L94 x Vada1 1 2A 2 (2H6) 25 66 see text 2B 2 (2H) 11 51 L94 x Vada1 2 L94 x 116-52 3A 3 (3H) 36 72 Lina x HS3 4 L94 x Vada1 3B 3 (3H) 6 24 Lina x HS3 1 4 4 (4H) 24 43 L94 x Vada1 2 Proctor x Nudinka4 5 5 (1H) 32 67 L94 x Vada1 2 6 6 (6H6) 13 20 Lina x HS3 see text L94 x Vada1 Prisma x Apex5 7 7 (5H) 19 36 L94 x Vada1 2 U1 -- 2 12 -- -- U2 -- 6 9 -- -- Total 202 445 14

1 Qi et al. 1998; 2 P. Lindhout, pers. comm.; 3 Ramsay et al. 2000; 4 Becker et al. 1995; 5 Yin et al. 1999; 6 Tentative assignment (see text) Linkage groups U1 and U2 remained ‘unassigned’.

The chi-square values for hampered the coverage we initially aimed goodness-of-fit ranged from 0.83 to 1.60 at. for the 11 linkage groups, indicating a We have estimated the good overall fit. Thus, even though the proportion of the wild barley genome current map had to be assembled by covered by the present map in the removing a substantial part of the data, following way. By repeated sampling of the remaining data still resulted in a markers, without replacement, from the reliable map that can serve as a basis for map we calculated the average map further linkage mapping and QTL length covered by a marker sample of mapping in wild barley. given size. Average coverage was based The linkage map presented in on 20,000 samples of given size. By this chapter covers only part of the wild increasing the sample size up to the barley genome. Although the total actual number of markers in the map and number of markers we used should, in by fitting an exponential curve to the principle, be sufficient to cover the relation between sample size and map genome, the unforeseen high degree of length covered, we estimated the heterozygosity of one of the parents has asymptotic upper limit to be

21 600

500

400 Map length covered map length covered length map 300

200 0 50 100 150 200 250 markers sampled

Figure 2. Map length covered by markers randomly sampled from the map. Fitting an exponential curve to the observations yields the estimate of the upper limit, 550 cM. approximately 550 centimorgans (see ‘Ashkelon’ parent is most likely due to a Figure 2; the validity of this procedure recent outcrossing event, which is known has been verified extensively using to occur in wild barley (Brown et al. simulated mapping data; Stam, 1978a). Because about 45% of the unpublished results.) Therefore, we markers could not be mapped, this estimate the total genome length that suggests that altogether the can be mapped with this population to be heterozygosity in both parents covers about 550 centimorgans. Of this some 45% of the genome. The following ‘mappable’ part we have covered a observations indicate that the outcrossing proportion of 445 / 550 = 81 %. must have occurred quite recently (in Assuming that the actual total map length terms of generations). First, of wild barley equals that of cultivated heterozygosity declines rapidly in a barley, i.e. about 1000 centimorgans predominantly self-fertilising population (e.g. Kleinhofs et al. 1993, Qi et al. 1998, and it could not be maintained at 45%. Yin et al. 1999, Ramsay et al. 2000), we Secondly, the heterozygosity cannot be infer that approximately 550 / 1000 = distributed over tiny linkage blocks, 55% of the wild barley genome can be dispersed throughout the genome. In that mapped with this population. case the ‘mappable’ markers surrounding The heterozygosity of the such small genomic segments would still

22 allow an almost complete coverage of the small to allow a detailed comparison of genome. Since the actual ‘mappable’ this wild barley map and maps of proportion of the genome was estimated cultivated barley. Nevertheless, for the to be approximately 55%, we conclude purpose of QTL mapping the present map that the ‘unmappable’ part must be enables a comparison of chromosomal concentrated in fairly large linkage locations of QTLs (Elberse 2002, Poorter blocks, rather than being dispersed over et al. 2004, Verhoeven et al. 2004b). tiny segments. This in turn is in agreement with a recent outcrossing Acknowledgements event, because heterozygosity of large We wish to thank Peter van Tienderen for genomic segments would rapidly break his stimulating discussions. The fruitful down into small segments over co-operation with Keygene B.V is generations. Thus we conclude that our gratefully acknowledged. The Earth and linkage map has fairly large gaps that Life Science Foundation (ALW) which is cannot readily be filled by additional subsidised by the Netherlands’ markers. Organisation for Scientific Research Although seven linkage groups (NWO), financially supported this study. could unambiguously be assigned to barley chromosomes, the number of markers shared between the current map and other linkage maps of barley is too

Chapter 3

Noo, we turn tae 'John Barleycorn. Thou king o' grain.' It's the unique growin soil, an' the ancient still An' the generations o' skilled craftsmen That mak Scotch whiskey the 'soul o' plays an pranks' Add tae that the pure, peaty, heilan water An' ye hiv the recipe fur the barley-bree Tae sample at yur will an 'forget yur loves or debts'. Shame! The secret o' Whiskey is oot! H Marshall (http://www.it-serve.co.uk/poetry/Worst/secrets.php)

Environmental, phenotypic and genetic variation of wild barley (Hordeum spontaneum) from Israel

T.K. Vanhala, C.P.E. van Rijn, J. Buntjer, P. Stam, E. Nevo, H. Poorter & F.A. van Eeuwijk Euphytica, in press

Abstract Wild relatives of crop plants offer an attractive gene pool for cultivar improvement. We evaluated genetic and phenotypic variation for a set of 72 Israeli accessions of wild barley from 21 populations. These populations were grouped further into four ecotypes. In addition, environmental variables describing the local conditions for the populations were used to infer the environmental divergence. Genetic, phenotypic and environmental distances were estimated from the data and UPGMA dendrograms constructed. The results showed that genetic variation was larger between populations than within them, whereas for phenotypic measurements variation was larger within populations than between them. No significant correlation was found between genetic and phenotypic similarities, or between phenotypic and environmental similarities, whereas a weak correlation between genetic and environmental similarities was detected. Twenty-three AFLP markers were identified to be ecotype-specific. Chromosomal location was known for five of these markers. Four of the five ecotype-specific markers were correlated with both phenotypic traits and environmental variables.

Introduction secondary habitats are found in Israel (Nevo 1992). The level of genetic Wild barley, Hordeum spontaneum variation of H. spontaneum in Israel has (C.Koch) Thell. is a progenitor of been estimated using phenotypic cultivated barley (Hordeum vulgare L.) characters, isozyme loci, and different (Harlan & Zohary 1966). It is a diploid PCR-based molecular markers (e.g. and mostly inbreeding annual, which Brown et al. 1978b; Nevo et al. 1979, grows in a wide range of habitats in the 1984, 1998; Baum et al. 1997; Pakniyat eastern Mediterranean and in Southwest et al. 1997; Turpeinen et al. 2001). All Asia. The majority of the primary and these studies concluded that genetic

26 variation in wild barley is substantial. This traits are more or less directly influenced large genetic variation of wild barley and by the environment, while molecular the fact that it can be crossed with markers are potentially numerous and cultivated barley to produce fully fertile are influenced only indirectly by hybrids make it attractive for cultivar environment, if at all (Ayele et al. 1999). improvement. In this study we have estimated There are several molecular the genetic variation in wild barley tools for estimating genetic variation. populations from Israel using AFLP AFLP is a method that has become widely markers. Variation was also estimated applied in plant population genetics since from phenotypic data as well as its development in 1995 (Vos et al. environmental variables from the same 1995). Compared to other methods, the populations. For each type of major advantages of AFLP lie in its high characterisation the pattern of variation diversity index and the number of was studied to see whether these differ markers per assay unit (Russell et al. among the populations. Subsequently, 1997). In addition, AFLP markers are the correlations between the various reproducible and exhibit intraspecific characterisations were studied in order to homology (Rouppe van der Voort et al. detect any general adaptations of the 1997). populations to their environment. Finally, Phenotypic characters can also associations were studied between be used to estimate the variation within individual markers, phenotypic traits and and between populations. Studies on the environmental variables. This was done correlation between molecular marker to find out whether there are any and phenotypic distance measures have correlations between markers from a revealed weak or no association (Pigliucci specific part of chromosome and et al. 1991; Burstin & Charcosset 1997; phenotype or environment. Schut et al. 1997; Autrique et al. 1996; Ayele et al. 1999; Palacios et al. 1999). There are several explanations for these observations. One of them is that phenotypic data sets are usually limited in number of traits measured and these

from Israel. of populations for 21 as percentages frequencies of accessions per population and ecotype, and AFLP band and names, number abbreviations ecotype and 1. Population Table S Steppic and Marginal Steppic S E Mhl 29 51 32 38 17 3 4 17 30 3 3 24 3 23 3 Nahal Oren South 28 Tel Shoket 3 Mehola 3 4 40 terraTabigha rossa basalt Tabigha 3 4 4 Tabigha NOS 1 TS Mount Hermon ME 3 TATR 4 TAB 3 Nahal Oren TA North Bar-Giyyora MH Shechem 2 Maalot Mount Meron NON BG SH MA C MM Atlit Akhziv CA AT AZ ZHerz HZ CCoastalpo Plain1726 Q Aheo 34 4 Ashqelon AQ DDesert 1536 MMedi H Yrhm414 37 39 34 4 4 4 3 Yeroham Revivim Sede Boqer Wadi Qilt YH RV SB WQ Ec ab oty brev pu la pe ti ia a on t io nd n

population Mediterranean Ec oty aes te pe liyy ra425 4 area rra and a419 ne n1 32 18 an accessions 232 22 Number of Number H. spontaneum and population and frequencyBand (%) per ecotype

T populations of 2000). able 2. Phenotypic traits and their units measured in 21 measured units and traits their 2. Phenotypic able hsooia eaiegot aemg/g/day Relative growthrate Physiological related T mea hmclChlorophyll Chemical Biomass allocat Biomass opooia edms mg Seed mass Morphological ype su of r eme nt H. spontaneum io n htsnhssprui efms nmol/g/s Photosynthesisper unit leaf mass efms rcing/g massLeaf fraction efae ai m Leaf arearatio ecnaeo eprto % Photosynthesis per unit leaf area respiration of Percentage ho eprto nmol/g/s Shoot respiration pcfcla ram area leaf Specific tmms rcing/g massStem fraction soi oeta MPa mg/g concentration Organic acid Osmotic potential Tr otrsiainnmol/g/s Root respiration otms rcing/g fraction Root mass abncnetainmg/g mg/g mg/g Nitrate Carbon concentration Nitrogen concentration Mineral concentration ae otn fro g/g g/g Water content of root stem of content Water Wat efwdhmm width Leaf thickness Leaf angle Leaf / ai g/g C/N ratio egtcm tillers of Number epidermis of Thickness Height rai irgnmg/g Organic nitrogen ai tU er c ocnrto mg/g concentration neto efg/g ontent of leaf from Israel (Van Rijn et al µ µ µ µ ° mol/m mol/m m m . ni 2 2 /kg /kg t 2 2 /s

28 Materials and Methods DNA isolation and AFLP method

Four to ten plants were grown per Accessions accession for DNA isolation. Young leaves Twenty-one wild barley (Hordeum were collected from two-week old plants. spontaneum (C.Koch) Thell.) populations, The samples were stored at -80°C. DNA containing two to four accessions each was isolated from 200-300 mg of frozen (Table 1), were used in this study. The leaves according to the CTAB protocol populations were collected from 18 (Ausubel et al. 1999). locations in Israel between 1974 and An AFLP protocol was used as 1978 (Nevo et al. 1979, Figure 1). Based described in Vos et al. (1995). DNA was on ecological and geographical data, Van digested with restriction enzymes EcoRI Rijn et al. (2000) grouped these and MseI. AFLP bands were visualised by populations into four ecotypes (Table 1). radioactive [γ33P]-ATP labelling. Scoring was done by eye, and all clear bands with lengths between 80 and 500 nucleotides were included. In total 11 primer combinations previously tested with cultivated barley (Qi & Lindhout 1997) were used: E32M61, E33M55, E33M58, E35M48, E35M55, E35M61, E38M54, E38M55, E39M61, E42M51, and E45M55.

Phenotypic measurements Phenotypic data were obtained from a study by Van Rijn et al. (2000) in which a total of 30 traits were measured for 72 accessions, including physiological, biomass allocation -related, chemical and morphological characters (Table 2). Plants were grown and measured under Coastal Plain close-to-optimal conditions in a growth Mediterranean Steppic and marginal Mediterranean chamber. Desert Environmental data Environmental data were obtained from Figure 1. Map of Israel with geographical locations of 21 populations Nevo et al. (1985). It included of H. spontaneum. For population geographical, temperature, rainfall and abbreviations see Table 1. humidity data (Table 3).

Table 3. Environmental data for 21 populations of of populations 21 for data Environmental 3. Table mean annual evaporation (Ev). These environmental data are from Nevo et al. (1985). index (Th) and moisture Thornthwaite’s (Dw), in summer nights dewy of number (Hua), mean annual humidity mean (Hu14), hours at 14:00 humidity mean include measures humidity (Rd); days rainy of number mean and (Rn) annual rainfall mean include measurements rainfall (Trd); days tropical of number and mean and (Sh) days dry number hot mean (Tdd), of difference temperature temperature mean day-night differenceseasonal (Td), (Tj), mean in January (Ta), mean temperature in August temperature (Tm), mean annual temperature mean include measures temperature (Alt.); altitude (Lat. N) and north E), latitude Q3.03.35 02 41 02 0443 47 53 120 30 55 72 64 38 424 80 20 10 13 14 27 20 50 31.63 34.60 AQ Z3.03.51 02 21 03 5605 06 91 130 10 59 67 60 56 620 15 30 10 13 12 26 20 10 33.05 35.10 AZ B3.83.7401 691 3- 0 11 65 05 168 -- 50 -- 163 70 -- 50 160 53 160 -- 36 -- 55 30 30 15 59 -- 58 58 -- 58 45 91 -- 57 32 57 690 100 45 45 -- 133 45 280 -- 45 59 -- 100 10 -- 436 -- 13 436 60 75 120 120 690 15 -- 12 72 60 60 -- 65 9 -- 15 10 10 48 -- 26 11 11 17 17 500 -- 19 24 490 26 15 15 0 19 30.98 -- 450 19 32 32 34.90 30.87 30 11 75 24 375 24 34.78 24 32.43 9 31.32 YH 35.02 34.92 0 19 0 13 SB 32.90 32.90 13 75 35.53 NOS 35.53 TS 26 32.43 35.02 20 TAB TA 50 NON 32.70 35.2332.23400SH 34.95 34.8032.1725HZ AT 18249 2026131310200 1510700 618 530 4546604210160 5065727530130 abbr. V3.53.2302 71 51 -10101 85 55 170 50 65 160 55 38 160 30 18 no 58 130 60 57 155 130 45 58 50 45 -- 52 50 70 436 14 1600 61 120 15 49 60 0 65 10 10 1010 80 27 17 0 20 6 15 85 19 320 32 31.02 8 1 24 34.75 16 20 0 11 6 RV 32.90 1530 22 WQ 35.3831.8350 35.53 33.28 14 35.75 ME 35.4832.13-150223013171368183270TATR 1150 33.05 MH 35.40 MA 35.2733.00500MM 34.9032.5010CA 2330141613110125170 17238 202613139 1510680 2210539 785 3240552550180 5550645510150 3934532250180 4865727510130 P B A

opulat 50 17 6 72 01 07 3 34 15 0155 10 58 61 49 43 537 75 80 9 15 10 26 17 760 31.72 35.08 G eae3.43.4231 61 51 86 2 25 15 1154 31 57 61 50 42 520 67 58 10 15 11 26 19 293 32.24 35.14 verage

io n

Lo Ge ng og r ELat. Alt N ap

T hy

(m)

( Tm 92 01 3- 0 3 83 36 0168 50 65 53 35 18 130 100 -- 13 16 10 26 19

emp C)

e ra (°C) Ta ueR ture

H. spontaneum (°C) Tj

(°C) Td

(°C) T from Israel. Geographical data include longitude east (Long. dd

# # Trd

(mm) Rn ainf

Humidity all

# Rd

14 Hu

Dw Hua

Ev Th

30 Statistical methods As a formal addition to the Genetic distances were calculated from graphical comparison of genetic, the AFLP data following the Jaccard phenotypic and environmental similarities distance (Gordon 1981). Phenotypic in the form of dendrograms, Mantel tests distances were calculated as Euclidean were carried out to produce correlations distances and environmental distances and corresponding permutation tail- were calculated as simple matching probabilities (Manly 1997). (Gordon 1981). Phenotypic and Simple band frequency was used environmental data were standardised as a measure of gene diversity for AFLP using normal distribution to have mean data. The closer to 0.5, the higher the zero and a standard deviation of 1 (z=(x- diversity. For ecotype gene diversity µ)/σ, where x is the observed measures, all the accessions within the measurement, µ is the estimated mean of populations of the respective ecotypes the trait and σ is the estimated standard were pooled and band frequency deviation of the trait). Longitude and estimated. AFLP markers were defined as latitude were left out from the distance specific for an ecotype, when band calculations. These distance calculations presence/absence was above 0.60 in one were performed with the program ecotype, while below 0.40 in other PhylTools (Buntjer 2001). ecotypes. For the genetic, phenotypic and Pearson correlations were environmental distances, an average calculated between previously mapped linkage, or unweighted pair-group AFLP markers and phenotypic method using arithmetic averages measurements. These markers were (UPGMA) dendrogram (Nei & Kumar mapped in a wild barley (Chapter 2) or 2000) was constructed. Bootstrapping cultivated barley (Qi et al., 1998) (n=100) was performed to evaluate the mapping populations. As AFLP-markers robustness of the branching points using are biallelic the Pearson correlation Phyltools (Buntjer 2001). The Neighbor coefficient is the equivalent of a t-test on and Consense programs from the Phylip the phenotypic trait using the presence or (Felsenstein 1993) program package absence of the marker as classification were used to construct the dendrograms criterion. that were subsequently visualised using Treeview (Page 1996). Bootstrap values, as percentages of how many times a specific branching point occurred among the 100 resampled trees, from a consensus tree were added into the original tree provided the branching point was the same and the value >50%.

31 Results and Discussion variation between populations (Figure 2a). The original choice of ecotypes is A total of 737 AFLP-markers were scored reasonably supported by the using 11 primer combinations. Of these dendrogram. 637 (85%) were polymorphic over all The coastal populations form the accessions. The largest variation was most distinct cluster in the dendrogram. observed within TS (51% band The populations CA, HZ and AT are presence), a steppic population in the located between Tel Aviv and Haifa (i.e. northern Negev Desert, and the smallest geographically close, Figure 1). They within the AZ (1 % band presence), a form the most robust cluster. The other northern coastline population (Table 1). two coastal populations AZ and AQ are further away (north from Haifa and south Environment from Tel Aviv, respectively) both Environment is the directing force that geographically and environmentally, but influences the plant populations in the still grouping together with the other nature. The breeding success of a plant coastal populations. High humidity, low depends on how it can adjust to different evaporation and high number of dewy environments and grow and reproduce nights are characteristic for the coastal optimally. A plant growing in an ecotype. There are no altitude environment, which is changing differences. dramatically, whether predictably or not, Populations belonging to the will need to have more variation Mediterranean ecotype (MA, MM, SH and genetically to be able to adjust and BG) do not cluster together in the survive. A stable environment, however, dendrogram. However, they form two will not put as much pressure on the pairs: MA and SH form one pair and MM plant for it to maintain as much genetic and BG form the other. Although the variation as the plant living in an unstable Mediterranean populations are not environment. Israel is environmentally geographically close and vary greatly in very diverse and therefore the wild barley their altitude, the climate in this ecotype populations growing in Israel are of great is average compared to the environment importance for the possible use in barley of the other populations. If soil type and breeding. plant community measures (Nevo et al., The populations used in this 1985) were taken in consideration, these study were divided into ecotypes by Van populations clustered together (data not Rijn et al. (2000). To verify this grouping shown). Thus the Mediterranean ecotype we calculated simple matching distances is not defined only by altitude, from the environmental data and used a temperature, rainfall and humidity but dendrogram to visualise the pattern of also by soil type and plant community.

MM 100 BG

MA 51 SH

TAB

TA 100

TATR

74 AZ

57 HZ

71 AT 87 CA

77 YH

ME 64 WQ

NOS

99 NON 0.1

2a.

Figure 2. UPGMA dendrograms of H. spontaneum populations and accessions from Israel. Bootstrap values (%) for each branch point are indicated if they are >50%. a) Simple matching distances calculated from environmental data of each population, b) Euclidean distances calculated from phenotypic data of each accession, and c) Jaccard’s distances calculated from AFLP markers of each accession. For population abbreviations see Table 1.

33 The desert populations form Phenotype their own ecotype, which is very distinct Phenotypic traits are the most important environmentally from the coastal and target for conventional breeding. Wild Mediterranean ecotypes. In fact it is quite species do not always seem to offer the opposite of the coastal ecotype, phenotypic variation that would improve experiencing the lowest humidity and the qualities of the crop species. highest evaporation. The number of dewy However, even if there has not seemingly days is high, because of the high been useful phenotypic variation for temperature difference between day and breeding purposes in the wild species, night in the desert. sometimes further research has proven The least definable populations this first observation wrong. A clear are the ones belonging to the steppic and example is the introgression of wild marginal Mediterranean ecotype. Based tomato alleles to improve the tomato on the environmental data, MH and cultivars (Tanksley & McCouch, 1997). Tabigha-location -populations cluster Phenotypic variation in wild barley has among the Mediterranean ecotype. TA been studied vigorously and these studies has characteristically high temperatures. have been concentrating on the traits The steppic populations ME and TS have that would benefit the modern cultivars. an environment similar to the desert This study focuses on the variation found populations. The two slopes of Nahal within and among different growth Oren cluster together with steppic TS. related traits. The environmental data here do not Van Rijn et al. (2000) initially distinguish between the two different observed that the phenotypic variation in slopes; microclimatic data would be the traits (except in seed mass, leaf needed to do this. thickness and leaf width) was larger Thus, the wild barley populations within populations and accessions than in Israel are divided into groups based on between them. These results were further their environment. Clear groups are visualised by the dendrogram (Figure 2b) coastal, desert and Mediterranean in the present study. ecotypes, especially if soil type and plant In the dendrogram, the communities are taken into account, populations do not cluster according to while the fourth ecotype steppic and their ecotypes. The phenotypes of the marginal Mediterranean is only a loose accessions from the Mediterranean group. If the environment, in the broad population MM cluster closest together. sense, has had a strong influence on the Coastal population HZ clusters mostly phenotypic and genetic variation, the together as well, although the bootstrap same pattern should emerge from the values are not particularly high. following results. Accessions from the other populations seem to cluster randomly. Overall the

RV SB RV MM MM 99 MM NON NON MM YH YH TA 55 BG MA HZ MH MA AQ AQ SB AQ TS HZ HZ HZ CA 65 CA

57 MA 65 CA 59 MA CA MH AT AZ 85 SB SB ME AQ ME ME TA BG TA 51 BG RV 61 RV TATR TATR YH BG 60 NON TAB YH TATR NOS TAB NOS TAB 80 NOS AT SH TS 74 SH TS SH TS WQ WQ WQ MH AZ 60 0.1 AT

2b. figure 2 continued

35 bootstrap values are not very high, which between populations than within them. demonstrates again the earlier results of This was visualised in the dendrogram Van Rijn et al. (2000). The phenotypic where accessions were grouping mainly data were measured under close to according to their populations (Figure optimal conditions, and only three 2c). No distinctly clear groupings of all morphological traits were more different accessions within their ecotypes occurred. between populations than within them Coastal accessions formed a group with (Van Rijn et al. 2000). This means that only AZ and AT accessions missing from under optimal conditions the populations the ecotype group. This reflects quite well do not differ much from each other and the associations of these coastal that the population specific adaptations populations relative to their environment. might be disguised. The desert populations YH and SB formed also a distinct group as well as the Genotype steppic populations from the Tabigha- The variation in phenotypic traits is based location including accession from MH and on the variation and interactions on the TS. Mediterranean populations MM and genotypic level of the plant as well as on MA were the most uniform overall, the pressures that the environment although coastal population AZ was the places on the plant. Breeding decisions least variable according to band based at least partly on genotypic frequency. information offers faster and possibly As expected from the more durable solutions than conventional contrasting pattern of variation for breeding through phenotypic selection. phenotypic and genotypic similarities, However, in order to get to the point there was no correlation between these where genotypic information can be two types of similarity. reliably and efficiently used in breeding, The coastal ecotype was in much basic research is needed. general less variable than the other Populations from diverse environments ecotypes (Table 1). This is also seen from such as the wild barley from Israel are the clustering of the populations within very useful for such research, because of the ecotype in the dendrogram. The the selection pressures the environment distinct environment in the coastal plain imposes upon them. In this paper we might have an influence on this lower have genotyped 72 accessions originally genetic variation detected. According to collected from 18 locations in Israel, in Nevo (2001), the genetic variation is order to compare the variation detected higher in drier and more stressful with the variation observed in the environments and lower in areas with environment and the phenotype. optimal conditions. Plants do not survive In contrast to the phenotype, in unpredictable environments without a the genotypic variation was larger wider genetic background, whereas in

36 TA TS MH 100 TA 100 TA 62 TAB TATR 100 TATR 100 74 TATR TAB 56 TAB NON 100 NON MH 100 MH MA 50 MA 100 MA 91 MA TS 55 TS 67 WQ RV 90 RV 87 RV 86 63 RV MM 100 MM 71 MM 99 MM AZ 100 AZ TS SH 95 SH 100 SH HZ 100 HZ 70 HZ 99 53 HZ AQ 94 AQ 82 AQ CA 100 CA 100 CA 100 CA NON AQ 94 99 SB AT NON 90 76 NOS NOS AT 66 AT BG 100 BG 88 BG 90 BG WQ 83 WQ YH 99 YH 100 YH 97 YH SB 95 SB 100 SB ME 100 ME 89 0.1 ME

2c.

figure 2 continued

37 areas of stable environment they do not mapped markers with a certain ecotype have to maintain large genetic variation. (Table 4). Of the five mapped markers In general, the results indicate higher two were mapped on chromosome 5 genetic variation in climatically more (1H). One of these two (E35M48 433) stressful environments both regionally was associated significantly with several across Israel and locally at Evolution phenotypic data and highly significantly Canyon (populations NOS and NON). (p<0.001) with the rate of However, even though the coastal photosynthesis per leaf mass (Van Rijn ecotype shows the least variation (26%), 2001). The slender desert ecotype, in populations AQ and especially AT have a contrast to the robust Mediterranean much higher variation (34 and 40% ecotype, with significantly lower band respectively). When looking at the frequency of E35M48 433 has on average variation of the populations within each the thinnest and narrowest leaves, ecotype, the least variable populations lightest seeds, highest photosynthesis, are within Mediterranean ecotype, and fastest relative growth rate (data not although as an ecotype it is more shown). High photosynthetic capacity has variable, reflecting the bigger differences earlier been associated with dry between the different populations within environments in wild emmer wheat in it. The coastal population AT is in fact just Israel (Nevo et al. 1991). The marker a bit more variable than the desert E35M48 433 is also associated highly populations SB and RV or the steppic TA. significantly (p<0.001) with longitude, This implies that AT has retained its latitude and mean annual rainfall and variation in spite of the more optimal significantly (p<0.05) with mean climate. However, there are neither humidity at 14:00 hours (data not microclimatic data from the actual shown). collection sites nor data about the The desert accessions are fluctuations of the climate between years. grouped relatively closely together These data would help us to understand (except the accessions of WQ), which what are the real pressures the would account for the association of the environment is imposing on the marker with the geographical co- populations. ordinates without altitude (the ecotype Many studies have detected does not differ in the altitude). Mean associations between individual markers annual rainfall and mean humidity at and environmental factors in wild barley 14:00 hours were both positively (e.g. Nevo et al. 1979; Ivandic et al. associated with presence of a band in the 2002). We have approached this matter marker E35M48 433. Thus lower band from a slightly different angle and looked frequency in the marker E35M48 433 in for ecotype-specific markers. We were the desert ecotype mirrors these able to associate 18 unmapped and five environmental factors common in deserts

38 Table 4. Ecotype specific AFLP markers of wild barley, Hordeum spontaneum, from Israel.

Marker Frequency of present allele Map Association with name position traitsc C M S D E32M61 210 0.65 0.00 0.09 0.33 - E32M61 235 0.65 0.11 0.18 0.20 - E33M55 230 0.65 0.67 0.27 0.67 chr. 4, oa 49 cMa E33M55 238 0.18 0.61 0.32 0.20 - E33M55 398 0.65 0.33 0.18 0.20 - E33M58 394 0.12 0.33 0.27 0.67 - E33M58 395 0.82 0.67 0.64 0.33 - E33M58 490 0.94 0.89 0.32 1.00 - E35M48 246 0.65 0.39 0.95 0.80 chr. 6, lmf 11 cMb E35M48 433 0.65 1.00 0.73 0.27 chr. 5, d, c, e, lt, m, pa, 111 cMa pm, rgr, lw, sm, a E35M55 410 0.18 0.61 0.05 0.27 - E35M55 87 0.65 0.28 0.91 0.67 - E35M61 104 0.24 0.67 0.73 0.80 - E35M61 160 0.88 0.67 0.32 0.93 - E35M61 216 0.65 0.22 0.36 0.13 - E38M54 128 0.35 0.33 0.64 0.13 - E38M54 221 0.65 0.61 0.23 0.67 chr. 5, 7 cMb E38M55 423 0.35 0.28 0.27 0.67 - E42M51 101 0.18 0.72 0.18 0.33 chr. 2, m, rmf, smf, wl, 141 cMa ws, lw, sm, a E42M51 159 0.65 0.33 0.27 0.07 - E42M51 325 0.18 0.61 0.18 0.27 - E45M55 112 0.88 0.39 0.82 0.67 - E45M55 343 0.88 0.67 0.32 0.93 - Total 6 7 6 4 5 aQi et al. 1998 bChapter 2 cVan Rijn 2001 Their name, frequency in each ecotype, map position (if known) and possible association with traits. Associations with traits were calculated using Pearson correlation coefficient. Traits are oa = organic acids, lmf = leaf mass fraction, rmf = root mass fraction, smf = stem mass fraction, d = density, c = carbon content, e = epidermal thickness, lt = leaf thickness, m = mineral content, pa = photosynthesis per leaf area, pm = photosynthesis per leaf mass, rgr = relative growth rate, lw = leaf width, sm = seed mass, a = leaf angle, wl = water content of leaf, ws = water content of stem.

(low humidity and rainfall) providing a ecotype. These markers may well be straight link between genotype, associated with genes or QTL, which are phenotype and environment. in some way advantageous in the given In any case, it is not likely that environment. A study to find QTL for random genetic drift has lead to the near drought resistance in wild and cultivated fixation of these 23 ecotype specific barley cross has been conducted in Israel alleles, because this fixation of alleles is (Huang et al. 2001). It would be proceeding into the same direction across interesting to see if there are any all the populations within a given correspondences between the QTLs found

39 and the location of the marker E35M48 plotted against each other, genotypically 437 on chromosome 5. similar accessions were also phenotypically similar whereas General conclusions genotypically distant accessions were We have analysed in total 72 accessions phenotypically either similar or distant, from 21 populations of wild barley across the data points thus forming a triangular Israel both phenotypically and shape between the two axes in a genetically. Including environmental data, diagram. This type of relationship has we set out to compare the patterns of been observed in other crops as well variation of these accessions and (Burstin & Charcosset 1997). populations in order to detect any general Wild barley belongs to the adaptations of the populations to their primary genepool of cultivated barley environment. together with the landraces of barley The environment differs between (Van Hintum 1994). These wild groups of populations, where these accessions carry an important amount of environmental groups were designated genetic variation, which is vital for the here as ecotypes. The ecotypes do not improvement of modern cultivars with, as exhibit special phenotypic features but a result of domestication and breeding, they do contain ecotype-specific alleles narrowed genetic backgrounds (e.g. Nevo close to fixation. The genotype is 1992; Nevo 1998). One of the main furthermore loosely connected to targets in barley improvement is abiotic environment, as revealed by clustering of stress tolerance to enhance crop populations to their ecotypes. Multi- reliability (Ellis et al. 2000). Before wild marker genotypes do not reflect multi- accessions can be utilised, they have to trait phenotypes (no correlation between be studied in detail. The collection from genotypic and phenotypic similarities). the Fertile Crescent, where Israel However, if a specific trait is selected, contains the most variable populations correlations are found between the trait (Nevo 1998; Ivandic et al. 2002), is an and specific markers. Also, correlations obvious choice for such studies, because exist between distances calculated from it is the centre of diversity as well as the certain groups of traits, like origin of barley domestication (Badr et al. morphological or physiological traits, and 2000). Only Jordan has high genetic distances calculated from all markers diversity of wild barley similar to Israel (data not shown). Across selected (Baek et al. 2002). (mapped) markers and phenotypic traits, the genetic and phenotypic distances exhibited a triangularly shaped relationship (data not shown), i.e. when genetic and phenotypic distances were

40 Acknowledgements This study has been funded by the Earth and Life Science Foundation (ALW) which is subsidised by the Netherlands’ Organization for Scientific Research (NWO). E. Nevo would like to thank the Ancell Teicher Foundation of Molecular Genetics and Evolution for financial support.

Chapter 4

Let husky wheat the haughs adorn, An' aits set up their awnie horn, An' pease and beans at e'en or morn, Perfume the plain: Leeze me on thee, John Barleycorn, Thou king o'grain!

On thee aft Scotland chows her cood, In souple scones, the wale o'food! Or tumbling in the boiling flood Wi' kail an' beef; But when thou pours thy strong heart's blood, There thou shines chief.

Robert Burns

Association of AFLP markers with growth- related traits in Hordeum spontaneum

Tytti K. Vanhala1, Cynthia P.E. van Rijn1, Eviatar Nevo, Hendrik Poorter, Fred A. van Eeuwijk & Piet Stam 1 These authors contributed equally

Abstract In this chapter, quantitative trait loci (QTL) as identified within a specific cross between two wild barley (Hordeum spontaneum) populations are compared with marker-trait associations assessed across a set of 81 wild barley accessions. The accessions were measured for 33 traits related to growth, C and N economy as well as plant morphology. The accessions were genotyped for 68 AFLP markers, mapped earlier in cultivated barley as well as in wild barley. Of the 68 markers 60 had significant correlations to one or more traits. Marker-trait associations supported several QTL detected earlier. For relative growth rate, two out of four QTL were supported. Four markers related to photosynthetic rate per unit leaf area were mapped on chromosome 4, where also the QTL for photosynthetic rate and stomatal conductance were found. One of these markers was also related to chlorophyll content, suggesting that this location on chromosome 4 might be very important for photosynthesis-related traits. One QTL was detected for specific leaf area on chromosome 7. This QTL was supported by the only marker-trait association for specific leaf area. Markers on chromosome 1, 2 and 4, were strongly associated with leaf thickness, leaf width and seed mass, suggesting that these traits are genetically linked. An alternative to the classical Bonferroni correction for controlling the false discovery rate in multiple testing is discussed and applied to the test results. This leads to a less stringent significance threshold for individual tests than the Bonferroni-based correction.

Introduction fraction (LMF, leaf mass per unit of plant mass) (for a review see Poorter & Van de Plant species differ considerably in their Werf, 1998). A range of physiological, potential relative growth rate (RGR, net chemical and morphological traits is increase in biomass per unit biomass correlated with the potential RGR of a already present per unit of time) with plant (Lambers & Poorter, 1992). plant species from fertile habitats Wild barley (H. spontaneum), showing much higher RGRs under optimal the progenitor of cultivated barley is conditions than those from infertile widely distributed in the Fertile Crescent habitats (Grime & Hunt, 1975; Poorter, (Zohary & Hopf, 1988) and occupies a 1989). These differences in RGR are wide range of different habitats (Nevo et mainly due to variation in specific leaf al. 1979). The populations collected from area (SLA, leaf area per unit leaf mass) around the Fertile Crescent are and to a lesser extent due to leaf mass genetically divergent (for a review see

44 Nevo, 1992; Forster 1999). The species In this study, AFLP markers were also shows large morphological and associated with the variation in growth physiological variation which can be traits in H. spontaneum populations and related at least partly to the compared with the QTL found by Poorter ecogeograpical origin of the populations et al. (2004). studied (e.g. Nevo et al. 1986b; Forster 2000; Chapter 3). The variation in physiological Material and Methods and morphological growth traits within and among populations from Israel has Plant material been determined under standardised, Eighty-one wild barley accessions controlled conditions (Van Rijn et al. grouped in 21 populations from a wide 2000). Two accessions of these range of locations in Israel, were used in populations, divergent for growth-related this study. The populations along with traits, were crossed and an AFLP marker available climatic data of the locations are map was constructed (Chapter 2). listed in Chapter 3. Growth-related traits were measured on Seeds were germinated on the offspring (F3-lines) and quantitative moistened filter paper on Petri dishes at trait loci (QTL) were detected (Poorter et 6°C and an irradiance of 10 µmol m-2 s-1. al. 2004). After one week seedlings were An alternative way of linking transferred to a white beach sand filled genetic markers to traits is analysis of container with drainage holes. The sand marker-trait associations in a set of was saturated with half strength of the accessions or populations (Pakniyat et al. following nutrient solution: 603 µM

1997; Forster et al. 2000). Using a set of Ca(NO3)2 , 795 µM KNO3 , 190 µM wild barley accessions instead of a KH2PO4, 270 µM MgSO4, 0.2 µM MnSO4, mapping population of a cross between 0.9 µM ZnSO4, 20 µM H3BO3, 0.3 µM two parents has a number of advantages. Na2MoO4, 40 µM Fe-EDTA, 40 µM FeSO4

First, there is no need to develop an and 47 µM SiO2. The container was experimental cross. Second, the observed placed in a growth room for five days in associations are not limited to a single the following conditions: 14/10 h cross (Kraakman et al. 2000), which day/night, 20°C day/night, irradiance of enables evaluation of a much wider 450 ± 25 µmol m-2 s-1, relative humidity germplasm. A third, related advantage is 70%. Thereafter seedlings were that screening of a wider range of transferred to 33 L tanks containing the genotypes minimises the risk run in QTL nutrient solution described above, experiments that both parents by chance aerated and at full-strength, which was have the same allele for a number of replaced weekly. The pH of the nutrient traits (Kraakman et al. 2000).

45 solution was adjusted regularly to 5.8 of traits, somewhat arbitrarily categorised with H2SO4. To avoid mutual shading, the in three groups related to growth number of plants on each container analysis, C and N-economy and ranged from 18 and 6, depending on the morphology. Plants were measured at 23 size of the plants. Plants were rotated to 25 days after germination, when there four times a week within the growth were 2-10 tillers. Whole-shoot room. photosynthesis and shoot and root respiration were measured on two plants DNA isolation and AFLP analysis of each accession. Fresh and dry mass of Four to ten plants were grown per leaves, stems and roots, leaf area, leaf accession for DNA isolation. Leaves were width, leaf angle, shoot height and the collected from two-week old plants. DNA number of leaves and tillers were also was isolated from 200-300 mg of frozen determined on these two plants as well as (-80°C) leaves according to the CTAB on two additional plants. Two other plants method (Ausubel et al. 1999). were used for measurements of osmotic The AFLP protocol was used as potential and to determine the chlorophyll described in Vos et al. (1995). The DNA concentration and the remaining two was digested with restriction enzymes plants were used for measurement of leaf EcoRI and MseI. The AFLP bands were thickness. The latter four plants were also visualised by radioactive [γ33P]-ATP used for chemical analyses. Because of labelling. The presence or absence the large number of plants and the time (dominant scoring) of AFLP fragments required for the physiological was scored by eye, and all clear bands measurements we staggered the with lengths between 80 and 500 germination and growth of the plants. nucleotides were included. In total 10 Four randomly chosen accessions of primer combinations previously tested different populations were measured each with H. vulgare (Qi et al. 1997) were week. used: E32M61, E33M55, E35M48, E35M55, E35M61, E38M54, E38M55, Measurements E39M61, E42M51, E45M55. Only markers Seed mass of each seed was determined that were mapped in a cultivated barley separately. Leaf width and thickness were cross ‘L94 x Vada’ (Qi et al. 1998) and in measured on the youngest fully expanded a wild barley cross ‘Ashqelon x Mehola’ leaf. Leaf angle was assessed as the (Chapter 2) were included in the analysis. average angle of the four oldest leaves. Plant height was determined by Experimental design measuring total shoot length. Plants from four accessions per Leaf area, fresh and dry mass of population were grown. Eight plants per the leaves (leaf blades), stems (leaf accession were used to measure a range sheaths) and roots were determined to

46 calculate water content (fresh mass - dry mass / dry mass) of leaf, stem and root Statistical analyses (WCleaf, WCstem, WCroot, respectively), Relative growth rate (RGR) was leaf area ratio (LAR, leaf area per total estimated, on the basis of a plant's C- plant dry mass), specific leaf area (SLA, economy, using the formula given in leaf area per leaf dry mass), leaf mass Poorter & Pothmann (1992): fraction (LMF, leaf dry mass per total PSa × SLA × LMF − ShR × (LMF + SMF) − RR × RMF plant dry mass), stem mass fraction RGR = C (SMF, stem dry mass per total plant dry mass) and root mass fraction (RMF, root where, PSa = daily rate of Photosynthesis dry mass per total plant dry mass). per unit leaf area, ShR = daily Shoot Carbon concentration and Respiration, RR = daily Root Respiration, nitrogen concentration were determined SLA= Specific Leaf Area, LMF =Leaf Mass with an elemental analyser (Carlo Erba Fraction, SMF = Stem Mass Fraction, RMF 1110, Milan, Italy). Nitrate concentration = Root Mass Fraction and C = Carbon was quantified according to Cataldo et al. concentration of the plant biomass). We (1975). Ash and ash alkalinity were determined the carbon content of the determined as described by Poorter and leaves, assuming that it is representative Villar (1997). Results were used to of that of the whole plant. In reality, the calculate concentrations of organic acids, carbon content of roots and shoots tend minerals and organic nitrogen to be slightly lower than in leaves compounds. The osmotic potential of the (Poorter & Bergkotte, 1992), but these leaf sap was measured using a Wescor differences are not likely to affect the Vapour Pressure Osmometer (Logan, UT, RGR-calculation to more than a small USA). The chlorophyll concentration of extent. A second assumption is that the the leaf was determined according to rates of photosynthesis and respiration, Lichtenthaler and Wellburn (1983) after both measured over a two-hour period, extraction with 80% acetone. can be integrated over 24 hours. All Net photosynthesis, dark parameters of the RGR-formula were respiration and root respiration were measured on the same day. measured as CO exchange. CO and H O 2 2 2 To study marker-trait exchange were measured differentially to associations, simple product moment calculate photosynthesis per unit leaf correlations were calculated (Pearson area and per unit leaf mass, shoot correlations) between a selected set of respiration, root respiration and water markers and the 33 quantitative traits. use efficiency. Markers were included if they were Further details on the phenotypic mapped to either ‘Ashqelon x Mehola’ analyses are given in Van Rijn et al. (Chapter 2) or the ‘L94 x Vada’ (Qi et al. (2000).

47 1998) map. Of the original 643 were associations between several polymorphic markers, 68 were mapped. A markers and morphological traits, and test for the correlation is in this case three between a marker (chromosome 5, equivalent to a two-sample t-test 26cM on ‘Askelon x Mehola’ map) and comparing the mean of the accessions chemical traits CN, mineral content and with a specific marker band with the N. mean of the accessions without that Figure 1 shows the results of the marker band. A significance level of 0.05 marker-trait correlations positioned on was chosen, besides a more strict 0.0007 the ‘L94 x Vada’ and ‘Ashqelon x Mehola’ (a Bonferroni corrected level of maps. The QTL are from Poorter et al. significance; 0.05 divided by the number (2004). of selected markers). All the calculations were performed using SAS (SAS system Mapped QTL supported by marker- for Windows 6.12, 1989-1996 SAS trait associations Institute Inc. Cary, NC, USA). Fifteen QTL were clearly supported by at least one marker-trait correlation at the 0.05 significance level (Table 1). At the Results strict 0.0007 significance level four marker-trait correlations (on As mentioned earlier, of the 643 chromosomes 2 and 4) supported four polymorphic markers 68 were mapped. QTL. Supportive marker-trait associations Of these 68 mapped markers, 60 are indicated as grey boxes in Figure 1. correlated significantly (p < 0.05) with at Two QTL (height and seed mass) on least one of the measured traits. For chromosome 2 were supported by these 60 markers in total 267 marker- marker-trait association only if the trait correlations were observed at the ‘Ashkelon x Mehola’ chromosome is 0.05 significance level. 2244 tests were orientated as shown in Figure 1. The performed and at the 0.05 significance remaining 13 supported QTL were clear in level 112 false positives are expected. At this respect. the strict significance level of 0.0007, 32 marker-trait correlations were found Mapped QTL not supported by significant. Only 1.5 false positives are marker-trait associations expected at this level. The strongest There were 17 QTL that were not clearly correlation was found between seed mass supported by the marker-trait and a marker from chromosome 4 (33 cM correlations. In 11 cases significant in ‘Ashqelon x Mehola’ map; r=-0.70). marker-trait correlations were detected at There were in total 13 marker-trait the same chromosome as the associations with p≤0.0001. Ten of these corresponding QTL, but not in the actual position of the QTL. In one of these cases

48 the associated marker lies on the edge of by marker-leaf width associations, three the QTL interval (LMF on chromosome 7). of these at the 0.0007 significance level. There were several traits that were not measured in the population Other marker-trait associations study (Table 1). However, some of these The strongest correlations with are strongly correlated with some other genetic markers were observed for traits that were measured in the morphological traits such as seed mass populations. A good example is the and leaf width or thickness. RGR showed density measures. Leaf mass density also a strong correlation with a marker on (LMD) was estimated within the chromosome 2 together with one of its populations whereas root (RMD) and components, RMF. On chromosome 5, stem mass density (SMD) were three chemical traits, mineral content, N determined in the F3. There were three and CN, were highly significant as well as QTL detected for both RMD and SMD. the rate of photosynthesis per mass and Two of the SMD QTL were supported leaf width. Chromosomes 3, 6 and 7 unambiguously by marker-LMD contained only one or two strong marker- association. One RMD QTL on trait correlations whereas chromosomes 2 chromosome 1 was supported only if the and 4 contained many highly significant orientation is as shown in Figure 1. associations. Another example of traits not measured in the natural populations is leaf length. Leaf length is strongly correlated with leaf width and all the four QTL are supported

Figure 1. The significant marker-trait correlations among H. spontaneum accessions and QTLs in a H. spontaneum cross. The 60 markers were based on two linkage maps; 'L94 x Vada' (Qi et al. 1998) and 'Ashqelon x Mehola' (Chapter 2). The arrows point to the marker positions. The marker-trait correlations are shown on the left side of the chromosomes. The traits that correlate with a marker at the 0.0007 significance level are shown in boldface, and those that correlate at the 0.05 significance level are shown in italics. The traits that correlate with a marker and support a QTL are shown in grey boxes. The QTL with 1 and 2 LOD confidence intervals are given on the right side of the 'Ashqelon x Mehola' map. The QTL with positive effect of the Ashkelon allele are shown in black (LOD >3.1), or slanted black (LOD 2.5-3.1) and the QTL with positive effect of the Mehola allele are shown in grey (LOD >3.1) or slanted grey (LOD 2.5-3.1). The common markers shared between the two maps are connected with lines. Dashed lines are used to point to the approximate positions of the SSR markers (Ramsay et al. 2000) in the 'L94 x Vada' map.

56 Table 1. The traits measured in wild barley accessions and F3 of the cross ‘Ashkelon x Mehola’, the number of marker-trait correlations at 0.05 and 0.0007 significance levels, number of QTL detected by Poorter et al. (2004) and the number of supported QTL by one or more marker-trait correlations at the 0.05 and 0.0007 significance levels.

Trait Number of marker- QTL Number of QTL trait correlations* supported* P<0.05 P<0.0007 p<0.05 p<0.0007 Growth related Total dry mass (TDM) 6 1 1 0 0 Leaf area ratio (LAR) 2 0 1 0 0 Leaf mass fraction (LMF) 10 1 4 2 0 Relative growth rate (RGR) 8 1 4 2 0 Root mass fraction (RMF) 10 1 1 0 0 Specific leaf area (SLA) 1 0 1 1 0 Stem mass fraction (SMF) 10 0 0 0 0 C and N economy related Carbon content (C) 7 0 0 0 0 Chlorophyll 10 0 0 0 0 Mineral content 10 1 0 0 0 Nitrogen content (N) 5 1 0 0 0 NO3 60000 Organic acids 6 0 0 0 0 Organic nitrogen/leaf area (LNC) 80200 C/N ratio (CN) 6 1 - - - Osmotic potential 1 0 0 0 0 Photosynthesis/leaf area (PSA) 12 0 4 2 0 Photosynthesis/leaf mass (PSM) 8 1 4 1 0 %Respiration 2 0 0 0 0 Root respiration (RR) 8 0 1 1 0 Shoot respiration (SR) 1 0 0 0 0 Water use efficiency (WUE) 6 0 1 0 0 Morphological Height 12 0 2 1 0 Leaf Angle 11 1 2 1 1 Leaf area 7 0 - - - Leaf mass density (LMD) 10 0 - - - Leaf thickness 10 2 0 0 0 Leaf width 17 6 2 2 2 Number of tillers 14 3 1 0 0 Seed mass 16 5 2 2 1 Water content leaf (WCleaf) 13 4 0 0 0 Water content root (WCroot) 3 1 0 0 0 Water content stem (WCstem) 11 2 0 0 0 Traits not measured in populations Leaf length - - 4 - - Root length - - 2 - - Photosynthetic nitrogen use - - 2 - - Stem mass density (SMD) - - 3 - - Root mass density (RMD) - - 3 - - Stomatal conductance (Gs) - - 2 - - Unit leaf rate (ULR) - - 1 - - Total 267 32 50 15 4 *The numbers at 0.0007 significance level are included in the columns for p<0.05

Multiple testing significance level when multiple tests are One problem with association mapping is performed is a difficult task and the the issue of multiple testing when Bonferroni correction is often used to evaluating hundreds of markers for tens control the type I error. However, this is of traits. Selecting an appropriate sometimes overly stringent and many

Figure 2. Scaled frequency histogram of p-values of the correlation tests. true alternative hypotheses are discarded markers have an effect on the trait. as non-significant. Storey and Tibshirani Figure 2 presents a scaled frequency (2003) suggest another way of histogram of wild barley marker-trait determining significance in genomewide association p-values from the current studies. The false discovery rate (FDR; chapter. This clearly shows that a originally introduced by Benjamini and proportion of the results represents true Hochberg 1995) is defined as the alternatives, i.e. a proportion of the estimated proportion of the false marker-trait correlations are expected to positives among the tests deemed to be be real. Therefore, the histogram is a significant. For calculation of FDR, the mixture of two distributions: a uniform proportion of true nulls (π0) among the distribution of true nulls and an unknown tests has to be estimated. Applications of distribution of true alternatives, mainly

FDR to date have assumed π0 to be one, concentrated close to zero. π0 is i.e. all tests are a priori assumed to be estimated as the proportion of uniformly true nulls. Storey and Tibshirani (2003) distributed p-values in the mixture estimate π0 using the distribution of the (Figure 3a).The next step is to determine p-values from all the tests. When all tests the FDR, or q-values for the different are true nulls, a uniform distribution of p- tests. The q-value for a given test is the values between zero and one is expected. minimum false discovery rate incurred by That is, when in reality none of the calling that test significant. FDR

58 Figure 3. Four graphs illustrating a. the estimation of π0 (where λ is p-value cut-off and the points represent the proportion of results p>λ; the estimated π0 at λ=1, is 0.729), b. the relationship between q- and p-values, c. q-value cut-off in relation to the number of significant tests and d. the number of expected false positives within the amount of significant tests. The graphs were made in R-script QVALUE v 1.1 (Storey 2002) based on the p-values. estimation was done with the help of the largest p-value for a FDR of ≤0.05 is R-script QVALUE v.1.1 (Storey, 2002). 0.002, which is less stringent that the

For the association experiment, π0 was Bonferroni corrected p-value of 0.0007. If estimated to be 0.73, implicating that a FDR of 5% is accepted, 59 marker-trait

0.27 (1-π0) of the marker-trait effects are associations are deemed significant. Out real. Figure 3 shows four graphs; a graph of these about 3 are thus expected to be estimating π0, p-values plotted against q- false positives. Table 2 shows the values, q-value cut-off against the differences in the number of tests number of significant tests and the deemed significant when accepting FDR number of significant tests against the of 5% instead of the p-value of 0.0007. expected number of false positives. The As can be seen from Figure 3, the maximum estimated q-value (=FDR, number of expected false positives when calling all p-values at the chosen remains fairly low until about 100 level significant) for the stringent significant tests. The FDR is about 10%, Bonferroni corrected p-value of 0.0007 is and thus among the 100 significant tests 0.03. For a p-value of 0.05 it is 0.28. The about 10 are expected to be false

59 Table 2. The traits measured in wild barley accessions, the number of marker-trait correlations at 0.05 and 0.0007 significance levels and at the FDR of 5%.

Trait Number of marker-trait correlations P<0.05 P<0.0007 FDR of 5% Growth related Total dry mass (TDM) 6 1 1 Leaf area ratio (LAR) 2 0 0 Leaf mass fraction (LMF) 10 1 2 Relative growth rate (RGR) 8 1 2 Root mass fraction (RMF) 10 1 2 Specific leaf area (SLA) 1 0 0 Stem mass fraction (SMF) 10 0 0 C and N economy related Carbon content (C) 7 0 0 Chlorophyll 10 0 1 Mineral content 10 1 1 Nitrogen content (N) 5 1 1 NO3 60 1 Organic acids 6 0 0 Organic nitrogen/leaf area (LNC) 80 0 C/N ratio (CN) 6 1 1 Osmotic potential 1 0 0 Photosynthesis/leaf area (PSA) 12 0 1 Photosynthesis/leaf mass (PSM) 8 1 2 %Respiration 2 0 0 Root respiration (RR) 8 0 0 Shoot respiration (SR) 1 0 0 Water use efficiency (WUE) 6 0 0 Morphological Height 12 0 3 Leaf Angle 11 1 1 Leaf area 7 0 1 Leaf mass density (LMD) 10 0 5 Leaf thickness 10 2 4 Leaf width 17 6 8 Number of tillers 14 3 6 Seed mass 16 5 7 Water content leaf (WCleaf) 13 4 5 Water content root (WCroot) 3 1 1 Water content stem (WCstem) 11 2 3 Total 267 32 59

positives. This could also be taken as an carried out to determine the genomic alternative cut-off point instead of a fixed regions that control these traits and to p-value. assess the overlap between QTL for different traits (Poorter et al. 2004). In Discussion the present study we compared the QTL found for growth-related traits with the Variation in RGR and its underlying marker-trait associations in 81 accessions components have been studied of H. spontaneum. A number of linkage extensively, but to what extent these groups in the ‘Ashqelon x Mehola’ map traits are genetically linked and/or could be assigned to a specific controlled by common factors is still chromosome due to markers identical largely unknown. A QTL analysis was with those found for H. vulgare. However,

60 in some cases there was only one Marker-LMF associations common marker, which complicates the supported two out of the four LMF QTL. comparison between the two approaches. LMF is usually not the most important Fortunately this affected the comparisons factor explaining differences in RGR, but of only two QTL on chromosome 2. is sometimes positively correlated with RGR (Ingestad, 1981; Poorter & Remkes Marker-trait associations for growth- 1990), sometimes negatively (Hunt et al. analysis traits 1987; Shipley & Peters 1990; Van Rijn A total of eight markers were associated 2001). with RGR. The marker that showed the strongest correlation with RGR explained Marker-trait associations for C and N 15% of the variation and was mapped on economy-related traits chromosome 2. One of the other markers There were 12 markers associated with that correlated with RGR was located in PSa and eight associated with PSm. PSa is the middle of a RGR QTL on chromosome positively correlated (p<0.001) with Gs 1 and explained 11 % of the total and ULR, and negatively (p<0.001) with variation. LAR (Van Rijn 2001). QTL for these traits

SLA is the most important trait coincide on chromosome 4, where Gs, explaining differences in RGR in many ULR and PSa show a positive effect of the studies (see for a review Poorter & Van Ashkelon allele and LAR shows a positive de Werf, 1998) and it has the highest effect of the Mehola allele. Three markers correlation with RGR (Poorter et al. correlated with PSa were mapped on 2004). However, there was almost no chromosome 4, two of these supported difference in SLA in the 81 accessions the QTL and one was just outside the QTL (Van Rijn et al. 2000), and no significant interval. These four markers together difference between the 21 populations. In explained 32% of the total variation. Note contrast with these results, the F3 that photosynthesis was determined population showed substantial differences differently in Poorter et al. (2004), where in SLA (ranging from 33 to 45 m2 kg-1). it was measured on a single leaf. In this Only one marker (on chromosome 7) was study, photosynthesis was determined on correlated with SLA among the the whole plant. The fact that both accessions. The only QTL for SLA was measurements point to the same detected at the same location as the direction makes these observations marker-SLA association on chromosome relatively robust. Another interesting 7. Even though there was a difference detail is that a QTL for chlorophyll content between the SLA measurements on the was also found on chromosome 4 in population and the cross level, both of barley (This et al. 2000). Poorter et al. the resulting associations point at the (2004) did not measure chlorophyll same location. content, but in the population study it

61 was measured and the marker that were mapped in cultivated barley and this showed the best correlation with does not necessarily mean that those chlorophyll content (r = 0.36) was also alleles are also present in H. located on chromosome 4. These results, spontaneum. together with the mapping of a Rubisco activase gene on chromosome 4 in H. Conclusions spontaneum (Becker & Heun 1995) show Marker-trait associations in 21 wild barley that this location on chromosome 4 might populations support several QTLs mapped be very important for area-based by Poorter et al. (2004). Marker trait photosynthetic traits. associations supported two out of four RGR QTL. However, no association with Marker-trait associations for SLA was found at these locations. The morphological traits QTL for SLA and its supporting marker- Strong marker-trait associations support trait association is found on chromosome the QTL for leaf width, seed mass and 7 with a negative association with LMF. leaf angle on chromosome 2. There are Markers associated with PSa and three other morphological QTL on this chlorophyll content were mapped on chromosome, height, leaf length and root chromosome 4, where also QTL for PSa length, as well as a QTL for RGR. Leaf and stomatal conductance were found. and root lengths were not measured in Another cluster of photosynthesis traits the population study. Several markers PSm and PSa QTL and marker-trait are strongly associated with seed mass, associations were found on chromosome leaf thickness and leaf width on 5. Many markers are associated with leaf chromosomes 1, 2 and 4. QTL for seed thickness, leaf width and seed mass, mass and leaf width coincide on suggesting that these traits are tightly chromosome 2 and QTL for leaf width and linked. leaf length coincide on chromosome 4. They are also correlated with each other Acknowledgements (Van Rijn 2001). These results suggest The authors thank Margreet ter Steege that these morphological traits are at for giving valuable comments on previous least genetically linked, but maybe also versions of this manuscript. The authors controlled by a common factor. Because would also like to thank Dirk-Jan de dwarfing genes have been mapped in Koning for his comments on the FDR. The barley on chromosome 2 (Börner et al. Earth and Life Science Foundation (ALW), 1999) and on chromosome 4 (Ivandic et which is subsidised by the Netherlands al. 1999), a GA controlled gene might be Organisation for Scientific Research a likely candidate. However, these genes (NWO), financially supported this study.

Chapter 5

The island lies like a leaf upon the sea. Green island like a leaf new-fallen from the tree. Green turns to gold, as morning breeze gently shakes the barley, bending the yellow corn. Green turns to gold, there's purple shadows on the distant mountains, sun in the yellow corn.

Christy Moore – Green Island

Quantitative trait loci for seed dormancy in wild barley (Hordeum spontaneum)

Tytti K. Vanhala & Piet Stam

Abstract A quantitative trait locus analysis was carried out to unravel the genetic basis of dormancy in wild barley (Hordeum spontaneum) from Israel. Two accessions, ‘Ashkelon’ and ‘Mehola’, from divergent environments were crossed to produce a mapping population. A linkage map was produced from the F2 population, and F4 seeds were used for germination experiments. Five quantitative trait loci (QTL) were detected for dormancy across the different germination experiments. These QTL were found on chromosomes 1, 2, 5, 6 and 7. The variation explained by each QTL varied between 8% and 25%. Ashkelon alleles increased the germination except for the QTL on chromosome 5.

Introduction the seed coat dormancy that ultimately determines when the seed germinates Seed dormancy is an important trait not (Rodriguez et al. 2001). Although only for the agricultural industry but nondormant seeds are desirable in the also for seedling survival in wild species. malting industry, these might sprout in It has been well studied in several crop the ear in wet conditions before species, such as barley, wheat, oat and harvesting and therefore reduce yield rice (for a review see Foley and and seed quality. Highly dormant seeds, Fennimore 1998). A seed is dormant on the other hand, create storage when it fails to germinate even though problems during their after-ripening it is mature and conditions for period as well as being a weed problem. germination are optimal. Dormancy can The level of dormancy does not be due to the embryo or the seed coat depend only on the genetic make-up of (Bewley and Black 1994). Embryo the seed but also on the environmental dormancy is lost first and therefore it is growing conditions of the maternal plant

64 during the seed maturation process, The aim of this study was to although this seems to depend also on detect QTL for seed dormancy in wild the cultivar (Schuurink et al. 1992). barley and to compare the results to the Germination success is also dependent QTL found in cultivated barley. on the environmental conditions during germination process. Especially temperature (Fennimore et al. 1998) Material and Methods and water saturation level (Thomas et al. 1996) play a crucial role. Plant material Several quantitative trait loci A single pair cross between two (QTL) have been detected in cultivated accessions of Hordeum spontaneum barley for seed dormancy (Ullrich et al. from Israel was made. The paternal 1992; Oberthur et al. 1995; Han et al. plant was from the site Ashkelon, on the 1996; Thomas et al. 1996). A major Mediterranean coast, and mother plant QTL (SD1) has been found on from Mehola, in the Jordan valley chromosome 7, explaining 36% of the (Chapter 2). We refer to the accessions variation in dormancy (Ullrich et al. as Ashkelon and Mehola, after the site 1992). In the same cross three minor of origin. Ashkelon has a moderate level QTL were found on chromosomes 1, 4 of dormancy whereas Mehola is highly and 7 (Ullrich et al. 1992). dormant, requiring a long after ripening

Dormancy is much stronger in period. F1 and subsequently F2 were left wild than in cultivated barley (Ogawara to self-fertilise. Ten F3 seeds per one F2 and Hayashi, 1964; Gutterman et al. plant were pooled and grown together 1996). The removal of the glumellae in a large (25 cm diameter) pot in order and the husk enhance the germination to produce F4 seeds. In the remainder of greatly (Gutterman et al. 1996; Wang this chapter the bulked F4 seeds

1997). This seems to be largely due to deriving from a single F2 plant are the increased abscisic acid (ABA) referred to as a line. The plants were diffusion from the seed (Wang 1997). grown in a non-heated greenhouse, The duration of after ripening in wild sown autumn 1999 at the Ecological barley depends on the population; the Institute, Heteren, The Netherlands. more extreme the habitat the longer it The F4 seeds were collected takes for the dormancy to break randomly from all the ten F3 plants. (Gutterman and Nevo, 1994). This has Because wild barley has a brittle rachis, an important effect on seedling survival complete synchronisation of the seed in drier areas where germination after ripeness was not possible. Instead, unusual rain during the dry season seeds were collected when they were would be fatal. getting loose from the ear. Already

65 dropped seeds were excluded and seeds total amount of germinated seeds per that were not loose were left to ripen line was used in the QTL analyses. further. The loose seeds were collected approximately every 3 days during a AFLP map four-week period in June 2000 from 102 A linkage map using dominant and co- lines. The seeds were counted per line, dominant AFLP-markers and a few let to air dry further at +15˚C, 30% microsatellite markers was constructed humidity for approximately 3 days, then from the F2. The map covered sealed in plastic bags and stored at approximately 45% of the wild barley -20˚C until the germination genome due to unexpectedly high experiments could be started. heterozygosity of the Ashkelon parent (Chapter 2). Two hundred and two Germination experiments (202) markers were mapped on 11 Six germination experiments were linkage groups. This full map was used conducted with 14-day intervals. Forty as a basis in the QTL analysis.

F4 seeds per line were used for every germination experiment. The Statistical analyses germination experiments were Germination percentages were conducted using intact dispersal units, calculated from the germination data. i.e. the husks were not removed. For Distributions of the germination the first germination experiment, seeds percentages were non-normal and were let to thaw at room temperature therefore arcsin square root over night before placing them on petri transformations were applied (Figure 1). dishes between two water-saturated The QTL analysis was performed using blotting papers. The remainder of the the transformed data. seeds were put in paper envelopes and QTL analysis was conducted after-ripened in a dry oven at +40°C. using MapQTL 4.0 (van Ooijen & Batches of seeds were taken from these Maliepaard 1996). Interval mapping envelopes every 14 days to germinate (IM) was used at first, multiple QTL them. The germination was done at mapping (MQM) was performed after +10°C for five days then at +20°C for that with inclusion of cofactors. 10 days, dark. Germinating seeds were Cofactors were selected to be markers counted and removed from the petri with LOD score above 2. When the LOD dishes after five, seven and 10 days at values stabilised in MQM, restricted +20˚C. The seeds were counted and MQM (RMQM) was performed with the removed from the petri dishes this way cofactors and these values were taken in order to avoid overcrowding. The as the result of the mapping procedure. A LOD threshold value of 2.7 for a

66 significant QTL was used based on Van The breaking of dormancy was Ooijen et al. (1999). The estimated more or less continuously increasing in dominance effects obtained from 67% of the lines (group b; Figure 2). MapQTL were multiplied by two to Within these lines, the germination correct for the different generations in percentage increased or remained the which marker data and phenotypic data same with prolonged after-ripening. were collected, i.e. F2 and F4, However, 33% of the lines experienced respectively (cf. Verhoeven 2003). a reduction in germination on day 56 in comparison to the germination percentage of day 42 (group c; Figure Results and discussion 2). The most extreme line germinated only by 7.5% on day 56 after Germination percentages were germination of 65% on day 42. On day calculated for each germination 70, germination increased to the same experiment (from day 0 to day 70). Five level as it was on day 42 or exceeded lines started to germinate (2.5–5%) on that level substantially. Surprisingly, day 0. For a different set of five lines four lines did not seem to ‘recover’ but the onset of germination was on day 14 germinated less than on day 42. One of (2.5-7.5%). On day 28, 85% of the these four lines germinated even less lines had started to germinate (2.5- than on day 56. Ogawara and Hayashi 75%). Only two lines remained (1964) observed similar reduction in completely dormant on day 42 and on germination in their experiments day 56 all the lines were germinating between days 87 and 101. However, (24-100%). Complete breaking of these authors did not observe such a dormancy with 100% of germination decrease in germination in dehusked or was first observed for three lines on day cut seeds. This would point towards the 42. After 70 days of after-ripening, 42% involvement of the husk in the decrease of the lines reached germination of 90% of germination. Perhaps there is a or over. critical after-ripening temperature and The average germination time effect on germination in nature percentages are shown in Figure 2. related to survival. The seeds used in They are divided into tree groups, i.e. this study were intact caryopses and (a) the total sample, (b) lines perhaps the hydration level of the seed continuously increasing in germination coat together with the plant hormone and (c) lines decreasing in germination metabolism inhibited germination of the between days 42 and 56. The reasons ‘decreasing’ lines. This inhibitory effect, for this division are explained below. however, is mostly lost after further 14 days of after-ripening.

67 day 28 25

20 15

10 5

day42 25 20 15 10 5 0 day 56 25 Frequency 20 15 10 5 0

day 70 25 20 15 10 5 0 0 2.6 12 22 32 46 61 75 87 95 100

Germination percentage Figure 1. Frequency histograms of the transformed germination percentages (arcsin square root) of the F4 seeds in the four germination experiments used in the QTL analysis. On the x-axis the germination percentages for the different classes have been back transformed.

Another possibility is that by non-viable seeds varies greatly among chance part of the seeds sampled on successive random samples taken from that day were not viable and therefore the same line, in a pattern that exactly the germination percentage seemed to corresponds to the observed decrease in be decreasing. However, no selection of germination. The viability of non- seeds was conducted when taking them germinated seeds was not tested. This out of the paper bags and therefore it is was assumed not to vary between the highly unlikely that the proportion of lines.

68 90 80 70 60 total 50 increasing 40 decreasing 30 20

Germination percentage 10 0 Day 0 Day 14 Day 28 Day 42 Day 56 Day 70 Germination experiment

Figure 2. Average germination percentages for each germination experiment in total and divided in increasing in germination and decreasing in germination lines.

These explanations for the Another line stayed dormant having low reduction of germination percentage on but increasing germination percentages day 56 remain speculative and further reaching 24% by day 70. Yet another research is needed to establish the example is a line which did not reason behind these results in intact germinate until day 56 reaching 95% wild barley seeds. It would not be germination on day 70. surprising, if this trend is not observed in all accessions or populations, as in QTL mapping the F4 population of this study only one QTL mapping was conducted on the third of the lines showed this reduction. transformed data for days 28, 42, 56 Seeds from parental accessions and 70. In total five QTL with LOD harvested at the same time as the F4 scores above 2.7 were detected across seeds were germinated alongside the the experiments. The QTL were found mapping lines. Ashkelon seeds first on chromosomes 1, 2, 5, 6 and 7. Table broke dormancy on day 28 (48% 1 summarises the QTL results. germination) whereas Mehola seeds had QTL mapping was performed at to be after-ripened until day 70 before first using the full map data with 202 any germination (15%) was observed. markers across 11 linkage groups

No F4 line was more dormant than (Chapter 2). Close inspection of the Mehola. marker data revealed that 51 markers There were marked differences had a very low information content (less in the rate of the release of dormancy than 10 F2 plants with known between lines. One line lost its genotype). These markers were dormancy fast after 28 days after- removed from the data set and thus all ripening, gaining 100% by day 42. subsequent QTL analyses were

69 performed using the remaining 151 et al. (1996) found two QTL on markers. chromosome 1. One of these (near A QTL was detected on marker PBI12) might also be the SD3 chromosome 1 for day 70. The QTL. significance of this QTL is fairly high On chromosome 2A, a QTL was (LOD 3.95) but it is based on found for days 28 and 56 (LOD 2.90 and information only from one marker class 3.16, respectively). The highest LOD and thus is rather suspect. To find out peaks per experiment were found in the whether there was real lack of other middle of the chromosome, although allele classes or whether more LOD peaks over 2.7 were also detected information could have been obtained at the top of the chromosome and thus on this occasion by using the full sample might point towards a possible second size of 233 F2 derived F4 lines, we QTL on this chromosome. The QTL checked the information content of the explained 10% and 12% of the variation surrounding markers in the full sample. and was consistently additive. The Per1 The results show that no more gene is involved in dormancy release information could be gathered in this (Stacy et al. 1996) and is nearby a way; the nearest balanced marker marker B15C on chromosome 2 position remains 10 cM away from the highest 66cM on the barley consensus map (Qi LOD peak. This distortion in the marker et al. 1996). The QTL found in this data could be due to segregation study on chromosome two is around this distortion. But, as noted in Chapter 2, position. Ullrich et al. (1992) detected a due to the heterozygosity of especially QTL also near the marker B15C the Ashkelon parent many homozygous (ABC306, 69 cM on barley consensus markers per F1 ‘family’ were removed map). Thomas et al. (1996) mapped from the data. Therefore little can be two QTL on this chromosome (PBI21a, said about the segregation distortion in 26 cM and CDO64, 49 cM), but not this mapping population. around the Per1 gene. Ullrich et al. (1992) detected a On chromosome 5, a QTL was QTL for seed dormancy on chromosome detected for day 56 (LOD 2.75). This 1 (SD3) associated with the marker was the only QTL of which the Mehola Amy2 (position 85 cM on barley allele enhanced germination. Thus even consensus map; Qi et al. 1996). though Mehola is very dormant, it still Unfortunately only one of our AFLP contains alleles for inducing markers on this chromosome is shared germination. The QTL explained 12% of with the cultivated barley map, and the variation and was overdominant. therefore we cannot determine the On chromosome 6 we detected orientation of the chromosome. Thomas a QTL for days 28 and 42. Thomas et al.

70 Table 1. QTL for transformed germination data. Experiment, map location, LOD values, percentage of variation explained by the QTL, additive and dominance effect of the QTL, and the associated marker. The dominance effect is corrected for F4 as described by Verhoeven (2003).

map location Exp. Chr. cM LOD % add. dom. nearest marker expl effect effect day 28 2A 35 2.90 10.1 0.12 -0.08 E38M54-169 6 14 3.46 13.3 0.10 0.20 E38M54-349 7 12 4.57 15.4 0.15 0.04 E39M61-255 day 42 6 14 4.84 21.5 0.22 -0.02 E38M54-349 7 12 3.39 14.6 0.17 -0.04 E39M61-255 day56 2A 31 3.16 12.6 0.13 -0.18 E33M55-436 5 53 2.75 11.7 -0.04 -0.38 E33M55-591 7 11 2.11 8.6 0.12 -0.06 E33M61-221 day 70 1 42 3.95 25.0 0.20 0.08 E38M58-84

(1996) detected a QTL for dormancy also observed on both sides of the around this position as well. The detected QTL. These were considered to chromosome is linked to the cultivated be rather suspect as markers at both barley map only with one marker, so ends of the chromosome are only of one the orientation is not resolved. The QTL marker class as was the case with the explained 13% and 22% of the variation QTL on chromosome 1. Extending the for the two different days, respectively. population to the full set of 233 F2 QTL x time interaction was observed at plants it appeared that no more this QTL; for day 28 the QTL was information could be obtained for these completely dominant whereas for day markers. Therefore, it is not possible to 42 it was additive. determine whether there are two more On chromosome 7 a QTL was QTL on this chromosome or not. To detected for days 28 and 42. A putative solve these problems, a new cross QTL was detected at the same position should be made with less heterozygous also for day 56 (LOD 2.11). The parents, so as to maximise the genome variance explained by the QTL was coverage. about 15% for both days 28 and 42, Ullrich et al. (1992) reported a whereas the putative QTL on day 56 major seed dormancy QTL (SD1) on explained 9% of the variation. The QTL chromosome 7 explaining up to 36% of had a consistent additive effect across the variation in dormancy. The SD1 QTL the experiments. High LOD peaks were is associated with the marker PSR128,

71 position 76 cM on barley consensus map percentage on day 56 – germination (Qi et al. 1996). The approximate percentage on day 42) and QTL position of the SD1 is estimated to be at mapping was performed. One LOD peak the end of the chromosome on the of 2.32 was observed at one end of an ‘Ashkelon x Mehola’ map. Thus the QTL unassigned linkage group U2 (see detected in this study on the same Chapter 2) explaining 30% of the chromosome is not the SD1 QTL. It variation. A LOD value of 2.3 in this could be that the SD1 QTL is expressed linkage group corresponds with a p- also in wild barley, but our map data value of p<0.011 according to a may be failing to detect it. permutation test. The reduction in Different QTL at different time germination at this locus is associated points reflect a difference in the with homozygosity for the Mehola allele. cumulative germination curves of the Individuals being homozygous for the lines. A priori, another approach could Ashkelon allele experience less of a have been taken, i.e. to fit an S-shaped reduction but heterozygotes have the curve to the observed cumulative largest increase in germination and thus germination data for each line and take the QTL was overdominant. It is the parameter(s) of those curves as the remarkable to see that the reduction in trait(s) to be analysed. However, germination between day 42 and 56 is because of the observed drop in apparently being controlled by a QTL germination percentage in a number of that is not involved in the ‘normal’ lines, this approach does not apply. breaking of dormancy.

About one third of the F4 mapping lines experienced a reduction Conclusions in germination percentage on day 56 The level of dormancy is much higher in compared to day 42. The reasons for wild barley than in the crosses studied this reduction are unknown, although in cultivated barley. The mapping based on the results of Ogawara and population used in this study started Hayashi (1964) the seed coverings germinating after 28 days of after- might have something to do with the ripening, including the less dormant phenomenon, as this reduction in parent, whereas the highly dormant germinability seems to be restricted to parent Mehola needed 70 days of after- intact seeds. ripening. Removing the husk would To establish whether QTL increase the germination of wild barley mapping would detect any genomic seeds (Gutterman and Nevo 1994), but areas associated with the reduction, a we doubt whether this would be enough new trait was defined for the reduction to allow germination of Mehola seeds in germination percentage (germination immediately after harvest.

72 We have detected several QTL for breaking of seed dormancy in a wild barley cross. Because the ‘Ashkelon x Acknowledgements Mehola’ map does not have enough The authors would like to thank Ivonne markers linking it to the cultivated Elberse and Koen Verhoeven for barley map, the QTL found here could growing the F3 plants, and for their help not be fully compared with the QTL on harvesting and storing the F4 seeds, found earlier with confidence. However, and Dirk-Jan de Koning for his some comparisons could be made assistance and comments during the revealing that three out of the five QTL analysis. This study is financed by detected QTL probably correspond to Earth and Life Science Foundation QTL found earlier in cultivated barley (ALW) which is subsidised by the crosses. This indicates that wild barley Netherlands’ Organization for Scientific may harbour dormancy controlling Research (NWO). genes that have not yet been exploited by barley breeders.

Chapter 6

Now the ploughman he shall plough, And shall whistle as he go, Whether it be fair or blow, For another barley mow, O'er the furrow merrily: Merrily, merrily, will we sing now, After the harvest, the fruit of the plough.

The Barley Mow

Summarising discussion

Wild barley (Hordeum spontaneum) carries important genetic variation that is potentially useful for the improvement of barley cultivars. This is why it is of paramount importance to study wild barley accessions from different environments. To this end, different aspects of diversity, as well as linkage, QTL and association mapping in wild barley from Israel were studied in this thesis. A linkage map was constructed covering approximately 45% of the genome. This limited coverage was due to unexpected heterozygosity of the paternal parent. Diversity of 21 wild barley populations was estimated using environmental, phenotypic and genetic information. Environmental diversity was loosely associated with genetic diversity, whereas phenotypic diversity in general did not correlate with either one. Ecotype-specific markers were found. Some of these were mapped and correlated with phenotypic measurements as well as the environmental variables. Marker-trait associations were calculated and the resulting significant mapped associations plotted against results from a previous QTL study. This revealed many instances where the associations and QTL mapped to same genomic region. A dormancy study was performed in which five QTL were detected. Three of these might be the same as found earlier with cultivated barley crosses. These results of this thesis add to the characterisation of the diverse wild barley populations from Israel and aid in the understanding of the genetical backgrounds of different growth characteristics as well as seed dormancy.

Linkage mapping in wild barley Ashkelon parent plant was found to be heterozygous for many markers and this This thesis provides the first decreased the maximum proportion of intraspecific linkage map for wild barley. the genome that could be mapped to The experimental ‘Ashkelon x Mehola’ 55% (the estimated actual genome cross was made as a single plant cross coverage is 45%). Wild barley is a as the accessions within populations predominantly inbreeding species, but were found to be polymorphic. However, outcrossing does happen (Brown et al. even more unexpectedly, the paternal 1978a). The outcrossing event in the

76 Ashkelon parent has been very recent were detected between the populations, given the high marker heterozygosity whereas phenotypically no division into that was observed. populations was observed. This result Linking the wild barley map may be affected by the selected traits to cultivated barley maps is a very as for some morphological traits a important basic requirement if the population structure was observed. The obtained results are to be used for environment, although being very cultivar improvement. The linkage varied across Israel, differs between mapping in Chapter 2 includes many groups of populations rather than shared markers, potentially linking the between populations themselves. The wild barley map to five different populations from the more extreme cultivated barley maps. Unfortunately, environments (steppic and desert most of these markers remained populations) were genetically more unmapped in the end and only a handful divergent than populations from the of them could be used in assigning the more stable environment (coastal and linkage groups to known barley Mediterranean populations). chromosomes. For further research and Genetic diversity did not other intraspecific wild barley maps, it is correlate with the overall phenotypic important to consider genotyping with diversity as expected from the opposing as many markers mapped in cultivated results concerning the differences barley as possible. between and within populations. However, if the traits were divided into physiological, chemical and Genotype, phenotype and morphological traits and analysed again, environment a weak correlation (r=0.23, p<0.001) emerged between genetic and As discussed in Chapter 3, the different morphological diversity. This is in environments where wild barley agreement with the results from the populations grow, differ dramatically population structure. within Israel. This natural setting A number of markers were provides good opportunities of finding found to be ecotype-specific. These large genetic and phenotypic variation markers might be linked to genomic within populations for the use of barley areas important in the adaptation of the cultivar improvement. populations to their habitat. A marker The 21 wild barley mapped on chromosome 5 (111.5 cM) populations used in this thesis were had a lower band frequency within the studied genetically and phenotypically. desert ecotype. This marker correlated At the genetic level, clear differences with several phenotypic traits among

77 the accessions (see Figure 1 in Chapter The results of the present 4). QTL for stem mass density and population survey as well as the QTL height are also located near this marker mapping studies of Elberse (2002) and as well as QTL for seed number (Mehola Verhoeven (2003) clearly indicate that a site; Verhoeven et al. 2003) and leaf number of physiological traits are length (Elberse 2002). Another ecotype- involved in the adaptation of wild barley specific marker is located on the same to its environment. It should be noted chromosome, estimated to be near the however that Verhoeven et al. (2004b) marker at the position 111.5 cM (7.5 cM did not observe QTL with opposite on the ‘Ashkelon x Mehola’ map). This in effects in contrasting environments. turn is associated with the steppic Thus, it seems that adaptation results ecotype and correlated with chlorophyll from selection pressure that varies in content and water use efficiency. The magnitude among environments, but ecotype specific marker on chromosome not from opposing selection pressures. 6 (11 cM ‘Ashkelon x Mehola’ map) is Our results suggest that nevertheless associated with the Mediterranean these selective forces may result in populations and is coinciding with QTL ecotype-specific alleles at several loci. for root and leaf mass fraction, root length (Chapter 4) and relative growth rate (Chapter 4; Elberse 2002) as well Association and QTL mapping as seed mass (Verhoeven et al. 2004b; Elberse 2002), leaf width, number of Mapping phenotypic traits within wild roots and leafs (Elberse 2002). populations increases the chances of Chromosome 2 has also a locating new alleles for the use of barley Mediterranean ecotype specific marker, breeding. Ideally, it would be which is located on the same position as advantageous to screen as many of the QTL for root respiration. Chromosome 4 natural populations as possible for the has several QTL for photosynthesis desired traits. Creating several crosses related traits (Chapter 4) as well as an between individual plants from different ecotype specific marker for steppic habitats is one option, although this is populations (49 cM). Other QTL found at time consuming. Another approach is to this marker position include leaf area use association mapping where the ratio, leaf width and leaf mass fraction phenotypic traits measured across a (Chapter 4; Elberse 2002), specific leaf number of populations are analysed for area (Elberse 2002), seed weight and association with individual markers number of seeds per head (Verhoeven which are already mapped either in wild et al. 2004b). or cultivated barley crosses. Association mapping gives more information in

78 some aspects compared to QTL sprouting but low enough to not to mapping, because it is not restricted to cause problems in the form of extended the genetic make up of the two parents storage or weeds in the following crop that are used to make an experimental cycle. Wild barley is known to show cross for linkage mapping. The results dormancy up to much higher levels than from association mapping can also be what is observed in cultivated barley. used as a criterion for selecting parental Therefore, studying dormancy within a accessions for another cross with wild barley cross might offer several individuals from accessions carrying new alleles involved in dormancy different alleles for the marker-trait maintenance and release for the associations of interest. This way breeding of optimally dormant cultivars association mapping can be effectively However, studying dormancy used to screen a large number of in wild barley is not as straightforward populations and aid the decision process as it is in cultivated barley. The main for further research with these difficulty is the brittle rachis. This makes populations. it virtually impossible to synchronise the In this thesis, for several ripeness of the seeds as one would do traits, QTL detected in the experimental with cultivated barley. Another cross (Poorter et al. 2004) and difference to cultivated barley is the associations detected across populations husked seed. This is important to take it (Chapter 4), map to the same genome into account as the husk is related to regions. This co-localisation underlines the level of dormancy. that association mapping is a useful Chapter 5 records the first alternative to the use of segregating attempt to discover whether the mapping populations, provided that the dormancy QTL found in cultivated barley linkage disequilibrium causing are also found within a wild barley association is not the result of forces cross. Five QTL were detected across other than linkage itself. different chromosomes. Three of these QTL could be the same as detected Dormancy earlier in cultivated barley, thus leaving two new dormancy QTL. Dormancy remains an important trait in It is clear that the dormancy barley breeding. Most of the varieties QTL analysis has suffered from have lost their dormancy completely, incompleteness of the linkage map. A although some cultivars exhibit still linkage map covering the whole wild some amount of dormancy. Ideally, the barley genome would have provided cultivars should have a level of more markers in common with other dormancy preventing preharvest mapping populations, enabling a more

79 thourough comparison with dormancy related traits as well as dormancy. QTL studies in cultivated barley. Although this linkage map does not Complementary to QTL cover the whole wild barley genome, a studies of dormancy in mapping number of QTL have been located populations, association mapping using which, in principle, enables efficient mapped markers, as described in introgression of favourable genome Chapter 4 for RGR-related traits could segments from wild barley into the provide an interesting overview of the cultivated barley genetic background. presence of dormancy genes in the This linkage information was populations across the whole of Israel. complemented by a diversity study of wild barley populations from Israel, both at the DNA and the phenotypic level. Conclusions Although the pattern of intra- and interpopulation diversity reflected by Wild barley populations are diverse both phenotypic and genotypic differences genetically and phenotypically. were not parallel, all the traits studied Cultivated barley, on the other hand, were associated with at least one has lost much of its variation through mapped molecular marker. Many of breeding. As wild and cultivated barley these trait-associated markers are produce fully viable hybrids with normal located in the same genomic regions as chromosomal pairing, the larger QTL underlying these traits detected in variation detected in wild barley can be mapping populations. This concurrence used to improve barley cultivars. illustrates the potential usefulness of The wild barley populations association mapping for breeding from Israel studied here were diverse in purposes. Lastly five QTL for dormancy all levels; genetic, phenotypic and were detected. At least two of these environmental. The genetic variation appear to be novel QTL, not yet was larger between populations than detected in cultivated barley. within them, whereas phenotypic variation was larger within populations than between them. The environment differed between populations, although the difference was more notable between groups of populations, designated as ecotypes. An intraspecific molecular linkage map was constructed with the aim to locate QTL involved in growth-

Samenvatting

81 Samenvatting

In het Kort Wilde gerst (Hordeum spontaneum) vormt een belangrijke genetische bron voor cultuurgerst, die, als gevolg van intensieve veredeling, een beperkte genenpool heeft. Het is daarom van belang om de genetica van verschillende eigenschappen van wilde gerst te bestuderen, als men deze wil gebruiken voor de verbetering van gerst. Dit proefschrift beschrijft onderzoek aan de verschillende aspecten van diversiteit, genetische koppeling, QTL- en associatie-analyse bij wilde gerst. De natuurlijke populaties die zijn bestudeerd, zijn verzameld in diverse habitats in Israël. De nakomelingen van een kruising tussen twee accessies uit contrasterende habitats zijn gebruikt om een koppelingskaart van moleculaire merkers te maken. Wegens een onverwacht hoge graad van heterozygotie van één der kruisingsouders bedekte de kaart 45% van het gerstgenoom. Deze moleculaire merker kaart vormt de basis voor de vervolgstudies die in dit proefschrift beschreven zijn. De genetische diversiteit binnen en tussen 21 populaties is bestudeerd. Deze is vervolgens gerelateerd met diversiteit gebaseerd op milieukarakteristieken en 33 eerder gemeten groei-eigenschappen. De genetische diversiteit was licht gecorreleerd met de milieu diversiteit. In het algemeen was er geen significante correlatie tussen enerzijds de genetische en milieudiversiteit en anderzijds de kenmerkdiversiteit. Enkele merkers waren specifiek voor een bepaald milieutype. Sommigen van deze merkers waren eerder in kaart gebracht en behalve met milieueigenschappen waren zij ook significant gecorreleerd met groei- eigenschappen. Om na te gaan of de waargenomen genetische differentiatie wellicht parallel loopt aan de fenotypische differentiatie, zijn correlaties geschat tussen de gekarteerde merkers en individuele eigenschappen, gemeten in dezelfde 21 populaties.De significante associaties zijn vervolgens vergeleken met eerder gevonden QTL. Veel van deze associaties vallen samen met dezelfde genoomregio’s als de QTL, hetgeen illustreert hoe deze twee verschillende analyses elkaar complementeren. In het laatste deel van dit proefschrift, is de moleculaire merker kaart gebruikt om QTL voor kiemrust bij wilde gerst te vinden. Er werden vijf QTL gevonden, waarvan drie waarschijnlijk eerder zijn beschreven bij cultuurgerst. Voor verder onderzoek is het raadzaam om een nieuwe kruising op te zetten met als doel een kaart te verkrijgen die het gerstgenoom beter bedekt. De resultaten van dit proefschrift dragen bij aan de beschrijving van de genetische aspecten van diverse wilde gerst populaties uit Israël, en vergroten het inzicht in hun potentie voor verbetering van cultuurgerst.

82 Wilde gerst relatief weinig concurrentie van andere Wilde gerst is de voorouder van soorten (Von Bothmer 1992). Wilde cultuurgerst. Hij behoort tot de gerst is verspreid over zeer diverse Poaceae- familie en binnen deze familie klimaatgebieden en bodemtypes in het tot de Triticeae. De Triticeae oostelijk Middellandse zee gebied en in vertegenwoordigen een plantengroep zuidoost Azië. Wilde gerst wordt vooral van de gematigde klimaatzone, aangetroffen in de zogenaamde ‘Near voornamelijk geconcentreerd in Centraal East Fertile Crescent’, een gebied in het en Zuidoostelijk Azië, hoewel de soorten nabije Oosten dat zich, min of meer uit dit taxon over de hele wereld sikkelvormig, uitstrekt van het oostelijk voorkomen. Binnen de Triticeae treffen Middellandse zeegebied tot in Irak en we veel economisch belangrijke granen waar de eerste vormen van landbouw en ruwvoedergewassen aan, naast zijn ontstaan (Zohary 1969). In het ongeveer 350 wilde soorten. De wilde algemeen is wilde gerst niet bestand soorten zijn van groot belang als tegen extreme koude en wordt dan ook potentiële genetische bronnen voor zelden aangetroffen boven 1500 meter commerciële veredeling. hoogte. De droogteresistentie Het genus Hordeum omvat 30 daarentegen is beter dan die van soorten (Von Bothmer 1992), zowel Emmer (wilde tarwe) en de wortels één- als meerjarigen. Afhankelijk van dringen diep in de bodem van de warme het locale klimaat is wilde gerst van het steppes en woestijnen (Zohary & Hopf winter- of zomertype (al dan niet 1988). vernalisatiebehoeftig). Het is een Wilde gerst en twee-rijige diploïde (2n=14) en meestaal cultuurgerst hebben een vergelijkbare zelfbevruchtende plant, hoewel morfologie. De opvallendste verschillen sommige varianten een zekere mate bij wilde gerst zijn de omhulde zaden en van kruisbevruchting vertonen. Het de broze aarspil, waardoor de rijpe gemiddelde zaden op de grond vallen. Zes-rijige kruisbevruchtingspercentage is 1.6%, gerst is ontstaan gedurende de variërend van 0 tot 9.6%, afhankelijk domesticatie van gerst; het kenmerk van de standplaats. In de gematigd- wordt veroorzaak door een hoofdgen op vochtige regio’s is het percentage chromosoom 2 (Komatsuda et al. 1999; kruisbevruchting doorgaans hoger dan Tanno et al. 2002). Wilde gerst is de in de droge regio’s van het enige wilde Hordeum soort die volledig verspeidingsgebied (Brown et al. vruchtbare hybriden oplevert na 1978a). kruising met cultuurgerst (met normale De wilde éénjarige Hordeum soorten chromosoomparing en segregatie in de komen voor in open habitats met meiose). Deze hybriden komen ook van

83 nature voor wanneer wilde en gevolg van selectie. Omdat wilde en cultuurgerst in dezelfde omgeving cultuurgerst probleemloos gekruist voorkomen (Asfaw & Von Bothmer kunnen worden, kan de grotere variatie 1990). in wilde gerst worden benut om De collectie van wilde gerst uit cultuurgerst te verbeteren. Daarom is Israël is bijeengebracht tussen 1974 en het van belang om wilde gerst 1976 (Nevo et al. 1979). Gedurende variëteiten van verschillende locaties deze periode zijn duizenden individuele grondig te bestuderen. Via het planten (accessies) verzameld vanuit bestuderen van de diversiteit, het geheel Israël. Op uiteenlopende maken van een genetische merker plaatsen zoals wegbermen, kaart, alsmede QTL- en berghellingen, akkers en woestijnen zijn associatiestudies levert dit proefschrift monsters genomen. Lengtegraad, een belangrijke bijdrage aan de kennis breedtegraad, hoogte, alsmede over wilde gerst in Israël. neerslag-, vochtigheids- en temperatuurgegevens werden Moleculaire merker kaart van wilde verkregen van nabijgelegen gerst weerstations en zijn toegevoegd aan de Een merkerkaart van wilde gerst is collectiegegevens. Deze collectie wordt gemaakt met de F2 generatie uit de beheerd door professor Eviator Nevo en kruising tussen de accessies ‘Ashkelon’ zijn medewerkers op het Institute of en ‘Mehola’. Daarbij zijn dertien Evolution in Haifa, Israël. In de mircosatelliet merkers en 22 AFLP daaropvolgende jaren zijn extra primer combinaties gebruikt, monsters, afkomstig uit Tabigha (Nevo resulterend in 384 informatieve merkers et al. 1986) en de zogenaamde waarvan er uiteindelijk 202 geplaatst “Evolution Canyon” (Nevo et al. 1995) konden worden op 11 toegevoegd aan de verzameling. koppelingsgroepen. De kaart omspant Accessies van deze verzameling in Haifa 445 centiMorgan (cM) met een zijn over de hele wereld verspreid voor gemiddelde afstand van 2.2 cM tussen onderzoek. Omdat er zoveel accessies de merkers. Om de koppelingsgroepen beschikbaar zijn is er echter maar toe te wijzen aan beschreven weinig overlap tussen de verschillende gerstchromosomen is gebruik gemaakt studies die gebruik maken van deze van 33 AFLP merkers die eerder in kaart collectie. waren gebracht in vier verschillende Wilde gerst populaties zijn kruisingen van cultuurgerst. Ook van de zowel genetisch als fenotypisch zeer microsatellieten was bekend tot welk gevarieerd. Cultuurgerst , daarentegen gerstchromosoom zij behoren. Omdat heeft veel van zijn variatie verloren als één van de kruisingsouders

84 heterozygoot bleek te zijn voor een Tesamen met de resultaten verkregen in groot aantal merkers, beslaat de huidige een andere studie werpt deze analyse kaart ongeveer 45% van het wilde gerst licht op het mechanisme dat ten genoom. Deze kaart is de eerste grondslag ligt aan genotypische en intraspecifieke merkerkaart van wilde fenotypische differentiatie tussen de gerst. wilde gerst populaties.

Genetische, fenotypische en milieu Associatie en QTL analyse variatie in wilde gerst Quantitative trait loci (QTL) voor De genetische en fenotypische variatie uiteenlopende fysiologische is geschat voor 72 Israëlische accessies eigenschappen, die gevonden zijn in de afkomstig van 21 populaties. Deze kruising van twee wilde gerst lijnen zijn populaties kunnen worden opgedeeld in vergeleken met merker-kenmerk vier milieutypes. De lokale associaties die geschat zijn aan 81 wilde milieuvariabelen zijn gebruikt om de gerst accessies. Aan deze accessies zijn milieudiversiteit te schatten. 33 kenmerken gemeten met betrekking Genetische, fenotypische en tot groei, stikstof- en koolstof- milieuafstanden zijn geschat en efficiëntie alsmede plantmorfologie. De vervolgens gebruikt voor de constructie accessies zijn getypeerd voor 68 AFLP van UPGMA dendrogrammen. Tussen merkers, die eerder in kaart waren populaties bleek de genetische variatie, gebracht in de genoemde wilde gerst zoals weerspiegeld door moleculaire kruising dan wel in een kruising tussen merkers, groter te zijn dan binnen gerstrassen. Van deze 68 merkers, populaties , terwijl de fenotypische vertoonden 60 een significante variatie binnen populaties groter was correlatie met één of meerdere dan die tussen populaties. Er was geen kenmerken. Merker-kenmerk associaties significante correlatie tussen genetische bevestigden een aantal van de eerder en fenotypische afstanden noch tussen beschreven QTL resultaten. Voor fenotypische en milieuafstanden. Er was relatieve groeisnelheid werden twee van enige mate van correlatie tussen de vier QTL bevestigd door merker- genetische en milieuafstanden. kenmerk associaties. Vier merkers met Drieëntwintig AFLP-merkers waren een effect op fotosynthese per specifiek voor een bepaald milieutype. bladeenheid lagen op chromosoom 4, Voor vijf van deze merkers was ook de waar ook een QTL voor fotosynthese en chromosoomlocatie bekend. Van deze stomata-geleiding gevonden was. Eén vijf waren vier merkers significant van deze merkers heeft ook een effect gecorreleerd met fenotypische op chlorofyl hoeveelheid wat suggereert kenmerken en milieuvariabelen. dat dit gebied op chromosoom 4 erg

85 belangrijk is voor kenmerken die zijn zaden van F4-lijnen, afkomstig uit de gerelateerd aan fotosynthese. Er was kruising ‘Ashkelon’ х ‘Mehola’, gebruikt één QTL gevonden (op chromosoom 7) en diende de merkerkaart gebaseerd op voor specifiek bladoppervlak. Dit QTL de F2 van deze kruising om QTL te werd ondersteund door de enige localiseren. In totaal zijn vijf QTL merkerassociatie voor dit kenmerk. gevonden voor de verschillende Merkers op chromosoom 1, 2 en 4 tijdstippen van het kiemexperiment. waren sterk gecorreleerd met bladdikte, Deze QTL zijn gevonden op bladbreedte en zaadgewicht, wat chromosoom 1, 2, 5, 6 en 7. Deze QTL suggereert dat deze kenmerken verklaren tussen 8 en 25 % van de genetisch gecorreleerd zijn. variatie in kiempercentage. Voor alle QTL geeft het ‘Ashkelon’-allel een hoger QTL voor kiemrust kiempercentage, met uitzondering van Om de genetische basis van kiemrust bij het QTL op chromosoom 5. Een aantal wilde gerst te ontrafelen is een QTL QTL zijn uniek voor deze studie terwijl analyse uitgevoerd voor deze anderen mogelijk eerder gevonden QTL eigenschap. Voor de kiemproeven zijn bevestigen.

Tiivistelmä

Villiohra on tärkeä geeniluovuttaja viljellylle ohralle, jonka perinnöllinen tausta on kaventunut huomattavasti jalostuksen myötä. Jotta villiohraa voitaisiin käyttää ohralajikkeiden ominaisuuksien parantamiseksi, on tärkeää tutkia villiohran erilaisten ominaisuuksien perinnöllisyyttä. Tämä väitöskirja käsittelee villiohran muutelevuuden eri tasoja, kytkentäkartan tekoa sekä QTL- ja assosiaatiokartoitusta. Tutkitut luonnonpopulaatiot kerättiin 70-luvulla Israelista, joka on hyvin muunteleva ympäristöltään. Kaksi kasvia eri ympäristöistä risteytettiin ja molekyläärisiin merkkialueisiin perustuva kytkentäkartta muodostettiin. Kartta käsitti 45% ohran genomista toisen vanhemman odottamattoman suuren heterotsygotian vuoksi. Tätä karttaa käytettiin kaikissa seuraavissa tämän väitöskirjan tutkimuksissa. Perinnöllinen muuntelu arvioitiin 21 luonnonpopulaation sisällä ja välillä. Tätä muuntelua verrattiin samojen populaatioiden fenotyyppiseen ja ympäristölliseen muunteluun. Perinnöllinen muuntelu korreloi väljästi ympäristön muuntelun kanssa. Yleisesti ottaen fenotyyppinen muuntelu ei korreloinut perinnöllisen eikä ympäristöllisen muuntelun kanssa. Eri ympäristöille ominaisia molekyläärisiä merkkialueita löydettiin. Muutama näistä oli kartoitettu kytkentäkartalle ja ne korreloivat merkittävästi ei vain ympäristömuuttujien vaan myös fenotyyppisten ominaisuuksien kanssa. Korrelaatiot kartoitettujen merkkialueiden ja fenotyyppisten ominaisuuksien välillä laskettiin käyttäen samoja luonnonpopulaatioita. Tilastollisesti merkittäviä merkkialue-fenotyyppinen ominaisuus - korrelaatioita verrattiin aiemmin kartoitettuihin QTL alueisiin. Monet näistä assosiaatioista kartoittuivat samalle alueelle kuin niitä vastaavat QTL-alueet. Lopuksi kytkentäkarttaa käytettiin QTL alueiden löytämiseksi villiohran siemenen itämislevolle. Viisi QTL aluetta löydettiin, joista kolme saattaa olla samoja aiemmin ohralla löydettyjen QTL alueiden kanssa. Tulevaisuudessa olisi hyödyllistä tehdä uusi risteytys suuremman kytkentäkartan muodostamiseksi. Tämän väitöskirjan tulokset lisäävät israelilaisten villiohrapopulaatioiden tuntemusta sekä antavat enemmän mahdollisuuksia villiohran käyttämiseen ohralajikkeiden parantamisessa.

Villiohra lauhkean vyöhykkeen kasviryhmä, joka Hordeum spontaneum (villiohra) on on suurimmaksi osaksi keskittynyt viljellyn ohran esi-isä. Se kuuluu Keski- ja Kaakkois-Aasian alueelle, Poaceae –heinäkasvien sukuun ja sen vaikka siihen kuuluvat lajit ovat sisällä Triticeae –heimoon. Triticeae on levittäytyneet ympäri maailman.

88 Triticeae sisältää monta ekonomisesti aroilla ja aavikoilla (Zohary & Hopf tärkeää viljeltyä vilja- ja rehulajia sekä 1988). myös noin 350 villiä lajia. Nämä villit Villiohra ja viljelty kaksirivinen lajit ovat erittäin mielenkiintoisia ohra ovat aikalailla samanlaisia potentiaalisina geeniluovuttajina ulkomuodoltaan. Suurimmat erot niiden kaupallisessa kasvinjalostuksessa. välillä ovat se, että villiohran siemenet Hordeum -suku käsittää 30 lajia tippuvat kypsyttyään ja se, että (Bothmer 1992). Nämä ovat sekä yksi- villiohran siemenen kuori ei irtoa että monivuotisia lajeja. Villiohra voi olla siemenestä. Kuusirivinen ohra on joko talvella tai kesällä kasvava kehittynyt domestikaation aikana, ja yksivuotinen riippuen paikallisesta sitä kontrolloi geeni kromosomissa 2 ilmastosta. Se on diploidi (2n=14) ja (Komatsuda et al. 1999; Tanno et al. suurimmaksi osaksi itsesiittoinen, 2002). Villiohra on ainoa villi Hordeum - vaikkakin joillakin populaatioilla on laji, joka voi risteytyä viljellyn ohran korkeampi ristisiittoisuusaste. kanssa ja muodostaa täysin Keskimäärin tämä on 1.6%, muunnellen elinvoimaisia ja fertiilejä jälkeläisiä. 0% ja 9.6% välillä, riippuen Näitä villiohran ja viljellyn ohran ympäristöstä; ristisiittoisuus on risteymiä muodostuu myös luonnossa, yleisempää alueilla, joiden maa on jos nämä kaksi lajia kasvavat samassa rehevämpää verrattuna alueisiin, joiden paikassa (Asfaw & Bothmer 1990). maa on köyhää (Brown et al. 1978a). Israelilainen villiohra-kokoelma Villit yksivuotiset Hordeum -lajit kerättiin vuosina 1974-1976 (Nevo et kasvavat avoimilla alueilla, joilla muiden al. 1979). Tuona aikana yli tuhat eri lajien asettama kilpailu kasvualasta on linjaa (linjaksi kutsun tässä yhdestä vähäistä (Bothmer 1992). Villiohran kasvista kerättyjä siemeniä) kerättiin alkuperäinen levinnäisyysalue ulottuu koko Israelin alueelta. Keräyskohteina itäisen Välimeren alueelta aina olivat monet erilaiset habitaatit, kuten Kaakkois-Aasiaan. Se kasvaa tienposket, vuortenkupeet, niityt ja kaikenlaisissa ilmastoissa ja maaperissä. aavikot. Paikkakoordinaatit, korkeusaste Se on erittäin yleinen Lähi-Idän ja erilaiset sade- ja kosteustiedot sekä Hedelmällisen Puolikuun alueella lämpötilat otettiin ylös läheisiltä (Zohary 1969). Yleisesti ottaen villiohra sääasemilta. Tätä kokoelmaa pidetään on herkkä erittäin kylmille lämpötiloille, yhä yllä Evoluutioinstituutissa Haifassa. ja sitä löydetään vain harvoin yli 1500 Pääkokoelmaan on sen keräysvuosien m korkeudesta. Villiohra on kuitenkin jälkeen liitetty enemmän populaatioita kuivuudenkestävämpi kuin esimerkiksi Tabighan alueelta Kinneret-järven villivehnä ja kasvaa myös lämpimillä rannalta (Nevo et al. 1986) ja Evoluutio Kanjonista Haifan lähistöltä (Nevo et al.

89 1995). Näitä villiohrapopulaatioita on solun kromosomit muodostavat yksilön jaettu ympäri maailman, mutta genomin. kokoelman suuruuden takia useimmat Jokainen DNA- tutkimusryhmät tutkivat eri linjoja kaksoisjuostemolekyyli sisältää suuren populaatioiden sisällä, ja koska määrän perintötekijöitä eli geenejä. populaatioiden sisällä on muuntelua, Geeni on pätkä DNA’a, joka koodaa tutkimuksia ei voi helposti vertailla erilaisia valkuaisaineita. Geeni ei koostu keskenään. välttämättä vain valkuaisaineita koodaavasta emäsjärjestyksestä vaan myös emäsparijaksoista, jotka leikataan DNA, elämän perusta pois geenistä muodostetusta kopiosta Deoksiribonukleiinihappo, eli DNA, on ennen valkuaisaineen koodausta. kaiken elämän perusta (lukuunottamatta RNA viruksia). DNA- DNAn merkkialueet ja niiden käyttö kaksoisjuoste muodostuu kahdesta tutkimuksissa yhteen liitetystä neljän eri emäksen, Koska jokaisen yksilön genomin adeniinin (A), sytosiinin (C), tymiinin (T) sekvensointi ei ole vielä mahdollista, ja ja guaniinin (G), ketjusta. Nämä kaksi koska emme vielä tiedä jokaisen geenin ketjua ovat suurimmaksi osaksi rakennetta, niiden vuorovaikutuksia toistensa peilikuvia ja liittyvät yhteen sekä tehtävää, perinnöllisissä vetysidoksin siten, että A pariutuu aina tutkimuksissa käytetään usein hyväksi T:n kanssa ja C G:n kanssa muistuttaen DNA merkkialueita. Merkkialueet ovat pitkiä tikapuita. Tämä DNA- pieniä DNA pätkiä, ja ovat kuin kaksoisjuoste kiertyy ensin kilometripylväitä DNA-ketjussa. pituusakselinsa ympäri ja sitten histoni- Merkkialueet saattavat olla geenien valkuaisaineen ympärille, jotka taas sisällä tai niiden välissä. Merkkialueita pakkautuvat tiiviisti yhteen solun käytetään hyväksi esimerkiksi yksilöiden jakautumisen lähestyessä muodostaen perinnöllisen muuntelevuuden kromosomin toisen puolen, jos kyseessä havainnoimiseksi sekä tutkimalla mitkä on diploidi eliö. Yksi kromosomi merkkialueista liittyvät tiettyihin muodostuu siis kahdesta tietyn fenotyyppisiin ominaisuuksiin. pituisesta pakkautuneesta DNA- Merkkialueet voidaan laittaa kaksoisjuosteesta, jotka ovat liittyneet järjestykseen tekemällä risteytys yhteen tietystä kohtaa solun kahden eri yksilön kesken ja jakautumisen ajaksi. Kromosomi analysoimalla tämän risteytyksen muistuttaa muodoltaan pyykkipoikaa. jälkeläistön merkkialueet, jotka eroavat Jokaisessa yksilön solussa on samat ja vanhemmissa. Järjestys saadaan yhtä paljon kromosomeja. Kaikki yhden aikaiseksi arvioimalla, mitkä

90 merkkialueista käyttäytyvät samalla haluttu geeni on löydetty, se voidaan tavalla ja siten kytkeytyvät toisiinsa. siirtää haluttuun yksilöön parantamaan Näin voidaan muodostaa koko sen tuottoa. kromosomin kattava merkkialueisiin perustuva kytkentäkartta. Villiohran kytkentäkartta Kytkentäkarttaa voidaan taasen Villiohran molekyläärinen merkkialue käyttää hyväksi eri fenotyyppisten kytkentäkartta tehtiin käyttäen ominaisuuksien kartoittamiseksi risteytyksen ‘Ashkelon x Mehola’ F2 tiettyihin kromosomien osiin. Useat populaatiota. Käytetyn Ashkelon-linjan kaupallisesti tärkeät fenotyyppiset alkuperäinen keräyspaikka on tienvarsi ominaisuudet, kuten viljojen Välimeren rannalla sijaitsevan Ashkelon siementuotto tai lehmän kaupungin laitamilla, kun taas Mehola maidontuotanto, ovat jatkuvia eli kerättiin Jordan joen rannalta Kinneret kvantitatiivisia ominaisuuksia. Näitä ei järven ja Kuolleen Meren välimaastosta. yleensä ohjaa vain yksi geeni, vaan Nämä kaksi lijaa valittiin niiden niiden perustana on monta eri geeniä. erilaisten ympäristöolosuhteiden ja Näitä kvantitatiivisia ominaisuuksia kasvuominaisuuksien pohjalta. voidaan kartoittaa liittämällä niissä Kolmetoista mikrosatelliittia ja 22 AFLP havaittu muuntelu merkkialueisiin (ns. alukeparia käytettiin 384 muuntelevan kvantitatiivinen ominaisuuslokus eli QTL merkkialueen saamiseksi, joista analyysi, jossa käytetään hyväksi loppujenlopuksi 202 pystyttiin risteytyksiä tai sitten yksinkertainen kartoittamaan 11 kytkentäryhmään. assosiaatioanalyysi, jossa suurta Kahta kytkentäryhmää ei pystytty määrää eri linjoja tai populaatioita tunnistamaan minkään kromosomin käytetään hyväksi). Tällätavoin perimän osaksi, muut muodostivat osia kaikista merkkialueet voivat mm. ennustaa sen, ohran seitsemästä kromosomista. millaisia tuotteita tai miten paljon eri Kartoitettu alue oli 445 senttiMorgania yksilöt tuottavat tulevaisuudessa. Kun (cM). Keskimääräinen etäisyys kahden merkkialueet on saatu liitettyä tiettyihin merkkialueen välillä oli 2.2 cM. Jotta ominaisuuksiin (ns. QTL alueet), kartan kytkentäryhmät voitiin tunnistaa voidaan niitä käyttää myös hyväksi tunnettujen ohran kromosomien osiksi, jalostuksessa. Tavanomaisessa 33 AFLP- ja 13 jalostuksessa niitä voidaan käyttää eri mikrosatelliittimerkkialuetta, jotka olivat risteytysmenetelmien kanssa aiemmin kartoitettu viljellyn ohran varmistamassa, että haluttu alue kytkentäkarttoihin, otettiin mukaan. kromosomia on mukana. Niitä voidaan Koska toinen vanhemmista oli yllättäen myös käyttää itse ominaisuuksiin heterotsygoottinen monen merkkialueen vaikuttavien geenien etsimiseen. Kun suhteen, kytkentäkartan kattavuus on

91 arvioitu olevan suurimmillaan 55% etäisyyksien välilläkään. Hyvin ohran genomista. Tämä kytkentäkartta hienoinen korrelaatio havaittiin on ensimmäinen villiohran lajinsisäinen perinnöllisen ja ympäristön etäisyyksien kartta. välillä. Kaksikymmentäkolme AFLP merkkialuetta tunnistettiin Villiohran perinnöllinen, ekotyyppispesifiseksi, eli niiden fenotyyppinen ja ympäristön muuntelu oli erilainen eri ekotyyppien muuntelu välillä. Näistä viisi oli kartoitettu. Neljä Perinnöllinen ja fenotyyppinen muutelu näistä kartoitetuista arvioitiin 72 linjan ja 21 villiohran ekotyyppispesifisestä merkkialueesta luonnonpopulaation sisällä ja välillä. korreloi sekä ympäristön että Nämä populaatiot ryhmitettiin lisäksi fenotyyppisten ominaisuuksien kanssa. neljään erilaiseen ympäristötyyppiin eli Näin havaittiin suora yhteys perimän, ‘ekotyyppiin’. Perinnöllisen ja fenotyypin ja ympäristön kanssa. fenotyyppisen muuntelun lisäksi Tarkemmat mikroklimaattiset ympäristömuuntelu arvioitiin eri ympäristötiedot ja epäoptimaalisissa ympäristömuuttujista, jotka kuvaavat olosuhteissa mitatut fenotyyppiset paikallisia populaatioiden ominaisuudet mahdollistaisivat ympäristöolosuhteita. Perinnölliset, paremman ympäristön, perimän ja fenotyyppiset ja ympäristölliset fenotyyppisten ominaisuuksien etäisyydet arvioitiin eri linjojen ja vertailun. populaatioiden välillä ja UPGMA dendrogrammit (‘sukupuut’) Villiohran assosiaatioanalyysi ja sen rakennettiin niiden pohjalta. Tulokset vertailu aiemmin löydettyihin QTL osoittivat, että perinnöllinen muuntelu alueisiin oli suurempaa populaatioiden välillä Aiemmassa tutkimuksessa havaittuja kuin niiden sisällä, ja siten QTL alueita vertailtiin merkkialueiden ja populaatiorakenne havaittiin odotetusti. fenotyyppisten ominaisuuksien Fenotyyppinen muuntelu oli taasen assosiaatioihin, jotka oli arvioitu 81 täysin päinvastaisesti enemmän villiohralinjassa. Näissä linjoissa populaatioiden sisällä kuin välillä, eikä mitattiin 33 eri fenotyyppistä kasvuun, populaatiorakennetta havaittu. hiili ja typpiekonomiaan sekä Toisinsanoen eri populaatioiden välillä ei morfologiaan liittyvää ominaisuutta. ollut niitä selkeästi eroittavia eroja. Linjat genotyypattiin ja tässä Perinnöllisten ja fenotyyppisten tutkimuksessa käytettiin 68 AFLP etäisyyksien väillä ei siten ollut mitään merkkialuetta, jotka oli aiemmin korrelaatiota. Korrelaatiota ei havaittu kartoitettu viljellyn ohran ja villiohran fenotyyppisen ja ympäristön kytkentäkartoille. Näistä 68

92 merkkialueesta 60 korreloi tilastollisesti taustan tutkimiseksi. Kun siemen on merkittävästi yhden tai useamman itämislevossa, se ei idä, vaikka se olisi fenotyyppisen ominaisuuden kanssa. tarpeeksi kypsä ja vaikka olosuhteet Useat näistä merkkialue-ominaisuus itämiselle olisivat optimaaliset. assosiaatioista tukivat aiemmin Useimmat viljellyt ohralajikkeet ovat havaittuja QTL alueita. Merkkialue- menettäneet itämisleponsa lähes suhteellinen kasvunopeus -assosiaatiot kokonaan. Tietynasteinen itämislepo on tukivat kahta neljästä suhteellisen kuitenkin tärkeä, koska ilman sitä kasvunopeuden QTL alueesta. Neljä siemen saattaa itää tähkässä ennen merkkialuetta, jotka liittyvät kasvin sadonkorjuuta. Luonnossa itämislepo on yhteyttämisnopeuteen, kartoitettiin erittäin tärkeä varsinkin epävakaassa kromosomiin 4, johon oli kartoitettu ympäristössä, jolloin itäminen väärään myös yhteyttämisnopeuden ja lehden aikaan saattaa aiheuttaa taimen ilmarakojen konduktanssin QTL alueet. kuolemisen. Liian voimakas itämislepo Yksi näistä neljästä merkkialueista viljellyssä ohrassa on taasen myös korreloi myös viherhiukkasmäärän huono asia, koska siemenet täytyy kanssa, ehdottaen, että tämä säilöä tietynlaisessa ympäristössä kromosomialue saattaa olla hyvinkin kunnes itämislepo saadaan poistettua. tärkeä kasvin yhteyttämiseen liittyville Liian voimakas itämislepo aiheuttaa ominaisuuksille. Yksi spesifisen lehtialan myös rikkaruohoefektin pelloilla, joilla QTL alue kartoitettiin kromosomiin 7. seuraava viljelty laji ei ole Tätä QTL aluetta tuki merkkialue- samanlajikkeinen ohra. Tämän spesifinen lehtiala assosiaatio. tutkimuksen villiohran siementen

Spesifinen lehtiala on tärkeä itävyys testattiin F4 populaatioissa. suhteellisen kasvunopeuden Yhteensä viisi QTL aluetta havaittiin eri osakomponentti. Merkkialueet itävyystesteissä. Nämä QTL alueet kromosomeissa 1, 2 ja 4 liittyivät sijoittuivat kromosomeihin 1, 2, 5, 6 ja vahvasti lehden paksuuteen ja 7. Eri QTL alueet selittivät 8% - 25% leveyteen sekä siemenpainoon, näin itävyyden kokonaismuuntelusta. ehdottaen, että nämä ominaisuudet Ashkelon alleelit nostivat itävyyttä paitsi ovat perinnöllisesti kytkeytyneitä kromosomi 5’n QTL alue, jossa Mehola toisiinsa. alleeli paransi itävyyttä.

Villiohran siemenen itämislepoon liittyvät QTL alueet QTL analyysi suoritettiin villiohran siemenen itämislevon perinnöllisen

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103 Arnold RL (2001) Predicting Schuurink RC, Van Beckum JMM, preharvest sprouting susceptibility Heidekamp F (1992) Modulation of in barley: A model based on grain dormancy in barley by temperature during grain filling. variation of plant-growth Agron J 93: 1071-1079. conditions. Hereditas 117: 137-143. Romagosa I, Han F, Clancy JA, Ullrich Shipley B, Peters RH (1990) The SE (1999) Individual locus effects allometry of seed weight and on dormancy during seed seedling relative growth rate. development and after ripening in Functional Ecology 4: 523-529. barley. Crop Sci 39: 74-79. Song WN, Henry RJ (1995) Molecular Rouppe van der Voort JNAM, van analysis of the DNA polymorphism Zandvoort P, van Eck HJ, of wild barley (Hordeum Folkertsma RT, Hutten RCB, spontaneum) germplasm using the Draaistra J, Gommers FJ, Jacobsen polymerase chain reaction. Genet E, Helder J, Bakker J (1997) Use of Resour Crop Evol 42: 273-280. allele specificity of comigrating Stacy RAP, Munthe E, Steinum T, AFLP markers to align genetic maps Sharma B, Aalen RB (1996) A from different potato genotypes. peroxiredoxin antioxidant is Mol Gen Genet 255: 438-447. encoded by a dormancy-related Russell JR, Fuller JD, Macaulay M, Hatz gene, Per1, expressed during late BG, Jahoor A, Powell W, Waugh R development in the aleurone and (1997) Direct comparison of levels embryo of barley grains. Plant Mol of genetic variation among barley Biol 31: 1205-1216. accessions detected by RFLPs, Stam P (1993) Construction of AFLPs, SSRs and RAPDs. Theor Appl integrated genetic linkage maps by Genet 95: 714-722. means of a new computer package: Saghai Maroof MA, Zhang Q, Biyashev JOINMAP. Plant J 3: 739-744. R (1995) Comparison of restriction Storey JD (2002) A direct approach to fragment length polymorphisms in false discovery rates. Journal of the wild and cultivated barley. Genome Royal Statistical Society, Series B 38: 298-306 64: 479-498. Schut JW, Qi X, Stam P (1997) Storey JD, Tibshirani R (2003) Association between relationship Statistical significance for measures based on AFLP markers, genomewide studies. P Natl Acad pedigree data and morphological Sci USA 100: 9440-9445. traits in barley. Theor Appl Genet Thomas WTB, Powell W, Swanston JS, 95: 1161-1168. Ellis RP, Chalmers KJ, Barua UM, Jack P, Lea V, Forster BP, Waugh R,

104 Smith DB (1996) Quantitative trait in Israel. Theor Appl Genet 106: loci for germination and malting 1333-1339. quality characters in a spring barley Ullrich SE, Hayes PM, Dyer WE, Blake cross. Crop Science 36: 265-273. TK, Clancy JA (1992) Quantitative Tanksley SD, McCouch SR (1997) Seed trait locus analysis of seed banks and molecular dormancy in ‘Steptoe’ barley. pp maps:unlocking genetic potential 136-145. In Walker-Simmons MK from the wild. Science 277: 1063- and Ried JL (eds) Preharvest 1066. sprouting in cereals 1992. Am Tanno K, Taketa S, Takeda K, Assoc Cereal Chem, St Paul, MN. Komatsuda T (2002) A DNA marker Van Hintum TJL (1994) Drowning in closely linked to the vrs1 locus the genepool; managing genetic (row-type gene) indicates multiple diversity in genebank collections. origins of six-rowed cultivated Dissertation. Förvaltningsavdelnings barley (Hordeum vulgare L.). Theor Repro, Alnarp, Sweden. Appl Genet 104: 54-60. Van Ooijen JW, Maliepaard C (1996) This D, Borries C, Souyris I, Teulat B MapQTL ™ version 4.0: Software (2000) QTL study of chlorophyll for the calculation of QTL positions content as a genetic parameter of on genetic maps. CPRO-DLO, drought tolerance in barley. Barley Wageningen. Genetics Newsletter http://www.kyazma.nl http://grain.jouy.inra.fr/ggpages/b Van Ooijen JW (1999) LOD significance gn/30/dt2_2.htm thresholds for QTL analysis in Turpeinen T, Kulmala J, Nevo E (1999) experimental populations of diploid Genome size variation in Hordeum species. Heredity 83: 613-624. spontaneum populations. Genome Van Ooijen JW, Voorrips RE (2000) 42: 1094-1099. Joinmap version 3.0: Software for Turpeinen T, Tenhola T, Manninen O, the calculation of genetic linkage Nevo E, Nissilä E, (2001) maps. Plant Research International, Microsatellite diversity associated Wageningen, The Netherlands. with ecological factors in Hordeum Van Rijn CPE, Hirsche I, Van Berkel spontaneum populations in Israel. YAM, Nevo E, Lambers H, Poorter H Molecular Ecology 10: 1577-1591. (2000) Growth characteristics in H. Turpeinen T, Vanhala T, Nevo E, Nissila spontaneum populations from E (2003) AFLP genetic different habitats. New Phytologist polymorphism in wild barley 146: 471-481. (Hordeum spontaneum) populations Van Rijn C (2001) A physiological and genetic analysis of growth

105 characteristics in Hordeum Wang M (1997) The role of abscisic spontaneum. Dissertation. Ponsen acid in the regulation of barley and Looijen B.V., Wageningen, The grain germination. Seed Sci Technol Netherlands. 25: 67-74. Verhoeven K (2003) A genetic analysis Yin X, Stam P, Dourleijn CJ, Kropff MJ of selection and adaptation in wild (1999) AFLP mapping of barley. Dissertation. Ponsen and quantitative trait loci for yield- Looijen B.V., Wageningen, The determining physiological Netherlands. characters in spring barley. Theor Verhoeven KJF, Biere A, Nevo E, van Appl Genet 99: 244-253. Damme JMM (2004a) Differential Zohary D (1969) The progenitors of selection of growth rate-related wheat and barley in relation to traits in wild barley, Hordeum domestication and agricultural spontaneum, in contrasting dispersal in the old world. In Ucko greenhouse nutrient environments. PJ, Dimbleby GW (eds) The J Evol Biol 17: 184-196. domestication and exploitation of Verhoeven KJF, Vanhala TK, Biere A, plants and animals. General Nevo E, van Damme JMM (2004b) Duckworth and Co. Ltd., London, pp The genetic basis of adaptive 47-66. population differentiation: A Zohary D, Hopf M (1988) quantitative trait locus analysis of Domestication of plants in the old fitness traits in two wild barley world. Oxford: Clarendon Press. populations from contrasting habitats. Evolution 58 (2): 270- 283. Vos P, Hogers R, Bleeker M, Reijans M, Van de Lee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP:a new technique for DNA fingerprinting. Nucl Acids Res 23: 4407-4414.

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Addresses of co-authors:

Piet Stam, Fred van Eeuwijk Laboratory of Plant Breeding, Department of Plant Sciences, Wageningen University, P.O.Box 386, 6700 AJ Wageningen, The Netherlands

Cynthia van Rijn, Hendrik Poorter Plant Ecophysiology, Utrecht University, P.O.Box 800.84, 3508 TB Utrect, The Netherlands

Jaap Buntjer Keygene NV, P.O.Box 216, 6700 AE Wageningen, The Netherlands

Eviatar Nevo Institute of Evolution, University of Haifa, Haifa 31905, Israel

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Acknowledgements

In many ways plants are easier to work I would also like to thank all with than animals. For example they the people in the department during the can’t run away or make noises when years that I worked there. The labs at you are taking a sample… But there is the department are organised and the other side that I found out when I managed expertly by a league of was spending endless hours in the fantastic technicians. Thanks for the greenhouses bagging plants, planting, support especially to Petra, Fien and tying them to canes or taking samples. Elly. Thanks for all the colleagues, with In hot summer weather the greenhouse whom I’ve shared some good times. was pretty much a good substitute for It was not all work at the sauna. Although, alas, there was no department, we had plenty of time for lake within a jumping distance. cake eating as well. Thanks for all the My promotor, professor Piet delicious treats for the members of our Stam deserves the first place in the cake-club! acknowledgements. He has always been This thesis is the last one of there for me in any situation, good or four within the bigger research bad, helping and advising. Without his programme. I have fully enjoyed the co- time and help this thesis would not have operation with Ivonne Elberse, Koen been possible. I wish him all the best for Verhoeven and Cynthia van Rijn, not to the remainder of his working career and mention their supervisors Peter van loads of relaxing and happy years of Tienderen, Arjen Biere, Jos van Damme retirement. and Hendrik Poorter. We had our ups Thanks are also in order for all and downs, mainly due to the wildness my supervisors Johan Dourlijn, Jaap of wild barley, but in the end everything Buntjer and Fred van Eeuwijk. They all worked out rather well. We also shared contributed to the work I did in their a very interesting field trip to Israel in own fields of expertise. Special thanks the spring of 2000. It was an eye- to Jaap, who didn’t mind me turning opener to the diverse nature in Israel. around and bugging him anytime I had Unforgettable trip, and fortunately we a question or request for some managed to see also other things improvement to his program. besides wild barley.

108 The plants we were all working stable at Macmerry and in Temple Farm with were kindly supplied by prof. at Temple, where we stable our Eviatar Nevo, from the Institute of gorgeous gentleman, Jack, have been Evolution in Haifa, Israel. I would like to vital in getting us settled down. Who thank him in my part for his hospitality could forget the speed gallops at the during our trip to Israel and showing us beaches of Dunbar or the beautiful around the famous Evolution Canyon. mornings out hacking on the Temple A year or two before my fields with good company (or winter contract was to end, we started thinking days in the caravan with a cup of hot where to go afterwards. I liked living in chocolate and a biscuit)! Thanks are due the Netherlands, but missed the space to all our stable mates and riding pals! and nature dearly. So, we decided upon And a big apple for Jack for bearing me Edinburgh. My husband found a job in even when I sometimes didn’t manage Roslin and I found my way to Deborah to let go of working day and failed to Charlesworth with the help of Peter give him the fair attention he needs… Visscher. Thank you Deborah, for taking Of course nothing of this would me in with the burden of my ‘unfinished have been possible without the support business’. I have thoroughly enjoyed of my family. They have always stood (and still am) working in Edinburgh by my decisions and encouraged me to among lovely colleagues, thanks for be what I wanted to be, even though bearing with me during the last part of this has taken me quite far away from this thesis! them. However, the physical distance As many people, who come has actually brought us even closer. into contact with me, know, work is not Many, many thanks for my parents for everything to me. A big chunk of my being there for me! Kiitokset Isälle ja spare time is spend with horses (and if Äidille, ilman teidän tukea tähän asti not horses, it’ll be growing things in the pääseminen olisi ollut vaikeaa. garden, and if not garden, it’ll be Then there is my dear walking the hills…). Luckily I managed husband, Dirk-Jan. He has been the to lure my husband into the hobby as most important support and motivator well. Riding and just taking care of the in the course of this research project. horses has been the perfect stress- On numerous accounts he has helped releaser. With horses you will have to with good advice, critical views, analysis give your undivided attention to them and editing. He has kicked me on, when and leave the working day behind. The I have needed it, loved me and kept me social circles in Whiteloch Farms riding sane… Dank je wel, lieffie!

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The Road goes ever on and on Down from the door where it began. Now far ahead the Road has gone, And I must follow, if I can, Pursuing it with eager feet, Until it joins some larger way Where many paths and errands meet. And whither then? I cannot say.

The Road goes ever on and on Out from the door where it began. Now far ahead the Road has gone, Let others follow it who can! Let them a journey new begin, But I at last with weary feet Will turn towards the lighted inn, My evening-rest and sleep to meet.

Still round the corner there may wait A new road or a secret gate; And though I oft have passed them by, A day will come at last when I Shall take the hidden paths that run West of the Moon, East of the Sun.

JRR Tolkien

110

Curriculum vitae

Tytti Kaarina Vanhala was born in June the 18th 1971 in Saarijärvi, Finland, in the middle of thousands of lakes and hectares of forests. She went to the comprehensive school in Saarijärvi 1978 – 1987. After the basic education she continued to study in Lukio in Saarijärvi and graduated in 1990. Until the last exams she was unsure where to continue her studies, favourites were history (archaeology) and information science (the one to do with libraries, not computers). But then, at the last moment, she realised that what really interested her was biology. She took her entrance exams in mind to study cell and molecular biology in the University of Jyväskylä, but got into the University of Oulu instead. In the meanwhile she was also admitted to a professional school to study to be a seamstress. But in the end life in science lured her more than career in fashion. In Oulu she chose to study genetics, and was not deterred even after the first genetics courses involving sucking Drosophilas out of their bottles with glass tubes… Wanting to work in animal genetics she did her practical period in the Agricultural Research Centre of Finland in Jokioinen during the summer of 1993. Her main research there consisted of typing bulls for their kappa-kasein locus. In the autumn of 1994 she returned to Jokioinen to start her Master’s thesis research. Her task was to look into the genetic variation within and between several chicken lines using microsatellite markers. Towards the end of the year, she decided it was time for some foreign experience before graduation and she applied to go to the Trinity College in Dublin for an Erasmus exchange. Unfortunately their quota was filled, and in the autumn of 1995 she went to Wageningen University, The Netherlands, instead. During her 9 months stay at the department of Animal Beeding and Genetics, she helped to find and develop more microsatellite markers in the chicken genome. After the stay in the Netherlands she finished her studies in the University of Oulu, formally graduating on 7th of April 1997. Before that she had already moved back to Wageningen following her boyfriend’s work. In October 1997 she started as an OIO in the department of Plant Breeding in Wageningen, the results of the research being accounted in this thesis. In the end of September 2001 she moved to Cowbraehill, Scotland, on a side of a hill amongst the sheep. She started working with sequence diversity in Antirrhinum, and later Silene, in the Institute for Cell, Animal and Population Biology, University of Edinburgh, Scotland. At first she was funded by the Marie Curie fellowship for half a year, and subsequently by Leverhulme Trust.

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