DEVELOPMENT AND USE OF cDNA-DERIVED SSR MARKERS FOR STUDYING
PUCCINIA STRIIFORMIS POPULATIONS AND MOLECULAR MAPPING OF
NEW GENES FOR EFFECTIVE RESISTANCE TO STRIPE RUST
IN DURUM WHEAT
By
PENG CHENG
A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY
WASHINGTON STATE UNIVERSITY Department of Plant Pathology AUGUST 2012
To the Faculty of Washington State University:
The members of the Committee appointed to examine the dissertation of PENG
CHENG find it satisfactory and recommend that it be accepted.
Xianming Chen, Ph.D., Chair
Scot H. Hulbert, Ph.D.
Tobin Peever, Ph.D.
Kulvinder Gill, Ph.D.
ii
ACKNOWLEDGMENTS
I am very grateful to Dr. Xianming Chen for providing me such a great opportunity to study in his program. I want to thank Dr. Chen for his time, advice and encouragement for my course work and research. Also, I would like to thank Dr. Scot Hulbert, Dr. Tobin Peever, and Dr. Kulvinder Gill for serving on my committee and their precious suggestions for my studies in the department, including the classes and research, and their time for critically reviewing my dissertation. Special thanks to Dr. Brenda Schroeder, Dr. Lori Carris, Dr. Hanu
Pappu, Dr. Lee A. Hadwiger, and Dr. Patricia Okubara for their big encouragement and nice advice during my graduate study.
I also want to show my appreciation to my colleagues in our laboratory, especially Dr.
Meinan Wang, Dr. Anmin Wan, and Dr. Kent Evans for helping me in the lab and greenhouse work. I also like to thank my collaborators Dr. Chuntao Yin and Dr. Paul Ling for the stripe rust EST libraries. I thank all my fellow graduate students and friends for being there to share all the good and bad times with me. Special thanks to the office staffs in the
Department of Plant Pathology for their help and support during my graduate study. Last but not least, I want to express my appreciation to my husband Dr. Liangsheng Xu for his support, sacrifice, understanding, and love.
iii
DEVELOPMENT AND USE OF cDNA-DERIVED SSR MARKERS FOR STUDYING
PUCCINIA STRIIFORMIS POPULATIONS AND MOLECULAR MAPPING OF
NEW GENES FOR EFFECTIVE RESISTANCE TO STRIPE RUST
IN DURUM WHEAT Abstract
by Peng Cheng, Ph.D. Washington State University August 2012
Chair: Xianming Chen
Puccinia striiformis , a basidiomycete fungus, produces dikaryotic urediniospores causing stripe rust of wheat, barley, and many grass species. To study its population biology, three cDNA libraries were screened for simple sequence repeats (SSRs) and their flanking sequences were used to design primers. Seventeen primer pairs which produced stable polymorphic markers among 28 isolates of the pathogen were demonstrated to be useful for population studies.
To characterize stripe rust on grasses and determine if somatic hybridization occur between P. striiformis f. sp. tritici (Pst , the wheat stripe rust pathogen) and P. striiformis f. sp. hordei (Psh , the barley stripe rust pathogen), 103 isolates from wheat, barley, and various grasses were tested on 20 wheat and 12 barley genotypes that are used to differentiate races of Pst and Psh , respectively. Virulence analyses indicated that some grass isolates were able to attack some differential genotypes of wheat, barley, or both. Molecular testing with 20 SSR markers showed that some of the grass isolates are hybrids between Pst and Psh . The results suggest that somatic hybridization occurs between Pst and Psh on grasses.
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To determine how the Pst population reproduces in the US Pacific Northwest (PNW), a systemic collection of single-stripe samples were made in 2010 in 26 wheat fields in the
PNW especially the Palouse region, where plants of Berberis vulgaris , an alternate host of P. striiformis , still grow. Twenty one races and 66 molecular haplotypes were identified. The
SSR marker data revealed two genetic groups: homokaryotic (most PNW isolates) and heterokaryotic (most non-PNW US isolates). The different karyotypes were related to the groups of races. The analysis of multi-locus association ruled out the possibility of sexual reproduction in the PNW population.
Because growing resistant cultivars is the most effective approach to control stripe rust and new resistance genes are needed in breeding programs, studies were conducted to identify and map new genes for effective resistance. Two mapping populations were developed by crossing durum wheat genotypes PI 331260 and PI 480016 with susceptible common spring wheat genotype Avocet Susceptible (AvS). A single dominant resistance gene was identified in each of the mapping populations. Using wheat SSR markers, both genes were mapped to wheat chromosome 1BS, but at different loci. Common wheat lines with these genes were selected for breeding programs to develop stripe rust resistant cultivars.
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TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS……………………………………………………………………iii
ABSTRACT…………………………………………………………………………………..iv
LIST OF TABLES…...... viii
LIST OF FIGURES…………………………………………………………………………....x
DEDICATION…………………………………………………………………………….....xii
CHAPTER
1. Literature review……………………………..…………………………………………...1
Stripe rust ……………....……...…………………………………….……………..……….1 Control of wheat stripe rust ……………………………………….………..…….…….....13 References …...…………………………..…………………………………………………22
2. Development and characterization of expressed sequence tag-derived microsatellite markers for the wheat stripe rust fungus Puccinia striiformis f. sp. tritici …..……...... 36
Abstract ………………………………………………………………………………….36 Introduction ……………………………..……………………………………………….…..37 Material and methods ……………………………………………………………….…...37 Results ….…………………………………………………………………………...……....41 Discussion ……………………………………………………………………………….…42 References ……...…………………………………………………………………………..46
3. Somatic hybridization between wheat stripe rust Puccinia striiformis f. sp. tritici and barley stripe rust ( P. striiformis f. sp. hordei ) in grasses revealed by virulence patterns and microsatellite markers...... 48
Abstract ………………………………………………………………………………….48 Introduction …..………………………………………………………………………...…....49 Material and methods ………………………………………………………………...….53 Results ….…………………………………………………………………………………...64 Discussion ……………………………………………………………...... ……………...84 References ……...…………………………………………………………………..………91
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4. Virulence and microsatellite markers revealed only asexual reproduction in the US Pacific Northwest Puccinia striiformis f. sp. tritici population...... 99
Abstract .………...……………………………………………………………………….99 Introduction ……..……………………………………………………………………...…..100 Material and methods ………………………………………………………………...... 104 Results ……………………….………………………………………………………….....113 Discussion ……………………………………………………………...... …………...133 References …...……………………………………………………………………………139
5. Molecular mapping of two genes for stripe rust resistance in durum wheat genotypes PI 331260 and PI 480016 from Ethiopia...... 146
Abstract ………………………………………………………………………………...146 Introduction ………………………..……………………………………………………….147 Material and methods ……………………………………………………………….….149 Results ………………………………….…………………………………………...……..156 Discussion …………………………………………………………………………...……163 References …...……………………………………………………………………………166
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LIST OF TABLES
Chapter 1
1. Wheat genotypes used to differentiate races of Puccinia striiformis f. sp. tritici in the United States…….………………………………...……………………...... …5
2. Wheat single gene lines used to differentiate races of Puccinia striiformis f. sp. tritici in the United States…….……………………..……………………………...... …6
3. Barley genotypes used to differentiate races of Puccinia striiformis f. sp. tritici in the United States…….……………………………………...………………...... …7
4. Comparison of all-stage resistance and HTAP resistance…………………………….....15
5. Genes for resistance to stripe rust ( Puccinia striiformis f. sp. tritici ), examples of wheat genotypes containing the genes, their chromosomal locations, types of resistance, and references.……………………………………………………...…...... …19
Chapter 2
1. Seventeen EST-SSR markers for Puccinia striiformis f. sp. tritici and their primer sequences, PCR annealing temperature, number of alleles and product size range, allele frequency, observed (Ho) and expected (He) heterozygosity, cross-species amplification, corresponding supercontig identification numbers of Puccinia striiformis f. sp. tritici (Pst ), P. graminis f. sp. tritici (Pgt ) and P. triticina (Pt )………………………………...39
Chapter 3
1. Hosts, collection locations, Puccinia striiformis f. sp. tritici (Pst ) and P. striiformis f. sp. hordei (Psh ) races, virulence phenotypes with combination of wheat and barley differential tests, and haplotypes and groups identified through molecular analysis of stripe rust isolates collected from wheat, barley, triticale, rye and various grasses……..54
2. Primer sequences, annealing temperatures and amplified fragment sizes of 20 microsatellite markers………...…………………….………………..………………….62
3. Virulence phenotypes, Puccinia striiformis f. sp. tritici (Pst ) and P. striiformis f. sp. hordei (Psh ) races identified from isolates of P. striiformis isolates collected from wheat, barley, triticale, rye, and various grasses………………………………………………...69
4. The mutation-scaled population size ( Θ), and migration rates (M) among the Puccinia striiformis populations from wheat, barley, and wild grasses based on the SSR data…..75
viii
5. Genotype assignment based on allele frequencies with 44 haplotypes from different hosts……………………………………………………………………………………...76
Chapter 4
1. Number of isolates, races, virulence group, haplotypes, and molecular group in collection regions…………………………………………………………………………….……106
2. Primer sequences, annealing temperatures (Tm) and primary sizes of amplified alleles of 20 microsatellite markers………………………………...…………………………….110
3. Puccinia striiformis f. sp. tritici races and their virulence formula, group and number of isolates in the PNW region, the non-PNW US, total number in the study and total frequency……………………………………………………………………………….116
4. Locations and dates of wheat fields sampled in 2010 and races and haplotypes of P. striiformis f. sp. tritici in the US Pacific Northwest……………………………………120
5. Nei’s gene diversity, Shannon’s information index, and Kosman index of the Puccinia striiformis f. sp. tritici populations in the Palouse region, the non-Palouse Pacific Northwest (PNW), and the non-PNW United States based on the SSR data…………..130
6. The mutation-scaled population size ( Θ), and migration rates (M) between the Puccinia striiformis f. sp. tritici populations in the Palouse region and the non-Palouse PNW; the PNW and the non-PNW US based on the SSR data……………………...……………131
7. Analysis of molecular variance (AMOVA) among and within the Puccinia striiformis f. sp. tritici populations in the Palouse region, the non-Palouse Pacific Northwest (PNW), and the non-PNW United States based on the SSR data…………..…………………...132
Chapter 5
1. Seedling infection types of PI 331260, PI 480016, and Avocet Susceptible (AvS) to races of Puccinia striiformis f. sp . tritici tested under controlled greenhouse conditions…...153
2. F6 plants and F 7 lines segregation for seedling resistance to races PST-127 of Puccinia striiformis f. sp . tritici in AvS/PI 331260 and AvS/PI 480016……………………...….157
3. Infection types on wheat genotypes with Yr genes on short arm of chromosome 1B produced by races of Puccinia striiformis f. sp. tritici …………………………………162
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LIST OF FIGURES
Chapter 2
1. Principal coordinates analysis of eight races of Puccinia striiformis using 17 SSR markers. PSH denotes races of P. striiformis f. sp. hordei , the barley stripe rust pathogen and PST denotes races of P. striiformis f. sp. tritici , the wheat stripe rust pathogen……44
Chapter 3
1. Cluster analysis of the 69 identified virulence patterns (UPGMA on Nei distances with virulence data). The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in bootstrap analysis using the Winboot program ………………………………………………………………....……..67
2. Three-dimensional plot of 69 virulence phenotypes using principle coordinates analysis. VG 1 - VG 3 corresponding to the clusters in Fig. 1………………..…………..…...….68
3. Examples of designated AA, AB, and BB types with two alleles (A), three alleles (B) and four alleles (C) of markers………………………………………………...……………..79
4. Molecular haplotypes revealed by 20 microsatellites. Markers from 1 to 20 are presented in Table 2. ……………………………………………………………...…..…………....80
5. Neighbor-joining tree of 44 molecular haplotypes based on SSR marker data by NTsyspc 2.21L program. MG 1 - 3 correspond to the molecular groups. The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in bootstrap analysis using the Winboot program…………………...…81
6. Three-dimentional plot of 44 molecular haplotypes using principle coordinates analysis. White, black, and gray circles indicate example samples collected from wheat, barley, and other grasses, repectively……………………...…...………………………………..82
7. Molecular groups revealed by STRUCTURE with 44 haplotypes, samples aligned by host, different color in each line represented the proportion of genetic different populations (A); Genotype frequency classes identified by NEWHYBRIDS with 44 haplotypes (B), black and white bars indicated the two pure species and gray bar
indicated the F 1 hybrids, other pattern corresponded to F 2 and backcross of two parental species…………………………………………………………………………………...83
Chapter 4
1. Map showing Puccinia striiformis f. sp. tritici samples collected from the Pacific
x
Northwest (PNW) and 20 states in the United States in 2010. Circles mark the 26 PNW fields where single stripe samples were collected and the numbers in the circles correspond to the field number in Table 4. The Palouse region is indicated by the broken line rectangle…………..………………………………………………………….……105
2. Frequencies of Puccinia striiformis f. sp. tritici virulences to the 18 Yr -gene lines in the Palouse region, the non-Palouse PNW, and the non-PNW US………………...……....115
3. Dendrogram showing the similarities of 21 Puccinia striiformis f. sp. tritici races determined by the UPGMA in the NTsyspc 2.21L program. VG 1 and VG 2 are virulence groups. The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in the bootstrap analysis using the Winboot program………………………………………………………………………………...118
4. Three-dimensional plot of 21 Puccinia striiformis f. sp. tritici races using principle coordinates analysis. VG 1 and VG 2 correspond to the clusters in Fig. 3. The number in a circle represents the number of isolates and the number outside the circle is the PSTv race name in number…………………………………………………………………...119
5. Molecular haplotypes of Puccinia striiformis f. sp. tritici determined using 20 SSR markers. Markers 1 to 20 are presented in Table 2. The numbers in the columns on the right are numbers of isolates in the different regions…………...……………………...124
6. Neighbor-joining tree showing the similarities of 66 haplotypes of Puccinia striiformis f. sp. tritici based on SSR markers using NTsyspc 2.21L program. MG 1 and MG 2 are molecular groups shown in Fig. 5. The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in bootstrap analysis using the Winboot program…………………………………………….……..125
7. Three-dimensional plot of 66 molecular haplotypes of Puccinia striiformis f. sp. tritici using principle coordinates analysis……….…………………………………………...126
8. Randomized distributions and observed the number of steps in most parsimonious trees of the Palouse Puccinia striiformis f. sp. tritici population. The distribution of step numbers under the null hypothesis (no association between alleles) was obtained after 1,000 randomizations of alleles in the individual isolates……………………………...129
Chapter 5
1. Linkage map for YrPI331260 and YrPI480016 on the short arm of chromosome 1B. The map distances of YrPI331260 and YrPI480016 to resistance genes Yr15 and Yr24 /Yr26 were based on common markers………………………………………………...... …...160
xi
DEDICATION
This thesis is dedicated to my parents, who always trust me and support me, in love and
gratitude.
xii
CHAPTER ONE
LITERATURE REVIEW
1. Stripe Rust
1.1 Discovery of stripe rust
Stripe rust, caused by Puccinia striiformis , was first described by Gadd in 1777 (Eriksson
& Henning 1896). Transcaucasia, the origin of domesticated wheat, also is assumed to be the center of origin for P. striiformis with the grasses as primary host (Stubbs 1985). The pathogen might have moved from the primary host grasses into Europe and along the mountain ranges to China and eastern Asia by winds (Stubbs 1985). Although the pathogen was first recognized in North America in 1915 by a visiting scientist, F. Kolpin Ravn, from
Denmark, it is believed that P. striiformis had existed in North America for at least 23 years before this first report since specimens collected in 1892 were later identified as P. striiformis
(Line 2002).
1.2 Host range and specialization
Puccinia striiformis has a wide host range including wheat, barley, triticale, rye, and various grasses only in the Gramineae (now Poaceae) family (Stubbs 1985). Stripe rust was observed on 372 lines representing 105 species in 16 genera by inoculating 948 randomly selected grass lines in a greenhouse at Pullman, WA (Dietz & Hendrix 1962). It is summarized that the host range of stripe rust consists of 320 species in 50 genera by natural infection or artificial inoculation (Hassebrauk 1965). Rusts from 30 grass species were able to infected wheat and conversely, wheat and barley stripe rust can infect about 150 grass species
1
(Hassebrauk 1965). Dormant mycelium of the pathogen was found in Elymus glaucus , E.
canadensis , Bromus marginatus , Hordeum nodosum , and H. jubatum at low elevations in
Oregon (Hungerford 1923). Additionally, urediniospores were found viable for 58 and 49 days on infected leaves of Agropyron dasystachyum and Elymus condensatus , respectively,
when kept in herbarium packets at room temperature. Other grass hosts found in Washington
were: Agropyron bakeri , A. reparium , A. spicatum , Bromus carinatus , B. pumpellianus , B. sitchensis , B. marginatus , Hordeum jubatum , Sitanion hystrix , and Poa nemoralis (Hendrix et
al. 1965). Successful infection was observed in Australia after inoculating wheat with
urediniospores collected from Bromus mollis , B. unioloides , Hordeum hystrix , H. leporinum ,
H. marinum , H. vulgare , Phalaris minor , P. paradoxa , and Triticosecale (Holmes & Dennis
1985).
Based on the adaptation to specific host genera, five formae speciales of the pathogen
based on the host genus were reported in the 19 th century: P. striiformis f. sp. tritici (Pst ) on
wheat, P. striiformis f. sp. hordei (Psh ) on barley, P. striiformis f. sp. secalis on rye, P.
striiformis f. sp. elymi on Elymus spp., and P. striiformis f. sp. agropyron on Agropyron spp.
(Eriksson 1894). Three additional formae speciales were reported in the 20 th century.
Collections from orchard grass ( Dactylis glomerata ) were designated as P. striiformis f. sp.
dactylidis (Manners 1960; Tollenaar 1967); collections from Kentucky blue grass ( Poa
pratensis ) were designated as P. striiformis f. sp. poae (Tollenaar 1967), and collections from
Leymus secalinus were designated as P. striiformis f. sp. leymi (Niu et al. 1991). In the
beginning of this century, another forma specialis was named. Stripe rust samples collected
from Hordeum spp. that were virulent on wheat cultivar ‘Chinese 166’ and certain barley
2
cultivar ‘Skiff’ with distinct genotypes from Pst and Psh was considered as P. striiformis f. sp . pseudo-hordei (Wellings et al. 2000; Wellings 2007). Therefore, a total of nine formae
speciales have been named under the species of P. striiformis . However, the subdivision of P. striiformis into formae speciales has been questioned as the presence of overlapped hosts in different formae speciales (Chen 2005). Same situation exists in other pathogenic fungi such as Puccinia graminis and Fusarium oxysporum . Some genotypes of wheat are susceptible to both formae speciales of stem rust fungi P. graminis f. sp. tritici (Pgt ; on wheat, Triticum aestivum ) and P. graminis f. sp. secalis (Pgs ; on cereal rye, Secale cereale ) (Sanghi & Luig
1971). Likewise, common hosts in beet and cultivars of sugarbeet have been found for vascular wilt pathogen F. oxysporum f. sp. spinaciae (on spinach) and F. oxysporum f. sp. betae (on beet) (Armstrong & Armstrong 1976). The term forma specialis is coined to designate variants that morphologically indistinguishable but adapted to parasitizing different host species.
Molecular markers have been widely used to charcaterize the pathogen. The virulence and random-amplified polymorphic DNA (RAPD) analyses clarified the relationships among
P. striiformis f. sp. hordei , P. striiformis f. sp. tritici , and P. striiformis f. sp . poae (Chen et al.
1995c). It is indicated that Puccinia striiformis f. sp. hordei and P. striiformis f. sp. tritici were more closely related to each other than they were to P. striiformis f. sp. poae . This finding agreed with the new nomenclature proposed recently using molecular (ITS and
β-tubulin sequences) and morphological data. Stripe rust infecting Dactylis glomerata was newly named P. striiformoides and stripe rust infecting Poa spp. was newly named P. pseudostriiformis (Liu & Hambleton 2010). Molecular markers helped discriminate formae
3
speciales of other pathogenic fungi such as F. oxysporum. Sequence-unbiased approaches for
molecular identification of pathogenic strains have proven to be effective for the
identification of several formae speciales and races of F. oxysporum (Chiocchetti et al. 2001;
Pasquali et al. 2006; Lievens et al. 2007). Another example with powdery mildew pathogen
Blumeria graminis using ITS and β-tubulin sequences data suggests the isolates of B. graminis f.sp avenae (from oat) is a sister group to isolates from wheat and rye, while isolates from barley is an outgroup (Wyand & Brown 2003).
1.3 Races
Within the forma specialis of either Pst or Psh , races have been used to distinguish isolates based on their virulence/avirulence patterns on differential cultivars of wheat or barley. The virulence/avirulence patterns of an isolate define the race designation. In the
United States, 20 wheat genotypes (Table 1) were used to differentiate races of P. striiformis f. sp. tritici (Chen et al. 2002). Recently, a set of single gene lines (Table 2) consisting of 18
Yr (Yellow rust resistance) genes have been selected to differentiate races of Pst (Wan and
Chen, unpublished data). For Psh race differentiation, 12 barley genotypes are used (Table 3)
(Chen 2004).
4
TABLE 1 . Wheat genotypes used to differentiate races of Puccinia striiformis f. sp. tritici in the United States.
Differential No. Cultivar or line Yr gene
1 Lemhi Yr21 2 Chinese 166 Yr1 3 Heines VII Yr2 , YrHVII 4 Moro Yr10 , YrMor 5 Paha YrPa1 , YrPa2 , YrPa3 6 Druchamp Yr3a , YrD , YrDru 7 AvSYr5NIL Yr5 8 Produra YrPr1 , YrPr2 9 Yamhill Yr2 , Yr4a , YrYam 10 Stephens Yr3a , YrS , YrSte 11 Lee Yr7 , Yr22 , Yr23 12 Fielder Yr6 , Yr20 13 Tyee YrTye 14 Tres YrTr1 , YrTr2 15 Hyak Yr17 , YrTye 16 Express YrExp1 , YrExp2 17 AvsYr8NIL Yr8 18 AvsYr9NIL Yr9 19 Clement Yr9 , YrCle 20 Compair Yr8 , Yr19
5
TABLE 2 . Wheat single gene lines used to differentiate races of Puccinia striiformis f. sp. tritici in the United States.
Differential No. Genotype Yr gene 1 AvSYr1NIL Yr1 2 AvSYr5NIL Yr5 3 AvSYr6NIL Yr6 4 AvSYr7NIL Yr7 5 AvSYr8NIL Yr8 6 AvSYr9NIL Yr9 7 AvSYr10NIL Yr10 8 AvSYr15NIL Yr15 9 AvSYr17NIL Yr17 10 AvSYr24NIL Yr24 11 AvSYr27NIL Yr27 12 AvSYr32NIL Yr32 13 Avs/IDO377s F3-41-1 Yr43 14 Avs/Zak 1-1-35-1 Yr44 15 AvSYrSPNIL YrSP 16 AvSYrTr1NIL YrTr1 17 Avs/Exp 1/1-1 Line 74 YrExp2 18 Tyee YrTye
6
TABLE 3 . Barley genotypes used to differentiate races of Puccinia striiformis f. sp. tritici in the United States.
Differential No. Name Resistance gene 1 Topper None 2 Heils Franken Rps4 , rpsHF 3 Emir rpsEm , rpsEm2 4 Astrix Rps4 , rpsAst 5 Hiproly rpsHi1 , rpsHi2 6 Varunda rpsVa1 , rpsVa2 7 Abed Binder 12 rps2 8 Trumpf rpsTr1 , rpsTr2 9 Mazurk Rps1.c 10 Bigo Rps1.b 11 I 5 Rps3 , rpsI5 12 Bancroft RpsBa
7
1.4 Life cycle
It was believed that only dikaryotic (n+n) uredial, dikaryotic to diploid (2n) telial, and
haploid (n) basidial stages exist in the P. striiformis f. sp. tritici stripe rust life cycle (Stubbs
1985; Chen 2005) until the alternate host Berberis spp. was determined under controlled greenhouse conditions (Jin et al. 2010). The basidiospores germinated from Pst could infect
Berberis spp. to produce pycnia (n) on the upper side of barberry leaves. This is where uninucleate pycniospores (also called spermatia) fertilize haploid receptive hyphae. Fertilized receptive hyphae (n+n) further develop into dikaryotic (n+n) aecia on the lower side of the leaves. Dikaryotic aeciospores that are produced from aecia on Berberis spp. are able to infect wheat plants again to produce dikaryotic urediniospores (Jin et al. 2010). However, whether the alternate host plays a role under natural environment is yet to be determined.
Interestingly, Jin et al. (2010) observed aecia on barberry plants in Minnesota under natural condition and identified them were as P. striiformis f. sp. poeae , which is now considered as a different species, P. pseudostriiformis (Liu & Hambleton 2010).
Therefore, the reproductive modes of the stripe rust pathogen may inlude clonality, recombination, and mating. Under clonality, genome of each progeny would be an exact copy of the single parent and all parts of the genome would have the same evolutionary history.
The only factor would generate diversity in a strictly clonal population is mutation. It has been widely detected that stripe rust pathogen populations in Australia, Europe, and the
United States reproduce clonally and diversify through mutations (Steele et al. 2001;
Hovmøller et al. 2002; Chen et al. 2010). On the other hand, recombination can occur via hybridization or mating. In rust fungi, somatic hybridization involves the fusion of dikaryotic
8
vegetative hyphae, nuclear exchange, and possibly whole chromosomes exchange between
two nuclei. Parasexual recombination could occur via fusion of two haploid nuclei, followed
by mitotic crossing over to mix the parental genomes and haploidization of the diploid nuclei
(Park & Wellings, 2012). Studies of somatic hybridization under controlled conditions
usually start with mix inoculation of two races on a common host. Then host genotypes that
are susceptible to one parent but resistant to the other would be used to eliminate the
contamination error (Nelson 1956). Besides the difference of virulences on certain host
resistant genotypes, urediniospore color of rust is another marker to identify and select
putative hybrids (Newton et al. 1986). The recovery of isolates with different pathogenicity
from the two parental races without the presence of alternate host in rust fungi implicates the
mechanism of somatic hybridization (Flor 1960). In a study of flax rust fungi Melampsora
lini , four host genotypes that susceptible to race 22 (known homozygous for virulence to the
four host genotypes) but resistant to race 1 (known heterozygous for virulence to the four
host genotypes) and the F 1 hybrids were used to screen the mix of four F 1 hybrids. Isolates virulent for one of the four host genotypes were recovered and 118 out of 129 were identified as race 22. It was proposed that two mating type nuclei exchange was the straight forward explanation for pathogenicity change of the resulting F 1 hybrids by comparing virulence pattern with both parents. Nonparental races isolated from single spore cultures of two crown rust races were suggested to arise from multinucleate parents or mitotic crossing over from dikaryotic parents following nuclei fusion (Bartoš et al. 1969). Two genetically distinct lineages of M. lini collected from an endemic wild herbaceous plant Linum. marginale
(referred to as AA and AB) were revealed by microsatellite and AFLP datasets (Barrett et al.
9
2007). The AA lineage displayed low heterozygosity and the AB lineage displayed high
heterozygosity. With nuclear staining of both lineages confirming dikatyotic, the authors
concluded that lineage AB was generated by nuclear exchange between lineage AA and a
putative BB lineage that carries B genome. A later study with two avirulence genes AvrP123 and AvrP4 and AFLP markers indicated that AA lineage was able to reproduce both clonally and sexually while AB lineage is completely asexual (Barrett et al. 2008). Somatic hybridization was also detected in rust fungi in regions where sexual recombination is absent or extremely low in nature such as Australia (Park & Wellings, 2012). Potential sexual recombination was also supported by a study in stripe rust that showed high genetic variation and greater telial production in population in regions with distribution of identified alternate host Berberis (Ali et al. 2010; Jin et al. 2010).
1.5 Population studies
The population structure of a pathogen can be affected by five evolutionary forces: mutations, population size and random genetic drift, gene and genotype flow, reproduction and mating system, selection by resistant hosts (McDonald & Linde 2002). For asexually reproducing fungi which the clonal mechanism plays a major role, mutation is commonly considered as the main factor to influence the population structure. This can be seen in many asexual pathosystems with race variation generated by single-step mutations such as the west gall rust fungus Peridermium harknessii (Vogler et al. 1991; 1997). The probability of
mutants is affected by population size which can influence the diversity of genes through
random genetic drift. Severe reductions in population size (bottlenecks) make pathogen populations less diverse and slower to adapt than populations that maintain a high population
10 size year round. Genotype and gene flow through hybridization and bacteria or virus infection also influence the structure of pathogen population. Hierarchical analysis of DNA fingerprints and restriction fragment length polymorphism (RFLP) markers in a large population of the wheat pathogen Mycosphaerella graminicola collected from 11 countries on five continents suggested a global scale gene flow (Zhan et al. 2003). Analysis of AFLP variation showed that the stripe rust fungus frequently migrated between the UK, Germany, France, and
Denmark (Hovmøller et al. 2002), and more recently two new strains and their rapid spread in the world were identified by the same group using AFLP markers (Hovmøller et al. 2008).
Reproduction and mating system are of great importance in pathogen population. Many studies have shown that asexual and clonal fungi may have cryptic species that can be recombining in nature (Taylor et al. 1999). One cryptic species of banana pathogen Fusarium oxysporum f. sp. cubense has been found likely to be recombining in nature (O’Donnell et al.
1998). Molecular analysis of six loci in citrus brown spot pathogen Alternaria alternata suggested putative mitotic recombination or meiotic haploid fruiting through a cryptic sexual cycle, parasexual cycle or both (Steward 2011). Detailed studies showed parasexual recombination occurs in Aspergillus nidulans , A. niger , Penicillium chrysogenum , and F. oxysporum (Pontecorvo 1956). Novel races arose from mixtures of two races of oat crown rust pathogen Puccinia coronata f. sp. avenae suggested occurrence of nuclear exchange following hyphal anastomosis and nuclear fusion and mitotic crossing over (Bartoš et al.
1969). Strong selection due to differences in host resistance resulted in shorter-term regional genetic variation in barley powdery mildew Blumeira graminis f. sp. hordei thoughout
Europe (Wolfe & McDermott 1994).
11
AFLP markers successfully differentiated the new population collected since 2000 from
the old population (collected before 2000) of the stripe rust pathogen in the eastern United
States (Markell & Milus 2008). For the dikaryotic organisms like Puccinia species, co-dominant markers such as SSRs are more informative in revealing genetic variations when compared to dominant markers (Selkoe & Toonen 2006). The first group of SSR markers for the stripe rust pathogen was reported by a French group in 2002 (Enjalbert et al. 2002).
Recently, a strong geographical structure of P. striiformis f. sp. tritici was showed within
France by using these SSR markers (Enjalbert et al. 2005). Both virulence and molecular marker data provided evidence to a foreign incursion of wheat stripe rust in Western
Australia (Wellings et al. 2003). More recently, expressed sequence tags (ESTs) from cDNA libraries have served an important resource for developing new SSR markers to assess genetic diversity. Twenty polymorphic SSR markers derived from the expressed sequence tags of P. striiformis f. sp. tritici have been developed (Chen et al. 2009). In our study, 46
EST-SSR primers were developed from genes characterized in the full-length cDNA library
of Pst (Cheng et al. 2012). Using the SSR markers, we have recently studied genetic
variations of stripe rust samples collected from grasses and obtained molecular evidence of
somatic hybridization of Puccinia striiformis in a relatively small population (Cheng & Chen
2009). Using gene sequences of 22 P. striiformis isolates from the U.S. and China, Liu et al.
(Liu et al. 2009) provided sequence evidence of heterokaryon in some isolates. However,
studies are needed to determine if the heterokyotic sequences are resulted from mutation or
somatic recombination and to determine frequency of the somatic recombination. For
understanding the pathogen biology, functional gene-based markers may be preferred over
12
the uncharacterized DNA sequences like RAPD, AFLP, and SSR markers.
1.6 Impact
The major impacts of stripe rust epidemics are the reduction in grain yield and the cost of
disease management. The stripe rust disease caused severe damage in the United States. For
example, in the State of Washington, the most severe yield losses recorded were 25%
(591,108 t) in 1960 and 17% (787,236 t) in 1976 (Chen 2007). Destructive epidemic of wheat
stripe rust occurs most often in the western USA, especially the Pacific Northwest
(Washington, Oregon, and Idaho), because the climatic conditions and cropping systems are
favorable to stripe rust. Since 2000, the wider distribution and more frequent epidemics have
made stripe rust of wheat more important throughout the U.S. (Chen 2005, 2007). In 2000,
the disease was reported in 20 states from the Pacific Northwest and California to Virginia
and from Texas to North Dakota (Chen et al. 2002). The widest distribution of the stripe rust in the recorded history was in 2005 with reported occurrence in over 35 states (Chen &
Penman 2006). In other years from 2000 to 2007, stripe rust occurred in at least 15 states every year (Chen et al. 2010). The yield loss caused by stripe rust in each year is worth of millions of dollars ((http://www.ars.usda.gov/Main/docs.htm?docid=10123 ). Without the
widely use of fungicides, the yield losses would have been two to four times of the estimates.
2. Control of wheat stripe rust
2.1 Genetic resistance
Although fungicides for controlling stripe rust have been effective since the first
large-scale successful use in North America in 1981 (Line 2002), the application of
13 fungicides add much extra cost to wheat production. Especially in developing countries, the use of fungicides brings both economic and healthy pressure to growers. Problems raised by the chemical control also include possible adverse effect on the environment and elicitation of fungicide-resistant strains of the pathogen. Thus, the best strategy to control stripe rust is growing resistant cultivars (Chen 2005). Types of resistance to stripe rust can be generally separated into two categories: all-stage resistance (also called seedling resistance) and adult-plant resistance such as the high temperature, adult-plant (HTAP) resistance (Table 4).
All-stage resistance is race-specific and can be detected at seedling stage but is also expressed at all growth stages of plant (Chen 2005). Rapid development of new virulent races of the pathogen through mutation and somatic recombination makes the cultivars with all-stage resistance become susceptible very soon after they are released (Wellings & McIntosh 1990).
This is because all-stage resistance is often conferred by race-specific single genes. In contrast, HTAP resistance is non-race specific, durable, but often quantitatively inherited and hard to incorporate into breeding cultivars (Qayoum & Line 1984; Chen & Line 1995a,
1995b; Line 2002; Chen 2005). Plant growth stage, temperature, and humidity are three major factors that affect HTAP resistance.
14
TABLE 4. Comparison of all-stage resistance and high-temperature and adult-plant (HTAP) resistance
All-stage resistance HTAP resistance
Number of loci Usually single genes Usually multiple QTL
Durability Not durable Durable
Effect stage All stages Adult plant
Specificity Race-specific Non race-specific
Level of resistance High Partial
Mode of inheritance Qualitatively Quantitatively
2.2 Resistance genes
So far, 53 Yr genes with official names have been reported and chromosomal locations of most of the genes have been determined (Table 5). Among the officially named genes, Yr11 ,
Yr12 , Yr13 , Yr14 , Yr16 , Yr18 , Yr29 , Yr30 , Yr34 , Yr36 , Yr39 , Yr46 , Yr48 , Yr49 , and Yr52 are
adult-plant resistance gene and the rest are race-specific all-stage resistance genes. Besides,
more than 30 genes or quantitative trait loci (QTLs) have been reported with provisional or
QTL names (Cheng 2008). All-stage resistance usually provide complete control of stripe
rust when it is effective, but the single-gene controlled all-stage resistance are easy to be
conquered by evolved new races of the pathogen. In contract, HTAP resistance is durable but
often not complete. Partial HTAP resistance may not be adequate when the disease develops
in the early stage and when temperatures are too low for HTAP resistance to fully express.
Therefore, the best genetic approach is to combine durable HTAP resistance with genes for
15
effective high-level all-stage resistance. Through the studies of past several years in our
program and other laboratories in the world, more than 30 genes or QTLs for HTAP
resistance have been reported and molecular makers are available for incorporate them into
breeding programs (Chen 2005, Uauy et al. 2005, Lin and Chen 2007, 2009, Chen and Zhao
2007, Santra et al. 2008, Carter et al. 2009, Guo et al. 2009, Ren et al. 2012). The effectiveness of these genes is generally not affected by changes of races. In contrast to the relative plenty of HTAP resistance genes, only Yr5 , Yr15 , and Yr45 are effective against all races identified so far in the U.S. (Chen et al. 2010; Wan and Chen 2012; Li et al. 2011). The first two genes have been recently used intensively in breeding programs throughout the U.S., and therefore, we expect that races overcoming these resistance genes will appear when cultivars with these genes widely grown. Therefore, it is urgent to identify new genes for effective all-stage resistance to be used in combination with HTAP resistance.
2.3 Resistance sources
Relatives of wheat have proven to be an invaluable gene pool for wheat improvement.
There are 14 Yr genes were transferred from wild relatives of wheat, such as Triticum aestivum subsp. spelta Album, T. turgidum , T. dicoccoides , T. turgidum var durum , Ae. ventricosa , Ae. tauschii , Ae. kotschyi , Ae. sharonenisis , Ae. geniculata , Ae. neglecta , and more distantly related species, Secalis cereal (Chen 2005). There are many drawbacks for utilizing resistance genes from alien species. It takes many years to move a resistance gene from an alien species to wheat. A translocated chromosome may carry too many undesirable traits that are hard to get rid of. Most rust resistance genes from alien species are not durable, which is exampled by Yr9 for stripe rust (Chen 2005), Lr26 for leaf rust (Datta et al. 2008),
16
and Sr31 for stem rust resistance from rye ( S. cereal ) (Mago et al. 2005). Yr9 virulence and
Lr26 virulence are widespread in the P. striiformis f. sp. tritici and P. triticina populations
worldwide, respectively, and the Ug99 stem rust races that are virulent on Sr31 has become
predominant in eastern Africa, spread to Iran and South Africa, and become a serious threat to
wheat production in the world (Visser et al. 2009). However, genes from wild relatives of wheat can be useful when they are used in pyramiding with other genes especially with
HTAP resistance genes.
Durum wheat ( T. turgidum L. subsp . durum ) is a tetraploid wheat, having 28 chromosomes (2n = 4× = 28, genome AABB) and grown on approximately 17 million hectares worldwide (Abdalla et al. 1992). Durum wheat with A and B genomes are the primary gene pool of hexaploid common wheat (T. aestivum L., 2n = 6×= 42, AABBDD genomes) for exploring desired genes to enhance the genetic diversity of common wheat varieties including disease resistance, drought tolerance, yield components, protein quality and quantity (Feldman & Millet 1993; Huang et al. 2003; Blanco et al. 2008). Resistance genes Yr15 , YrH52 , and Yr36 were originated from tetraploid wheat (Macer 1966; Ma et al.
2001; Uauy et al. 2005). In a study with 216 durum cultivars, it was found that 23% were
resistant to stripe rust (Mamluk 1992). A wide range of seedling and adult resistance to stripe
rust was observed in durum wheat cultivars from various countries (Ma et al. 1995; Ma et al.
1997a; Ma et al. 1997b). It is suggested that durum wheat germplasm is a rich source of stripe rust resistance genes. In addition, it is relatively easy to make crosses between durum wheat and common wheat genotypes, and thus durum wheat often was used as a bridging species to transfer new resistance genes from diploid wheat into common wheat (Chhuneja et
17
al. 2008). Therefore, exploring new Yr genes from durum wheat and transferring them into common wheat is an effective and convenient approach to diversify stripe rust resistance genes in common wheat cultivars. The successful transfer and characterization of alien introgression are needed to introduce and identify new resistance genes in wheat.
2.4 Molecular mapping
Molecular markers have been developed for several stripe rust resistance genes and have been used in marker-assist selection for developing resistant cultivars (Cheng 2008).
Commonly used marker techniques include random amplified polymorphic DNA (RAPD), simple sequence repeats (SSR), and amplified fragment length polymorphism (AFLP). Our lab developed the resistance gene analog polymorphism (RGAP) technique (Chen et al.
1998). Primers that designed based on the conserved regions of resistance genes sequence similarities amplified polymorphic bands. The conserved regions contain leucine-rich repeats, nucleotide-binding sites and protein kinase genes. Molecular markers for assessing the genetic diversity of germplasm were evident to be inherited as single loci. Bulk segregant analysis (BSA) (Michelmore et al. 1991) has been demonstrated as an effective way to identify markers for all-stage resistance genes and HTAP resistance QTL against stripe rust in wheat and barley (Shi et al. 2001; Yan et al. 2003; Pahalawatta & Chen 2005a, 2005b; Yan &
Chen 2006). HTAP in combination with effective race specific resistance has proven to be the best disease control strategy (Chen 2007). A quick, precise, and efficient method of marker assisted background selection (MABS) was proposed as a tool to transfer target genes among wheat cultivars or germplasms (Randhawa et al. 2009).
18
Table 5. Genes for resistance to stripe rust ( Puccinia striiformis f. sp. tritici ), examples of wheat genotypes containing the genes, their
chromosomal locations, types of resistance, and references
Yr gene Example of wheat genotype Chromosomal location Resistance type a Reference Yr1 AvSYr1NIL, Chinese 166 2AL RS, AS Macer 1966 Yr2 Heines VII, Kalyansona, 7B RS, AS Labrum 1980; Chen et al. 1995b Yr3 Nord Desprez; Vilmorin 23 5BL RS, AS McIntosh et al. 1995 Yr4 Hybrid 46; Opal 3B RS, AS McIntosh et al. 1995 Yr5 AvSYr5NIL, Triticum spelta album 2BL RS, AS Yan et al. 2003; Smith et al. 2007 Yr6 AvSYr6NIL, Heines Kolben 7BS RS, AS El-Bedewy & Röbbelen 1982 Yr7 AvSYr7NIL, Lee 2BL RS, AS Macer 1966; Yao et al. 2006 19 Yr8 Aegilops comosum 2A/2Mtrans RS, AS Riley et al. 1968b AvSYr8NIL, Compair 2D/2Mtrans RS, AS Riley et al. 1968a Yr9 AvSYr9NIL, Clement 1BL/1RStrans RS, AS Mago et al. 2002; Weng et al. 2005 Yr10 AvSYr10NIL, Moro 1BS RS, AS Chen et al. 1995b; Smith et al. 2002 Yr11 Joss Cambier unknown RS, AP McIntosh et al. 1995 Yr12 Mega unknown RS, AP McIntosh et al. 1995 Yr13 Maris Huntsman unknown RS, AP McIntosh et al. 1995 Yr14 Hobbit unknown RS, AP McIntosh et al. 1995 Yr15 AvSYr15NIL, Triticum turgidum var. 1BS RS, AS Gerechter-Amitai et al. 1989; McIntosh et dicoccoides G-25 al. 1995 Yr16 Cappelle Desprez 2D NRS, AP Worland & Law 1986
Yr17 AvSYr17NIL, Ae. ventricosa 2AS-6M trans RS, AS Bariana & McIntosh 1994 Yr18 AvSYr18NIL, Saar, Parula 7DS NRS, HTAP Suenaga et al. 2003 Yr19 Compair 5B RS, AS Chen et al. 1995a Yr20 Fielder 6D RS, AS Chen et al. 1995a Yr21 Lemhi 1B RS, AS Chen et al. 1995a Yr22 Lee 4D RS, AS Chen et al. 1995a Yr23 Lee 6D RS, AS Chen et al. 1995a Yr24 AvSYr24NIL, T. turgidum 1BS RS, AS McIntosh & Lagudah 2000 Yr25 Strubes Dickkopf, Heines Peko 1D RS, AS Calonnec & Johnson 1998 Yr26 AvSYr26NIL, T. turgidum 1BS RS, AS Ma et al. 2001; Yildirim et al. 2004 Yr27 AvSYr27NIL, Ciano 79, Selkirk 2BS RS, AS McDonald et al. 2004 20 Yr28 AvSYr27NIL, Ae. tauschii 4DS RS, AS Sharma et al. 1995; Singh et al. 2000 Yr29 AvSYr29NIL, Parula, Pavon 76 1BL NRS, AP William et al. 2003 Yr30 Parula, Pavon 76 3BS NRS, AP Singh et al. 2001 Yr31 AvSYr31NIL, Pastor 2BS RS, AS Zahravi et al. 2003 Yr32 AvSYr32NIL, Carstens V 2AS RS, AS Eriksen et al. 2004 Yr33 Batavia 7DL RS, AS Zahravi et al. 2003 Yr34 WAWHT2046 5AL AP Bariana et al. 2006 Yr35 T. turgidum var. dicoccoides 6BS RS, AS Marais et al. 2005b; Dadkhodaie et al. 2011 Yr36 T. turgidum var. dicoccoides 6BS NRS, HTAP Uauy et al. 2005
Yr37 Ae. kotschyi 2DL trans RS, AS Marais et al. 2005a Yr38 Aegilops sharonenisis 6AL tans , (6AL-6Lsh.6Ssh) RS, AS Marais et al. 2006; Marais et al. 2010 Yr39 Alpowa 7BL NRS, HTAP Lin & Chen 2007 Yr40 Ae. geniculata 5DS trans RS, AS Kuraparthy et al. 2007 (5DL.5DST5MSG) Yr41 cv. Chuannong 2BS RS, AS Luo et al. 2005; Luo et al. 2006 Yr42 Ae. neglecta 6ALtrans (6AenL.6AenS) RS, AS Marais et al. 2009 Yr43 cv. IDO377s 2BL RS, AS Cheng & Chen 2010 Yr44 cv. Zak 2BL RS, AS Sui et al. 2009 Yr45 PI 181434, PI 660056 3DL RS, AS Li et al. 2011, Wang et al. 1912 Yr46 PI 250413); RL6077 4DL NRS, AP Hiebert et al. 2010; Herrera-Foessel et al. 21 2011 Yr47 Line V336 5BS RS, AS Bansal et al. 2011 Yr48 Synthetic wheat 205 5AL NRS, AP Lowe et al. 2011 Yr49 cv. Chuanmai 18 3DS-6 (0.55-1.00) NRS, AP Spielmeyer et al. unpublished Yr50 CH233 (from Th. intermedium ) 4BL RS, AS Liu et al. unpublished Yr51 Line 5515, AUS 27858 4AL RS, AS Bansal et al. unpublished Yr52 PI 183527, PI 660057 7BL NRS, AP Ren et al. 2012 Yr53 PI 480148, AvS/PI 480148 F5-128 2BL RS, AS Xu, et al. unpublished
a RS = race specific resistance; AS = all-stage resistance; AP = adult plant resistance; HTAP = high-temperature adult plant resistance; NRS = non-race specific resistance.
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35
CHAPTER TWO
Development and characterization of expressed sequence tag-derived microsatellite
markers for the wheat stripe rust fungus Puccinia striiformis f. sp. tritici
P. CHENG,† X. M. CHEN,†‡*, L. S. XU,† D. R. SEE‡
(Accepted in Molecular Ecology Resources)
†Department of Plant Pathology, Washington State University, Pullman, WA, 99164-6430,
USA, ‡USDA-ARS, Wheat Genetics, Quality, Physiology, and Disease Research Unit,
Pullman, WA 99164-6430, USA
*Correspondence: Xianming Chen, USDA-ARS, Wheat Genetics, Quality, Physiology, and
Disease Research Unit, Pullman, WA 99164-6430, USA Tel.: +1 509 335 8086; fax: +1 509
335 9581. E-mail: [email protected]
Abstract
Puccinia striiformis , a basidiomycete fungus, produces dikaryotic urediniospores causing stripe rust of wheat, barley, and many grass species. Codominant microsatellite markers are needed to study its population biology. In this study, we characterized microsatellite loci based on three EST libraries previously developed for this fungus. By screening 3,311 unique EST sequences using the SSRIT software, 46 EST sequences were selected for microsatellite motifs. Primers were designed and initially screened against 8 isolates representing 5 P. striiformis f. sp. tritici (Pst , the wheat stripe rust pathogen) and 3 P. striiformis f. sp. hordei (Psh , the barley stripe rust pathogen) races. Seventeen primer pairs produced stable polymorphic and co-dominant bands among the eight isolates. The polymorphism and usefulness of these primers were further determined with 20 Pst isolates
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collected from three states of US in 2008 to evaluate their usefulness for population studies.
Based on their genomic locations, the microsatellite loci are dispersed throughout the genome.
These codominant microsatellite markers will be useful to study the population structure and
ecology of the stripe rust fungus.
Keywords: Puccinia striiformis ; EST; Microsatellite; Dikaryon
Stripe rust, caused by the fungus Puccinia striiformis Westend., is a major disease of wheat,
barley, and many grass species (Chen 2005). The disease is caused by dikaryotic
urediniospores which are produced asexually and dominate the pathogen lifecycle (Stubbs
1985; Chen 2005). The pathogen is highly variable, but the evolutionary mechanisms
generating the diversity are not clear (Hovmøller et al. 2011). Microsatellite markers are very powerful tools to study genetic structure of organisms due to their codominance and high polymorphism (Robinson et al. 2004). However, only a limited number of microsatellite markers are available for the stripe rust fungus with low polymorphism
(Enjalbert et al. 2002; Bahri et al. 2009; Chen et al. 2009). Recently, three EST libraries
(urediniospores, germinated urediniospores and haustoria) were constructed for the wheat stripe rust pathogen ( P. striiformis f. sp. tritici , Pst ) and their sequences are useful for development of microsatellite markers (Ling et al. 2007; Zhang et al. 2008; Yin et al. 2009).
The objective of this study was to develop additional microsatellite markers for studying the population genetics of the stripe rust pathogen.
The EST data used in this study were generated by sequencing three complementary
DNA (cDNA) libraries from urediniospores of a US Pst race, PST-78 (Ling et al. 2007), germinated urediniospores of a Chinese Pst race CYR32 (Zhang et al. 2008), and haustoria of
PST-78 (Yin et al. 2009). A total of 3,311 nonredundant sequences were obtained including
37
contigs and singlets. Microsatellite loci were identified by screening the EST data using the
SSRIT software (http://www.gramene.org/db/markers/ssrtool ). Of the 3,311 EST sequences,
72 ESTs contained microsatellite loci including 7 di-, 4 tri-, 4 tetra-, 3 penta- and 3
hexa-nucleotide repeats. Forty-six pairs of primers were designed based on related ESTs for
identification of putative microsatellites and tested on 5 Pst and 3 barley stripe rust P.
striiformis f. sp. hordei (Psh ) isolates selected to represent 8 most diverse virulence races of the two formae speciales of the stripe rust pathogens in the United States. A set of 20 Pst isolates randomly sampled in 2008 from three states (Washington, Idaho and Oregon) of the
US Pacific Northwest to represent the pathogen population in the region were used to assess the allelic variation of selected markers. DNA samples of a leaf rust ( P. triticina , Pt ) isolate, a wheat stem rust ( P. graminis f. sp. tritici , Pgt ) isolate, a bluegrass stripe rust ( P. pseudostriiformis , Pp ; syn: P. striiformis f. sp. poae ) (Liu & Hambleton 2010) isolate and a
wheat genotype ‘Avocet S’ ( Triticum aestivum ) were included in the study as references or
for determining specificity and cross-species transferability.
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Table 1 Seventeen EST-SSR markers for Puccinia striiformis f. sp. tritici (Pst )and their primer sequences, PCR annealing temperature, number
of alleles and product size range, allele frequency, observed (Ho) and expected (He) heterozygosity, cross-species amplification, corresponding
supercontig identification numbers of Pst , P. graminis f. sp. tritici (Pgt ) and P. triticina (Pt )
Supercontig GenBank Repeat Tm No. of alleles Major allele Cross-species identification number Locus accession motif Primer sequences (5'-3') (oC) (size range, bp)* frequency Ho He amplification† Pst Pgt Pt
PstP001 JK479800 (CTA) 6 F: ACCATCGGATTCCTGC 49 2 (355, 360) 355 (0.554) 0.62 0.43 Pt, Pgt 5 -* - R: ACGGTAGGCGAACGAC 360 (0.446)
PstP002 JK479800 (ACT) 6 F: CTGACCATCGGATTCCTGC 53 2 (361, 367) 361 (0.554) 0.18 0.17 Pgt 5 - - R: TGAACGGTAGGCGAACGAC 367 (0.446)
PstP003 JK479801 (AATA) 5 F: TAACCCCACGGCAACTCA 50 2 (224, 241) 224 (0.643) 0.67 0.45 Pt, Pgt 35 35 36 39 R: ATCGTTGGCAGCCTTACC 241 (0.357)
PstP004 JK479803 (TCA) 6 F: TCTCGCCTCGCTTGAATG 50 2 (500, 503) 500 (0.536) 0.08 0.08 Pt, Pgt - - - R: TCGCTGGAGTTGGATGGA 503 (0.464)
PstP005 JK479809 (ACC) 6 F: CCAACAGGCTCAAACTACCA 52 2 (319, 326) 319 (0.589) 0.24 0.21 Pt, Pgt 1 1 146 R: TCCGCTTCGATCATAGCAC 326 (0.411)
PstP006 GH737707.1 (TGT) 6 F: GTTTGATTTTCCCTATGC 45 2 (243, 246) 243 (0.554) 0.11 0.11 Pt 5 5 82 R: AACTGAACGGAAGATGC 246 (0.446)
PstP007 GH737942.1 (GAA) 9 F: GATTTGCGAGGTCACTTT 46 2 (306, 312) 306 (0.214) 0.01 0.43 No amplicon - - - R: TGGTTGTGATAACGATGA 312 (0.786)
PstP008 GH737984.1 (CAA) 7 F: CCCTTGAGTAGTATGACC 48 2 (454, 457) 454 (0.875) 0.11 0.11 Pt, Pgt - 14 - R: AGAAGAGGACGAGAAGAT 457 (0.125)
PstP021 GH737353.1 (CT) 8 F: CCTCGACGCCCTCATTC 52 2 (193, 196) 193 (0.679) 0.08 0.08 Pt, Pgt 44 44 170/ R: TTGGTGACGAGCAGGTAT 196 (0.321) 20
PstP025 EG374292.1 (GA) 9 F: ATGTAAATGTAGCACCAAAC 48 3 (358, 364, 385) 358 (0.304) 0.11 0.30 Pgt 84 - -
R: TCATGCTCGGTATGTCTC 385 (0.464)
PstP027 JK479804 (TC) 13 F: CAGCGTAACTCCCAGGAT 50 2 (250, 252) 250 (0.518) 0.10 0.13 No amplicon 2 2 - R: GACCGTGTTCAGCCAAGT 252 (0.482)
PstP028 JK479808 (AAG) 6 F: GCATTCAAACAGCAGCAA 50 2 (489, 491) 489 (0.429) 0.09 0.08 Pgt - 51 135 R: GGTTAGGGTATGGCAAGG 491 (0.571)
PstP029 JK479813 (CAA) 9 F: ACAATCCTCAAGGTGGTG 48 3 (191,195, 205) 191 (0.536) 0.11 0.17 Pt, Pgt, Pp - - 30 R: GTTCGCTTTGTTGGTTAT 202 (0.304)
PstP030 GH737337.1 (GAT) 6 F: AAGGAAAAGAACTGTATG 41 2 (304, 315) 304 (0.214) 0.11 0.21 Pt, Pgt, Pp - - - R: TTCAGATGCTCTATTCAA 315 (0.786)
PstP031 GH737347.1 (GAA) 12 F: TTGGGCGTCCTGGCATTG 57 2 (277, 281) 277 (0.839) 0.01 0.30 No amplicon - - - R: ACCCGTTCCTTCTTGGTCTTGC 281 (0.161)
PstP033 GH737872.1 (AC) 8 F: ACAGAAGGAAGGCAGATT 46 3 (433, 446, 451) 433 (0.429) 0.13 0.12 Pt, Pgt - - - R: GGGGTTTGATGTTATTAC 451 (0.339)
PstP034 GH737893.1 (CT) 8 F: CCTCTTTTGTCCGCTTCC 50 2 (206, 208) 206 (0.393) 0.11 0.11 Pt, Pgt, Pp - - - 40 R: GTGCGACATGGTTTGACATT 208 (0.607)
*Length (ABI): expected fragment length plus 19 bps M13 tail for ABI detection.
†Pt : leaf rust ( P. triticina , Pt ) isolate; Pgt : wheat stem rust ( P. graminis f. sp. tritici , Pgt ) isolate, Pp : bluegrass stripe rust ( P. pseudostriiformis ,
Pp ; syn: P. striiformis f. sp. poae ) isolate.
‡-: No hits found.
DNA of all rust isolates were extracted from urediniospores using the method described
by Aljanabi and Martinez (1997). In order to use fluorescence to detect polymerase chain
reaction (PCR) products, an M13 tag (5’-CACGACGTTGTAAAACGAC) was added to the 5’
end of each forward primer (Schuelke 2000). Each PCR reaction contained 1× PCR buffer
(10 mM of Tris-HCl (pH=8.0), 50 mM of KCl), 200 M of dCTP, dGTP, dTTP and dATP, 1.5 mM MgCl 2, 5 pM tagged M13 fluorescent dyes (Applied Biosystems, Foster city, CA), 1 pM
5’-tagged forward primer, 5 pM reverse primer, 1 U of Taq polymerase (New England
Biolabs, Ipswich, MA) and 0.75 ng of DNA in a final volume of 12 l. PCR was performed in an iCycler (Biorad) thermal cycler (Watertown, MA, USA) with the following profile: 94
ºC for 5 min, 35 cycles of 94 ºC for 30 s, 50 ºC for 30 s (varies for each primer pair), and 72
ºC for 30 s, and 72 ºC for 10 min followed by a 4 oC holding step. Every four loci in the order listed in Table 1 tagged with FAM (blue), VIC (green), NED (yellow) and PET (red), respectively were pooled into one ABI sample. Then PCR products of 3.0 l FAM, 3.0 l
VIC, 4.0 l NED, and 6.0 l PET were added into 9 l ddH 2O to get a 25 l dilution. A total volume of 13 l containing 9.93 l formamide, 0.07 l DNA ladder (445-LIZ, Applied
Biosystems) and 3 l diluted PCR product was denatured at 95 ºC for 5 min and held at 4 ºC.
The size of the PCR products was estimated using capillary electrophoresis on an ABI3100
Genotyper (Applied Biosystems, Foster City, Calif., USA). The internal molecular weight standard for the ABI3100 was Genescan 445-LIZ (Applied Biosystems). Alleles were called using the GeneMapper v3.7 software.
A total of 34 primer pairs produced polymorphic bands, of which 17 produced single bands in a few tested isolates and 17 produced codominant bands (2 to 3 alleles) in the tests with the initially selected 8 Pst and Psh isolates. The 17 codominant markers were further tested with the 20 Pst isolates collected from Idaho, Oregon and Washington in 2008. The amplicon sizes of the co-dominant markers ranged from 191 to 503 bp containing 5 to 13 di-,
41
tri- or tetra-nucleotide repeats (Table 1). There were no null alleles among the 20 Pst isolates and the allele frequencies of markers are presented in Table 1. A total of 14 haplotypes were identified with the highest frequency of 15% in the tested population (data not shown). Four and five alleles were detected with four of the markers (PstP001, PstP002,
PstP005, PstP025) when tested with international mainly Asian isolates (Sharma et al. personal communication). This result is agreeable with study by Chen et al. (2009) which
13 of 20 their EST-SSR detected 2 to 3 alleles, 5 tected 4 alleles and 2 detected 7 alleles in a population of 25 Pst isolates collected from China and Iran. Barhi et al. (2009) used a test population consisted isolates mainly from Pakistan and revealed 5,7, and 8 alleles by 3 of their reported SSR where the rest 7 pairs of primer produced 2 to 3 alleles. It is indicated that the EST-SSR may be a good tag to describe the heterkaryon/heterozygous feature of stripe rust and reflect the clonal character of US isolates with less allele diversity and more complex reproduction carried by the Asian isolates with more allele diversity. Most markers in this study detetcted only 2 alleles in tested US isolates suggested a single copy of functional genes (ESTs) in each nucleus and could be powerful to characterize the nucleus type or genotype of P. striiformis isolates.
To determine their genomic locations, the marker sequences were blasted with the P. graminis f. sp. tritici (Pgt ) and P. triticina (Pt ) genomic sequence databases
(http://www.broadinstitute.org/annotation/genome/puccinia_group/Blast.html?sp=Sblastn ).
Near half of the sequences were located to different stem rust or leaf rust genome
supercontigs (Table 1). By searching the Pst linkage maps constructed by Ma et al. (2009),
8 out of the 17 microsatellite loci were found on 6 linkage groups, indicating that these
microsatellite loci are dispersed throughout the genome (Table 1). The observed and
expected heterozygosity values ranged from 0.01 to 0.67 and from 0.08 to 0.45, respectively.
Of the 136 possible pairwise combinations of the 17 co-dominant markers tested for linkage
42 disequilibrium with the 20 randomly sampled isolates using GenePop version 4.0.10
(Raymond & Rousset, 1995; Rousset, 2008), 95 (69.9%) combinations had significant linkage disequilibrium (LD) at the P = 0.05 level and 41 (30.1%) did not. When the
Bonferroni’s correction (Rice 1989) was applied, the significant LD pairs were reduced to
34.6%. However, none of the paired loci were on the same supercontig. This result was expected as the fungal population is putatively asexually reproducing and clonal.
Chi-squared tests for Hardy-Weinberg equilibrium were conducted for the marker loci among the 20 isolates collected in 2008 by GenAlEx 6.41 (Peakall & Smouse 2006). None of the loci fitted Hardy-Weinberg equilibrium because the reproduction mechanism of the stripe rust population is clonal (Hovmøller et al. 2011). Principal coordinate analysis (PCoA) based on
Euclidean distances between SSR genotypes using software GenAlEx 6.4 (Peakall & Smouse
2006) illustrated that the 17 markers distinguished the eight isolates representing diverse races of P. striiformis (Fig. 1).
43
Fig. 1 Principal coordinates analysis of eight races of Puccinia striiformis using 17 SSR markers. PSH denotes races of P. striiformis f. sp. hordei , the barley stripe rust pathogen and PST denotes races of P. striiformis f. sp. tritici , the wheat stripe rust pathogen.
44
Of the 17 primer pairs which produced codominant bands among the P. striiformis
isolates, 14 also produced amplicons in one or more isolates of other Puccinia species (Table
1). The rates of cross-species transferability of the EST-SSR markers designed from Pst
from high to low is in the order of Pgt > Pt > Pp . None of the primer pairs amplified bands
from wheat DNA, suggesting that these microsatellite markers may also be useful in
detecting rust pathogens from infected wheat plants before sporulation.
In conclusion, EST libraries were good resources to design SSR markers. The SSR
primers derived from Pst ESTs are useful for characterization of population structures in P.
striiformis and potentially useful for other Puccinia species. The microsatellites that are
randomly located throughout the P. striiformis genome may better profile the pathogen
populations.
Acknowledgement
This research was supported by the US Department of Agriculture, Agricultural Research
Service (Project No. 5348-22000-014-00D) and Washington Wheat Commission (Project No.
13C-3061-3925). PPNS No. 0587, Department of Plant Pathology, College of Agricultural,
Human, and Natural Resource Sciences, Agricultural Research Center, Project Number
WNP00663, Washington State University, Pullman, WA 99164-6430, USA.
45
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47
CHAPTER THREE
Somatic hybridization between wheat stripe rust Puccinia striiformis f. sp. tritici and
barley stripe rust ( P. striiformis f. sp. hordei ) in grasses revealed by virulence patterns
and microsatellite markers
P. CHENG*, X. M. CHEN*†, R. A. MCINTOSH‡, D. R. SEE†
*Department of Plant Pathology, Washington State University, Pullman, WA 99164-6430,
USA; †USDA-ARS, Wheat Genetics, Quality, Physiology, and Disease Research Unit,
Pullman, WA 99164-6430, USA; ‡Plant Breeding Institute, Cobbitty, University of Sydney,
Private Bag 4011, Narellan, NSW, 2567, Australia
Abstract
Puccinia striiformis causes stripe rust on wheat, barley and many grass species. Somatic hybridization is a possible mechanism for generating variation in an asexually reproducing population, but evidence is lacking. There are also questions about the possibility of somatic hybridization between the wheat stripe rust pathogen ( P. striiformis f. sp. tritici , Pst ) and the barley stripe rust pathogen ( P. striiformis f. sp. hordei , Psh ). This study was undertaken to search for evidence of somatic hybridization through virulence and molecular characterization of natural isolates collected from various grasses as well as wheat and barley.
A total of 103 isolates were tested on 20 wheat and 12 barley genotypes that are used to differentiate Pst and Psh , respectively, and tested with 20 codominant microsatellite markers.
Virulence analyses identified isolates from grasses which were able to infect some differential genotypes of wheat, barley, or both. Microsatellite markers showed that the isolates capable of infecting both wheat and barley are very likely hybrids between Pst and Psh . The results
48 indicate that somatic hybridization occurs between Pst and Psh on grasses, especially wild barley grasses ( Hordeum spp.) which are often infected by both the formae speciales.
Keywords : microsatellite markers, virulence, resistance genes, population structure, somatic hybridization, grasses, stripe rust, Puccinia striiformis
Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the
U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.
Introduction
Stripe rust, caused by Puccinia striiformis Westend. which is an obligate, biotrophic and dikaryotic fungus, is a major disease in the world infecting wheat, barley and many grass species (Stubbs 1985; Chen 2005). In the literature, 320 grass species classified in 50 genera of the grass family Poaceae can be infected by stripe rust (Hassebrauk 1965).
According to the pathogen-host coevolution theory (Anderson & May 1982), the rust from wild grasses (high genetic diversity) could harbor more genetic variation than the ones from domestic common wheat (low genetic diversity) due to the host selection.
The P. striiformis species is separated into several formae speciales based on their specialization on different host plants. Eriksson (1894) reported the first five formae speciales of P. striiformis : P. striiformis f. sp. tritici (Pst ) on wheat, P. striiformis f. sp. hordei
(Psh ) on barley, P. striiformis f. sp. secalis on rye, P. striiformis f. sp. elymi on Elymus spp. and P. striiformis f. sp. agropyron on Agropyron spp. Later, three more formae speciales were reported: P. striiformis f. sp. dactylidis (Psd ) on orchard grass ( Dactylis glomerata L.)
(Manners 1960; Tollenaar 1967), P. striiformis f. sp. poae (Psp ) on Kentucky blue grass ( Poa
49
pratensis L.) (Tollenaar 1967) and P. striiformis f. sp. leymi on Leymus secalinus (Niu et al.
1991). Recently, a new forma specialis ( P. striiformis f. sp. pseudo-hordei , Psp-h) was
proposed for P. striiformis on wild barley grass ( Hordeum spp.) in Australia (Wellings et al.
2000). The host specificity of P. striiformis f. sp. hordei , P. striiformis f. sp. tritici and P.
striiformis f. sp . poae (from blue grass) were confirmed by greenhouse virulence tests and the
three formae speciales can be separated from each other by random amplified polymorphism
DNA (RAPD) analysis (Chen et al. 1995). Based on spore morphology and sequences of
ITS and beta-tubulin DNA, the stripe rust pathogens on bluegrass and orchard grass were
described as new species, P. pseudostriiformis and P. striiformoides , respectively (Liu &
Hambleton 2010) .
In the United States, wheat stripe rust was first recognized in 1915 (Carleton 1915).
The disease is most frequently destructive in the western United States, especially the Pacific
Northwest (PNW) and California, and since 2000 it has also become a serious production
problem in states east of the Rocky Mountains (Chen 2007). Barley stripe rust, caused by
Psh , is relatively new in the United States and first found in 1991 in Uvalde, Texas (Roelfs et al. 1992; Marshall & Sutton 1995). It became an invasive disease in the following years in
North America and has been found in Arizona, California, Colorado, Idaho, Montana, Oregon and Washington of the United States and Canada (Brown et al. 2001). The severe wheat stripe rust epidemics and very low levels of barley stripe rust in recent years clearly show that the diseases are caused by different formae speciales of P. striiformis (Chen, 2010 and 2011, unpublished data). The separation of Pst and Psh were also supported by analysis of molecular markers (Chen et al. 1995). Therefore, Pst races have been differentiated by a set of wheat genotypes and Psh races by a set of barley genotypes in the United States (Chen et al. 1995; Chen 2005; Wan & Chen 2012). Although Pst mostly infects wheat and Psh mostly infects barley, wheat and barley have been found as common hosts for both formae
50
speciales. Before Psh was first detected in the United States in 1991 (Roelfs et al. 1992), stripe rust collected from barley, rye, triticale and various grasses, except bluegrass and orchard grass, had been identified as the Pst races commonly found in wheat fields (Line &
Qayoum 1992; Line 2002). Since 1991, stripe rust samples from grasses (also except
bluegrass and orchard grass) have been identified as Pst races, sometimes Psh races, and occasionally as both Pst and Psh races (Chen 2005; Chen et al. 2010). Furthermore, stripe rust samples collected from barley were occasionally identified as both Pst and Psh races based on tests on both wheat and barley differential genotypes (Chen et al. unpublished data).
These observations let us speculate that grasses serving as a common host for both Pst and
Psh may provide the opportunity for the two formae speciales to hybrid.
The stripe rust pathogen is highly variable as demonstrated by both virulence and molecular tests (Stubbs 1985; Line 2002; Chen 2005; Hovmøller et al. 2011). However, the evolutionary mechanisms generating this diversity are not clear. Although some Berberis spp. have been demonstrated to serve as alternate hosts for Pst under greenhouse conditions
(Jin et al. 2010), sexual reproduction for Pst and Psh under natural conditions has not been demonstrated. A recent study showed that barberry ( Berberis vulgaris ) plants are not important for stripe rust in the US Pacific Northwest (Wang et al. 2011). Clonal reproduction via urediniospores is thought to be the major feature of the pathogen in the US
(Chen 2005) and Australia and Europe (Hovmøller et al. 2002; Enjalbert et al. 2005;
Hovmøller & Justesen 2007). The high ability to circumvent the specific resistance genes in wheat cultivars is thought to be due to mutation which results in new alleles and genotypes
(Wellings & McIntosh 1990; Line & Qayoum 1992). A stepwise mutation model was proposed by analyzing P. striiformis samples collected from Australia and New Zealand with
RAPD and AFLP markers (Steele et al. 2001). In addition to mutation, somatic hybridization, which is through karyogamy to re-assort nuclei and possibly leads to 51 re-assortment of chromosomes from different nuclei (somatic recombination), is thought to be a mechanism for creating variations in the pathogen population (Stubbs 1985; Chen 2005).
Evidence of somatic hybridization under controlled conditions have been showed by virulence difference in resulting isolates from two co-inoculated parental races with many rust fungi including flax rust, crown rust, stem rust, stripe rust and leaf rust (reviewed by Park
& Wellings 2012). A novel race of stripe rust was produced by inoculating two races on a common susceptible wheat cultivar, and somatic hybridization of whole nuclei during germ-tube fusion was demonstrated (Little & Manners 1969a, b; Wright & Lennard 1980).
Somatic hybridization has also been observed by electron microscopy (Kang et al. 1993a, c, b, d; Ma et al. 1993). Heterokaryosis, a phenomenon that a single- urediniospore isolate contains two different nuclei, has been found to be very common in Pst isolates by gene sequencing (Liu et al. 2009). Genetic recombination has also been proposed by studying the genetic diversity of the Pst population in Gansu, China (Mboup et al. 2009; Duan et al. 2010).
Detections of hybrid isolates in nature were also found in many other organisms. A new fungal pathogen as a result of hybridizing two Phytophthora spp. was able to attack a novel host species (Brasier et al. 1999). It is indicated that hybridization played a key role in adaptation of wild sunflowers to extreme habitats (Rieseberg et al. 2003). Hybridization also occurred between non-sister species of butterfly in genus Heliconius (Dasmahapatra et al.
2007). The recovery of red wolves in North Carolina was threatened by hybridizing with coyotes (Adams et al. 2007).
There is a great potential for new race generation if Pst and Psh can hybridize and produce races infecting both wheat and barley cultivars. A common host must be available for the growth of both formae speciales for somatic hybridization to take place. Although some wheat genotypes are susceptible to Psh and some barley genotypes are susceptible to
Pst , few commercial cultivars of wheat and barley are susceptible to Psh and Pst , respectively
52
(Chen et al. 1995; Pahalawatta & Chen 2005a, b). Wild grasses especially the barley
grasses ( Hordeum spp.) could serve as the common hosts for both formae speciales to
hybridize. This is the first study that provided both virulence and molecular evidence of
somatic hybridization between Pst and Psh in nature.
Materials and methods
Fungal collection and spore multiplication
Among 103 pathogen isolates used in this study, 41 were collected from 13 species of wild grasses in 2000-2008 (Table 1), 46 from wheat, 11 from barley, 4 from triticale and 1 from rye. The isolates from wheat and barley were selected from the collections made between
2000 and 2008 as references for Pst and Psh , respectively, except for six Pst isolates representing historically important races (PST-1, PST-17, PST-21, PST-43, PST-45 and
PST-59) from 1960s to 1999 (Line & Qayoum 1992; Chen 2005). All rust samples were increased in the greenhouse either on wheat cultivar ‘Nugains’ which does not have resistance in seedling stage to any Pst races so far in the United States (Line & Qayoum 1992; Chen et
al. 2002; Chen et al. 2010), or ‘Chinese 166’ ( Yr1 ), which is susceptible or moderately
susceptible to races of Psh (Stubbs 1985); and barley cultivar ‘Steptoe’, which is susceptible
to all races of Psh and resistant to most Pst races (Chen et al. 1995; Chen et al. 2010),
following the standard procedures as previously described (Chen & Line 1992a, b). The
single-spore isolates developed by Chen et al. (1993) were used for the six isolates
representing the races before 2000, and the remaining isolates were single-uredium isolates.
Increased urediniospores were dried and kept in a desiccator at 4 oC for less than two months
and in liquid nitrogen for a long period.
53
Table 1 Hosts, collection locations, Puccinia striiformis f. sp. tritici (Pst ) and P. striiformis f. sp. hordei (Psh ) races, virulence phenotypes with
combination of wheat and barley differential tests, and haplotypes and groups identified through molecular analysis of stripe rust isolates
collected from wheat, barley, triticale, rye and various grasses
Virulence analysis Molecular analysis Host, No. of isolates & isolate ID* State Pst race† Psh race† Phenotype Group Genotype Group Wheat ( Triticum aestivum ) (46) 08-4 CA PST-127 N/A‡ V68 VG 3 G1 MG 1 PST-127 (07-211-13-Sp1) WA PST-127 N/A V68 VG 3 G2 MG 1 08-308-6-Sp1 WA PST-116 N/A V67 VG 3 G2 MG 1 08-304-15 WA PST-137 N/A V69 VG 3 G4 MG 1
54 08-42 WA PST-109 N/A V23 VG 2 G15 MG 3a 08-165 KS PST-123 N/A V48 VG 3 G15 MG 3a 08-254 WI PST-117 N/A V49 VG 3 G15 MG 3a PST-17 WA PST-17 N/A V31 VG 2 G16 MG 3a PST-43 WA PST-43 N/A V36 VG 2 G16 MG 3a PST-59 CA PST-59 N/A V29 VG 2 G16 MG 3a 08-12-3 WA PST-25 N/A V34 VG 2 G16 MG 3a 08-25 WA PST-92 N/A V19 VG 2 G16 MG 3a 08-70 WA PST-23 N/A V32 VG 2 G16 MG 3a 08-223 WA PST-46 N/A V33 VG 2 G16 MG 3a PST-1 WA PST-1 N/A V15 VG 2 G17 MG 3a PST-3 WA PST-3 N/A V17 VG 2 G18 MG 3a PST-45 WA PST-45 N/A V28 VG 2 G18 MG 3a 08-327 ID PST-114 N/A V51 VG 3 G19 MG 3a
08-58-2 CA PST-67 N/A V30 VG 2 G30 MG 3b 08-224 OR PST-102 N/A V46 VG 3 G34 MG 3c PST-80 (2K048-8) TX PST-80 N/A V53 VG 3 G35 MG 3c PST-100 (03-202-10-Sp1) WA PST-100 N/A V41 VG 3 G36 MG 3c PST-98 (02-184-16-10) VA PST-98 N/A V42 VG 3 G39 MG 3c PST-78 (2K041-Yr9) AR PST-78 N/A V52 VG 3 G40 MG 3c 08-5-2 CA PST-129 N/A V44 VG 3 G40 MG 3c 08-7 GA PST-101 N/A V45 VG 3 G40 MG 3c 08-92 GA PST-100 N/A V41 VG 3 G40 MG 3c 08-120 CA PST-98 N/A V42 VG 3 G40 MG 3c 08-124 CA PST-111 N/A V55 VG 3 G40 MG 3c 08-141 CA PST-129 N/A V44 VG 3 G40 MG 3c 08-142 CA PST-98 N/A V42 VG 3 G40 MG 3c
55 08-156 KY PST-110 N/A V43 VG 3 G40 MG 3c 08-164 KS PST-117 N/A V49 VG 3 G40 MG 3c 08-167 VA PST-100 N/A V41 VG 3 G40 MG 3c 08-179 WA PST-119 N/A V50 VG 3 G40 MG 3c 08-237 OR PST-133 N/A V60 VG 3 G40 MG 3c 08-243 OR PST-102 N/A V46 VG 3 G40 MG 3c 08-244 WI PST-102 N/A V46 VG 3 G40 MG 3c 08-252 WI PST-131 N/A V59 VG 3 G40 MG 3c 08-253 WI PST-114 N/A V51 VG 3 G40 MG 3c 08-259 WI PST-117 N/A V49 VG 3 G40 MG 3c 08-269 ID PST-115 N/A V58 VG 3 G40 MG 3c 08-284 OR PST-101 N/A V45 VG 3 G40 MG 3c 08-291 OR PST-113 N/A V47 VG 3 G40 MG 3c 08-93 GA PST-115 N/A V58 VG 3 G43 MG 3c
08-225 OR PST-111 N/A V55 VG 3 G44 MG 3c Barley ( Hordeum vulgare ) (11) 06-223-N MN PST-102 PSH-48 V40 VG 3 G37 MG 3c PSH-75 (06-005) AZ N/A‡ PSH-75 V11 VG 1 G8 MG 2 08-275 OR N/A PSH-71 V13 VG 1 G8 MG 2 08-140 CA N/A PSH-54 V8 VG 1 G9 MG 2 08-66 WA N/A PSH-70 V5 VG 1 G10 MG 2 08-169 OR N/A PSH-77 V12 VG 1 G11 MG 2 PSH-53 (01-248) WA N/A PSH-53 V7 VG 1 G12 MG 2 PSH-72 (04-051-12) OR N/A PSH-72 V6 VG 1 G13 MG 2 08-110 CA N/A PSH-68 V9 VG 1 G25 MG 3b 08-114 CA N/A PSH-33 V1 VG 1 G25 MG 3b 08-137 CA N/A PSH-37 V10 VG 1 G27 MG 3b
56 Triticale ( Triticosecale spp.) (4) 05-161 GA PST-115 N/A V58 VG 3 G3 MG 1 02-089-10-N OR PST-133 N/A V60 VG 3 G5 MG 1 PST-21 CA PST-21 N/A V14 VG 2 G25 MG 3b 04-146 OR PST-101 PSH-33 V63 VG 3 G33 MG 3c Rye ( Secale cereal ) (1) 04-147-2-Sp1 OR PST-100 N/A V41 VG 3 G16 MG3a Foxtail barley grass ( Hordeum jubatum , H. spontaneum ) (16) 06-032-C CA PST-113 N/A V47 VG 3 G2 MG 1 06-030-C CA PST-137 N/A V69 VG 3 G6 MG 1 00-071-S CA PST-81 PSH-33 V4 VG 1 G7 MG 2 06-076-N CA PST-92 N/A V19 VG 2 G14 MG 3a 00-016 WA PST-93 N/A V21 VG 2 G16 MG 3a 06-030-N CA PST-100 N/A V41 VG 3 G16 MG 3a
06-036-N CA PST-105 N/A V35 VG 2 G16 MG 3a 06-058-N CA PST-91 N/A V64 VG 3 G17 MG 3a 06-035-N CA PST-105 N/A V35 VG 2 G18 MG 3a 04-063-S CA PST-6 PSH-33 V24 VG 2 G22 MG 3a 08-45-S CA PST-21 PSH-33 V2 VG 1 G25 MG 3b 08-146-S CA PST-21 PSH-33 V2 VG 1 G25 MG 3b 08-121-S CA PST-21 PSH-33 V2 VG 1 G27 MG 3b 08-145-S CA PST-21 PSH-46 V3 VG 1 G28 MG 3b 08-146-N CA PST-21 PSH-33 V2 VG 1 G29 MG 3b 08-121-N CA PST-101 PSH-33 V63 VG 3 G42 MG 3c Jointed goatgrass ( Aegilops cylindrica ) (6) 05-316 KS PST-50 N/A V37 VG 2 G16 MG 3a 07-137 WA PST-117 PSH-33 V39 VG 3 G32 MG 3c
57 07-137-6-Sp1 WA PST-53 N/A V20 VG 2 G16 MG 3a 07-179-S NE PST-98 PSH-46 V62 VG 3 G8 MG 2 08-JG WA PST-21 PSH-33 V2 VG 1 G24 MG 3b 08-268 WA PST-114 PSH-33 V65 VG 3 G40 MG 3c Crested wheatgrass ( Agropyron cristatum ) (1) 00-141-N ID PST-122 PSH-48 V66 VG 3 G3 MG 1 Wild oat ( Avena fatua ) (2) 08-wo-N WA PST-53 PSH-33 V25 VG 2 G23 MG 3b 08-wo-S WA PST-21 PSH-33 V2 VG 1 G26 MG 3b Meadow brome ( Bromus biebersteinii ) (3) 00-142-N ID PST-123 N/A V48 VG 3 G16 MG 3a 00-142-S ID PST-102 PSH-50 V61 VG 3 G20 MG 3a 00-142-C-S ID PST-20 PSH-50 V38 VG 2 G21 MG 3a Mountain brome ( Bromus marginatus ) (3)
08-74-N WA PST-114 PSH-33 V65 VG 3 G31 MG 3c 08-B1 WA PST-110 PSH-33 V56 VG 3 G38 MG 3c 08-B2 WA PST-110 PSH-33 V56 VG 3 G40 MG 3c Wild rye ( Elymus fedtschenkoi ; E. glaucus ) (2) 01-120 KS PST-122 N/A V57 VG 3 G16 MG 3a 05-469 ID PST-111 PSH-33 V54 VG 3 G41 MG 3c Western wheatgrass ( Pascopyrum smithii ) (2) 00-139-N ID PST-35 N/A V18 VG 2 G16 MG 3a 00-139-S ID PST-35 PSH-48 V26 VG 2 G21 MG 3a Bluebunch wheatgrass ( Pseudoroegneria spicata ) (3) 00-140-N ID PST-66 N/A V16 VG 2 G18 MG 3a 00-140-S ID PST-60 PSH-48 V27 VG 2 G21 MG 3a 00-140-Stephens ID PST-67 PSH-48 V22 VG 2 G21 MG 3a
58 Orchard grass ( Dactylis glomerata ) (2) 06-og-1 WA N/A N/A N/A N/A N/A N/A 06-og-2 WA N/A N/A N/A N/A N/A N/A Bluegrass ( Poa pratensis ) (1) 07-bg WA N/A N/A N/A N/A N/A N/A
* The first two digits of each isolate name stand for the collected year.
‡ N/A indicates that the isolate produced necrotic flecks or patches (ITs 1 or 2) but no uredia (avirulent) on any genotype of the differential set
and therefore designating a race name is not applicable. Differently, the orchard grass and bluegrass isolates did not produce any visible
symptom on any of the wheat and barley differential genotypes.
Virulence tests
Virulence patterns for each isolate were determined by testing on 20 wheat and 12 barley
genotypes that are used to differentiate Pst and Psh , respectively (Chen et al. 1995; Chen et al. 2002; Wan & Chen 2011). Fresh urediniospores or those kept in the desiccator at 4 oC for less than two months were used to inoculate the wheat and barley differential genotypes.
Seedlings at two-leaf stage were dust-inoculated with urediniospores mixed with talc (Sigma,
Milwaukee, WI, USA) at a ratio of 1:20. Inoculated plants were placed in a dew chamber for 24 h at 10 oC without light and then moved to a growth chamber to grow at a diurnal temperature cycle gradually changing from 4 oC at 2:00 am to 20 oC at 2:00 pm with a 16 h light and 8 h dark cycle. To prevent cross contamination, plants inoculated with different isolates were separated by plastic booths. Infection types (IT) were recorded 18-20 days after inoculation using the 0-9 scale (Line & Qayoum 1992; Chen et al. 2002). In this study, we only had ITs 0, 1 and 2 which were considered avirulent (A) and ITs 7, 8 and 9 which were considered virulent (V).
SSR markers
DNA was extracted from urediniospores following a modified protocol of DNA extraction
(Aljanabi & Martinez 1997). DNA concentration was determined using a ND-1000 spectrophotometer (Bio-Rad, Hercules, CA, USA) and stored at -20 oC. For PCR amplification, the stock DNA solution was diluted to 30 ng/ l as working solution and kept at
4oC. After initial screening, 20 SSR primer pairs with ability to detect homo/heterozygous
59
and polymorphic among 5 Pst races (PST-1, 21, 78, 100 and 127) and 3 Psh (PSH-4, 45 and
72) races were selected to better characterize the dikaryotic fungus which can be treated as diploid (Table 2). Of the 20 pairs of SSR primers, 3 (RJ18, RJ20 and RJ21) were developed from genomic DNA (Enjalbert et al. 2002) and 17 from expressed sequence tags (ESTs), including 4 (CPS02, CPS04, CPS08 and CPS13) developed by Chen et al. (2009), 2 (RJ2N and RJ8N) by Bahri et al. (2009a), and 11 (PstP001, PstP003, PstP004, PstP005, PstP006,
PstP007, PstP025, PstP029, PstP030, PstP031 and PstP033) by Cheng et al. (2012). All
primer sequences and annealing temperatures are listed in Table 2. In order to use
fluorescence to detect polymerase chain reaction (PCR) products, an M13 tag
(5’-CACGACGTTGTAAAACGAC) was added to the 5’ end of each forward primer
(Schuelke 2000).
Each PCR reaction contained 1× PCR buffer (10 mM of Tris-HCl, 50 mM of KCl); 200
M of dCTP, dGTP, dTTP and dATP; 1.5 mM MgCl 2; 5 pMol tagged M13 fluorescent
(Applied Biosystems, Foster city, CA); 1 pMol 5’-tagged forward primer; 5 pMol reverse
primer; 1 U of Taq polymerase (New England Biolabs, Ipswich, MA) and 0.75 ng of DNA in
a final volume of 12 l. PCR was performed in an iCycler (Bio-Rad) thermal cycler
(Watertown, MA, USA) with the following profile: 94ºC for 5 min, 35 cycles of 94ºC for 30 s,
45-57ºC for 30 s (varies for each primer pair) and 72ºC for 30 s, and 72ºC for 10 min
followed by a 4°C holding step. Three microliter PCR product was diluted to 25 L with
ddH 2O. A total volume of 13 L containing 9 L formamide, 1 L DNA ladder (445-LIZ,
Applied Biosystems) and 3 L diluted PCR product was denatured at 95ºC for 5 min and held
60
at 4ºC. The size of the PCR products was estimated using capillary electrophoresis on an
ABI3100 Genotyper (Applied Biosystems, Foster City, Calif., USA). To facilitate multiplex
detection of SSR markers, PCR products with four markers in the order listed in Table 2
tagged with FAM (blue), VIC (green), NED (yellow), and PET (red), were pooled into one
ABI sample. Then PCR products of 3.0 L FAM, 3.0 L VIC, 4.0 L NED, and 6.0 L PET
were added into 9 L ddH 2O to get a 25- L dilution. A total volume of 13 L containing
9.93 L formamide, 0.07 L DNA ladder (445-LIZ, Applied Biosystems) and 3 L diluted
PCR product was denatured at 95ºC for 5 min and held at 4ºC. The internal molecular weight standard for the ABI3100 was Genescan 445-LIZ (Applied Biosystems). Alleles were called using the GeneMapper v3.7 software.
61
Table 2 Primer sequences and annealing temperature of 20 microsatellite markers.
Tm No. Marker* Forward primer (5'-3') Reverse primer (5'-3') (°C) 1 RJ8N ACTGGGCAGACTGGTCAAC TCGTTTCCCTCCAGATGGC 53 2 PstP029 ACAATCCTCAAGGTGGTG GTTCGCTTTGTTGGTTAT 48 3 CPS04 GGGAAGCACAAGAACGGTC AGGGTGGTGTCAGCTAGTTGG 53 4 PstP001 ACCATCGGATTCCTGC ACGGTAGGCGAACGAC 49 5 PstP030 AAGGAAAAGAACTGTATG TTCAGATGCTCTATTCAA 41 6 RJ20 AGAAGATCGACGCACCCG CCTCCGATTGGCTTAGGC 53 7 PstP025 ATGTAAATGTAGCACCAAAC TCATGCTCGGTATGTCTC 48 8 PstP005 CCAACAGGCTCAAACTACCA TCCGCTTCGATCATAGCAC 52 9 PstP007 GATTTGCGAGGTCACTTT TGGTTGTGATAACGATGA 46 10 PstP006 GTTTGATTTTCCCTATGC AACTGAACGGAAGATGC 45 11 RJ21 TTCCTGGATTGAATTCGTCG CAGTTCTCACTCGGACCCAG 50 12 CPS02 GTTGGCTACGAGTGGTCATC TAACACTACACAAAAGGGGTC 50 13 PstP033 ACAGAAGGAAGGCAGATT GGGGTTTGATGTTATTAC 46 14 PstP031 TTGGGCGTCCTGGCATTG ACCCGTTCCTTCTTGGTCTTGC 57 15 PstP003 TAACCCCACGGCAACTCA ATCGTTGGCAGCCTTACC 50 16 CPS13 TCCAGGCAGTAAATCAGACGC ATCAGCAGGTGTAGCCCCATC 54 17 RJ18 CTGCCCATGCTCTTCGTC GATGAAGTGGGTGCTGCTG 53 18 CPS08 GATAAGAAACAAGGGACAGC CAGTGAACCCAATTACTCAG 50 19 PstP004 TCTCGCCTCGCTTGAATG TCGCTGGAGTTGGATGGA 50 20 RJ2N TTGTGGCGGAAGGGAACG GCATGAAACGATCAAAGAAGATAGC 53
* Markers with CPS (Chen et al. 2009), PstP (Cheng et al. 2012), and RJ?N (Bahri et al.
2009a) were developed from ESTs; and those with RJ (Enjalbert et al. 2002) were developed
from genomic DNA.
62
Data analyses
For cluster analysis, avirulent infection types (ITs) were converted to 0 and virulent ITs to 1 following the method of Chen et al. (1993, 1995). A similarity matrix based on simple match was generated using the SIMQUAL program using the NTsyspc 2.21L program (Rohlf
2008). Microsatellite data were used in all following molecular analysis. A neighbor-joining tree using Dice similarity index was generated by transformed dissimilarity matrix using NTsyspc 2.21L. Bootstrap analysis was used to determine the robustness of branches of the dendrogram with Winboot (Nelson et al. 1994). Principal coordinate analysis in the NTsyspc 2.21L program was used to construct a three-dimensional figure to show more detailed relationships of the isolates. Correlation between the SSR and virulence data was determined by comparison of the two similarity matrices using MXCOMP, a matrix comparison program of NTsyspc 2.21L. The existence of sub-structures in the population was also assessed on the SSR data using STRUCTURE (Pritchard et al. 2000), a Bayesian clustering algorithm that assigns individuals to putative subgroups with distinctive allele frequencies. The program STUCTURE HARVESTER
(http://taylor0.biology.ucla.edu/structureHarvester/ ) was used to determine the best fit number of clusters, K, by generating a plot of the mean likelihood values per K and a table of the Evanno results (Evanno et al. 2005; Earl & VonHoldt 2011). To identify the hybrid individuals in the population, program NEWHYBRIDS ver 1.1 (Anderson & Thompson,
2002) implementing a Bayesian method and a Monte Carlo Markov Chain (MCMC) procedure with 150,000 sweeps and a 150,000 burn-in was employed to analyze the uniqe
63
haplotypes detected by microsatellites. To estimate the introgression between isolates from
wheat, barley and wild grasses, MIGRATE-N ver. 3.2.19 was used to calculate the migration
rates (M). The maximum likelihood estimations theta ( Θ= 4Ne ) were estimated using the
Bayesian method in MIGRATE-N for microsatellite data (Beerli 2009). The Brownian motion approximation to the stepwise mutation model was used for the microsatellite data.
Five independent runs were used with 5 short chains and 5 long chains, for a total of 2000 and 20,000 generations, a burn-in of 20,000 steps for the calculations. We also conducted genotype assignment testes by GENECLASS2 (Piry et al. 2004), a program uses allele frequencies within populations to compute the likelihood of an individual genotype occurring in each population and then compares the likelihoods against simulated genotypes to provide a ‘probability of belonging’ ( P) for each individual from each sampled population (Paetkau et al. 1995).
Results
Virulence characterization
Of the 103 isolates tested, the selected 46 Pst isolates originally from wheat were identified as expected Pst races; the 10 selected Psh isolates originally from barley were identified as expected Psh races (Table 1); the 47 isolates from grasses, triticale and rye had complex virulence patterns, which are described as the following. Out of the 47 isolates, 18 were virulent only on wheat differentials, and therefore identified as Pst races. Seven were virulent on some barley differentials and Chinese 166, but not any other wheat differentials,
64 and therefore considered as Psh races. Nineteen were virulent on both wheat and barley, and therefore considered either Pst or Psh races, and three were not virulent on any of the wheat and barley differentials and therefore considered neither Pst nor Psh (Table 1). The four groups were highly associated to the hosts from which they were collected. Isolates from wheat belonged to Pst , isolates from barley belonged to Psh and those from grasses were Pst , Psh , or not separable to neither of the two formae speciales. The 19 isolates virulent on both wheat and barley differentials were all from grasses [ Aegilops cylindrica (3),
Agropyron cristatum (1), Avena fatua (1), Bromus biebersteinii (2), Bromus marginatus (3),
Elymus glaucus (1), Hordeum jubatum (3), Hordeum spontaneum (1), Pascopyrum smithii (1),
Pseudoroegneria spicata (2)] and triticale [ Triticosecale spp. (1)]. The three isolates, which did not produce any visible symptom (IT 0) on all wheat and barley differentials, were collected from orchard grass (06-og-1 and 06-og-2) or bluegrass (07-bg) and therefore were classified as P. striiformis f. sp. dactylidis (P. striiformoides ) or P. striiformis f. sp. poae (P. pseudostriiformis ) (Table 1).
Excluding the orchard grass and bluegrass isolates, the remaining 100 isolates from other grasses, wheat, barley, triticale and rye comprised 69 virulence phenotypes (pathotypes) based on the IT data produced on both wheat and barley differential sets (Table 3). Of the
69 virulence phenotypes, 41 were identified as Pst races only, 10 as Psh races only and 18 as possible hybrids between Pst and Psh .
Three virulence groups (VGs) were revealed (Fig. 1). Isolates in VG 1 were all Psh races except for three considered possible hybrids. Isolates in VGs 2 and 3 were all Pst
65
races along with 15 also identified as Psh races (Table 3). The major difference between the
latter two groups was that races in VG 2 had shorter virulence spectra than those in VG 3
(Table 3). Besides the selected Pst and Psh reference isolates from wheat and barley respectively, the host origins of the isolates in VG 1 were mainly H. jubatum , Ae. cylindricum and A. fatua (Table 1). VG 2 consisted of isolates from Ae. cylindricum , A. fatua , B.
biebersteinii , H. jubatum , P. smithii , P. spicata and Triticosecale spp. The isolates in VG 3
came from Ae. cylindricum , A. cristatum , B. biebersteinii , B. marginatus , E. fedtschenkoi , E.
glaucus , H. jubatum , Triticosecale spp. and S. cereale . Fig. 2 showed the relationships of
the three VGs in a three-dimensional plot of principle coordinate analysis based on the
virulence data. The three orchard grass and bluegrass isolates were not included in these
analyses as they were not pathogenic on any wheat and barley differentials.
66
Fig. 1 Cluster analysis of the 69 identified virulence patterns (UPGMA on Nei distances with virulence data). The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in bootstrap analysis using the Winboot program (Nelson et al. 1994). 67
Fig. 2 Three-dimensional plot of 69 virulence phenotypes using principal coordinates analysis. VG 1 - VG 3 corresponding to the clusters in Fig. 1.
68
Table 3 Virulence phenotypes, Puccinia striiformis f. sp. tritici (Pst ) and P. striiformis f. sp. hordei (Psh ) races identified from isolates of P.
striiformis isolates collected from wheat, barley, triticale, rye and various grasses
Virulence Virulence formula* Pst Psh Isolates Virulence type Wheat differentials Barley differentials race race No. ID group V1 None 1,7 N/A† PSH-33 1 08-114 VG 1 V2 2 1,7 PST-21 PSH-33 6 08-JG VG 1 V3 2 1,7,8 PST-21 PSH-46 1 08-145-S VG 1 V4 1,14 1,7 PST-81 PSH-33 1 00-071-S VG 1 V5 None 1,7,10,12 N/A PSH-70 1 08-66 VG 1 V6 None 1,2,3,4,5,6,7,8,9,10,11,12 N/A PSH-72 1 PSH-72 VG 1
69 V7 None 1,8,9 N/A PSH-53 1 PSH-53 VG 1 V8 None 1,7,8,12 N/A PSH-54 1 08-140 VG 1 V9 None 1,6,7,8,10,12 N/A PSH-68 1 08-110 VG 1 V10 None 1,2,4,7 N/A PSH-37 1 08-137 VG 1 V11 None 1,2,3,4,5,6,7,8,9,10,12 N/A PSH-75 1 PSH-75 VG 1 V12 None 1,3,5,7,8,9,10,12 N/A PSH-77 1 08-169 VG 1 V13 None 1,3,5,6,7,8,9,10,12 N/A PSH-71 1 08-275 VG 1 V14 2 None PST-21 N/A 1 PST-21 VG 2 V15 1,2 None PST-1 N/A 1 PST-1 VG 2 V16 1,2,10,11,12,16 None PST-66 N/A 1 00-140-N VG 2 V17 1,3 None PST-3 N/A 1 PST-3 VG 2 V18 1,10 None PST-35 N/A 1 00-139-N VG 2 V19 1,10,12 None PST-92 N/A 2 06-076-N VG 2
V20 1,6,10 None PST-53 N/A 1 07-137-6-sp1 VG 2 V21 1,6,10,12 None PST-93 N/A 1 00-016 VG 2 V22 1,2,3,11,12,16 1 PST-67 PSH-48 1 00-140-step VG 2 V23 1,4,8,10,12 None PST-109 N/A 1 08-42 VG 2 V24 1,6,8,12 1,7 PST-6 PSH-33 1 04-063-S VG 2 V25 1,6,10 1,7 PST-53 PSH-33 1 08-wo-N VG 2 V26 1,10 1 PST-35 PSH-48 1 00-139-S VG 2 V27 1,12,16 1 PST-60 PSH-48 1 00-140-S VG 2 V28 1,3,12,13,15 None PST-45 N/A 1 PST-45 VG 2 V29 1,3,11,12,16 None PST-59 N/A 1 PST-59 VG 2 V30 1,2,3,11,12,16 None PST-67 N/A 1 08-58-2 VG 2 V31 1,2,3,9,11 None PST-17 N/A 1 PST-17 VG 2 70 V32 1,3,6,9,10 None PST-23 N/A 1 08-70 VG 2 V33 1,3,6,9,10,11 None PST-46 N/A 1 08-223 VG 2 V34 1,3,6,8,9,10,12 None PST-25 N/A 1 08-12-3 VG 2 V35 1,8,10,11,12,16,17,20 None PST-105 N/A 2 06-035-N VG 2 V36 1,3,4,5,12,14 None PST-43 N/A 1 PST-43 VG 2 V37 1,3,4,5,14 None PST-50 N/A 1 05-316 VG 2 V38 1,6,8,10,12 1,5 PST-20 PSH-50 1 00-142-c-s VG 2 V39 1,3,6,8,9,10,11,12,14,16,17,18,19,20 1,7 PST-117 PSH-33 1 07-137 VG 3 V40 1,3,8,9,10,11,12,14,16,17,18,19,20 1 PST-102 PSH-48 1 06-223-N VG 3 V41 1,3,8,9,10,11,12,16,17,18,19,20 None PST-100 N/A 5 PST-100 VG 3 V42 1,3,8,10,11,12,16,17,18,19,20 None PST-98 N/A 3 PST-98 VG 3 V43 1,3,8,9,11,12,16,17,18,19,20 None PST-110 N/A 1 08-156 VG 3 V44 1,2,3,8,10,11,12,16,17,18,19,20 None PST-129 N/A 2 08-5-2 VG 3
V45 1,2,3,8,9,10,11,12,16,17,18,19,20 None PST-101 N/A 2 08-7 VG 3 V46 1,3,8,9,10,11,12,14,16,17,18,19,20 None PST-102 N/A 3 08-224 VG 3 V47 1,2,3,8,9,10,11,12,14,16,17,18,19,20 None PST-113 N/A 2 06-032-C VG 3 V48 1,3,6,8,9,10,11,12,16,17,18,19,20 None PST-123 N/A 2 08-165 VG 3 V49 1,3,6,8,9,10,11,12,14,16,17,18,19,20 None PST-117 N/A 3 08-164 VG 3 V50 1,3,4,8,9,10,11,12,16,17,18,19,20 None PST-119 N/A 1 08-179 VG 3 V51 1,3,4,8,9,10,11,12,14,16,17,18,19,20 None PST-114 N/A 2 08-253 VG 3 V52 1,3,11,12,16,17,18,19,20 None PST-78 N/A 1 PST-78 VG 3 V53 1,3,8,11,12,16,17,18,19,20 None PST-80 N/A 1 PST-80 VG 3 V54 1,3,5,8,10,11,12,16,17,18,19,20 1,7 PST-111 PSH-33 1 05-469 VG 3 V55 1,3,5,8,10,11,12,16,17,18,19,20 None PST-111 N/A 2 08-124 VG 3 V56 1,3,8,9,11,12,16,17,18,19,20 1,7 PST-110 PSH-33 2 08-B2 VG 3 71 V57 1,2,3,6,8,9,10,11,12,14,16,17,18,19,20 None PST-122 N/A 1 01-120 VG 3 V58 1,3,5,8,9,10,11,12,14,16,17,18,19,20 None PST-115 N/A 3 08-269 VG 3 V59 1,3,5,6,8,9,10,11,12,14,16,17,18,19,20 None PST-131 N/A 1 08-252 VG 3 V60 1,2,3,5,,6,8,9,10,11,12,14,16,17,28,29,20 None PST-133 N/A 2 08-237 VG 3 V61 1,3,8,9,10,11,12,14,16,17,18,19,20 1,5 PST-102 PSH-50 1 00-142-S VG 3 V62 1,3,8,10,11,12,16,17,18,19,20 1,7,8 PST-98 PSH-46 1 07-179-S VG 3 V63 1,2,3,8,9,10,11,12,16,17,18,19,20 1,7 PST-101 PSH-33 2 08-121-N VG 3 V64 1,9,10 None PST-91 N/A 1 06-058-N VG 3 V65 1,3,4,8,9,10,11,12,14,16,17,18,19,20 1,7 PST-114 PSH-33 2 08-268 VG 3 V66 1,2,3,6,8,9,10,11,12,14,16,17,18,19,20 1 PST-122 PSH-48 1 00-141-N VG 3 V67 1,3,4,5,8,9,10,11,12,14,16,17,18,19,20 None PST-116 N/A 1 08-308-6-sp1 VG 3 V68 1,2,3,5,6,8,9,10,11,12,13,15,16,17,18,19,20 None PST-127 N/A 2 PST-127 VG 3 V69 1,2,3,5,6,8,9,10,12,13,15,17,18,19,20 None PST-137 N/A 2 06-030-C VG 3
* Pst races were based on wheat differential cultivars: 1 = Lemhi ( Yr21 ), 2 = Chinese 166 ( Yr1 ), 3 = Heines VII ( Yr2 ,YrHVII ), 4 = Moro
(Yr10 ,YrMor ), 5 = Paha ( YrPa1 ,YrPa2 ,YrPa3 ), 6 = Druchamp ( Yr3a ,YrD ,YrDru ), 7 = AvSYr5NIL ( Yr5 ), 8 = Produra ( YrPr1 ,YrPr2 ), 9 =
Yamhill ( Yr2 ,Yr4a ,YrYam ), 10 = Stephens ( Yr3a ,YrS ,YrSte ), 11 = Lee ( Yr7 ,Yr22 ,Yr23 ), 12 = Fielder ( Yr6 ,Yr20 ), 13 = Tyee ( YrTye ), 14 = Tres
(YrTr1 ,YrTr2 ), 15 = Hyak ( Yr17 ,YrTye ), 16 = Express ( YrExp1 , YrExp2 ), 17 = AvSYr8NIL ( Yr8 ), 18 = AvSYr9NIL ( Yr9 ), 19 = Clement
(Yr9 ,YrCle ), 20 = Compair ( Yr8 ,Yr19 ). Psh races were based on barley differential cultivars: 1 = Topper (None), 2 = Heils Franken ( Rps4 ,
rpsHF ), 3 = Emir ( rpsEm , rpsEm2), 4 = Astrix ( Rps4 , rpsAst ), 5 = Hiproly ( rpsHi1 , rpsHi2 ), 6 =Varunda ( rpsVa1 , rpsVa2 ), 7 = Abed Binder
12 ( rps2 ), 8 = Trumpf ( rpsTr1 , rpsTr2 ), 9 = Mazurka ( Rps1.c ), 10 = Bigo ( Rps1.b ), 11 =I 5 ( Rps3 , rpsI5 ), and 12 = Bancroft ( RpsBa ). 72
† None
Molecular analyses
The predominant genotype among the 46 preseletced Pst isolates for each locus was designated as the AA type, the other homozygote genotype was designated as the BB type and the AB type was designated when both genotype were present (heterozygote) (Fig. 3).
In this way, typical Pst isolates should have more AA loci and typical Psh isolates should have more BB loci. Twenty pairs of SSR primers identified 47 haplotypes from the 103 isolates (Fig. 4).
The neighbor-joining tree generated with the SSR data clustered all 44 haplotypes into three molecular groups (MGs) (Fig. 5). The two orchard grass isolates and one bluegrass isolate were excluded from the cluster analysis as they did not have any amplified fragment at 6-8 of the 20 loci (Fig. 4) and were classified as different species. The three MGs for P. striiformis were well supported by the three-dimensional plot of principle coordinate analysis (Fig. 6). MG 1 consisted of six haplotypes with predominantly (55-95%) AA loci and fewer BB and/or AB loci. MG 2 consisted of seven haplotypes with predominant
(65-80%) BB loci and fewer AA and/or AB loci. MG 3, consisting of 34 haplotypes, was the biggest and most diverse group, and therefore further separated into three subgroups.
MG 3a had nine haplotypes with similar numbers of AA, BB and AB loci. MG 3b had eight haplotypes with more than 50% AB loci, 15-30% BB loci and few AA loci. MG 3c had 14 haplotypes with predominant (60-85%) AB loci and few AA and/or BB loci. The
MGs were associated with their original host plants. Isolates from wheat were in MG 1 and MG 3, those from barley in MG 2 and from grasses in MG 1, MG 2, and MG 3. In
73
general, isolates from H. jubatum (wild barley grass or foxtail) were in all three groups
(Table 1). Correlation of the virulence matrix with the molecular matrix using MXCOMP
in the NTsyspc 2.21L showed a moderate, but highly significant correlation coefficient (r =
0.54). The highest K value yielded by STRUCTURE was 4, which indicated four
population subdivisions of the complete samples (Fig. 7A). Isolates from wheat consisted
of three subdivisions including MG1, MG3a and MG3c in Fig. 4. Isolates from barley
consisted of two subdivisions corresponding to MG2 and MG3 in Fig. 4. Isolates from
other grasses consisted of all four subdivisions. NEWHYBRIDS ananylsis resulted
similar molecular groups identified by STRUCTURE (Fig. 7B). Isolates from wheat
contained one pure forma specialis ( P. striiformis f. sp. tritici ) and F 1 hybrids. Isolates
from barley consist of the other pure forma specialis ( P. striiformis f. sp. hordei ) and F 1 hybrids. Isolates from other grasses consist of both pure formae speciales and the hybrids
(Fig. 7B). Maximum likelihood estimates of migration rates among isolates from different hosts were listed in Table 4. Gene migration can occur between isolates from wheat and barley with rates of 1.14 and 1.01, respectively (Table 4). Gene flow was detected from the wheat population into the grass population and from the barley population into the grass population but not the converse. Genotypes of all sampled isolates assigned using GENECLASS2 were listed in Table 5. In addition to the rust population of the collected host, some of the isolates from wheat and barley can be assigned to the population from grasses. Similarly, isolates from grasses also can be assigned to either the wheat or barley population. These results further indicated that the
74
isolates from wheat and barley can hybrid and produce hybrid isolates capable of infecting
wheat, barley andgrasses.
Table 4 The mutation-scaled population size ( Θ) and migration rates (M) among the
Puccinia striiformis populations from wheat, barley and grasses based on the SSR data
Migration rate Recipient Source population population Θa Wheat Barley Grasses Wheat 0.96±0.07 1.01±0.15 0.99±0.15 Barley 0.70±0.10 1.14±0.17 0.96±0.17 Grasses 0.92±0.70 1.24±0.18 1.10±0.17
a Maximum likelihood estimates of migration rates ( M = m/ ) and 95% confidence
intervals (parentheses) were calculated using MIGRATE-N 3.2.19.
75
Table 5. Probabilities of assignment of individual isolates collected from wheat, barley and grasses can be assigned to populations of these host groups using GENECLASS2.
Probability Host/sample name Wheat Barley Grasses Wheat/PST-127 0.016 0 0.015 Wheat/08-4 0.016 0 0.015 Wheat/08-308-6-Sp1 0.016 0 0.015 Wheat/08-01-15 0.118 0 0.084 Wheat/08-58-2 0.207 0.019 0.606 Wheat/08-93 0.228 0.006 0.216 Wheat/PST-80 0.293 0.033 0.279 Wheat/08-7 0.477 0.025 0.372 Wheat/PST-1 0.558 0.021 0.944 Wheat/PST-3 0.558 0.021 0.944 Wheat/PST-17 0.558 0.021 0.944 Wheat/PST-43 0.558 0.021 0.944 Wheat/PST-45 0.558 0.021 0.944 Wheat/PST-59 0.558 0.021 0.944 Wheat/08-12-3 0.558 0.021 0.944 Wheat/08-25 0.558 0.021 0.944 Wheat/08-42 0.558 0.021 0.944 Wheat/08-70 0.558 0.021 0.944 Wheat/08-165 0.558 0.021 0.944 Wheat/08-223 0.558 0.021 0.944 Wheat/08-254 0.558 0.021 0.944 Wheat/08-327 0.558 0.021 0.944 Wheat/08-225 0.641 0.001 0.16 Wheat/PST-78 0.875 0.007 0.231 Wheat/PST-98 0.875 0.007 0.231 Wheat/PST-100 0.875 0.007 0.231 Wheat/08-5-2 0.875 0.007 0.231 Wheat/08-92 0.875 0.007 0.231 Wheat/08-120 0.875 0.007 0.231 Wheat/08-124 0.875 0.007 0.231 Wheat/08-141 0.875 0.007 0.231 Wheat/08-142 0.875 0.007 0.231 Wheat/08-156 0.875 0.007 0.231 Wheat/08-164 0.875 0.007 0.231 Wheat/08-167 0.875 0.007 0.231 Wheat/08-179 0.875 0.007 0.231 76
Wheat/08-237 0.875 0.007 0.231 Wheat/08-243 0.875 0.007 0.231 Wheat/08-244 0.875 0.007 0.231 Wheat/08-252 0.875 0.007 0.231 Wheat/08-253 0.875 0.007 0.231 Wheat/08-259 0.875 0.007 0.231 Wheat/08-269 0.875 0.007 0.231 Wheat/08-284 0.875 0.007 0.231 Wheat/08-291 0.875 0.007 0.231 Wheat/08-224 0.952 0.003 0.296 Barley/PSH-72 0 0.129 0.002 Barley/08-110 0.341 0.13 0.742 Barley/08-114 0.341 0.13 0.742 Barley/08-137 0.341 0.13 0.742 Barley/08-66 0 0.602 0.047 Barley/PSH-75 0 0.838 0.066 Barley/08-140 0 0.838 0.066 Barley/08-275 0 0.838 0.066 Barley/PSH-53 0 0.872 0.229 Barley/08-169 0 0.872 0.229 Grasses/07-bg 0 0.005 0.013 Triticale/05-161 0.016 0 0.015 Grasses/06-032-C 0.016 0 0.015 Grasses/04-063-S 0 0.048 0.039 Grasses/06-030-C 0.041 0.001 0.062 Grasses/00-071-S 0 0.838 0.066 Grasses/07-179-S 0 0.838 0.066 Grasses/00-141-N 0.111 0 0.092 Grasses/05-469 0.582 0.004 0.106 Grasses/06-og-1 0.141 0.003 0.136 Grasses/06-223-N 0.082 0.012 0.137 Grasses/08-B1 0.082 0.012 0.137 Grasses/06-og-2 0.069 0.001 0.146 Triticale/04-146 0.005 0.033 0.175 Grasses/08-268 0.875 0.007 0.231 Grasses/08-B2 0.875 0.007 0.231 Grasses/07-137 0.045 0.019 0.298 Triticale/02-089-10-N 0.295 0.001 0.357 Grasses/08-121-N 0.28 0.055 0.42 Grasses/08-74-N 0.635 0.012 0.454 Grasses/08-145-S 0.015 0.194 0.565 Grasses/08-146-N 0.302 0.073 0.59
77
Grasses/06-076-N 0.022 0.069 0.671 Triticale/PST-21 0.341 0.13 0.742 Grasses/08-45-S 0.341 0.13 0.742 Grasses/08-121-S 0.341 0.13 0.742 Grasses/08-146-S 0.341 0.13 0.742 Grasses/08-JG 0.341 0.13 0.742 Grasses/08-wo-N 0.341 0.13 0.742 Grasses/00-142-S 0.043 0.156 0.748 Grasses/08-wo-S 0.328 0.17 0.786 Grasses/06-058-N 0.574 0.018 0.909 Rye/04-147-2 sp1 0.558 0.021 0.944 Grasses/00-016 0.558 0.021 0.944 Grasses/06-030-N 0.558 0.021 0.944 Grasses/06-035-N 0.558 0.021 0.944 Grasses/06-036-N 0.558 0.021 0.944 Grasses/07-137-6-Sp1 0.558 0.021 0.944 Grasses/05-316 0.558 0.021 0.944 Grasses/00-142-N 0.558 0.021 0.944 Grasses/01-120 0.558 0.021 0.944 Grasses/00-139-N 0.558 0.021 0.944 Grasses/00-140-N 0.558 0.021 0.944 Grasses/00-142-C-S 0.304 0.106 0.979 Grasses/00-139-S 0.304 0.106 0.979 Grasses/00-140-S 0.304 0.106 0.979 Grasses/00-140-Step 0.304 0.106 0.979
78
Fig. 3 (A) Examples of designated AA, AB, and BB types with two alleles (B) three alleles and four alleles (C) markers.
79
Genotype Marker No. Isolate Host Molecular No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 No. Example name group G1 AAAAAA AA AA AAAAAAAAAAAAAAAAAA AA AA AA AA AA AB 1 08-4 Wheat MG1 G2 AAAAAA AA AA AAAAAAAAAAAAAAAAAA AA AA AB AA AA AB 3 PST-127 Wheat MG1 G3 AAAAAA AA AA AAAAAAAAAAAAAAAAAA AA AA AA AB BB BB 2 05-161 Triticale MG1 G4 AAAAAA AA AA AAAAAAAAAAAAAAAAAA AA AA AB AB BB AB 1 08-304-15 Wheat MG1 G5 AAAAAA AA AA AAAAAAAAAAAAAAAA BB BB AB AB AB AA AA 1 02-089-10-n Triticale MG1 G6 AAAAAA AA AA AAAAAAAA ABABABABAA AA AB AB AB BB AB 1 06-030-C Foxtail MG1 G7 AAAA BB BB BB BB BB BB BB BB BB AB AB BB BB AA AA BB BB BB 1 00-071-S Foxtail MG2 G8 AA BB BB BB BB BB BB BB BB BB BB AB AB BB BB AA AA BB AA BB 3 PSH-75 Barley MG2 G9 AA BB BB BB BB BB BB BB BB BB BB AB AB BB BB AA AA BB BB BB 1 08-140 Barley MG2 G10 AA BB BB BB BB BB BB BB BB BB AB AB AB BB BB AA AA BB AA BB 1 08-66 Barley MG2 G11 AA BB BB BB BB BB BB BB AB BB BB AB AB BB BB AA AA BB AA BB 1 08-169 Barley MG2 G12 AA BB BB BB BB BB BB BB AB BB BB AB AB BB BB AA AA BB BB BB 1 PSH-53 Barley MG2 G13 BB BB BB BB BB BB BB BB BB BB BB AB AB BB BB AB AB BB BB BB 1 PSH-72 Barley MG2 G14 AAAAAA AA AA ABABABABABAB BBAA AB AB AA AB BB BB AB 1 06-076-N Foxtail MG3a G15 AAAAAAABABAAAAABAAABAA BB AB BB BB AA AB BB BB BB 3 08-165 Wheat MG3a G16 AAAAAAABABAAABABAAABAA BB AB BB BB AA AB BB BB BB 16 PST-43 Wheat MG3a G17 AAAAAAABABAAABABAAABAA BB AB BB BB AA AB BB BB AB 2 PST-1 Wheat MG3a G18 AAAAAAABABAAABABAAABAA BB AB BB BB AA AB BB AB BB 4 PST-3 Wheat MG3a G19 AAAAAAABABAAABABAAABAA BB AB BB BB AA AB BB AB AB 1 08-327 Wheat MG3a G20 AAABAAABABABABABAAAB BB BB AB BB BB AA AA BB BB BB 1 00-142-S Meadow MG3a G21 AAABAAABABABABABAAABAB BB AB BB BB AA AA BB BB BB 4 00-140-S Bluebunch MG3a G22 AAABAAABAB BB BB AB BB ABAB BB AB BB BB AA AB AA BB AB 1 04-063-S Foxtail MG3a G23 AAABAAABAB BBAAABAAABABABABAB AB AA AA BB AA BB 1 08-wo-S Wild oat MG3b G24 AAABAAABAB BBAAABAAABABABABAB AB AA AB BB AA BB 1 08-JG Jointed goat MG3b G25 AAABAAABAB BB ABABAAABABABABAB AB AA AB BB AA BB 5 PST-21 Triticale MG3b G26 AAABAAABAB BBAAABAAABABABABAB AB AA AB BB BB BB 1 08-wo-N Wild oat MG3b G27 AAABAAABAB BB ABABAAABABABABAB AB AA AB BB BB BB 2 08-121-S Foxtail MG3b G28 AAABAAABAB BB ABABABABABABABAB AB AA AB BB AA BB 1 08-145-S Foxtail MG3b G29 AAABAAABAB BB ABABAAABABABABAB AB AB AB BB BB BB 1 08-146-N Foxtail MG3b G30 AAABABABABABABABAAABABABABAB AB AA AB AB AA BB 1 08-58-2 Wheat MG3b G31 ABAAAAABABABABABAAABABABAB BB BB AB AB BB BB AB 1 08-74-N Mount brome MG3c G32 ABAAABABABABABABABABABABAB BB BB AB AB BB AB AB 1 07-137 Jointed goat MG3c G33 ABABABABAB BB ABABABABABABAB BB AB AB AB AB BB AB 1 04-146 Triticale MG3c G34 ABAAAAABABABABAAAAABABABABAB AB AB AB BB AB AA 1 08-224 Wheat MG3c G35 ABAAABABAB BB ABAAAA BB ABABABAB AB AB AB BB BB AA 1 PST-80 Wheat MG3c G36 ABAAABABAB BB ABAAAAABABABABAB AB AB AB BB BB AA 1 PST-100 Wheat MG3c G37 ABAAABABAB BB ABAAABABABABABAB AB AB AB BB BB AA 1 06-223-N Barley MG3c G38 AB AA ABABAB BB ABAAABABABABABAB AB AB AB BB AB AA 1 08-B1 Mount brome MG3c G39 ABAAABABAB BB ABAAAAABABAB BB AB AB AB AB BB AB AA 1 PST-98 Wheat MG3c G40 ABAAABABAB BB ABAAAAABABABABAB AB AB AB BB AB AA 23 PST-78 Wheat MG3c G41 ABAAABABAB BB ABAAAAABABABABAB AB AB AA BB AB AA 1 05-469 Wild rye MG3c G42 ABAAABABAB BB ABABAAABABABABAB AB AB AB BB AB BB 1 08-121-N Foxtail MG3c G43 ABAAABABABABAAAAAAABABABABAB AB AB AB AB AB AA 1 08-93 Wheat MG3c G44 ABAAABABABABABAAAAABABABABAB AB AB AB AB AB AB 1 08-225 Wheat MG3c Psd -1 BBAB ABABAB ABAAABAA BB BB BB AA BB 1 06-og-1 Orchard grass Psd -2 BBAA AA AAAAAAABBB BB BB AB AB BB AA 1 06-og-2 Orchard grass Psp -1 BB AA BB BB BB AA BB BB BB AB AB BB 1 07-bg Bluegrass
Fig. 4 Molecular genotypes revealed by 20 microsatellites, markers from 1 to 20 are presented in Table 2. The genotypes are sorted by molecular groups (MGs).
80
Fig. 5 Neighbor-joining tree of 44 molecular haplotypes based on SSR marker data by
NTsyspc 2.21L program. MG 1 - 3 corresponds to the molecular groups. The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in bootstrap analysis using the Winboot program (Nelson et al. 1994).
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Fig. 6 Three-dimentional plot of 44 molecular haplotypes based on SSR data using principal coordinates analysis. White , black and gray circles indicate samples collected from wheat, barley and grasses, repectively.
82
A. B.
Fig. 7 Molecular groups revealed by STRUCTURE (A) and NEWHYBRIDS ( B) with 44 haplotypes of Puccinia striiformis . The molecular genotypes are aligned by their hosts. The different patterns in each bar represent the proportion of genetic groups: blank denotes pure P. striiformis f. sp. tritici , black pure P. striiformis f. sp. hordei ; gray F 1 hybrids, and other patterns for F2 and backcross of two parental species. 83
Discussion
Somatic hybridization has been postulated or experimentally demonstrated with many
fungi including basidiomycetes, ascomycetes and oomycetes (Burdon & Silk 1997). Gene
flow via hybridization can quickly introduce new genetic material into populations and create
evolutionarily advanced hybrids (Brasier 2000; Goss et al. 2011; Inderbitzin et al. 2011). It
has been well documented that new strains can arise for the stripe rust (Little & Manners
1969a, b; Kang et al. 1993a, c), stem rust (Luig & Watson 1972) and leaf rust (Park et al.
1999) pathogens of wheat by somatic hybridization. Simple nuclear exchange has been
demonstrated in powdery mildew pathogen Erysiphe graminis under controlled labarotary
conditions (Menzies & MacNeill 1986). The previous studies were focused on use of the
co-inoculation of mixed isolates on a common susceptible host to produce virulence-changed
strains under controlled conditions and observation of fusion between germ tubes or between
hyphae. None of these studies demonstrated genomic changes. The first study attempted
using molecular (double-stranded RNA and isozyme) approaches and different urediniospore
pigmentations to obtain hybrids between Pst and Psh isolates failed to show somatic
hybridization and let the authors to conclude possible genetic barriers between the two
formae speciales (Newton et al. 1986). Recently, a study by our group conducted under
controlled greenhouse conditions demonstrated that somatic hybrid isolates can be relatively
easily obtained (Cheng et al. 2011, unpublished). Similar to the earlier studies, this study
used wheat and/or barley genotypes commonly susceptible to different isolates of Pst and/or
Psh . Their results showed that hybrid isolates can be obtained between Pst and Psh , but not
as easy as between Pst isolates. In the present study, our results show that a large number of
isolates from grasses are possible hybrids between Pst and Psh through both virulence and molecular marker characterization.
The success of detecting hybrid isolates in the present study was largely due to the use
84 of SSR markers which identify heterozygous loci in a prescreen with typical Pst and Psh isolates (Fig. 3). Using the selected 20 SSR markers, we identified three groups that agreed with groupings based on virulence phenotypes to validate the hypothesis that somatic recombination between Pst and Psh isolates can occur on grasses, which may produce different races and molecular haplotypes. Taking isolate 08-4 in MG 1 which can only infect wheat differentials, as an example of a typical Pst isolate, it has the AA allelic type at all of the marker loci except one locus where it is AB (Fig. 4A). Similarly, PSH-72 in MG 2, which can infect only barley differentials, is an example of typical Psh and has the BB type at
16 loci and AB type at 4 loci (Fig. 4A). As an example of a hybrid isolate, 08-121-N that was identified as either PST-101 using the wheat differentials or PSH-33 using the barley differentials had the AB allele type at 15 loci and AA at 2 loci and BB at 3 loci. This isolate was collected from foxtail grass ( H. jubatum ). Sixteen of the loci fit the hybrid model
(AA+BB=AB or AA+AB=AB), whereas at only 4 loci (2, 6, 9 and 17) the AA or BB types were unchanged (AA+BB=AA or AB+BB=BB). The non-hybridization loci could be caused by mutation, chromosomal re-assortment and/or mitotic crossover after karyogamy.
It is also possible that the exact parental isolates for isolates 08-121-N were not detected in this study. Likewise, MG 1 represents typical Pst isolates, MG 2 represents typical Psh isolates, and MG 3 isolates appear to be a somatic hybrid group between isolates of MGs 1 and 2, and many of them are able to infect some wheat and barley differentials. The four subgroups revealed by STRUCTURE ananlysis suggested that wheat can be attacked by both typical Pst isolates (G1, G2, and G4 in Fig. 7A) and the isolates with a few AB loci (MG3a and MG3c in Fig. 4). Two subdivisions were found with isolates from barley suggested that barley can be attacked by typical Psh isolates as well as the hybrids. All four subgroups were identified with isolates from grasses confirmed our hypothesis that both typical Pst and
Psh can attack wild grasses and produce hybrids (MG3). These results suggested that wheat
85
harbors typical Pst isolates and barley harbors typical Psh isolates. Both Pst and Psh can
attack grasses and produce hybirds that can infect wheat and barley. Similar conclusion can
be drawn by the NEWHYBRIDS analysis that typical Pst isolates were identified as a pure forma specialis of P. striiformis f. sp. tritici (G1, G2 and G4), typical Psh isolates were identified as a pure P. striiformis f. sp. tritici forma specialis (G8-G13), and isolates from grasses contained both formae speciales and their hybrids (Fig. 7B). Gene flow estimation among the isolates from wheat, barley and grasses suggested that Pst and Psh can exchange
genetic information and serve as source isolates to produce hybrid isolates from grasses
(Table 4).
Puccinia striiformis variants can be generated by mutation and somatic hybridization
(Line 2002; Chen 2005). In the previous studies, mutation has been considered as the major
mechanism of the pathogen evolution in Europe, Australia and New Zealand (Steele et al.
2001; Hovmøller & Justesen 2007; Bahri et al. 2009b). Genetic recombination was
proposed for the Pst populations in some areas of China (Mboup et al. 2009), but whether it
is somatic or sexual is not clear. In North America, new races with a wide virulence
spectrum appear to be hybrids or recombinants of previously existing races with shorter
virulence spectrum (Line and Qayoum 1992; Chen et al. 2010). Our data here indicate
hybridization and/or recombination with more complex processes. MGs 1, 2 and 3 fit in the
somatic hybridization/recombination model which involves karyogamy and re-assortment of
chromosomes according to the 20 loci polymorphisms.
Stripe rust pathogens on bluegrass and orchard grass have long been considered different
from those on wheat and barley because of their distinct host range, temperature requirement
and RAPD marker genotypes (Tollenaar 1967; Chen et al. 1995). The present study also
found both virulence and molecular evident that the isolates from bluegrass and orchard grass
were very different from those collected from wheat, barley, triticale, rye and other grasses.
86
The results supported the classification of the stripe rust pathogens on bluegrass and orchard
grasses into different species, P. pseudostriiformis on Poa spp. and P. striiformoides on
Dactylis spp. (Liu & Hambleton 2010) .
The results of this study also provide some insights into evolutionary relationships of the wheat and barley stripe rust pathogens and different races or virulence groups. First, the virulence and molecular data support the previous finding that Pst and Psh are quite different, but they are closely related (Chen et al. 1995). With some exceptions, typical Pst races do not infect barley differentials and typical Psh races do not infect wheat differentials. Pst races have more A alleles (AA and AB dominant groups) while Psh races have more B types
(BB dominant groups). When the A and B types are in more or less balance, the isolates tend to infect both wheat and barley (Fig. 4, Table 3). Also, isolates with more
“homozygous” marker loci of AA tend to be Pst races from wheat, isolates with more
“homozygous” loci of BB tend to be Psh races from barley, and isolates with more
“heterozygous” loci of AB tend to be either Pst or Psh race from grasses and wheat with few exceptions. As it is generally accepted that stripe rust on cereal crops is originally evolved from those on grasses, “heterozygous” state could be more progenitors and has some advantages in adaptation to various grasses. The results of the present study support this hypothesis. The earliest races, PST-1 and PST-3, identified in the early 1960s had more AB loci. Also, PST-21, which was first identified from an isolate collected from triticale in
California in 1980, had 12 AB loci, 5 AA loci and 3 BB loci (Fig. 4), indicating it is a possible hybrid. This race is virulent only on Chinese 166 ( Yr1 ) among the wheat differentials and some other wheat genotypes, such as Nugaines, PS 279, and Michigan
Amber (Chen & Line 1992a), but not virulent on any of the barley differentials. In addition to this earliest PST-21 isolates, six more isolates (08-wo-S, 08-JG, 08-121-S, 08-145-S,
08-146-N and 08-146-S) (Table 1) collected from grasses were also identified as PST-21
87
based on their virulence only on Chinese 166 of the wheat differentials. However, these
isolates were also virulent on some barley differentials and therefore, also can be considered
as Psh races. Similarly, they have 11-12 AB loci and generally more AA than BB loci.
Our results agreed with a rencent study of populations of flax rust fungi Melampsora lini from its native Australian host Linum marginale (Barrett et al. 2007). Analysis of microsatellite and AFLP markers revealed two genetically divergent lineages AA and AB indicating a hybrid origin of the AB lineage. It is suggested that heterokaryosis in fungi is the best explanation for lineage AB with absent evidence of introgression of the putative A and B genomes. All isolates identified as either Pst or Psh races (PSH-33, PSH-46, PSH-48,
PSH-50) have relatively narrow virulence spectra, virulent only on 1 to 3 of the 12 barley differentials (Table 3). Given the recessive trait of a virulence gene, it is expected to see less virulence in the AB dominant ancestor group. In contrast, the isolates with more AA loci are
Pst races detected in recent years. For example, PST-127 and PST-137, which were first identified in 2007 (Chen et al. 2010) had the widest virulence spectra and the most AA loci
(Fig. 4). This group of Pst tends to have relatively high level of telia formation in short time compare to the AB loci dominant hybrid group, which is in agreement with the feature of AA lineage demonstrated in the flax rust study in 2007 (Barrett et al. 2007). Inability to identify the putative BB lineage at wide geographic scales and intensive sampling in local populations in their study leads to the assumption of a different host species for BB lineage. Our finding of the BB type which is predominant in the P. striiformis f. sp. hordei population agreed with their speculation as barley stripe rust was introduced to the US quite recently (Chen et al.
1995). Our data also suggested that AB type is predominant in Pst isolates originated from grasses and reproduces clonally while AA type is exotic and have ablility to mating. From an evolutionary stand point, AB type is more advanced in adaptation with ability to attack diverse hosts while AA type is more aggressive with high level of virulence. Adapation
88 insures the pathogen is not restricted by a lack of potential hosts while aggressiveness saves the pathogen under selection of host resistance. In case of stripe rust, dynamic balance can be achieved between fitness and virulence by somatic hybridization to better assist pathogens surviving under various environmental conditions.
Although some isolates have relatively similar numbers of virulences on barley differentials and similar molecular haplotypes, they can have very different virulence patterns on wheat differentials. For example, isolate 08-121-S (PST-21, PSH-33) was virulent on wheat differential 2 (Chinese 166); 04-063-S (PST-6, PSH-33) on wheat differentials 1
(Lemhi), 6 (Druchamp), 8 (Produra) and 12 (Fielder); and 08-74-N (PST-114, PSH-33) on 1,
3 (Heines VII), 4 (Moro), 8, 9 (Yamhill), 10 (Stephens), 11 (Lee), 12, 14 (Tres), 16 (Express),
17 (AvSYr8NIL), 18 (AvSYr9NIL), 19 (Clement) and 20 (Compair). In general, isolates identified as same or similar races had either the same or similar molecular haplotypes within the same molecular groups. However, isolates 05-161 and 08-93 were both identified as
PST-115, but had very different haplotypes (Fig. 4). If we assume one of the isolates (likely
08-93) was produced through somatic hybridization, the two isolates may not be very different as both have at least one A allele at all loci. Isolates 08-327 and 08-74-N, both identified as PST-114 but not different haplotypes, may have the similar relationship.
Grass species may also have something to do with the preference of somatic hybridization to happen. Our results showed that H. jubatum harbors all genotype groups that can be Pst ,
Psh and possible hybrids of Pst and Psh . Comparison between isolates of Pst and Psh from
Hordeum spp. may explain the possibility of a new forma specialis of P. striiformis (Wellings et al. 2000; Wellings 2011). Other species may have certain selections to different rust genotypes. Hybrids may increase the cereal rust survival ability on grasses that are perennial
(e. g. Hordeum spp.) or have a longer of different growth seasons (Luig & Watson 1972). The wild grasses play an important role as a green bridge for rust to over season when no wheat or
89 barley available in the field. From the inoculum standard point, grasses may not as important as susceptible crops and volunteer plants. However, grasses are more important to serve as reservoirs for maintaining various races or genetic variants which may not be able to reproduce on crops and provide favorable host tissues for different variants to hybrid, resulting in new races. Taking account of the role of grasses to cereal stripe rusts, control of susceptible grasses may add to disease management. Stripe rust survey and monitoring should pay more attention to grasses. The results of the present study also suggests a serious attention should be paid by breeding programs when transfer resistance genes from the involved wild wheat relatives.
Acknowledgements
This research was supported by the US Department of Agriculture, Agricultural Research
Service (Project No. 5348-22000-014-00D) and Washington State University (Project No.
13C-3061-3925) PPNS No. 0???, Department of Plant Pathology, College of Agricultural,
Human, and Natural Resource Sciences, Agricultural Research Center, Project Number
WNP00663, Washington State University, Pullman, WA 99164-6430, USA. We thank Dr.
Meinan Wang for technical support of the rust DNA extraction, Ms. Laura Penman and Dr.
Anmin Wan for increasing urediniospores and identifying races for some of the stripe rust isolates used in this study. We also thank Dr. Calvin Qualset for help in stripe rust collection in California. We would like to thank Drs. Scot Hulbert, Tobin Peever and Kulvinder Gill for critical review of the manuscript.
90
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CHAPTER FOUR
Virulence and microsatellite markers revealed only asexual reproduction in the US
Pacific Northwest Puccinia striiformis f. sp. tritici population
Peng Cheng and Xianming Chen
First and second authors: Department of Plant Pathology, Washington State University,
Pullman, WA, USA
Second author: USDA-ARS, Wheat Genetics, Quality, Physiology, and Disease Research
Unit, Pullman, WA 99164-6430, USA
* Corresponding authors: X. M. Chen ([email protected] )
ABSTRACT
Cheng, P., and Chen, X. M. 2012. Virulence and microsatellite markers revealed only asexual
reproduction in the US Pacific Northwest population of Puccinia striiformis f. sp. tritici .
Phytopathology 000:000-000.
Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst ), occurs every year and has caused frequent epidemics in the US Pacific Northwest (PNW). Races of Pst change rapidly and barberry plants, which could be alternate hosts of the fungus, are found in the region. However, whether sexual reproduction occurs in the Pst population is not clear.
To determine the reproduction mode of Pst , a systematic collection of single-stripe leaf
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samples of Pst was made in 26 fields in the PNW in 2010. A total of 270 isolates obtained
from the PNW collection, together with 66 isolates from 20 other states collected in the same
year, were characterized by virulence tests and simple sequence repeat (SSR) markers. A
total of 21 races and 66 haplotypes were detected, of which 15 races and 32 haplotypes were
found in the PNW. Cluster analysis with the SSR marker data revealed two genetic groups,
the first group was mainly found in the PNW containing more “homozygous” isolates and the
second group consisted of more “heterozygous" isolates collected throughout the US
including the PNW. The molecular genetic groups generally corresponded to the two
virulence groups. The analyses of multi-locus association, parsimony tree length
permutation, and Hardy-Weinberg equilibrium ruled out the possibility of sexual reproduction
in the PNW population, indicating that Pst reproduces asexually.
Additional keywords : stripe rust, heterokaryotic, sexual recombination, Puccinia striiformis f. sp. tritici , alternate host, Berberis spp.
Puccinia striiformis Westend. f. sp. tritici Erikss. ( Pst ) is an obligate biotrophic fungus
causing wheat stripe rust, one of the most important plant diseases worldwide. The Pst life
cycle was previously believed to consist of only dikaryotic (n+n) uredial, dikaryotic to
diploid (2n) telial, and haploid (n) basidial stages (Stubbs 1985; Chen 2005). The fungus
had been believed to reproduce asexually by dikaryotic urediniospores, which infect its cereal
crop and grass hosts. Mutation and somatic hybridization through karyogamy that may lead
to somatic recombination through chromosomal re-assortment are considered as the only
possible mechanisms creating genetic diversity (Stubbs 1985; Wellings & Mcintosh 1990;
Chen 2005; Hovmøller et al. 2011). However, Berberis spp. were recently identified by Jin
et al. (2010) as alternate hosts for Pst and P. pseudostriiformis (Syn. P. striiformis f. sp. poae )
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(Liu & Hambleton 2010). Like stem rust caused by P. graminis , haploid (n) basidiospores produced from diploid (2n) teliospores on wheat and other grass hosts can infect Berberis spp. to produce pycnia (n) on the upper side of barberry leaves. This is where uninucleate pycniospores (also called spermatia) fertilize haploid receptive hyphae. Fertilized receptive hyphae (n+n) further develop into dikaryotic (n+n) aecia on the lower side of the leaves.
Dikaryotic aeciospores that are produced from aecia on Berberis spp. are airborne and able to infect wheat plants again to produce dikaryotic urediniospores (Jin et al. 2010). The complete sexual lifecycle of Pst was also confirmed in our laboratory (Wang and Chen, unpublished data). Because the fungus goes through the sexual reproduction cycle on barberry plants, more diverse uredinial isolates can be produced (Wang and Chen, unpublished data). Therefore, sexual reproduction of Pst on barberry plants may increase the pathogen variation as well as provide aecial inoculum to infect wheat crops and grasses.
So far, sexual reproduction for stripe rust fungi was only demonstrated from naturally infected barberry plants for bluegrass stripe rust in Minnesota (Jin et al. 2010), which is caused by different species ( P. pseudostriiformis ) from wheat stripe rust (Liu & Hambleton
2010). Whether Pst infects barbery under natural conditions is not clear. If sexual reproduction of Pst occurs in nature, it should be detected through characterizing the genotypic diversity of its urediniospore population.
Populations of the stripe rust fungus have long been considered as clonal in many parts of the world. This conclusion has been made not only by virulence tests, but also by analysis of different molecular markers (Steele et al. 2001; Hovmøller et al. 2002; Enjalbert et al. 2005; Hovmøller & Justesen 2007; Bahri et al. 2009b; Liu et al. 2011). This conclusion was generally accepted because of the lack of evidence of alternate hosts for the stripe rust fungus until the discovery of the ability of Berberis spp. to be alternate hosts (Jin et al. 2010). High genetic diversity and high rate of Pst teliospore production detected in the
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Tianshui region of Gansu province in China made the authors suggest the existence of a sexual cycle in this species (Mboup et al. 2009). Another study with samples also collected from Gansu, China supported the hypothesis that the reproductive mode of the pathogen is not strictly clonal (Duan et al. 2010). Genetic recombination, although it was not clear whether it resulted from a sexual or asexual process, was detected among isolates of a Pst pathotype from Pakistan (Bahri et al. 2011). With the observation of high telial production and genetic diversity in the Pst populations in China, Nepal, and Pakistan, an extensive discussion was made regarding to the evolution of sex, center of origin, and distribution of alternative hosts for the stripe rust fungus (Ali et al. 2010).
In the US, more than 140 races have been identified (Chen et al. 2010; Wan & Chen
2011). This is more than any other country where Pst races have been reported, indicating a greater diversity of the pathogen in the US. Early molecular studies using random amplified polymorphic DNA (RAPD) markers also revealed the high genetic diversity of the US Pst population (Chen et al. 1993a, 1995). The high virulence and genetic variation prompted these authors to test for random mating of the Pst populations based on virulence frequencies
(Chen et al. 1993b). Because of the discovery that barberry plants can be infected by Pst and P. pseudostriiformis (Jin 2011), sexual reproduction was proposed to be an explanation for the high genetic diversity of Pst . However the aecial samples from barberry plants in the state of Minnesota were identified as the bluegrass stripe rust fungus ( P. pseudostriiformis ) and barberry plants as alternate hosts of Pst were only demonstrated by artificial inoculation under much extended dew-forming conditions (Jin et al. 2010; Wang et al. 2011).
Therefore, whether Pst can reproduce sexually on barberry plants needs to be studied.
Temperature and humidity are the two most important environmental factors for the infection and growth of the stripe rust fungus and development of the disease when the pathogen and susceptible host plants are available (Stubbs 1985; Chen 2005). Low night
102 temperatures and dew formation are favorable to stripe rust infection. The US Pacific
Northwest (PNW), including Washington (WA), Oregon (OR), and Idaho (ID), has weather conditions favorable to stripe rust epidemics. In addition to the favorable weather conditions, both spring and winter wheat crops are grown, plus the long periods of planting and harvesting in the same region, providing host plants for stripe rust infection and development. Therefore, stripe rust epidemics causing significant yield loss occur almost every year as long as susceptible cultivars are grown (Chen 2005; Sharma-Poudyal & Chen
2011b). A recent study using historical weather and stripe rust data demonstrated that the
PNW is one of the key regions for stripe rust to over-summer and over-winter
(Sharma-Poudyal & Chen 2011a). More races are detected in this region than any other regions in the US every year and most new races have been first detected in the region (Line
& Qayoum 1992; Chen 2005; Chen et al. 2010; Wan & Chen 2011). Races of Pst , differentiated with a set of wheat genotypes with different resistance genes, have been detected every year from rust-infected leaf samples of wheat and grasses collected in the
United States (Line & Qayoum 1992; Line 2002; Chen 2005; Chen et al. 2010; Wan & Chen
2011). Predominant races with more virulence factors than previous races have evolved to be able to infect more wheat cultivars (Chen 2005; Chen et al. 2010; Wan & Chen 2011).
Although eradication has been conducted in 1940s to 1970s, barberry plants, mainly Berberis vulgaris L., are still found in the PNW, especially the Palouse region, including Whitman and
Spokane counties of Washington and Latah County of Idaho, in the eastern PNW (Murray et al. 2011). In this region, stem rust infection in wheat fields is always associated to heavy infection of rust on barberry plants, including high levels of infections of stem rust situations in 2009 and 2010 (Chen, unpublished data). Because of the sexual reproduction of the stem rust fungus ( P. graminis f. sp. tritici , Pgt ), a great diversity of Pgt races were identified in the region, even in a single wheat or barley field (Jin et al. unpublished data). However, natural
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Pst infection of barberry in the region has not been identified (Wang et al. 2011). Thus, whether the stripe rust fungus goes through the sexual cycles on barberry plants in the PNW, especially the Palouse region, is not known.
The co-existence of barberry plants and Pst made the Palouse region of the US PNW an ideal area for studying the role of barberry and sexual reproduction of the pathogen under natural conditions. The direct examination and characterization of rust from barberry plants was briefly reported (Wang et al. 2011) and the detailed results from the study using various approaches will be reported elsewhere. The major objective of this study was to determine if any sexual reproduction occurs in the region through virulence and molecular characterization of the Pst population. The data can be used to reveal any role of barberry plants in the diversity of the fungal population and the disease epidemics.
MATERIALS AND METHODS
Stripe rust sampling and urediniospore multiplication. Collection trips were taken during the stripe rust season in May to July in 2010 to collect samples mostly in commercial wheat fields. A total of 270 single-stripe samples were collected from 26 locations in the
US PNW (Washington, Idaho, and Oregon) with an average of 10 samples in each field (Fig.
1, Table 1). The Palouse region, covering about 12,500 km 2 and including Whitman and
Spokane counties in Washington and Latah County in Idaho, was sampled more intensively
(17 fields) as barberry bushes have been found in the region. The distances between fields were at least five kilometers. The area of a single field ranged from approximately a couple hundred to a couple of thousand hectares. In each field, the distances between samples were at least 50 meters to reduce the possibility of picking up leaf samples infected by spores produced from the initial single spore infection in the beginning the crop season . Each sample consists of a single leaf bearing a single stripe of uredia, which was presumably
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produced from a single-spore infection. The collections were made during the early
development of stripe rust in most of the PNW locations in order to obtain single -stripe
isolates and a maximal diversity of the pathogen. An additional 66 Pst samples fro m 20
other states were randomly picked for comparison (Fig. 1).
Fig. 1. Map showing Puccinia striiformis f. sp. tritici samples collected from the Pacific
Northwest (PNW) and 20 states in the United States in 2010. Circles mark the 26 PNW fields
where single stripe samples were collected and the numbers in the circles correspond to the
field number in Table 4. The Palouse region is indicated by the broken line rectangle. The
four black dots indicated locations with presence of baberry. 105
TABLE 1 Number of isolates, races, virulence group, haplotypes, and molecular group in collection regions
PSTv race Molecular genotype Region No. of isolates No. of races Group (%) No. of haplotypes Group (%) US 336 21 VG 1 (68), VG 2 (32) 66 MG 1 (70), MG 2 (30) PNW 270 15 VG 1 (84), VG 2 (16) 32 MG 1 (87), MG 2 (13) Palouse 180 13 VG 1 (84), VG 2 (16) 26 MG 1 (89), MG 2 (11) Whitman Co, WA 138 10 VG 1 (88), VG 2 (12) 18 MG 1 (89), MG 2 (11) Spokane Co, WA 26 8 VG 1 (50), VG 2 (50) 12 MG 1 (80), MG 2 (20) Latah Co, ID 16 1 VG 1 (100), VG 2(0) 3 MG 1 (100), MG 2 (0) Non-Palouse PNW 90 10 VG 1 (83), VG 2(17) 15 MG 1 (82), MG 2 (18) Washington 62 8 VG 1 (77), VG 2(23) 9 MG 1 (76), MG 2 (2 4) Idaho 4 2 VG 1 (75), VG 2(25) 4 MG 1 (75), MG 2 (25) 106 Oregon 24 3 VG 1 (100), VG 2(0) 5 MG 1 (100), MG 2 (0) Non-PNW US 66 13 VG 1 (3), VG 2(97) 41 MG 1 (2), MG 2 (98) California 5 4 VG 1 (20), VG 2(80) 4 MG 1 (0), MG 2 (100) Utah 1 1 VG 1 (0), VG 2(100) 1 MG 1 (0), MG 2 (100) Montana 3 3 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100) Texas 4 2 VG 1 (0), VG 2(100) 3 MG 1 (0), MG 2 (100) Oklahoma 5 2 VG 1 (0), VG 2(100) 5 MG 1 (0), MG 2 (100) Kansas 2 2 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100) Nebraska 5 3 VG 1 (0), VG 2(100) 5 MG 1 (0), MG 2 (100) South Dakota 2 2 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100) North Dakota 5 4 VG 1 (0), VG 2(100) 5 MG 1 (0), MG 2 (100) Louisiana 5 4 VG 1 (0), VG 2(100) 5 MG 1 (0), MG 2 (100) Arkansas 5 1 VG 1 (0), VG 2(100) 4 MG 1 (0), MG 2 (100) Minnesota 5 3 VG 1 (0), VG 2(100) 5 MG 1 (0), MG 2 (100)
Illinois 5 2 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100) Wisconsin 3 2 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100) Kentucky 1 1 VG 1 (0), VG 2(100) 1 MG 1 (0), MG 2 (100) Indiana 1 1 VG 1 (100), VG 2(0) 1 MG 1 (100), MG 2 (0) North Carolina 1 1 VG 1 (0), VG 2(100) 1 MG 1 (0), MG 2 (100) Virginia 4 1 VG 1 (0), VG 2(100) 3 MG 1 (0), MG 2 (100) Maryland 2 2 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100) New York 2 1 VG 1 (0), VG 2(100) 2 MG 1 (0), MG 2 (100)
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Each leaf sample was washed, placed on wet filter paper in a Petri dish, and incubated
for 1-2 days in a growth chamber at a diurnal temperature cycle gradually changing from 4 oC
at 2:00 am to 20 oC at 2:00 pm and a 16/8 light/dark cycle. The re-sporulated fresh
urediniospores were inoculated with a fine brush onto two-leaf-stage seedlings of wheat
cultivar ‘Nugains’, which is used to increase urediniospores of any Pst races (Chen et al.
2002; Chen et al. 2010). The inoculated plants were incubated in a dew chamber at 10 oC
for 24 h without light and grown in a growth chamber at the 4-20 oC temperature cycle and a
16/8 light/dark cycle as described above. To prevent cross contamination, plants inoculated
with different isolates were separated with plastic booths. Urediniospores produced from a
single sample were vacuum-collected with a custom-made glass collector. After using,
collectors were washed with water, soaked in a detergent solution for several hours,
re-washed, and dried for next use. Increased urediniospores, which were dried and kept in a
desiccator at 4 oC within two months, were used for virulence tests or transferred to foil bags,
which were sealed and stored in liquid nitrogen for later use.
Virulence tests. The virulence pattern for each isolate was determined by testing
urediniospores on 18 wheat lines each with a single Yr gene ( Yr1 , Yr5 , Yr6 , Yr7 , Yr8 , Yr9 ,
Yr10 , Yr15 , Yr17 , Yr24 , Yr27 , Yr32 , Yr43 , Yr44 , YrSP , YrTr1 , YrExp2 , and YrTye ), which are currently used to differentiate races of P. striiformis f. sp. tritici (Wan and Chen 2012
unpublished). Fresh urediniospores or those kept in the desiccator at 4 oC within two months were used in the virulence tests. Seedlings at two-leaf stage were dust-inoculated with urediniospores mixed with talc (Sigma, St. Louis, MO) at a ratio of 1:20. Inoculated plants
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were placed in a dew chamber for 24 h at 10 oC without light and then moved to a growth chamber to grow at 4-20 oC and 16/8 h light/dark cycle as described above. To prevent cross contamination, plants inoculated with different isolates were separated with plastic booths.
Infection types (IT) were recorded 18-20 days after inoculation using the 0-9 scale (Line &
Qayoum 1992; Chen et al. 2002). In this study, we did not have intermediate ITs 3 - 6 and therefore, ITs 0 - 2 were considered avirulent (A) and 7 - 9 virulent (V). If an isolate produced a virulence pattern different from most other isolates from the same field, it will be tested on the set of 18 differentials again to confirm the virulence pattern. Virulence pattern was scored by coding aviulence as 0 and virulence as 1.
Molecular characterization. DNA was extracted from dried urediniospores following a modified protocol of DNA extraction (Aljanabi & Martinez 1997). DNA concentration was determined using a ND-1000 spectrophotometer (Bio-Rad, Hercules, CA, USA) and the stock solution was stored at -20 oC. For PCR amplification, the stock solution was diluted to
1 ng/ l as a working solution and kept at 4 oC. A set of 20 SSR primer pairs were selected based on their polymorphism among Pst isolates detected in previous studies (Cheng et al.
2012a). All primer sequences and annealing temperatures are listed in Table 2. In order to use fluorescence to detect polymerase chain reaction (PCR) products, an M13 tag
(5’-CACGACGTTGTAAAACGAC) was added to the 5’ end of each forward primer
(Schuelke 2000).
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TABLE 2. Primer sequences, annealing temperatures (Tm) of 20 microsatellite markers No. Marker a Primer sequence (5'-3') Tm oC) 1 PstP001 F: ACCATCGGATTCCTGC 49 R: ACGGTAGGCGAACGAC 2 PstP002 F: CTGACCATCGGATTCCTGC 53 R: TGAACGGTAGGCGAACGAC 3 PstP003 F: TAACCCCACGGCAACTCA 50 R: ATCGTTGGCAGCCTTACC 4 PstP004 F: TCTCGCCTCGCTTGAATG 50 R: TCGCTGGAGTTGGATGGA 5 PstP005 F: CCAACAGGCTCAAACTACCA 52 R: TCCGCTTCGATCATAGCAC 6 PstP030 F: AAGGAAAAGAACTGTATG 41 R: TTCAGATGCTCTATTCAA 7 PstP006 F: GTTTGATTTTCCCTATGC 45 R: AACTGAACGGAAGATGC 8 PstP033 F: ACAGAAGGAAGGCAGATT 46 R: GGGGTTTGATGTTATTAC 9 PstP007 F: GATTTGCGAGGTCACTTT 46 R: TGGTTGTGATAACGATGA 10 PstP025 F: ATGTAAATGTAGCACCAAAC 48 R: TCATGCTCGGTATGTCTC 11 PstP031 F: TTGGGCGTCCTGGCATTG 57 R: ACCCGTTCCTTCTTGGTCTTGC 12 CPS10 F: TCTACTGGGCAGACTGGTC 47 R: CGGTTTGTTTTGTCGTTTC 13 CPS08 F: GATAAGAAACAAGGGACAGC 50 R: CAGTGAACCCAATTACTCAG 14 CPS02 F: GTTGGCTACGAGTGGTCATC 50 R: TAACACTACACAAAAGGGGTC 15 RJ21 F: TTCCTGGATTGAATTCGTCG 50 R: CAGTTCTCACTCGGACCCAG 16 RJ3N F: TGGTGGTGCTCCTCTAGTC 52 R: AGGGGTCTTGTAAGATGCTC 17 CPS13 F: TCCAGGCAGTAAATCAGACGC 54 R: ATCAGCAGGTGTAGCCCCATC 18 RJ8N F: ACTGGGCAGACTGGTCAAC 53 R: TCGTTTCCCTCCAGATGGC 19 RJ20 F: AGAAGATCGACGCACCCG 53 R: CCTCCGATTGGCTTAGGC 20 RJ18 F: CTGCCCATGCTCTTCGTC 53 R: GATGAAGTGGGTGCTGCTG
110
PCR amplifications were done following the protocol in a previous study (Cheng et al.
2012a). Every four loci in the order listed in Table 2 were tagged with FAM (blue), VIC
(green), NED (yellow), and PET (red), and pooled into one ABI sample. Then PCR
products of 3.0 l FAM, 3.0 l VIC, 4.0 l NED, and 6.0 l PET were added into 9 l ddH 2O
to get a 25- l dilution. A total volume of 13 l containing 9.93 l formamide, 0.07 l DNA
ladder (445-LIZ, Applied Biosystems) and 3 l diluted PCR product was denatured at 95ºC for 5 min and held at 4ºC. The size of the PCR products was estimated using capillary electrophoresis on an ABI3730 Genotyper (Applied Biosystems, Foster City, Calif., USA).
The internal molecular weight standard for ABI3730 was Genescan 445-LIZ (Applied
Biosystems). Alleles were called using the GeneMapper v3.7 software (Applied Biosystems,
Foster City, Calif., USA).
Data analyses. For cluster analysis to determine relationships among isolates,
avirulence ITs were converted to 0 and virulence ITs to 1 following the method of Chen et al.
(1993a, 1995). A neighbor-joining tree was constructed by the NTsyspc 2.21L program
using the microsatellite data. Bootstrap analysis was used to determine the robustness of
branches of the dendrograms with the Winboot program (Nelson et al. 1994). Principal
coordinate analysis based on a Dice similarity index in the NTsyspc 2.21L program was used
to construct a three-dimensional figure to show more detailed relationships of all races or
molecular haplotypes. Correlation between the SSR and virulence data was determined by
comparison of the two similarity matrices using MXCOMP, a matrix comparison program of
the NTsyspc 2.21L software. The existence of sub-structures in the population was assessed
111
on the microsatellite data using STRUCTURE (Pritchard et al. 2000), a Bayesian clustering
algorithm that assigns individuals to putative subgroups with distinctive allele frequencies.
The program STUCTURE HARVESTER (http://taylor0.biology.ucla.edu/structureHarvester/ )
was used to determine the best fit number of clusters, K, by generating a plot of the mean
likelihood values per K and a table of the Evanno results (Evanno et al. 2005; Earl &
VonHoldt 2011).
To test for the presence of recombination, three analyses were performed with the SSR
data using allele sizes in the Palouse population (with presence of barberry) and the whole
PNW population (extended Palouse region) (Fig. 1). First, the normalized index of
association was estimated and the null hypothesis r d = 0 was tested using 1,000 times
randomly shuffling alleles among isolates using the MULTILOCUS 2.2 program (Agapow &
Burt 2001). This is the measure of multilocus linkage disequilibrium. Second, the
parsimony tree length permutation test (PTLPT) derived from phylogenetics was used to
determine significance by comparing the length of the tree of the observed data to the
distribution of tree lengths of 1,000 permuted data sets (Burt et al. 1996). Phylogenetic trees were built from the multilocus haplotypes using parsimony in PAUP* version 4.0
(Swofford 2003) using an input file generated from MULTILOCUS. For a clonal population, the observed tree length should be significantly shorter than the distribution of tree lengths under the null hypothesis of random mating. Third, Chi-squared tests for
Hardy-Weinberg equilibrium were applied to isolates from each of the fields showing genetic variation and also all isolates of the Palouse region using GenAlEx 6.41 (Peakall & Smouse
112
2006).
To study population structures, Nei (1973), Shannon information indices (Shannon &
Weaver 1949), and Kosman index (Kosman 1996) were used to calculate genetic diversities
for the Pst populations in the Palouse region, the non-Palouse PNW, and the non-PNW U.S.
Nei and Shannon indices were conducted using the software POPGENE version 1.31 (Yeh et
al. 1997), Kosman index was calculated using the Virulence Analysis Tools (VAT) program
(http://www.tau.ac.il/lifesci/departments/plant_s/members/kosman/VAT.html ). To examine
migration between populations, the program MIGRATE-N ver. 3.2.19 was used to calculate
the ratio (M) of migration rate (m) to mutation rate ( ) (= m/ ), and maximum likelihood
estimations theta ( Θ= 4Ne ), where Ne is effective population size, were estimated using the
Bayesian method in MIGRATE-N for microsatellite data (Beerli 2009). The Brownian motion approximation to the stepwise mutation model was used for the microsatellite data.
Runs were repeated to ensure consistency of results. Two independent runs were used with
5 short chains and 5 long chains, for a total of 2000 and 20,000 generations, a burn-in of
20,000 steps for the calculations. Analysis of molecular variance (AMOVA) was conducted to statistically assess genetic variation within and among the Pst populations with the
software package Arlequin version 3.11 (Scheider et al. 2000).
RESULTS
Virulence variation. In the Palouse region, more than 80% of the isolates that were
virulent to YrTye (80%), Yr1 (86%), Yr17 (87%), Yr7 (95%), Yr27 (98%), YrExp2 (98%),
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Yr43 (100%), Yr9 (100%), Yr44 (100%), Yr6 (100%), and Yr8 (100%) (Fig. 2). A moderate frequency was found for virulence to YrTr1 (41%) and less than 15% frequencies for Yr24
(11%), Yr10 (11%), Yr32 (10%), and YrSP (4%). The non-Palouse PNW had virulence frequencies for these genes similar to the Palouse region. For the non-PNW U.S., more than
75% of the isolates were virulent to Yr17 (76%), Yr27 (78%), Yr43 (88%), YrTr1 (99%), Yr7
(99%), Yr6 (100%), and Yr8 (100%), Yr9 (100%), Yr44 (100%), and YrExp2 (100%); and less than 5% of the isolates attacked Yr32 (3%), Yr10 (5%), and Yr24 (5%) (Fig. 2). No isolates from the non-PNW US collection were virulent to Yr1 , YrSP , and YrTye . None of the isolates tested in the study were virulent to Yr5 and Yr15 , indicating that these resistance genes are still effective
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Palouse 100 non-Palouse PNW 80 non-PNW US
60
40
20 Virulence frequency frequency (%) Virulence
0 Yr5 Yr1 Yr9 Yr6 Yr8 Yr7 Yr15 Yr32 Yr10 Yr24 Yr17 Yr27 Yr43 Yr44 YrSP YrTr1 YrTye YrExp2
Yr gene
Fig. 2. Frequencies of Puccinia striiformis f. sp. tritici virulences to the 18 Yr -gene lines in the Palouse region, the non-Palouse PNW, and the non-PNW US.
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TABLE 3. Puccinia striiformis f. sp. tritici races and their virulence formula, group and number of isolates in the Palouse region, the
non-Palouse PNW, the non-PNW US, total number in the study and total frequency
Virulence Palouse The non-Palouse PNW The non-PNW US Total Race Virulence formula ( Yr gene) group No. Freq (%) No. Freq (%) No. Freq (%) No. Freq (%) PSTv-11 1,6,7,8,9,17,27,43,44,Exp2,Tye 1 91 50.56 49 54.44 0 0.00 140 41.67 PSTv-14 1,6,7,8,9,17,27,43,44,Tr1,Exp2,Tye 1 45 25.00 23 25.56 0 0.00 68 20.24 PSTv-7 1,6,8,9,17,27,43,44,Exp2 1 7 3.89 0 0.00 1 1.52 8 2.38 PSTv-17 1,6,7,8,9,17,27,43,44,SP,Exp2,Tye 1 5 2.78 2 2.22 0 0.00 7 2.08 PSTv-16 1,6,7,8,9,10,24,32,43,44,Tr1,Exp2 1 4 2.22 0 0.00 1 1.52 5 1.49 PSTv-4 1,6,9,17,27,SP,Tye 1 1 0.56 0 0.00 0 0.00 1 0.30 PSTv-9 1,6,7,8,9,10,17,27,44,Tye 1 1 0.56 0 0.00 0 0.00 1 0.30 PSTv-13 1,6,7,8,9,17,27,43,44,SP,Tye 1 1 0.56 0 0.00 0 0.00 1 0.30 116 PSTv-8 1,7,8,9,17,27,44,Exp2,Tye 1 0 0.00 1 1.11 0 0.00 1 0.30 PSTv-12 1,6,7,8,9,17,43,44,Tr1,Exp2,Tye 1 0 0.00 0 0.00 1 1.52 1 0.30 PSTv-40 6,7,8,9,10,24,27,32,43,44,Tr1,Exp2 2 13 7.22 1 1.11 0 0.00 14 4.17 PSTv-37 6,7,8,9,17,27,43,44,Tr1,Exp2 2 6 3.33 5 5.56 36 54.55 47 13.99 PSTv-36 6,7,8,9,27,43,44,Tr1,Exp2 2 4 2.22 1 1.11 8 12.12 13 3.87 PSTv-38 6,7,8,9,17,24,27,43,44,Tr1,Exp2 2 1 0.56 1 1.11 1 1.52 3 0.89 PSTv-41 6,7,8,9,10,17,24,27,32,43,44,Tr1,Exp2 2 1 0.56 5 5.56 1 1.52 7 2.08 PSTv-30 6,7,8,9,44,Tr1,Exp2 2 0 0.00 0 0.00 2 3.03 2 0.60 PSTv-31 6,7,8,9,17,44,Tr1,Exp2 2 0 0.00 0 0.00 3 4.55 3 0.89 PSTv-32 6,7,8,9,43,44,Tr1,Exp2 2 0 0.00 0 0.00 4 6.06 4 1.19 PSTv-34 6,7,8,9,17,27,44,Tr1,Exp2 2 0 0.00 2 2.22 3 4.55 5 1.49 PSTv-35 6,7,8,9,17,43,44,Tr1,Exp2 2 0 0.00 0 0.00 4 6.06 4 1.19 PSTv-39 6,7,8,9,10,17,27,43,44,Tr1,Exp2 2 0 0.00 0 0.00 1 1.52 1 0.30
A total of 21 races were detected from the 336 isolates collected throughout the U.S.
Among the races, 3 (PSTv-4, PSTv-9, and PSTv-13) were detected only in the Palouse region;
1 (PSTv-8) only in the non-Palouse PNW; 6 (PSTv-12, 30, 31, 32, 35, and 39) only in the non-PNW US; 4 (PSTv-36, 37, 38, and 41) were detected in the Palouse, the non-Palouse
PNW, and the non-PNW US; and the remaining 7 (PSTv-7, 11, 14, 16, 17, 34, and 40) in two of these region categories (Table 3). The most frequent race in the Palouse region was
PSTv-11 (50.56%) followed by PSTv-14 (25.00%). These predominant races had the similar frequencies in the non-Palouse PNW, but not detected in the non-PNW U.S. In the non-PNW U.S., the most predominant race was PSTv-37 (54.55%) followed by PSTv-36
(12.12%). These two races were also detected in the PNW. All other races had less than
8.00% frequency in each of the region categories. All races had virulences to Yr6 and Yr9 and avirulences to Yr5 and Yr15 .
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Fig. 3. Dendrogram showing the similarities of 21 Puccinia striiformis f. sp. tritici races determin ed by the UPGMA in the NTsyspc 2.21L program based on virulence phe notypes.
VG 1 and VG 2 are virulence groups. The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,000 cycles in the bootstrap analysis using the Winboot program.
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The cluster and 3-D plot analyses revealed two major virulence groups (VGs) (Fig. 3,
Fig. 4). Virulence group 1 consisted of 10 races (PSTv -4, 7, 8, 9, 11, 12, 13, 14, and 17) and
VG 2 consisted of 11 races (PSTv -16, 30, 31, 32, 34, 35, 36, 37, 38, 39, 40, and 41). The
main differences between the two VGs were that races in VG 1 were all virulent to Yr1 , most
virulent to YrTye , and few virulent to YrSP , while none of the races in VG 2 were virulent to
these genes. Mo st PNW isolates (84%) belonged to races in VG 1 and most isolates from
the non-PNW of the U.S. (97%) belonged to races in VG 2 (Table 1, Table 3).
Fig. 4. Three-dimensional plot of 21 Puccinia striiformis f. sp. tritici races using princ ipal
coordinates analysis. VG 1 and VG 2 correspond to the clusters in Fig. 3. The number in a
circle represents the number of isolates and the number outside the circle is the PSTv race
name in number. 119
TABLE 4. Locations and dates of wheat fields sampled in 2010 and races and haplotypes of P. striiformis f. sp. tritici in the US Pacific
Northwest
Field Collect Exp/ PSTv race Multilocus haplotype no. date Location County State Com b (no. of isolates) (no. of isolates) The Palouse region 1 8 June Potlatch Latah ID C 14(16) 1(10),19(5),22(1) 2 8 June Latah Spokane WA C 16(2),36(1),40(6),41(1) 7(2),8(2),10(4),33(1),50(1) 3 8 June North Pine Spokane WA C 11(2),16(2),17(1),37(1) 6(1),11(1),19(2),23(1),63(1) 4 8 June Latah East Spokane WA C 9(1),11(8),17(1) 12(5),19(3),21(1),63(1) 5 25 May Central Ferry west Whitman WA E 14(19),11(1) 1(5),19(14),15(1) 6 8 June Whitlow farm Whitman WA E 11(11) 19(10),12(1) 120 7 8 June Farmington-1 Whitman WA C 11(3),40(7) 2(1),4(1),9(1),13(3),19(1),20(1),24(2) 8 8 June Farmington-2 Whitman WA E 11(10) 19(10) 9 8 June Malden Whitman WA C 7(7) 17(7) 10 8 June Rosalia Whitman WA C 11(2),14(4),36(3) 1(4),19(2),50(3) 11 8 June St John city Whitman WA C 11(10) 12(10) 12 8 June Palouse Whitman WA C 11(9),14(1) 1(1),12(2),19(7) 13 8 June SW Colfax Whitman WA C 11(11) 19(10),3(1) 14 8 June Tekoa Whitman WA C 11(2),14(2),17(1),37(5) 1(1),12(1),19(2),23(5),63(1) 15 8 June Endicott Whitman WA C 4(1),11(7),13(1),17(1) 5(2),12(1),19(6),63(1) 16 16 June Lamont Whitman WA C 11(5),14(3),17(1),38(1) 19(7),49(1),53(1),63(1) 17 6 July Colton Whitman WA C 11(10) 19(10) The non-Palouse PNW 18 17 June Lind Adams WA E 11(8),14(1),40(1) 7(1),19(9) 19 25 May Horse Heaven Hill Benton WA C 11(2),34(2),38(1) 19(2),30(1),42(2)
20 25 May Highway-12 Columbia WA C 11(10) 19(10) 21 17 June Connell Franklin WA C 11(4),17(1),37(5) 12(4),23(5),63(1) 22 16 June Harrington Lincoln WA E 11(7),14(2),17(1) 1(1),12(4),19(4),63(1) 23 25 May Walla Walla Walla Walla WA C 11(2),14(10) 12(2),19(10) 24 15 June Mt. Vernon Skagit WA E 41(5) 33(5) 25 25 May Pendleton Umatilla OR E 8(1),14(10) 21(1),19(10) 26 25 May Hermiston Umatilla OR E 11(13) 12(11),13(1),16(1)
aExp/Com: Experimental or commercial field.
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The races and the numbers of isolates for individual PNW fields are shown in Table 4.
Of the 26 fields, 10 (38.5%) had 1 race, 5 (19.2%) had 2, 6 (23.2%) had 3, and 5 (19.2%) had
4 races. At a county level, only one race was detected in Latah of Idaho (PSTv-14) and
Columbia (PSTv-11) and Skagit (PSTv-41) of Washington. Two races were detected in
Walla Walla of Washington. Three races were detected in Adams (PSTv-11, 14, and 40),
Benton (PSTv-11, 34, and 38), Franklin (PSTv-11, 17, and 37), and Lincoln (PSTv-11, 14, and 17) of Washington and Umatilla of Oregon (PSTv-8, 11, and 14). Eight races (PSTv-9,
11, 16, 17, 36, 37, 40, and 41) were detected in the Spokane county and ten races (PSTv-4, 7,
11, 13, 14, 17, 36, 37, 38, and 40) in the Whitman county. The high numbers of races detected in these two counties were partially due to the large number of isolates. Although the numbers of races were high, their frequencies were not even, ranging from 3.8% (one isolate for four of the races) to 38.5% (10 isolates for PSTv-11) in Spokane county and from
0.8% (one isolate for 4 races) to 60.2% (80 isolates for PSTv-11) in Whitman county.
Genetic variation. With the 20 SSR markers, a total of 66 multilocus haplotypes were identified from the 336 tested isolates. The “homozygous” (AA and BB) and “heterozygous”
(AB) states of the genotypes at each of the 20 SSR loci are shown in Fig. 5. Of the 66 haplotypes, 26 were detected in the Palouse region, 15 in the non-Palouse PNW, and 41 in the non-PNW U.S. (Table 1). The most popular haplotypes in the Palouse region were G19
(49.44%), G1 (11.67%), and G12 (11.11%). In the non-Palouse PNW, the most popular haplotypes were G19 (50.00%) and G12 (23.33%). In the non-PNW U.S., 18.18% of the isolates were G33, and haplotypes G39 and G50 each counted for 7.58% of the 66 isolates.
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The neighbor-joining tree constructed using Dices similarity index with the SSR data revealed two major molecular groups (MGs) (Fig. 6). The two MGs were also well supported by the three-dimensional plot of principle coordinate analysis (Fig. 7). Molecular group 1 consisted of haplotypes G1 to G22 with AA type predominant at most loci. G23 to
G66 with AB type at most SSR loci and few homozygous loci were grouped into MG 2.
About 89% of the 176 Palouse isolates were grouped to MG 1, 83% of the 94 non-Palouse
PNW isolates were in MG 1, and 78.9% the 66 non-PNW US isolates to MG 2 (Fig. 5). The
STRUCTURE analysis also determined two populations based on the SSR allele size data and was consistent with the molecular groups in Fig. 5.
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non-Palouse non-PNW Genotype 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Palouse PNW US Total MG G01 AAAAAAAAABAAAAAAAA BB AAAAAAAAAAAAAAAAAAAA 21 1 0 22 1 G02 AAAAAAAA AB AAAAAAAA AA AAAAAAAAAAAAAAAAAAAA 1 0 0 1 1 G03 AAAAAAAAABAAAAAAAA AA AB AAAAAAAAAAAAAAAAAA 0 1 0 1 1 G04 AA BB AAAA AB AAAAAAAA AA AAAAAAAAAA AB AAAAAAAA 1 0 0 1 1 G05 AAAAAAAA AB AAAAAA AB AA AAAAAAAAAAAAAAAA AB AA 2 0 0 2 1 G06 AAAAAAAAABAAAAAA BB AA AAAAAAAAAAAAAAAA AB AA 1 0 0 1 1 G07 AA AB AAAA AB AAAAAA BB AA AAAAAAAAAAAAAAAA AB AA 2 1 0 3 1 G08 AA AB AAAAABAAAAAA BB AA AAAAAAAAAAAAAAAAAAAA 2 0 0 2 1 G09 AA AB AAAAABAAAAAAAA BB AAAAAAAAAAAAAAAA AB AA 1 0 0 1 1 G10 AA AB AAAA AB AAAA AB BB AA AAAAAAAAAAAAAAAAAAAA 4 0 0 4 1 G11 AA AB AAAAABAAAAABAA AA AAAAAAAAAAAAAAAAAAAA 1 0 0 1 1 G12 AAAAAAAAAAAAAAAAAA AA BB AAAAAAAAAAAAAAAAAA 19 22 0 41 1 G13 AAAAAAAAAAAAAAAAAA AA AAAAAAAAAAAAAAAAAAAA 3 2 0 5 1 G14 AAAA AB AAAAAAAAAAAA AA AAAAAAAAAAAAAAAAAAAA 0 1 0 1 1 G15 AAAAAAAAAAAAAAAAAA AA AAAAAAAAAA BB AAAAAAAA 0 1 0 1 1 G16 AAAAAAAAAAAAAAAAAA AA BB AA BB AAAAAAAAAAAAAA 0 1 0 1 1 G17 AAAA AB AAAAAAAAAAAA AA BB AAAAAAAAAAAA BB AAAA 7 0 1 8 1 G18 AAAA AB AAAAAAAAAAAA AA BB AAAAAAAAAAAAAAAAAA 0 1 0 1 1 G19 AB AA AB AAAAAAAAAA BB AA BB AAAAAAAAAAAAAAAAAA 89 45 0 134 1 G20 AA AB AB AAAAAAAAAA BB AA AAAAAAAAAAAAAAAA AB AA 1 0 0 1 1 G21 AA AB AB AAAAAAAAAA BB AA AAAAAAAAAAAA AB AAAAAA1 1 0 21 G22 AA AB AB AAAAAAAAAAAA AA AAAAAAAAAAAAAAAAAA BB 0 1 0 1 1 G23 AB AB AB ABAAABABAB BB AB BB AB AB BB AB BB AB AB AAAA 6 5 1 12 2 G24 AB AB AB AB AA AB AB AA BB AB BB AB BB BB AB BB AB AB BB AB 2 0 2 4 2 G25 AB AB AB ABAAABABAB BB AB BB AB BB BB AB BB AB AB BB AB 0 0 2 2 2 G26 AB AB AB ABAAABABAA BB AB BB AB BB BB AB BB AB AB BB BB 0 0 1 1 2 G27 AB AB AB AB AA AB AB AB BB AB AB AB BB BB AA BB AB AB BB AB 0 0 1 1 2 G28 AB AB AB ABAAABABAB BB AB AB AB BB BB AB BB AB AB BB AB 0 0 1 1 2 G29 AB AB AB AAAAABABAB BB AB BB AB BB BB AA BB AB AB BB AB 0 0 1 1 2 G30 AB AB AB AB AA AB AB AB BB AB AA AB BB BB AAAA AB AB BB AB 0 1 1 2 2 G31 AB AB AB ABAAABABAB BB AB AA AB BB BB AA BB AB AB BB AB 0 0 2 2 2 G32 AB AB AB ABAAABABAA BB AB AA AB BB BB AAAA AB AB BB AB 0 0 1 1 2 G33 AB AB AB AB AA AB AB AB BB AB AA AB BB BB AB BB AB AB BB AB 1 5 12 18 2 G34 AB AB AB ABAAABABAB BB BB AA AB BB BB AB BB AB AB BB AB 0 0 2 2 2 G35 AB AB AB AB AA AB AB AB BB BB AA AB BB AB AB BB AB AB BB AB 0 1 0 1 2 G36 AB AB AAABAAABABAB BB AB AA AB BB BB AB BB AB AB BB AB 0 0 1 1 2 G37 AB AB AB ABAAABABAB BB AB AA AB BB BB AA BB AB AB BB AA 0 0 1 1 2 G38 AB AB AB AB AA AB AB AB BB AB AA AB BB BB AB BB AB AB BB AA 0 0 1 1 2 G39 AB AB AB ABAAABABAA BB AB AA AB BB BB AB BB AB AB BB AB 0 0 5 5 2 G40 AB AB AB ABAAABABAA BB AB AA AB BB BB AB BB AB AB BB AA 0 0 1 1 2 G41 AB AB AB AB AA AB AB AA BB BB AA AB BB BB AB BB AB AB BB AA 0 0 1 1 2 G42 AB AB AB ABAAABABAA BB BB AA AB BB AB AA BB AB AB BB AB 0 2 1 3 2 G43 AB AB AB ABAAABABAA BB BB AA AB BB BB AA BB AB AB BB AB 0 0 2 2 2 G44 AB AB AB AB AA AB AB AA BB BB AA AB BB BB AA BB AB AB BB BB 0 0 1 1 2 G45 AB AB BB ABAAABABAA BB BB AA AB BB BB AA BB AB AB BB AB 0 0 1 1 2 G46 AB AB AB ABAAABABAB BB BB AA AB BB BB AA BB AA AB BB AB 0 0 1 1 2 G47 AB AB AB AB AA AB AB AB AB AB AA AB BB BB AB BB AB AA BB AB 0 0 1 1 2 G48 AB AB AB ABAAAB BB ABAA AB AA AB BB BB AA BB AB AB BB AB 0 0 1 1 2 G49 AB AB AB AAAA AB AB AB BB AB AA AB BB BB AB BB AB AB AB AB 1 0 0 1 2 G50 AB AB AB AB AA AB AB AB BB AB AA AB BB BB AB BB AB AB AB AB 4 0 5 9 2 G51 AB AB AB ABAAABABAA BB AB AA AB BB BB AB BB AB AB AB AB 0 0 1 1 2 G52 AB AB AB AB AA AB AB AB BB AB AA AB AB BB AB BB AB AB AB AB 0 0 2 2 2 G53 AB AB AB ABABABABAB BB AB AA AB BB BB AB BB AA AB AB AB 1 0 0 1 2 G54 AB AB BB ABAAABABAB BB AB AA AB BB BB AB AA AB AB AB AB 0 0 1 1 2 G55 AB AB BB AB AA AB AB AB BB AB AA AB BB AB AA BB AB AB AB AB 0 0 1 1 2 G56 AB AB AB ABAAABAAAA BB AB AA AB BB BB AB BB BB AA BB AA 0 0 1 1 2 G57 AB AB AB ABAABBAAAA BB AB AA AB BB BB AB BB AB AB BB AB 0 0 1 1 2 G58 AB AB AB BB AA AB AB AA BB BB AA AB BB BB AA AB AB AB AB AB 0 0 1 1 2 G59 AB AA AB ABAAABAAAB BB BB AA AB BB BB AAAA AB AB BB AB 0 0 1 1 2 G60 AB BB AB AAAAABABAB BB AB AA AB BB BB AA AB AB AA BB AA 0 0 1 1 2 G61 AB AA AB AB AA AB AB AAAA AB AA BB BB BB AB BB AB BB BB AA 0 0 1 1 2 G62 AB AB AB ABAAAB BB AAAA AA AA BB BB BB AB BB AB AB AA BB 0 0 1 1 2 G63 AB AB AB AA AB AB AB AB BB AB BB AB AB AB AAAA AB AB AB AB 5 2 0 7 2 G64 AB AB AB AAAA AB AB AA BB AB AB AB AB AB AA AB AB AA AB AB 0 0 1 1 2 G65 BB AA BB BBAABB BB AA BB AB AAAA BB BB AB AA AB AB BB AB 0 0 1 1 2 G66 AB AB AB BB AB AB AAAA BB AB AAAA BB BB AB BB AAAA BB AA 0 0 1 1 2 Fig. 5. Molecular genotypes of Puccinia striiformis f. sp. tritici determined using 20 SSR markers. Markers 1 to 20 are presented in Table 2. The numbers in the columns on the right are numbers of isolates in different regions. 124
Fig. 6. Neighbor-joining tree showing the Dices similarities of 66 haplotype s of Puccinia striiformis f. sp. tritici based on SSR data using NTsyspc 2.21L program. MG 1 and MG 2 are molecular groups shown in Fig. 5. The number at each branch shows the percentage of times the group of isolates in that branch occurred based on 2,0 00 cycles in bootstrap analysis using the Winboot program. 125
Fig. 7. Three-dimensional plot of 66 molecular haplotypes of Puccinia striiformis f. sp. tritici using principal coordinates analysis.
126
Some of the molecular haplotypes in Fig. 6 corresponded to races in Fig. 3. In MG 1, isolates in G12 were all PSTv-11 and isolates of G19 were either PSTv-11 or PSTv-19. In
MG 2, G33 corresponded to PSTv-36, PSTv-37, and PSTv-41, which were the most common races in the non-PNW US. Overall, most PNW isolates were virulent on Yr1 and YrTye and was “homozygous” for the A alleles at most tested loci (fit into VG 1 and MG 1), the most of the non-PNW US isolates were avirulent on Yr1 and YrTye and were “heterozygous” at more than 50% of the marker loci tested (VG 2 and MG 2). The comparison of the virulence and molecular matrices using MXCOMP in the NTsyspc 2.21L program showed a moderate correlation coefficient (r = 0.39).
The value of the association index (rd) 0.33 was observed with the Palouse population by the multilocus test. The value was significantly different from zero value expected for a
panmictic population ( P < 0.001). Similarly, a 0.42 rd value ( P < 0.001) was obtained for
the whole PNW region. In addition, r d values ranging from 0.19 to 1.00 ( P < 0.001) were
observed for isolates from individual fields with genetic variation. All of these r d values for different components of the Pst population led to the rejection of the null hypothesis of random mating from sexual reproduction of the pathogen in the Palouse and the PNW region.
Furthermore, the tree steps estimated from the observed SSR dataset of the Palouse population in the parsimony tree length permutation test (PTLPT) was only 56, which was much shorter than the 318 steps on average generated from the randomized dataset (Fig. 8).
Similarly, the PTLPT observed steps was 56 and 173 steps from randomized dataset for the entire PNW population. A Chi-squared test for Hardy-Weinberg equilibrium with the
127
Palouse population, the whole PNW population, and individual fields for each polymorphic locus resulted in significant deviations from null hypothesis ( P < 0.001 for all tests).
Therefore, all three tests rejected the presence of sexual recombination in the Palouse region and the entire PNW. The genetic diversities of the Palouse region and the non-Palouse PNW, as measured with Nei’s gene diversity, Shannon’s information index, or Kosman diversity index were similar, but lower than the values for the non-PNW US (Table 5). As expected, the gene flow between the Palouse and the non-Palouse PNW populations was very high. In contrast, the gene flow was low between the PNW and the non-PNW US populations (Table
6). The results of AMOVA indicated that the majority (62.65%) of the total genetic variation was found within populations and only 35.45% among populations in the Palouse region, the non-Palouse PNW and the non-PNW US (Table 7). Both levels of variations were significant ( P < 0.01).
128
Fig. 8. Randomized distributions and observed the number of steps in most parsimonious trees of the Palouse Puccinia striiformis f. sp. tritici population. The distribution of step numbers under the null hypothesis (no association between alleles) was obtained af ter 1,000 randomizations of alleles in the individual isolates (Burt et al. 1996).
129
TABLE 5. Nei’s gene diversity, Shannon’s information index, and Kosman index of the
Puccinia striiformis f. sp. tritici populations in the Palouse region, the non-Palouse Pacific
Northwest (PNW), and the non-PNW United States based on the SSR marker data
Index a
Population H I Ko
The Palouse region 0.15 0.35 0.29
The non-Palouse PNW 0.17 0.38 0.33
The non-PNW US 0.58 0.54 0.99 a H = Nei’s gene diversity (Nei 1973); I = Shannon’s information index (Lewontin 1972);
and Ko = Kosman diversity index (Kosman 1997).
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TABLE 6. The mutation-scaled population size ( Θ) and migration rates (M) between the
Puccinia striiformis f. sp. tritici populations in the Palouse region and the non-Palouse
PNW; the PNW and the non-PNW US based on the SSR marker data
Θa Palouse non-Palouse PNW non-PNW
PNW US
Palouse 1.03±0.04 1.13±0.15
the non-Palouse PNW 1.03±0.05 1.44±0.18
PNW 1.11±0.03 0.51±0.11
the non-PNW US 0.95±0.05 0.34±0.09
a Maximum likelihood estimates of migration rates (M = m/ ) and 95% confidence
intervals (parentheses) were calculated using Migrate 3.2.19. Source and recipient
populations are in columns and rows, respectively.
131
TABLE 7. Analysis of molecular variance (AMOVA) among and within the Puccinia
striiformis f. sp. tritici populations in the Palouse region, the non-Palouse Pacific
Northwest (PNW), and the non-PNW United States based on the SSR marker data
Source DF a SS a PV a (%) EV a Pa
Among populations 2 556 35.45 1.35 <0.01
Within population 333 1641 64.55 2.45 <0.01
Total 336 2197 100.00 3.80
a DF = degree of freedom; SS = sum of squared deviation; PV = percentage of variance; EV
= estimated variance; and P = probability.
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DISCUSSION
A total of 270 isolates from the PNW and 66 isolates from 20 other states of the US were
tested on 18 single Yr -gene lines and with 20 SSR markers to determine variations in
virulence and molecular haplotypes. Isolates from different locations had common and
unique virulence patterns. All isolates were avirulent to Yr5 and Yr15 , indicating that these
genes are still effective against the Pst population in the US. This result was in consistent with previous studies (Chen et al. 2010; Wan & Chen 2011). In the PNW, virulences to Yr1 and YrTye were in high frequencies due to the selection of host resistance whereas the isolates from the non-PNW US mostly avirulent to these two genes.
The PNW isolates tended to be more “homozygous” (MG 1, AA dominant) and the non-PNW US isolates tended to be more “heterozygous” (MG 2, AB dominant). The different karyotypes were related to the groups of races. The two groups established based on molecular data generally corresponded to the two groups established by virulence data.
MG 1 and VG 1 included most PNW isolates and MG 2 and VG 2 contained most isolates from the non-PNW US. MG 1 represented isolates homozygous at most SSR loci while MG
2 had isolates with more heterozygous loci (Fig. 5). The correlation between the genotype and virulence data is consistent to our previous study on grass isolates which found that
PSTv-11 and PSTv-14 (old PST-127/139) harbor more homozygous marker loci than other races (Cheng and Chen, 2012). In addition, the AA and AB dominant haplotypes were detected only in isolates from wheat or grasses but not from barley. Interestingly, only two races, but seven haplotypes, were identified with ten isolates collected in one commercial
133
field in Farmington, Washington (Field No. 7). Six of the haplotypes were in MG 1 and
they were different at only 1 to 4 of the marker loci (6 loci were AA to AB, 3 loci were AA to
BB different). These differences might have been caused by single-step mutations.
Analyses for estimating whether sexual recombination is occurring were conducted on
different geographical scales. The association index r d was calculated for the population in
each field, and also for the Palouse region and the PNW. Excluding the 14 fields with single
haplotypes, none of the remaining 13 fields had observed values close to zero (0.19 < r d <
1.0). These results rejected the hypothesis that the urediniospore population has resulted
from random mating in each field. Similarly, the r d values 0.33 and 0.42 obtained with the
Palouse and the PNW populations, respectively, also ruled out the possibility of sexual
reproduction in the region. The PTLPT result with the Palouse isolates based on the SSR
data estimated a tree had a length of 56 steps that is significantly shorter than the trees
generated from a randomized data set with mean of 318 steps. When tested with the PNW
population, an observed length of 56 steps is also significantly shorter than the mean of 173
steps generated from a randomized data set. Both tests rejected the null hypothesis of sexual
recombination in the Palouse or PNW region even with the presence of B. vulgaris plants.
In the Potlatch field near the B. vulgaris bushes in Lahta County, Idaho, only one race
(PSTv-14) and three haplotypes (G1, G19 and G22) were detected. The three haplotypes were very similar, belonging to MG 1 (see Fig. 5) and should be considered in a same clonal lineage. Therefore, these results did not show any evidence of sexual reproduction. A low genetic variation was detected in the fields in the Palouse region surrounding the barberry
134
bushes, but the variation is more likely caused by single step mutations rather than by
segregation through sexual reproduction. The barberry plants were heavily infected by rust
in 2009 and 2010 and the winter wheat crop in field 1 was heavily infected by stem rust in
2009 and the spring wheat crop in the field was infected by both stem rust and stripe rust in
2010. In the wheat fields, the stem rust samples from the next wheat field (Field 1 in the
present study) in 2009 resulted in many Pgt races (Jin et al. unpublished data). In our group,
14 Pgt races were identified from 16 single uredial isolates produced from aecial samples on barberry leaves from the barberry bushes at this field site in 2011 (Wang and Chen, unpublished data), indicating that sexual reproduction on barberry plants produces a high diversity of races. The contrast result we obtained in the present study for stripe rust samples in the surrounding field and the region with barberry plants does not support any sexual reproduction for the Pst population. As in the past, the direct connection of rust on
the barberry plants and stem rust in the surrounding field was obvious. However, we did not
find such connection between rust on B. vulgaris plants with stripe rust on wheat. In a separate study, PCR amplification of thousands single-aecium and mixed aecia DNA samples using primers that can differentiate Pst from Pgt found them all Pgt (Wang et al. 2011; Wang
et al. 2012 unpublished data). Therefore, the present study together with other studies did
not reveal any role of B. vulgaris plants in the genetic diversity of the Pst population and
stripe rust epidemics under natural conditions in the PNW.
The present study is the first to show that populations collected from fields with
presence of barberry bushes did not carry on sexual recombination. Sexual recombination
135 of stripe rust had long been considered not possible as alternate hosts were not identified.
Questions about the existence of Pst sexual reproduction rose after the Berberis spp. was determined to be the alternate host under the greenhouse conditions (Jin et al. 2010; Wang and Chen, 2011). Several studies revealed genetic recombination in certain populations but could not determine whether it was through a sexual or asexual process (Mboup et al. 2009;
Duan et al. 2010; Bahri et al. 2011). An attempt was made to connect the production of sex-specific structure telia with the genetic diversity of stripe rust populations from different geographic origins (Ali et al. 2010). However, without the presence of the alternate host barberry, the ability of telia production is not evident for the existence of sexual recombination in the nature. In the US PNW, the Pst population did not produce abundant telia until the appearance of PST-127 and related races, which were first identified in
California and Washington in 2007 and since then have become predominant in the PNW
(Chen et al. 2010; Wan & Chen 2011; Wan and Chen 2012 unpublished data). The PSTv-11 and PSTv-14, which were differentiated using the single Yr -gene lines and found for most
PNW isolates in the present study (Table 3), are the PST-127 race groups differentiated using the old cultivar differential set (Wan and Chen, unpublished data). This group of races produces abundant telia in the fields and also on adult-plants under controlled greenhouse conditions. With telia produced in the field and in the greenhouse by this race group, we successfully infected barberry plants and obtained aecium-derived urediniospore isolates with very different virulence patterns under the controlled greenhouse conditions (Wang and Chen,
2012 unpublished data). Interestingly, this group of races is more homozygous than the old
136
races that do not produce abundant telia (Cheng and Chen 2012). Therefore, production of
telia does not necessarily result in sexual reproduction, although it is a pre-condition. We
are conducting studies to determine why Pst telia do not infect barberry under the natural conditions.
Importantly, analysis of genetic variations for each of the sampled P. striiformis populations suggested that the two molecular groups have geographically distinct distributions. The AA dominant group more likely to exist in PNW region and AB dominant group were mainly from the non-PNW US. Low gene flow between these two populations could be due to the geographic barrier created by the Rocky Mountain since it is hard for the initial inoculum urediniospores to get over the mountain by air. It is also possible that the time has not been long enough since we detected the races in the group one in the western US in 2007 (Chen et al. 2010) for the isolates in the two genetic groups to hybrid asexually to produce hybrid isolates.
Studying the way that the stripe rust fungus evolves is very important to understand the virulence variation of the fungus and to conduct better disease management. Our results suggest that barberry does not play a role in the wheat stripe rust life cycle in the PNW.
Stripe rust management should be focused on crop hosts and auxiliary grass hosts. Genetic variations including virulence variations resulted from mutation and somatic hybridization/recombination are selected by crop and grass hosts through clonal reproduction.
Therefore, these hosts for urediniospores should be intensively sampled to identify new races.
Utilization of non-race specific resistance, such as high-temperature adult-plant resistance,
137 and diverse genes for effective all-stage resistance (Chen 2005; Wang et al. 2012) should be the key strategies to achieve sustainable control of stripe rust.
ACKNOWLEDGEMENTS
This research was supported by the US Department of Agriculture, Agricultural
Research Service (Project No. 5348-22000-014-00D) and Washington State University
(Project No. 13C-3061-3925) PPNS No. ???, Department of Plant Pathology, College of
Agricultural, Human, and Natural Resource Sciences, Agricultural Research Center, Project
Number WNP00663, Washington State University, Pullman, WA 99164-6430, USA. We thank Dr. Meinan Wang for technical support of the rust DNA extraction, Dr. Anmin Wan for increasing urediniospores and identifying races for some of the stripe rust isolates used in this study. We would like to thank Drs. Scot Hulbert, Tobin Peever and Kulvinder Gill for critical review of the manuscript.
138
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CHAPTER FIVE
Molecular mapping of two genes for stripe rust resistance in durum wheat germplasm
accessions PI 331260 and PI 480016
P. Cheng · X. M. Chen
P. Cheng · X. M. Chen ( )
Department of Plant Pathology, Washington State University, Pullman, WA 99164-6430, USA e-mail: [email protected]
X.M. Chen
U.S. Department of Agriculture, Agricultural Research Service, Wheat Genetics, Quality,
Physiology and Disease Research Unit, Pullman, WA 99164-6430, USA.
Abstract Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst ), is one of the most important diseases of wheat worldwide. The best strategy to control stripe rust is to grow resistant cultivars. Durum wheat germplasm has excellent resistance to stripe rust, but not many genes for stripe rust resistance had been identified from durum wheat. Durum wheat germplasm accessions PI 331260 and PI 480016, originally from Ethiopia, were resistant in seedling tests to all tested US races of Pst under controlled greenhouse conditions and at multiple locations under natural infection of the pathogen for the past several years. To study the genetics of their resistance and transfer the resistance into common wheat, both accessions were crossed with a stripe rust susceptible spring wheat line, ‘Avocet Susceptible’
(AvS). F 3 plants with 42 chromosomes and stripe rust resistance were selected by counting
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Feulgen stained root tip cells and tested with PST-100 in the seedling stage under controlled
greenhouse conditions. The 3:1 segregation obtained in the F 4 lines derived from a single F 3
plant in each of the crosses indicated that both PI 331260 and PI 480016 carried a single
dominant gene for resistance. To develop an adequate mapping population, 146 F 6 plants of
AvS/PI 331260 and 172 F 6 plants of AvS/PI 480016 derived from a single F 5 plant were used as an “F 2” segregating population for mapping the resistance gene and the F 6 single-seed descent F 7 lines (treated as “F 3” lines for genetic analysis) were used to determine the stripe rust resistance genotype for each F 6 plant. A total of 576 simple sequence repeat (SSR) markers were screened for markers linked to the resistance locus in each cross. Ten markers were identified for each of the resistance genes and these markers mapped both YrPI331260 and YrPI480016 on the short arm of chromosome 1B. YrPI331260 was flanked by
Xbarc119 and Xgwm413 at a genetic distance of 3.0 cM and 3.5 cM, respectively; and
YrPI480016 was flanked by Xgwm18 and Xgwm273 at 1.2 cM and 2.1 cM, respectively.
Based on the chromosomal locations, reactions to various races of the pathogen, the two genes are different from all previously designated genes for stripe rust resistance.
Key words : Molecular mapping · Puccinia striiformis f. sp. tritici · Resistance genes · Stripe rust · Triticum aestivum ·
Introduction
Stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss. ( Pst ), damages wheat
crops worldwide (Stubbs 1985; Chen 2005; Wellings 2011). In the US, up to 90% of yield
loss on susceptible cultivars have been observed (Sharma-Poudyal & Chen 2011; Chen
unpublished data). Although successful use of fungicides can prevent multi-million dollar
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losses (Line 2002), the application of fungicides adds a significant extra cost to wheat
production. Growing resistant cultivars is the best method for stripe rust management.
All-stage resistance and adult-plant resistance, especially high temperature, adult-plant
(HTAP) resistance, have been two main types of resistance used in the US and many other countries to control stripe rust (Chen 2005). All-stage resistance, which can be detected at the seedling stage and expresses throughout all growth stages, generally provides high level of resistance, but often race-specific (Chen 2005). In contrast, HTAP resistance, which expresses when plants get old and weather becomes warm, is last long, but often provides partial resistance that may not be adequate (Line 2002; Chen 2005, 2007). Gene pyramiding and multiline cultivars have been successfully used in the US to provide relatively durable resistance (Chen 2007). Gene deployment requires a large number of genes conferring effective resistance. So far, 53 officially designated Yr (yellow rust) gene loci and numerous
temporarily designated genes have been identified in wheat
(http://www.shigen.nig.ac.jp/wheat/komugi/genes/symbolClassList.jsp ), but most of them
have become ineffective or provide a low level of resistance. Molecular markers have been
developed for some resistance genes and marker-assisted selection has been used in cultivars
resistant to stripe rust (Cheng 2008). Resistance genes can be stacked into popular wheat
cultivars by rapid and targeted marker-assisted background selection (Randhawa et al. 2009).
However, the number of effective resistance genes with usable markers is limited. New genes and user-friendly markers are needed to diversify resistance genes used in breeding programs.
Tetraploid wheat with A and B genomes is the primary gene pool of hexaploid common wheat for exploring resistance genes. Resistance genes Yr7 , Yr15 , Yr24 , Yr26 and Yr36 originated from tetraploid wheats (Macer 1966; McIntosh & Lagudah 2000; Ma et al. 2001;
Uauy 2005). Durum wheat [ Triticum turgidum L. subsp. durum (Desf.) Husn.], a tetraploid
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wheat (2n=4x=28, AABB genomes), is grown on approximately 17 million hectares worldwide (Abdalla et al. 1992). About 23% of 216 durum cultivars in West Asia and
North Africa were resistant to stripe rust (Mamluk 1992). A wide range of seedling and adult-plant resistance to stripe rust in durum wheat cultivars was observed from various countries (Ma et al. 1995; Ma et al. 1997b). Field resistance resulted from addition of two seedling resistance genes and one partially adult resistance gene from five durum wheat cultivars was reported (Ma et al. 1997a). Therefore, durum wheat may harbor many genes for stripe rust resistance and most of them have not been identified. Crossing durum wheat with common wheat is relatively easy compared to diploid wheat and other wild wheat relatives as durum wheat is often used as a bridging species to transfer resistance genes from diploid wheat into common wheat (Chhuneja et al. 2008). Thus it should be a convenient and effective way to discover new genes from durum wheat and then transfer them into common wheat.
In our screening for stripe rust resistant wheat germplasm, a number of durum wheat genotypes with high levels of resistance to stripe rust were identified based on resistance evaluation with selected predominant Pst races in the US under controlled greenhouse conditions and multi-year field tests under natural infections (Chen, unpublished data). In this study, we determined the genetic basis of resistance in two durum wheat germplasm accessions PI 331260 and PI 480016, both originated from Ethiopia. Molecular markers linked to the resistance genes and homozygous resistant progenies in a common wheat background were developed.
Materials and methods
Developing mapping population
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Durum wheat ( T. turgidum subsp. durum , 2n=28) lines PI 331260 and PI 480016, used as the male parents, were crossed with common ( T. aestivum , 2n=42) spring wheat line ‘Avocet
Susceptible’ (AvS) in 2005-2006 and F 1 plants were grown for F 2 seeds in a greenhouse in
2006. F 2 plants were grown, evaluated for stripe rust resistance under the natural Pst
infection, and harvested for F 3 seeds in an experimental field near Pullman, Washington in
2007.
Due to sterility, the numbers of seeds obtained for F 2 and F 3 generations were too small for used as mapping populations. In 2008, 28 F 3 seeds from AvS/PI 331260 and 20 F 3 seeds from AvS/PI 480016 were germinated in Petri dishes with moist filter paper and their chromosomes in root tips were analyzed using the standard Feulgen staining procedure (Chen et al. 1995; Xu et al. 2012). Of the F 3 seedlings of AvS/PI 331260, 16 had 42, 5 had 28 and
7 had 29-41 chromosomes; and of the F 3 seedlings of AvS/PI 480016, 3 had 42, 12 had 28 and 5 had 29-41 chromosomes. The F 3 plants with 42 chromosomes were inoculated with urediniospores of Pst race PST-100 for their reaction to stripe rust at about 4-leaf stage and grown to obtain F 4 seeds. About 20-40 F 4 seedlings were tested with PST-100 for each F 4 line derived from a single resistant F 3 plant with 42 chromosomes to identify segregating F 4 lines. The segregating F 4 lines showed a 3:1 ratio for resistant and susceptible plants ( P =
0.72 - 0.91). The F 4 plants of the segregating lines were grown to obtain seeds of F 5 lines.
Because sterility was still a problem, only 27 F 5 lines of AvS/PI 331260 and 15 F 5 lines of
AvS/480016 were obtained with limited seeds in each line.
Seeds of F 5 lines were planted, their homozygous resistant, homozygous susceptible and segregating reactions to natural Pst infection were recorded, and their derived single-plant derived F 6 seeds were harvested in the field in 2010. For each cross, a F 6 population derived from a single segregating F 5 line was selected for use as a mapping population based on their adequate seed quantity and relative desirable plant types such as common wheat heads, more
150
tillers, medium height and strong stems. F 6 and parental seeds were planted in 12x12x12
cm pots, three seeds per pot, filled with soil mixture and the plants were grown in a
greenhouse. At about 4-leaf stage, two leaves were collected from each F 6 plant or parental
line for DNA extraction, and then the plants were tested with PST-100 to obtain phenotypic
data. After infection type data were recorded 20 days after inoculation, sporulating leaf
parts were removed and the plants were grown to obtain F 7 seeds from each F 6 plant. A
total of 146 and 172 F 6 plants were phenotyped and the 146 and 156 F 7 lines were obtained
for AvS/PI 331260 and AvS/PI 480016, respectively.
About 15 seeds for each of the F 7 and parental lines were planted in the field in spring,
2011 and infection type and severity (leaf area infected) data were recorded at flowering
stage. The severe stripe rust epidemic resulted from natural infection allowed us to obtain
high quality stripe rust data without artificial inoculation. One F 7 line with homozygous
resistance to stripe rust and desirable agronomic traits such as medium height, big heads,
more tillers and strong stems was selected from each cross to be used as new germplasm lines
carrying the resistance genes in a common spring wheat background.
Pathogen isolates
A total of eight P. striiformis f. sp. tritici races (Table 1), with various virulence gene combinations (Chen et al. 2010; Wan & Chen 2011), were chosen to test seedlings of PI
331260, PI 480016, and AvS. PST-100 and PST-127, which has been most spread and have the most virulence genes, respectively in the US (Chen et al. 2010; Wan & Chen 2011), and are avirulent on PI 331260 and PI 480016 but virulent on AvS, were used to inoculate seedlings of the F 4, F 5 and F 6 progenies, together with the parents, in the greenhouse tests.
Urediniospores of each race were increased on susceptible wheat lines and tested on the 20
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wheat genotypes that are used to differentiate races of P. striiformis f. sp. tritici in the US
(Wan & Chen 2011) to determine its purity and correctness of the corresponding race before used to test the parents and progenies of the crosses.
Evaluation of stripe rust reaction
About 5 seeds of each parent and 25-36 seeds of the F 4 or 146-172 seeds of the F 6 generation for each cross were planted, 3 seeds per pot for the progenies and 5 seeds per pot for the parental lines, in the greenhouse for seedling tests and advancing generations. About 15-27
F5 and 146-156 F 7 lines of each cross were planted in fields in 2009 and 2011 for evaluating stripe rust reactions and selecting homozygous resistant or segregating lines. Seedlings at the two-leaf stage (about 10 days after planting) grown in a rust-free greenhouse (diurnal temperature cycle gradually changing from 10 oC at 2:00 am to 25 oC at 2:00 pm with the 16 h light/8 h dark cycle) were uniformly dusted with a mixture of urediniospores of the selected
Pst race with talc at a ratio of approximately 1:20. After inoculation, plants were placed in a dew chamber at 10 oC for 24 h and then transferred to a growth chamber operating at 16 h light and 8 h dark with diurnal temperatures gradually changing from 4 oC at 2:00 am to 20 oC at 2:00 pm (Chen & Line 1992a, b). A set of 20 wheat genotypes used to differentiate Pst races were also included in the tests to confirm the race identity. Infection type (IT) data were recorded 18-21 days after inoculation based on a 0-9 scale (Line & Qayoum 1992a).
Infection types 0-3, 4-6 and 7-9 were considered resistant, intermediate and susceptible, respectively.
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Table 1 Seedling infection types of PI 331260, PI 480016, and Avocet Susceptible (AvS) to
races of Puccinia striiformis f. sp . tritici tested under controlled greenhouse conditions
PST Infection type race a Virulence formula AvS PI 331260 PI 480016
PST-21 2 9 0 1
PST-43 1, 3, 4, 5, 12, 14 9 1 1
PST-45 1, 3, 12, 13, 15 9 1 1
PST-70 1, 3, 11, 12, 16, 18 9 1 1
PST-78 1, 3, 11, 12, 16, 17, 18, 19, 20 9 1 1
PST-100 1, 3, 8, 9, 10, 11, 12,16, 17, 18, 19, 20 9 1 1
PST-127 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20 9 2 2
PST-130 1, 3, 4, 8, 10, 11, 12, 16, 17, 18, 19, 20 9 1 1
a The virulence formulae are based on reactions on the following 20 wheat genotypes used to differentiate races of Puccinia striiformis f. sp. tritici in the US: 1 = Lemhi ( Yr21 ), 2 =
Chinese 166 ( Yr1 ), 3 = Heines VII ( Yr2 , YrHVII ), 4 = Moro ( Yr10 , YrMor ), 5 = Paha ( YrPa1 ,
YrPa2 , YrPa3 ), 6 = Druchamp ( Yr3a , YrD , YrDru ), 7 = AvSYr5NIL ( Yr5 ), 8 = Produra
(YrPr1 , YrPr2 ), 9 = Yamhill ( Yr2 , Yr4a , YrYam ), 10 = Stephens ( Yr3a , YrS , YrSte ), 11 = Lee
(Yr7 , Yr22 , Yr23 ), 12 = Fielder ( Yr6 , Yr20 ), 13 = Tyee ( YrTye ), 14 = Tres ( YrTr1 , YrTr2 ), 15 =
Hyak ( Yr17 , YrTye ) , 16 = Express ( YrExp1 , YrExp2 ), 17 = AvSYr8NIL ( Yr8 ), 17 =
AvSYr9NIL ( Yr9 ), 19 = Clement ( Yr9 , YrCle ), and 20 = Compair ( Yr8 , Yr19 ) (Chen et al.
2010; Wan & Chen 2011)
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Wheat lines ‘AvSYr15NIL’ ( Yr15 ), ‘AvSYr24NIL’ ( Yr24 ) and homozygous resistant F 7 lines of AvS/PI 331260 and AvS/PI 480016 were tested with seven races (PSTv-16, PSTv-23,
PSTv-26, PSTv-27, PSTv-38, PSTv-40 and PSTv-41).
DNA extraction
Each leaf sample consisted of two fresh leaf pieces of 2 cm (about 3 mg) and was pre-dried in a vacuum drier for 2 - 3 days. Genomic DNA was extracted from each sample for each of the F 6 plants and parents for both crosses using a modified CTAB protocol (Riede &
Anderson 1996). To each micro centrifuge tube with a leaf sample, 100 l 0.7 mm Zirconia beads (cat. 11079107zx, BioSpec Products, Bartlesville, OK, USA) were added. Tubes were covered with lids and put in a Mini Beadbeater (Biospec Products, Inc.). After beating for 2 min, 560 l 2X CTAB extraction buffer (1.4 M NaCl; 100 mM Tris-HCl pH8.0; 2%
CTAB (hexadecyltrimethylamonium bromide); 20 mM EDTA; 0.5% NaHSO 3; 1%
2-mercaptoethanol.), pre-warmed to 65°C, was added to each tube. The tube was inverted
4-6 times. After 30-min incubation at 65°C, 700 l solution of 24:1 (v/v) chloroform/isoamyl alcohol was added, vortex thoroughly and centrifuged at 5,000 rpm for 25 min. The upper phase 600 l solution was transferred to a new 1.5-ml microcentrifuge tube. The DNA was precipitated with 500 l of cold 70% ethanol (-20°C) and rinsed with 1 ml of 70% ethanol.
The air-dried DNA was dissolved in 100 l TE (10 mM Tris-HCl and 1 mM EDTA, pH 8.0) buffer with 20 µg/ml RNase and incubated for 1-2 h in a 37°C water bath or oven, and then stored at -20°C. DNA was quantified through electrophoresis and spectrophotometer
(NanoDrop ND-1000, Wilmington, DE, USA). The DNA stock solution was diluted to 30 ng/µl with sterilized ddH 2O for use as the working solution for polymerase chain reaction
(PCR).
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Bulk segregant analysis and SSR genotyping
Based on the phenotypic data, aliquots of DNA from 10 homozygous resistant and 10
homozygous susceptible F 6 plants were combined into resistant and susceptible bulks,
respectively for each cross. A total of 576 simple sequence repeat (SSR) markers were
screened for markers associated with the resistance locus in each cross. PCR were
performed in a GeneAmp® PCR System 9700 thermo-cycler. A 12 µl reaction mixture
consisted of 100 ng of template DNA, 1.2 µl Mg-free 10X PCR buffer (Promega, Madison,
WI, USA), 0.6 unit of Taq DNA polymerase (Promega), 1.2 µl of 25 mM MgCl 2, 0.96 µl dNTP’s (2.5mM) (Sigma Chemical Co., St. Louis, MO, USA), and 0.06 µl 10 µM forward primer with M13 tail (5’-CACGACATTGTAAAACGAC), 0.30 µl 10 µM reverse primer, and 0.24 µl 10 µM M13 labeled primer (Applied Biosystems, Foster City, Calif., USA).
M13 primers used to amplify resistant parent, resistant bulk, susceptible bulk and susceptible parent of each cross were labeled with four fluorescent dyes: FAM (blue), VIC (green), NED
(yellow) and PET (red). After 5 min of denaturation at 94°C, amplifications were programmed for 35 cycles, each consisting of 30 s at 94°C, 30 s at 50-61°C (depending upon the primer pair), and 72ºC for 30 s, and 72ºC for 10 min followed by a 4 oC-holding step.
Then PCR products of 3.0 l FAM, 3.0 l VIC, 4.0 l NED and 6.0 l PET were added into 9
l ddH2O to get a 25 l dilution. A total volume of 13 l containing 9.93 l formamide,
0.07 l 445-LIZ DNA ladder (Applied Biosystems) and 3 l diluted PCR product was
denatured at 95ºC for 5 min and held at 4ºC. The size of the PCR products was estimated
using capillary electrophoresis on an ABI3730X Genotyper (Applied Biosystems). Alleles
were called using the GeneMapper v3.7 software. Primer pairs showing association with
resistance in the bulk segregant analysis were used to genotype the F 6 population of each
cross and those linked to the resistance locus were used to construct linkage maps.
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After the resistance genes in both PI 331260 and PI 480016 were found on chromosome
1BS, additional 20 SSR markers specific to 1BS (Röder et al. 1998) were tested for
polymorphism with genomic DNA from the parents and F 7 lines to confirm chromosomal
locations of the resistance gene and to identify more linked markers. The primer sequence
information of SSR markers for 1BS tested in this study was obtained from the GrainGenes
2.0 website (http://wheat.pw.usda.gov/cgi-bin/graingenes/browse.cgi?class=marker ). The
DNA of six bin deletion lines of chromosome 1BS were used to further determine the contig
location of the two genes (Sourdille et al. 2004).
Data analyses
Chi-squared tests were used to determine the goodness of fit of the observed numbers of
plants or lines to the predicted segregation ratios of the progenies to establish the number of
stripe rust resistance genes, mode of inheritance, and relationships of genes for resistance to
different races. Marker distance in centi Morgans (cM) was calculated according to the
Kosambi mapping function (Kosambi 1944) using the MAPMAKER program (Lander et al.
1987). Linkage maps were constructed using MapDraw v 2.2 for each cross (Liu & Meng
2003). Chi-squared tests were also used to determine the goodness of fit to a single-locus
model for each marker in the F 6 populations.
Results
Phenotypic and genetic characterization of stripe rust resistance
The seedling IT data of PI 331260, PI 480016, and AvS tested with the eight P. striiformis f. sp. tritici races are shown in Table 1. Both durum wheat lines were resistant to all races whereas AvS was susceptible to all.
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Table 2 F6 plants and F 7 lines segregation for seedling resistance to races PST-127 of
Puccinia striiformis f. sp . tritici in AvS/PI 331260 and AvS/PI 480016
a Observed number of F 6 plants or F 7 lines Expected
Crosses Generation Resistance Segregating Susceptible ratio P
AvS/PI 331260 F6 112 - 34 3:1 0.63
F7 35 80 31 1:2:1 0.46
AvS/PI 480016 F6 114 - 58 3:1 0.32
F7 44 72 40 1:2:1 0.75
a For genetic analysis, F 6 was treated as F 2 and F 7 was treated as F 3. See the text for
development of the segregating populations.
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The numbers of resistant (ITs 0, 1 or 2) and susceptible (ITs 7, 8 or 9) plants in F 6 from the greenhouse tests with PST-127 and the F 7 lines in the field tests under natural infection are shown in Table 2. The F 6 populations of both AvS/PI 331260 and PI 480016 segregated at a ratio of 3 resistant: 1 susceptible plants and the segregation of the F 7 lines fitted a 1:2:1 ratio for homozygous resistant, segregating, and homozygous susceptible lines in the following year’s field test for both crosses. For both crosses, all F 7 lines derived from the F 6 plants susceptible in the greenhouse seedling tests were homozygous susceptible at the adult-plant stage in the field and F 7 lines derived from the F 6 plant resistant in the greenhouse test were either homozygouse resistant or segregating. These data showed that PI 331260 and PI 480016 had a dominant gene for effective all-stage resistance to stripe rust.
SSR markers
Of the first 576 SSR markers tested, Xbarc137 and Xgwm18 were found polymorphic between the bulks and parents of AvS/PI 331260. Xbarc137 was a dominant marker producing a 266-bp peak in AvS. Xgwm18 was a co-dominant marker producing a 209-bp peak in PI 331260 and a 211-bp peak in AvS. Xbarc181 and Xgwm498 produced peaks specific to both PI 480016 and the resistant bulk or both AvS and the susceptible bulk.
Xbarc181 was a co-dominant marker producing a 199-bp peak in PI 480016 and a 203-bp peak in AvS. Xgwm498 , also co-dominant, produced a 174-bp peak in PI 480016 and a
177-bp peak in AvS. All four markers localized both resistance genes to the short arm of chromosome 1B.
Because Yr15 and Yr24 /Yr26 were previously mapped to chromosome 1BS (Chague et al.
1999; Ma et al. 2001; Li et al. 2006), markers linked to these genes were assayed on the F 6 lines of both crosses. Linkage analysis using the markers with the F 6 populations of both
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crosses indicated that both genes were linked to Yr15 and Yr24/Yr26 , confirming the location of both genes on chromosome 1BS. To enrich the markers for linkage map and find closer markers, 20 additional markers including markers that linked to Yr15 and Yr24/Yr26 from
1BS were screened. Overall, a total of 40 markers specific to chromosome 1B were
screened and 12 were found associated to the AvS/PI 331260 bulk segregant analysis and 15
in the AvS/PI 480016 bulk segregant analysis. 15 markers were used to phenotype the
entire F 6 populations of both crosses and 8 and 10 were useful for constructing a linkage map
for AvS/PI 331260 and AvS/PI 480016, respectively.
Construction of linkage maps
Linkage maps containing the resistance gene in PI 331260 (YrPI331260 ) and the gene in PI
480016 ( YrPI480016 ) were constructed separately, but their relative locations on 1BS can be
illustrated by common markers (Fig. 1). The two closest flanking markers Xbarc119 and
Xgwm413 , were linked to YrPI331260 with genetic distances of 3.0 and 3.5 cM, respectively.
The closest markers, Xgwm18 and Xgwm273 , for YrPI480016 were 1.2 and 2.1 cM in
distance. Xbarc137 and Xgwm18 that were linked to Yr24 /Yr26 placed this locus 8.8 cM
away from the YrPI331260 locus and 2.6 cM away from the YrPI480016 locus. Xgwm413 ,
which was reported to be tightly linked to Yr15 (Murphy et al. 2009) indicated that Yr15 was
3.5 cM away from the YrPI331260 and 7.4 cM away from the YrPI480016 locus. These
data indicated that YrPI331260 , YrPI480016 , Yr24 /Yr26 and Yr15 are at different loci.
Using the two flanking SSR markers to each of the mapped loci with bin deletion system of
wheat genotype ‘Chinese Spring’, we found that the two genes were on different bins of
chromosome 1BS (Sourdille et al. 2004). YrPI331260 was on bin C-1BS10-0.50 which is
close to the centromere and YrPI480016 was on bin 1BS10-0.50-0.84.
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Fig. 1 Linkage map for YrPI480016 and YrPI331260 on the short arm of chromosome 1B.
The map distances of Yr PI480016 and YrPI331260 to resistance genes Yr15 and Yr24 /Yr26 were based on common markers (Chague et al. 1999; Peng et al. 2000; Li et al. 2006;
Murphy et al. 2009).
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Comparison to other Yr genes on 1BS using various races
To compare the specificities of YrPI331260 and YrPI480016 with other Yr genes on chromosome 1BS, PI 331260, PI 660064 (a selected homozygous resistant F 7 line of AvS/PI
331260), PI 480016, AvS/PI 480016 F7-12 (a selected homozygous resistant F 7 line of
AvS/PI 480016), AvSYr15NIL ( Yr15 ), and AvSYr24NIL (Yr24 ) were tested with seven races
(PSTv-16, PSTv-23, PSTv-26, PSTv-27, PSTv-38, PSTv-40 and PSTv-41). The reactions shown in Table 3 showed that YrPI331260 and YrPI480016 were genes different from Yr24 , but resistant against all tested races as Yr15 .
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Table 3 Infection types on wheat genotypes with Yr genes on short arm of chromosome 1B produced by races of Puccinia striiformis f. sp. tritici
Infection types produced by race (PSTv)
Yr gene Wheat line 16 23 26 27 38 40 41
Yr15 AvSYr15NIL 0 1 1 1 1 1 0
Yr24 AvSYr24NIL 8 8 8 8 7 8 8
YrPI331260 PI 331260 0 0 1 1 1 1 1
YrPI331260 PI 660064 2 2 2 2 2 2 2
YrPI480016 PI 480016 1 1 0 1 1 1 1
YrPI480016 AvS/PI 480016 F7-12 2 2 2 2 2 2 2
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Discussion
Durum wheat lines PI 331260 and PI 480016 were collected from Shewa, Ethiopia in 1973
and deposited in the USDA Small Grains Collection in 1968 and 1983, respectively
(http://www.ars-grin.gov/cgi-bin/npgs/acc/display.pl?1374952 ;
http://www.ars-grin.gov/cgi-bin/npgs/acc/display.pl?1374952 ). The germplasm lines were
first evaluated by our program in 2005 and showed high resistance in all greenhouse and field
tests. So far, no races have been found to circumvent resistance in the two lines. The
resistance was characterized as all-stage resistance with a broad spectrum against all tested
races. In the present study, the genetic analysis showed that the resistance in both PI
331260 and PI 480016 are controlled by a dominant gene. Molecular markers mapped both
genes on chromosome 1BS but at different chromosomal regions, and therefore they are
different genes. The results of race tests and SSR marker positions showed that the genes
are different from previously named Yr genes mapped on 1BS, including Yr15 and Yr24/Yr26
(Chague et al. 1999; Peng et al. 2000; Ma et al. 2001; Li et al. 2006; Murphy et al. 2009).
Resistance genes YrPI331260 , YrPI480016 and Yr15 are resistant to all Pst races identified in the US so far and Yr24 is susceptible to PSTv-16, 23, 26, 27, 38, 40 and 41 (Wan and Chen, unpublished data). The donor of Yr15 is an Israeli wild emmer wheat ( T. dicoccoides )
(Peng et al. 2000). Yr24 was derived from T. turgidum subsp. durum accession K733
(McIntosh & Lagudah 2000). Yr26 originated from γ80-1 ( T. turgidum ), a γ-radiated mutant of a Chinese landrace (Ma et al. 2001). PI 331260 and PI 480016 are both landraces of
Shewa, Ethiopia (T. turgidum subsp. durum ). Based on the origins and seedling reactions to the PSTv races tested, it can be concluded that both YrPI331260 and YrPI480016 are different from Yr15 and Yr24/Yr26 .
The SSR markers identified in this study were linked to other resistance genes on
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chromosome 1BS. From linkage groups constructed from data for two separate crosses
(AvS/PI 480016 and AvS/PI 331260), YrPI331260 was estimated to be 3.5 cM proximal to
Yr15 and 2.6 cM proximal to Yr24 /Yr26 ; and YrPI480016 was estimated to be 7.4 cM proximal to Yr15 and 6.0 cM proximal to Yr24 /Yr26 . YrPI331260 and YrPI480016 were estimated to be 10.9 cM apart and they were on different bins of chromosome 1BS . The consensus order of these genes is: YrPI331260 – (3.5 cM) – Yr15 – (7.4 cM) –YrPI480016 –
(2.6 cM) –Yr24/Yr26 . Therefore, both YrPI331260 and YrPI480016 are different from these genes.
In addition to Yr15 and Yr24 /Yr26 , YrH52 and YrCH42 were also located on the chromosome arm 1BS by different workers (Peng et al. 2000; Li et al. 2006). The resistance gene YrH52 derived from Hermon 52 ( T. dicoccoides ), was linked to Xgwm413 and Xgwm273a (Xgwm273d ) with a map distance of 1.3 and 2.7 cM from either side, respectively (Peng et al. 2000). YrPI331260 was estimated to be 3.5 cM proximal to
Xgwm413 and 9.9 cM proximal to Xgwm273. YrPI480016 was linked to Xgwm413 and
Xgwm273 with a map distance of 7.4 and 2.1 cm, respectively. YrCH42 from Decoy 1, a T. turgidum accession (AABB), was bracketed by Xgwm18 and Xgwm498 with genetic distances of 3.2 and 1.6 cM, respectively (Li et al. 2006). YrPI480016 was linked to
Xgwm18 and Xgwm498 with a map distance of 1.8 and 9.9 cM, respectively. YrPI331260 was estimated to be 7.4 cM proximal to Xgwm18 and 8.6 cM proximal to Xgwm498.
Considering their origins and the distances of molecular markers, YrPI331260 and
YrPI480016 are both different from YrH52 and YrCH42 .
Because the fast evolution of the stripe rust pathogen, new races are detected every year
(Chen et al. 2010; Wan & Chen 2011), more resistance genes are needed for breeding programs. The race-specific, all-stage resistance that is conferred mostly by single dominant genes can provide high level resistance, but is easily overcome by new races of the
164
pathogen (Line & Qayoum 1992b; Chen 2005, 2007). Although both YrPI331260 and
YrPI480016 from durum wheat are resistant to all identified races in the US so far, further work is needed to determine the effectiveness of these genes to Pst races in other countries.
Since these genes have already been transferred to common wheat AvS background, they can be used in breeding program. It is better to use these genes in combination with other all-stage resistance genes such as Yr5 (Yan et al. 2003), Yr15 (Murphy et al. 2009), Yr45 (Li et al. 2006), Yr53 (Xu et al. 2012), all of which are effective against all tested US Pst races,
It is even more desirable to combine the effective all-stage resistance genes with genes for non-race specific HTAP resistance genes such as Yr18 , Yr29 , Yr36 , Yr39 , Yr52 and many other QTL (Chen 2007) as molecular markers are available for these genes or QTL.
Acknowledgements This research was supported by the US Department of Agriculture,
Agricultural Research Service (Project No. 5348-22000-014-00D), Washington Wheat
Commission (Project No. 13C-3061-3925), and Vogel Foundation (Project No.
13Z-3061-3824). PPNS No. ???, Department of Plant Pathology, College of Agricultural,
Human, and Natural Resource Sciences, Agricultural Research Center, Project Number
WNP00663, Washington State University, Pullman, WA 99164-6430, USA. We are grateful to Dr. A.M. Wan and Dr. M.N. Wang for their technical assistance. We also would like to thank Drs. S. Hulbert, T. Peever, and K. Gill for their critical review of the manuscript.
165
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