Mapping Resistance to Stem Rust, Stripe Rust, and Powdery Mildew, and Genotype Screening of Breeding Germplasm for Disease Resistance

ABSTRACT VANGESSEL, CARL JOSEPH. Disease Resistance in Winter Wheat: Mapping Resistance to Stem Rust, Stripe Rust, and Powdery Mildew, and Genotype Screening of Breeding Germplasm for Disease Resistance. (Under the direction of Dr. David Marshall). Wheat production worldwide faces many challenges including fungal pathogens which can reduce growth, nutrient content, and yield. As the global population continues to increase, it is important to maximize production of wheat which provides a significant proportion of the human diet. Wheat breeders and pathologists are addressing the pathogen threat to wheat by breeding cultivars with improved resistance. However, as pathogen populations mutate and overcome resistance, it is important to identify sources of resistance to new pathogen races and understand the genetics of resistance in commercial cultivars.

Stem rust (Puccinia graminis), stripe rust (Puccinia striiformis), and powdery mildew (Blumeria graminis) are among the most common and aggressive pathogens of wheat occurring worldwide. The stem rust resistance gene Sr31 was reliably effective until being overcome in 1999 by the race Ug99. This new race of stem rust has since evolved to include 12 related races and are potentially virulent to a majority of commercially produced wheat globally. The soft red winter wheat (SRWW) line, MD01W28-

08-11, was identified as having adult plant resistance (APR) to Ug99 in Njoro, Kenya. This line was crossed with the susceptible SRWW cultivar Coker 9553 and the subsequent 279 doubled haploid (DH) population used for linkage mapping analysis to better characterize the source of stem rust APR. A linkage map with 3,159 SNPs was produced that identified a significant quantitative trait loci (QTL) on the short arm of chromosome 6D and two QTL on the long arms of chromosomes 2B and 4B. The 6DS

QTL, QSr.nc-6D, was the most significant QTL in both environments using two scoring systems and which accounted for 7-13% of the phenotypic variation. This QTL lies on the proximal end of the chromosome where at least five other stem rust associated QTL have been identified. KASP assays were developed from this analysis which will help to better characterize resistance on 6DS as well as assess the level of established resistance to Ug99 races in the eastern United States. This mapping population was similarly assessed for stripe rust and powdery mildew resistance by linkage mapping analysis. This

identified one stripe rust resistance associated QTL on the long arm of chromosome 4B from Coker 9553 and two QTL associated with powdery mildew resistance on the long arms of chromosome 2B and 6B from Coker 9553 and MD01W28-08-11, respectively. Together, these stem rust, stripe rust, and powdery mildew loci will be targeted for use in marker assisted selection (MAS) in winter wheat breeding programs.

Another objective was to genotype winter wheat breeding germplasm for Ug99 effective Sr markers and other disease resistance relevant to the eastern U.S. The Ug99 stem rust race group has so far been detected only in eastern Africa and the Middle East. It is important for wheat producing countries including the United States to assess the level of established resistance in germplasm to Ug99 races in preparation of the potential arrival of the pathogen. Of the 65 numerically designated stem rust resistance genes, 27 have some resistance to Ug99 or its race group however many are undesirable due to associated reductions in yield. It is important to have sources of stem rust resistance available for wheat breeders in the U.S. In order to determine germplasm sources of resistance, 141 winter wheat experimental lines ranging from F4 to F7 were genotyped for ten Ug99 race group effective markers. These lines were also genotyped for barley yellow dwarf virus, leaf rust, fusarium head blight, and stagonospora nodorum blotch toxin resistance which are economically important pathogens in the eastern U.S. These lines will provide a source of stem rust and other disease resistance for breeders in the eastern U.S.

Disease Resistance in Winter Wheat: Mapping Resistance to Stem Rust, Stripe Rust, and Powdery Mildew, and Genotype Screening of Breeding Germplasm for Disease Resistance

by Carl Joseph VanGessel

A thesis submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Master of Science

Plant Pathology

Raleigh, North Carolina 2018

APPROVED BY:

______David Marshall Christina Cowger Committee Chair

______Gina Brown-Guedira Paul Murphy

DEDICATION In dedication and gratitude to my Mom and Dad, and to Frank, Claudia, and Gladis whose support has made this journey possible.

BIOGRAPHY Carl was born in 1994 and grew up on the Eastern Shore. He spent childhood running around

Trees & Ponds with his siblings, playing sports, and reading every book he could and most of them twice.

His parents brought him around the field trials and research stations so much that something eventually stuck. They fostered a deep appreciation of science, biology, and ultimately agriculture. After graduating from Delmar High School, Carl attended The Catholic University of America where he made great friends while working towards a Bachelor of Science in Biology.

After undergraduate studies, he joined Dr. David Marshall and the USDA-ARS small grains breeding program in 2016 to study plant pathology and plant breeding for a Master of Science at North

Carolina State University.

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ACKNOWLEDGEMENTS

I’d like to thank Dave, for introducing me to the world of wheat and small grains pathology. I was

naïve to breeding at first but I couldn’t ask for a smarter or more experienced mentor and advisor. Thank

you also to Gina, you have always been helpful and patient while I began to grasp the complexities of

wheat genetics. You both have been extremely supportive and my desire to further study wheat genetics and breeding is in large part thanks to you.

Thank you also to all the wonderful people who I have met and worked with at North Carolina

State University and the USDA-ARS. Thank you to Christina Cowger and Paul Murphy who have made sure I stayed on track. A special thanks to Lynda Whitcher, it has been a joy to learn from and work with you, from the bench to the single head thresher. Thank you as well to Al-Sayed Mashaheet, Jared Smith,

Kim Howell, Myron Fountain, Charlie Glover, Bill Brown, Emily Myers, Gabe Supino, and all the NCSU students I have worked alongside at MidPines.

My biggest thanks are to my family. Mom and Dad, I had no idea what great teachers I had guiding me until I wasn’t around to pester you with more questions every day and appreciate the patient replies. You have shown me what it means to excel at what you do. To my siblings Frank, Claudia,

Gladis, and my parents,

Thank You.

TABLE OF CONTENTS

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

Literature Review ...... 1 Origin and Production of Wheat ...... 2 Regions and Market Types ...... 3 Puccinia graminis f.sp. tritici, Stem Rust of Wheat ...... 4 Conditions and Epidemic Potential ...... 5 Control ...... 6 Major and Minor Resistance ...... 7 Historical Sources of Resistance ...... 8 Ug99...... 9 Resistant Germplasm Development ...... 10 Genetic Improvement...... 11 Linkage Mapping ...... 14 Literature Cited ...... 17

Determining the Genetic Basis of Ug99 Stem Rust, Stripe Rust, and Powdery Mildew Resistance in a Double Haploid Soft Red Winter Wheat Population ...... 21 Introduction ...... 22 Material and Methods ...... 24 Plant Materials ...... 24 Stem Rust Assessment ...... 25 Stripe Rust Assessment ...... 26 Powdery Mildew Assessment ...... 27 QTL Map construction ...... 27 Results ...... 28 Phenotypic analysis ...... 28 Linkage map ...... 29 Stem Rust QTL ...... 30 Stripe Rust QTL ...... 30 Powdery Mildew QTL ...... 31 Discussion ...... 31 Stem Rust ...... 33 QSr.nc-6D ...... 33 Stripe Rust...... 35 Powdery Mildew ...... 37 Conclusion ...... 38 Literature Cited ...... 39

Ug99 and Multi-Disease Resistance Genotyping of Winter Wheat Breeding Germplasm ...... 42 Introduction ...... 43 Material and Methods ...... 45 Germplasm Panel ...... 45 Marker Analysis ...... 46 Results and Discussion ...... 48 Selected genotyping groups ...... 48 Discussion by gene ...... 51 Combined resistance ...... 57 Literature Cited ...... 58

LIST OF TABLES

CHAPTER II: Determining the Genetic Basis of Ug99 Stem Rust, Stripe Rust, and Powdery Mildew Resistance in a Double Haploid Soft Red Winter Wheat Population. Table 1: Sequence information of powdery mildew, stripe rust, and stem rust associated KASP markers; bolded markers were incorporated in Coker9553/MD01W28-08-11 linkage map, 6D markers were excluded; a positions determined by IWGSC_refseqv1.0; b resistant allele ...... 63 Table 2: Summary of Coker9553/MD01W28-08-11 genetic map including GBS and KASP markers .. . 64 Table 3: Position and effect of QTL for stem rust, stripe rust, and powdery mildew resistance based on interval mapping analysis of double haploid Coker9553/MD01W28-08-11 population; * P<0.05, ** P<0.01, *** P<0.001, *** P<0.0001; a Scoring method used for linkage mapping analysis summarized in material and methods; infection type (0- 9); composite (converted IT * severity); and ordinal (0-9) system; b Marker interval based on 1.0-step LOD score; c Percent of phenotypic variation associated with the QTL; d Positive or negative values indicate the allele was inherited from MD01W28- 08-11 and Coker9553, respectively; ePhysical position (bp) on chromosome of most significant marker on IWGSC_refseqv1.0 map...... 65 CHAPTER III: Ug99 and Multi-Disease Resistance Genotyping of Winter Wheat Breeding Germplasm. Table 4: Line designations and pedigree of genotyped selections ...... 66 Table 5: Primer sequences for KASP assays used in germplasm screening and associated controls ...... 71 Table 6: Primer sequences for gel, ABI, and CAPS based markers used in germplasm screening…...... 72 Supplementary Table 3.1: Germplasm source and genotyped markers ...... 73

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LIST OF FIGURES

CHAPTER II: Determining the Genetic Basis of Ug99 Stem Rust, Stripe Rust, and Powdery Mildew Resistance in a Double Haploid Soft Red Winter Wheat Population. Figure 1: Distribution of stem rust infection type ratings, severity ratings, and composite scores on the double haploid Coker9553/MD01W28-08-11 population in 2015 (blue) and 2016 (orange) in Njoro, Kenya. A) Infection type ratings varying from MR-S (moderately resistant - susceptible) B) Severity ratings (5 indicating 5% affected leaf area, 90 indicating 90% complete susceptibility) C) Composite score calculated by converted (0.1, 0.5, 0.9) infection type * severity; Arrows indicate parent phenotype as averaged in each year; MD, MD01W28-08-11; CK, Coker 9553 ...... 75 Figure 2: Distribution of stripe rust infection type ratings, severity ratings, and composite scores on the double haploid Coker9553/MD01W28-08-11 population in Njoro, 2015 and 2016 and Laurel Springs, 2015. A) Infection type ratings for Njoro, 2015 varying from R-S (resistant - susceptible) B) Composite scores for Njoro, 2016 calculated by converted (0.1, 0.5, 0.9) infection type * severity C) Ordinal scores for Laurel Springs, 2015 (0-9); Arrows indicate parent averaged phenotype within environment; MD, MD01W28-08-11; CK, Coker9553 ...... 76 Figure 3: Distribution of powdery mildew ratings on the double haploid Coker9553/MD01W28- 08-11 population in Raleigh, 2014 and Raleigh, 2016. Ordinal score ratings (0-9) for A) 2014 Raleigh and B) 2016 Raleigh; Arrows indicate parent averaged phenotype within environment; MD, MD01W28-08-11; CK, Coker 9553 ...... 77 Figure 4: Genetic map of QTL linked with stem rust, stripe rust, and powdery mildew on chromosomes 2BS, 2BL, 4B, 6B, and 6D of the double haploid Coker9553/MD01W28-08-11 population; black vertical bars indicate 1.0-step LOD interval of significant QTL; GBS marker name right of chromosome with co-located markers excluded; genetic position (cM) left of chromosome...... 78 Figure 5: Quantitative trait loci (QTL) for adult plant resistance to stem rust identified on chromosome 6DS in Coker9553/MD01W28-08-11 in Njoro 2015 and 2016; Composite and infection type (IT) rating scales used in linkage analysis are shown for each year...... 79

CHAPTER III: Ug99 and Multi-Disease Resistance Genotyping of Winter Wheat Breeding Germplasm. Figure 6: PCR amplification of csSr32#1 marker for Sr32; Lane 1 and 4, amplification at 184bp; Lane A, 100bp ladder...... 80 Figure 7: PCR amplified DNA fragment peaks for codominant markers cfd49Fd (top) and gpw5182 (bottom) for detection of Sr42; cfd149F heterozygous; gpw5182 homozygous resistant; size standard above peaks ...... 81 Figure 8: PCR amplified DNA fragment peaks for codominant markers cfd270 (top and middle) and wmc170 (bottom) for detection of Sr54; Top, susceptible 214bp fragment; middle, resistant 216bp fragment; bottom, resistant 210bp fragment; size standard above peaks ...... 82

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Figure 9: PCR amplification of CAPS marker Lr57/Yr40-MAS-CAPS16F; lane 1, resistant amplification of 450bp band; lane A, 100bp DNA ladder ...... 83 Figure 10: PCR amplified DNA fragment peaks for marker BYDV2; top, susceptible fragment 185bp peak; bottom, resistant fragment 200bp peak; size standard above peaks ...... 84 Supplementary Figure 2.1: GBS markers identified on chromosome 4B are plotted by their physical position relative to the IWGSC RefSeq v.1.0 reference map and the genetic map location; markers identified as QYr.nc-4B are indicated by brackets ...... 85 Supplementary Figure 2.2: GBS identified markers of CM population plotted by their genetic position (cM, Y axis) and physical potion relative to IWGSC RefSeq v.1.0 reference map (bp, X axis); rows grouped by chromosome group, columns grouped by genome; ie top-left panel shows chromosome 1A ...... 86

-CHAPTER I- Literature Review

Origin and Production of Wheat Common wheat (Triticum aestivum) is an allohexaploid species in the grass family (Poaceae) that is believed to have evolved approximately 8,000 years ago (Huang et al. 2002). Wheat and its’ progenitor species were among the first crops to be domesticated, arising in the Middle East and the Fertile Crescent.

The three progenitor species of T. aestivum share a common ancestor but diverged between 2.5 to 4.5 million years ago (Huang et al. 2002). T. aestivum has 21 pairs of chromosomes (2n=6x=42, AABBDD) organized into A, B, and D genomes. Two separate hybridization events led to the wild form of modern bread wheat. The wild diploid species Triticum uratu (2n=2x=14, AA) hybridized with the wild diploid species of goatgrass Aegilops speltoides (2n=2x=14, SS) to form the tetraploid wild emmer wheat species,

Triticum turgidum L. subsp. Dicoccoides(2n=4x=28, AABB) (Faris et al. 2014). Emmer wheat was cultivated about 10,000 years ago accompanied by the loss of the shattering trait and possible gain of the free-threshing trait that allowed the first farmers harvest more grain from wild stands (Tzarfati et al. 2013;

Dvorak et al. 2012). The second hybridization event likely occurred between this cultivated emmer wheat

(AABB) and a third wild diploid species Aegilops tauschii Coss.(2n=2x=14, DD) leading to the first wild hexaploid wheat species (Kihara 1944; McFadden and Sears 1946). The first farmers during this period of the agricultural revolution likely grew or harvested these landraces in mixed stands unintentionally allowing the naturally self-pollinating progenitor species to occasionally outcross due to close proximity.

There is debate to the geographical origin of hexaploid wheat within the Middle East and Eurasia.

Vavilov postulated the center of origin for wheat to be span from Afghanistan to Transcaucasia. Recent molecular and phylogenetic studies have brought this into question since each progenitor species having disparate possible centers of origin. Tetraploid emmer and likely early hexaploid wheat is currently believed to have been domesticated in the southeastern region of Turkey, further west of the Caucuses than proposed by Vavilov (Dvorak et al. 2011; Dvorak et al. 2012). Regardless of ancestral origin of T. aestivum, common bread wheat has been adapted to grow in many environments on every continent except Antarctica. The global area of harvested wheat peaked in early 1980’s just shy of 240 million

hectares and has stabilized around 220 million hectares since 2010 (http://www.fao.org/faostat, 2018).

Despite the slight decline in acreage, wheat production rose from 450 million tonnes to over 700 million

tonnes over the last three decades with improved cultivars and breeding practices. The United States is

currently the 4th largest producer of wheat coming behind China, India, and Russia. The United States

produced 62.8 million tonnes of wheat on approximately 18 million hectares in 2016 (fao.org, 2018).

Regions and Market Types The six major classifications for wheat in the U.S. are hard red winter, hard red spring, soft red winter, hard white, soft white, and durum. The first five of these are hexaploid T. aestivum which are categorized by grain hardness, grain color, and growth habit. Durum wheat is a cultivated form of T. turgidum L. var. durum. Winter, spring, and durum wheats make up approximately 75%, 20%, and 5% of wheat production respectively in the United States over the last 10 years (USDA ERS 2018). The Plains states produce mainly hard wheats (red and white), while the eastern third of the U.S. produces mainly soft wheats (red and white). The Pacific Northwest produces a variety of hard red and white, spring and winter wheats, and durums (all spring) which are limited to the Dakotas, Montana, and parts of California and Arizona (McFall and Fowler 2009). North Carolina produces principally soft red winter wheat. From

2012-16, North Carolina produced an average 1,005,750 tonnes of wheat per year (USDA 2018). Wheat is typically grown in 81 out of 100 counties in NC, with the larger acreages in eastern and central parts.

(USDA 2018).

Kernel hardness and grain color as well as flour strength determine hard, soft, red, and white classifications of wheat. These dictate a wheat variety’s end use target and market class. There are a number of micro and macro tests developed to evaluate these milling and baking qualities. Hard wheats are generally used for bread production while soft wheats are used for cookies and cakes. Durum wheats are used for pastas. The D genome has been shown to strongly influence baking qualities of common hexaploid wheats (Fehr and Justin 1988).

The most important classification of common and durum wheat is growth habit. This is

determined largely by vernalization (Vrn) and photoperiod (Ppd) genes. These dictate the cold

temperature and light exposure, respectively, required by the plant for optimal growth and grain yield.

Winter and spring wheats differ in their vernalization requirements. Winter wheats can range widely but generally perform best with a vernalization period of temperatures between 3°C and 6°C for 30 to 60 days

(Porter and Gawith 1999). Therefore, winter climates dictate whether a geographical area is suitable for winter or spring wheats. Within each of these classifications, Ppd, and earliness-per-se (Eps) genes to a smaller extent, determine the flowering date, grain filling period, and ultimately harvest dates. Cultivars that flower too early may expose pollen, anthers, and ovaries, as well as developing seed to sub-freezing temperatures thereby reducing or eliminating seed production. Alternatively, later flowering cultivars may expose the plant to temperatures too high for optimum seed development. Wheat breeders will select mainly for Ppd genes to fit the climate and latitude that a cultivar is being targeted for. Wheat farmers in

North Carolina typically plant winter wheat between mid-October and mid-November, although about a month earlier or later than the optimum can occur.

Puccinia graminis f.sp. tritici, Stem Rust of Wheat Stem rust of wheat is caused by Puccinia graminis f.sp. tritici (Pgt) and is also known as black rust or summer rust. The pathogen is easily identified by it’s dark-red rust colored pustules which erupt from the stems or leaves of wheat plants. The disease has references in Biblical and Roman texts dating back thousands of years, and spore structures were found in Isreal which dated to ca. 1300 BC (Kislev

1982). Stem rust is a polycyclic heteroecious biotrophic basidiomycete. The fungus has a famously complex life cycle involving two hosts and multiple spore stages. The P. graminis life cycle begins with succesful infection of the susceptible wheat plant. Asexual uredeospores (n+n) are produced 7 to 14 days after infection (Roelfs 1985). Large numbers of uredospores are produced from a single uredia and can sporulate for up to 30 days. Uredospores are principally wind dispersed. Most fall to the ground or onto the same or adjacent plants, however some can travel over thousands of miles and between continents

(Roelfs 1972; Grown and Hovmoller 2002). These only infect wheat hosts and can quickly cause

4 epidemics where susceptible wheat varieties are grown. Environmental cues signal the pathogen to alternate from uredospore production to teliospore production. Thick cell-walled teliospores (2n) can withstand harsher environmental conditions and germinate on wheat stalks or straw to produce basidiospores (n) which are wind dispersed and infect the alternate host, Barberis spp. The most common species in the United States is Barberis vulgaris and it is at this point on the alternate host when basidospores germinate and begin the sexual phase of the rust’s life cycle. Pycniospores (n) are formed and have + and – mating types that fuse with receptive hyphae of another pycniospore which acts as the complementary gamete. This can happen at the location of production or be carried by insect vectors until contact with compatible pycniospores occur. Following the sexual recombination which occurs, pycniospores migrate through the leaf tissue to the lower surface and produce aecium and aecial horns.

Aeciospores (n+n) are released from aecial horns and similar to previous stages of the rust life cycle, large number of spores are produced and can be wind-dispersed over long distances. These dikaryotic spores germinate and infect wheat or other grass hosts optimally under free-water conditions such as dew

(Roelfs 1985). Infections lead to hyphal mats forming below the epidermis and eventual pustule emergence. This occurs mostly on the tillers or leaf sheaths of wheat. This completes the sexual life cycle.

Conditions and Epidemic Potential Stem rusts’ abundant production of spores, polycyclic asexual life cycle, and long distance wind dispersal make the likelihood of epidemics high where susceptile hosts are grown in monoculture. Stem rust grows optimally in 25°C to 30°C daytime and 15°C to 20°C night temperatures. Moisture, typically in the form of repeated and prolonged dew, is required for uredospore infection. Stem rust epidemics have been more common on spring wheat, tropically-grown wheat, or late-maturing winter wheat where conducive conditions for repeated infection are more common. Local epidemics have occurred in every country where wheat is grown, and large scale or continental epidemics have occurred in North America and Australia such as in 1935, 1937, 1953, and 1954 (Roelfs 1978; Park 2007).

The prolific ability of P. graminis to evolve and produce variation has been the Achilles heel of

wheat breeders and farmers. Stem rust mutates in its asexual life cycle at low frequencies but the

enormous amount of uredospores produced makes this a significant source of virulence development. The

majority of mutations which occur during mitosis are detrimental to the fungal fitness and are eliminated

from the population. Without the alternative host in places such as North America, this is the predominant

mode of pathogen evolution. Stem rust populations appear to be losing their ability to produce teliospores

and their viability is decreasing in these populations as it no longer benefits populations in the United

States (Roelfs 1982). Meiosis in the sexual life cycle is a much more significant source of population

variation in stem rust of wheat. Recombination between various races produces new genetic architecture

and combinations of virulence (Avr) genes. Historically, both sources of variation have been a major

problem for pathologists and breeders as they attempt to understand the pathogen and predict which races

will be significant each growing season. An international system of nomenclature was established in 1988

in order to categorize races of stem rust (Roelfs and Martens 1988). This standardized a three letter Pgt-

race-specific code based on a serious of stem rust resistance genes (Sr genes) contained in a set of differential hosts. Sr genes correspond to Avr genes in the pathogen according to the gene-for-gene model

(Flor 1971). As new races have emerged in the decades since 1988, the stem rust nomenclature has

expanded to a five-letter code that refers to five sets of four gene differential wheat lines (Jin et al. 2009).

Control There are limited options for control for P. graminis f.sp. tritici. Barberry removal and eradication, fungicide application, breeding for resistance are the most commonly practiced methods.

Removal of the alternative host Barberis has produced significant results in countries where it has been implemented such as the United States. The main effects include delayed disease onset, reduction in inoculum, fewer stem rust races, and stabilization of the pathogen population (Roelfs 1982). A large-scale barberry removal program was instituted by the U.S. Department of Agriculture (USDA) in 1918 to reduce the sexual host. By 1933, 18 million bushes were removed from public and private lands across the United States (Leonard 2001). Today, 17 states across the U.S. from Washington to Pennsylvania

continue to participate in the barberry quarantine (Leonard 2001). The number of epidemics occurring in

these states decreased from about five per year throughout the 1920’s to less than one per year in the

1990’s (Leonard 2001). The removal of barberry limits stem rusts’ ability to overwinter in northern

latitudes and the pathogen’s mode of dissemination is from south to north from warmer-winter climates in

Texas, other Gulf States, and Mexico. The application of fungicides and chemical control have been

investigated and shown moderate success but is restricted by the feasibility of large-scale implementation.

Though a number of fungicides have been shown to be successful, wide-spread control of the disease is

difficult once epidemics begin so application timing is critical. The large area over which wheat is grown

makes complete coverage economically difficult for many farmers and is rarely used in developing

countries. This has left breeding for resistance to be the main method of disease control.

Major and Minor Resistance As the genetic basis of cultivar improvement became better understood, breeders have been able to target disease resistance in their programs more effectively while identifying new sources of resistance genes. The two types of resistance are major and minor resistance genes, also known as qualitative or quantitative respectively. Rust pathologists and breeders have historically focused research on major resistance genes. Major resistance genes in wheat provide seedling resistance characterized by reduced stem rust infection throughout the plants’ life cycle. The “qualitative” moniker comes from the discrete resistant or susceptible wheat phenotypes and fit the classical gene-for-gene model (Flor 1971). While some major genes provide broad resistance to all races of stem rust, most correspond to an Avr gene of certain races and thus ineffective if this Avr gene mutates or is absent so that it is no longer recognized by the host defenses. This leads to “boom and bust” use of major stem rust resistance genes or alleles as their effectiveness is overcome by new stem rust races (Sun and Yang 1999). Minor resistance genes are a less scrutinized source of plant-pathogen defense but their significance is gaining attention as wheat breeders look to expand their arsenal. Quantitative resistance genes provide adult plant resistance (APR) to wheat cultivars that reduce the severity of stem rust infection on mature plants. They may retard the progression

of rust infection, reduce the size or sporulation of pustules, or otherwise lessen the severity of stem rust

infections. These genes act in an additive manner and their phenotypes are continuous rather than

discrete. APR effects may be masked by major resistance genes also present in a cultivar, resulting in

APR genes more difficult to detect and maintain (Ellis et al. 2014). A distinguishing feature of APR genes

is their longevity in effectiveness. These genes do not directly correspond to an Avr gene in the pathogen

as a major gene might and are less susceptible to break down by pathogen mutation and variation. The

durable but partial resistance APR provides make them extremely valuable when combined with major

resistance genes by boosting resistance of a cultivar to a particular race and extending the effective life

span of the major gene.

Historical Sources of Resistance Genetic improvement of common wheat for resistance to P. graminis f.sp. tritici was slow up until the early part of the 20th century. As breeders began to understand the potential for resistance from exotic germplasm and more distantly related species, an effort was put on introducing disease resistance genes to adapted varieties of wheat. As of 2015, there were 73 stem rust resistance genes or alleles identified and deployed (Singh et al. 2015). The most readily available sources of resistance were from T. aestivum germplasm that could easily hybridize with locally adapted varieties. These are members of the same gene pool that have allelic variation for resistance genes (Harlan and de Wet 1971). Nearly half of the named Sr genes originated from T. aestivum. The next largest sources of resistance have been from T. monococcum and the progenitor species T. turgidum and A. tauschii (Singh et al. 2015). The large number of genes utilized from T. monococcum led to the long held belief that this diploid grass was the A genome progenitor until it was shown that the current T. aestivum A genome has more genetic commonality with

T. urartu and that the two diploids are not inter-fertile (Huang et al. 2002). The remaining Sr genes have been introgressed by interspecific hybridization from Triticum spp., Aegilops spp., Thinopyrum elongatum, Dasypyrum villosum, and Secale cereale (Singh et al. 2015).

Because of the high evolutionary potential of stem rust, Sr genes can vary in their life span. One example

is Sr21, a stem rust resistance gene on the long arm of chromosome 2A which originated from T.

monococcum. North and South American populations of P. graminis have largely overcome the gene but

Sr21 remains effective in Australian populations (McIntosh et al. 1995; Singh et al. 2015). This highlights

the complex population structure of Pgt and differences in distribution of pathotypes. Sr2 is an APR gene

on the short arm of chromosome 3B from T. turgidum that has maintained its slow rusting phenotype

overtime (McIntosh et al. 1995; Juliana et al. 2015). An example of a durable major resistance gene is

Sr31. Sr31 is located on the 1BL.1RS translocation from Secale cereale (rye) which is present on

chromosome 1B in varieties containing the translocation. German breeders in the 1930’s were the first to

introduce the rye chromosome segment into wheat lines (Zeller 1973). Sr31 provided good levels of

resistance to Pgt populations worldwide for more than three decades and persists in many areas of the

world today. North America has only experienced small local epidemics of stem rust since 1954,

attributed in large part to the deployment of resistant gene combinations and Sr31(Singh et al. 2015). The

deployment of early-maturing cultivars in the Great Plains after the 1950s, also contributed to the

reduction in stem rust epidemics in North America (Marshall 1989). That resistance has not been

universal however as an Ugandan race of stem rust overcame Sr31 in 1999 (Pretorius et al. 2000).

Ug99 The Ugandan race of stem rust was first identified in 1999 when wheat cultivars known to carry

Sr31 on the rye translocation 1BL.1RS appeared to have high levels of stem rust infection previously unseen (Pretorius et al. 2000). After replicated tests on differential lines confirmed that the new stem rust race was virulent to the long-used gene, it was designated Pgt-Ug99 or Ug99. This signaled to the international wheat breeding and pathology community that the major threat of stem rust had re-emerged.

In the nearly two decades since its emergence, a large effort has been underway to reduce the spread of

Ug99, screen existing cultivars for resistance, develop new genic combinations in breeding germplasm, and characterize the pathogen. The new race was the impetus for including a fifth letter to the race nomenclature of Roelfs and Martens so that its virulence profile could be accurately described. The

original race is TTKSK, with the last letter signaling that only Sr24 is effective out of the 5th set of

differential lines. The first variant of TTKSK was TTKST which developed virulence to Sr24 and thus all

monogenic resistance in the 5 set of differentials (Jin et al. 2008). As of February 2016, there are 13

variants comprising the Ug99 race-group identified across 13 countries along East Africa and the Middle

East (Fetch et al. 2016). These 13 races are; TTKSK, TTKSF, TTKST, TTTSK, TTKSP, PTKSK,

PTKST, TTKSF+, TTKTT, TTKTK, TTHSK, PTKTK, and TTHST. Countries in which one of these races has been identified are South Africa, Mozambique, Zimbabwe, Tanzania, Uganda, Kenya, Ethiopia,

Sudan, Eritrea, Rwanda, Egypt, Yemen, and Iran, although all the races do not occur in each country.

Most of these Ug99 variants emerged in response to release of wheat cultivars that contained single gene resistance and only lasted a short time before the particular gene lost effectiveness. As the race nomenclature implies, there are race-specific resistance genes that exist but broad-spectrum resistance remains elusive. Wheat cultivars such as ‘Robin’, and ‘Digalu’ have been released in Eastern Africa but none have held resistance to the entire race-group across all field locations (Singh et al. 2015; Worku et al. 2016).

It is unclear whether the original Ug99 race evolved by asexual mutation or sexual recombination. Stem rust is virulent to Berberis holstii, an alternative host that is present in eastern

Africa. The temperate climate of this highland region near the equator also means that the pathogen is present year round with a continuous growing season for wheat and could have mutated asexually (Ravi

P. Singh et al. 2015). Accordingly, other members of the Ug99 race-group could have also emerged from sexual recombination or asexual mutation.

Resistant Germplasm Development In 2000, up to 90% of wheat varieties grown around the world were susceptible to the Ug99 race groups (Singh et al. 2011, 2015) and there is a high potential for it to spread by long-distance spore dispersal or human travel. While it is important to develop cultivars for immediate release in countries under imminent threat of Ug99 epidemics, it is equally critical to develop durable resistance with novel

sources of resistance and stacked genic combinations utilizing APR genes. Screening facilities were set

up in Njoro, Kenya and Debre Zeit, Ethiopia in order to evaluate the vulnerability of the world’s wheat

and barley germplasm to Ug99 without introducing the pathogen to new regions. These are operated by

the Kenya Agricultural & Livestock Research Organization (KALRO) and the Ethiopian Institute of

Agricultural Research (EIAR) in conjunction with the Borlaug Global Rust Initiative (BGRI) and the

Durable Rust Resistance in Wheat project (DRRW). Wheat germplasm, including varieties, elite

experimentals, breeding lines, and populations from as many as 32 countries have been evaluated in a

single year (Singh et al. 2015). There has been an increase in the percent of entered lines screened that

show resistance or moderate resistance, from less than 20% in 2006 to approximately 40% in 2014, at the

main phenotyping site in Njoro, Kenya(Singh et al. 2015). The USDA-ARS has coordinated and

evaluated approximately 72,000 wheat and barley (winter and spring) lines between 2006-17 in East

Africa. Combining the field data from East Africa, with seedling screening data and molecular marker

genotyping, the USDA-ARS has distributed stem rust resistant germplasm to breeders in the U.S. and

across the world. The introduction of new stem rust resistance genes has been expedited in recent years

with advancements in molecular marker systems and has helped to identify Ug99 effective Sr genes and

gene combinations in elite, adapted germplasm.

Genetic Improvement The genetic advancement of wheat has increasingly relied on molecular analysis to identify genes underlying superior traits. Before such marker assisted selection (MAS) began use in the late 20th century, genetic improvement relied upon extensive phenotyping of large amounts of breeding material. A large

number of crosses were made between cultivars that had historically performed well, casting a large net

for progeny potentially superior but more often equal to or below the performance of the parents. While

extensive phenotyping and large number of crosses are still made in wheat breeding programs, the

number of lines that are advanced to successive generations can be quickly reduced using MAS. This has

been extremely beneficial for resource allocation in wheat breeding programs.

A marker can be any trait-, morphological-, protein-, or molecular-based, that indicates the presence of a gene. The reliability of a marker lies in its linkage disequilibrium (LD), or the likelihood of the marker being inherited with the gene of interest. A marker with high LD to a trait indicates that it can accurately predict the presence of the underlying gene. Linkage is most often physical with the marker residing on the same chromosome, region, or within the gene itself. This is not always the case however and the marker may reside on a different chromosome and still be inherited together with the gene. Before the gene Sr2 was known to reside on chromosme 3BS (Juliana et al. 2015), it could be selected for by the psuedo-black chaff (PBC) trait that accompanied its presence. This APR gene was located nearby on the short arm of 3B to a gene that caused the glumes and nodes of wheat to develop dark pigmentation. A breeder in the field could tell that varieties with the PBC phenotype likely posessed Sr2. Similar morphological markers such as the red-glume gene (Rg1) and leaf tip necrosis (Ltn) have allow for the

selection of Yr10 and Lr34 respectively (Metzger and Silbaugh 1970; Singh 1992; Singh 1992). Enzyme

based markers are a similar category in that they are identified by gene products. These markers utilize

basic laboratory procedures such as gel electrophoresis to identify proteins indicative of a trait. In wheat,

the glutenin genes Glu-A1, -B1, -D1 and Glu-A3, -B3, -D3 have high and low molecular weight,

respectively, that allow them to be distinguished on polyacrylamide agarose gels (Gupta and Shepherd

1990; Jackson et al. 1983).

Molecular markers are the newest category with more accuracy and application since they are

based on variability and polymorphism of DNA. These can be further broken down into hybridization-,

polymerase chain reaction-, and sequencing-based molecular markers. Hybridization-based markers like restriction fragment length polymorphisms (RFLPs) rely on complementarity of the sequence in the marker and restriction enzymes or other oligonucleotide probes. These produce mixed results with high labor input and their application depends on the organism being researched. Polymerase chain reaction

(PCR) based markers include random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), microsatellite-anchored fragment length polymorphisms (MFLP) and simple

sequence repeat (SSR) markers. These build upon hybridization by amplifying parts of the genome that

have complementary sequences to primers. Sequencing based markers utilize PCR but are sequence

specific, founded on the genetic variation at a single base-pair or indel. Single-nucleotide polymorphisms

(SNPs) are the marker of choice in this category and their use has increased with advancements in

genome sequencing.

SNPs are the most fundamental form of variation on an organisms genome, cover the entire length of the genome, and occur in both exons and introns around every 100-300bp (Xu 2010; Edwards et al. 2005; Jiang 2016). SNP based markers are co-dominant which allows heterozygotes to be distinguished from homozygous individuals. Once developed, SNP markers are inexpensive to use and screen high number of individuals (high-throughput).

The first step in SNP discovery is sequencing of some or all of a genome. The first method developed was the Sanger method in 1977 which was used to sequence a bacteriophage genome, the first complete genome (Sanger et al. 1977; Sanger et al. 1978). Next-generation-sequencing (NGS) platforms such as Illumina Sequencing (Illumina, San Diego, CA) and Pacific Biosciences SMRT Sequencing

(Pacific Biosciences, Menlo Park, CA) are currently used and provide higher quality sequence reads and higher throughput. The fragmented sequences that are produced by both methods are aligned to develop an ordered genome using bioinformatics and computational analysis. With individuals having been genotyped, SNP discovery can be accomplished with or without a reference genome. Where a reference genome can not be used, multiple entries of the same species are aligned and compared to determine major and minor alleles or SNPs. The first plant genome to be sequenced and used as a reference was

Arabidopsis thaliana (Jander 2002). The first sequence of T. aestivum was published in 2014

(International Wheat Genome Sequencing Consortium (IWGSC) 2014). A more complete genome was developed in 2017 which incorporated short Illumina reads, longer Pacific Bioscience reads, and the recently published A. tauschii genome (Zimin et al. 2017). The most recent 15 billion bp sequence itself has not been published yet but is available for use by request for some researchers. Wheat lines being

investigated for SNPs are compared to this reference geneome and base pair discrepencies are flagged.

After SNP discovery, SNP genotyping or characterizing part of the genome associated with a trait is next.

Sequencing an entire genome may be too costly and unnecessary for many research goals but

SNP genotyping can be sufficient for an individual, population, or diverse set of lines. Genotyping means determining the genetic composition, whether at a basepair or SNP, gene, or chromosome level. SNP genotyping can be applied to marker-assisted selection, QTL mapping, or association studies which are vital tools for modern breeders. Genotyping-by-sequencing (GBS) is a powerful method for wheat breeding studies as it allows marker discovery and genotyping simultaneously. The genome of each entry is digested by a restriction enzyme and fragments are ligated to barcode (for identification) and common adaptors. These are PCR amplified and sequenced such as with Illumina sequencing. The choice of restriction enzyme is tailored to the species and two may be used to reduce the complexity of genomes such as wheat (Poland et al. 2012). The two-enzyme GBS method is often used for highthrouput genotyping of wheat lines and construction of genetic maps.

Linkage Mapping Recent advancements in marker technology and SNP discovery has allowed comprehensive analysis of the wheat genome to identify quantitative trait loci (QTL). QTLs of various molecular marker types such SNPs from GBS are aggregated and assigned genomic positions by chromosome and basepair to create linkage maps. A linkage map allows for a statistical analysis of a genome with pairwise marker recombination (LD) to identify polymorphisms. Those that correlate to a trait of interest in the individuals that have been phenotyped are termed QTLs. The two main ways to discover QTL are linkage mapping and association mapping. Linkage mapping or QTL mapping utilize a known relationship between the individuals being studied such as biparental populations. Generally, these are from two individuals known to have differences in the trait being targeted. The amount of LD that is used to locate QTLs in linkage mapping is limited to that which occurs after the initial parental cross (Myles et al. 2009). This higher LD along with reduced genome coverage in linkage mapping studies can mean that determining exact

14 position of the gene of interest is difficult to distinguish from the marker position. Genetic positions may be limited to a chromosome arm or genomic regions rather than the functional polymorphism of the causal gene (Singh et al. 2015). A genome wide association study (GWAS) is performed on a much more diverse set of material, such as regional nursery material, that has varying degrees of inter-relatedness. LD breaks down over time as more recombination events occur and is lower in diverse panels of GWAS than in linkage mapping populations, giving them higher accuracy and power to detect QTLs. These are also more representative of the species as a whole because a larger sub-population is included rather than that of biparental populations. Each method of QTL discovery has benefits over the other. Linkage mapping studies require population development which can be time intensive, but phenotyping is typically easier to accomplish if trait of intrest is easily phenotyped or highly heritable. GWAS provides higher resolution and the ability to utilize developed germplasm previously phenotyped but requires precise knowledge of relatedness and selection history of the entries. Rare alleles at low frequency in GWAS may limit their detection whereas QTL mapping disregards any alleles not contributed by the parents. These differences between methods make them compatible and are often used in conjunction for QTL discovery and validation.

Linkage mapping studies have been incredibly beneficial in identifying new resistance genes to a number of wheat pathogens. A review of fusarium head blight resistance studies found 52 linkage mapping analyses with QTL discovered on every chromosme but 7D (Buerstmayr et al. 2009). The QTL

Fhb1 identified by linkage mapping was found to reduce disease severity and infected kernal grains when averaged in different backgrounds by 23% and 27% respectively (Pumphrey et al. 2007). In stem rust and other diseases, linkage mapping for major resistance genes with larger phenotypic effects is more readily achievable than for low effect APR genes. APR genes may have their additive effects masked by major genes present (Ellis et al. 2014). These major resistance genes must be accounted for in order to determine underlying causes of resistance.

Linkage mapping can be broken down into population development, phenotype screening,

15 linkage map development, and finally QTL detection. Populations in linkage mapping could be segregating F2, recombinant inbred lines (RIL), backcross populations (BC), or double haploids (DH).

RIL and BC populations take up to 8 years to develop sufficient homozygosity where as complete homozygous lines can be achieved in as few as three years with DH. Phenotyping for the trait of interest may require multiple locations and/or years of the population, but may be much quicker if the trait is apparent at seedling stages i.e. major resistance. Linkage map construction requires genotyping to identify polymorphisms such as SNPs between the parents that segregate within the population and knowledge of their genomic position. Finaly, QTL identification can be performed with a number of statistical programs such as ”r/qtl” (Broman et al. 2003) or MapMaker (Lander et al. 1987).

Once a QTL position and effect is determined, molecular markers such as Kompetitive Allele

Specific Primers (KASP) can be developed that allow high throughput screening of breeding material.

Breeders can incorporate molecular screening of the QTL (MAS) into their breeding program to eliminate material which does not contain the trait of interest and reduce the amount of phenotyping.

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-CHAPTER II- Determining the Genetic Basis of Ug99 Stem Rust, Stripe Rust, and Powdery Mildew Resistance in a Double Haploid Soft Red Winter Wheat Population

Introduction Cereals such as wheat (Triticum aestivum), rice (Oryza sativa), and maize (Zea mays) are staple crops in many countries around the world which together account for over 50% of humans’ caloric intake worldwide (Awika 2011). Just over 2,500 million tonnes of cereals are expected to be consumed for food, feed, and other end uses in 2017/18 with nearly a third from wheat (FAO 2017). Common wheat is a hexaploid crop species (2n = 6x = 42, AABBDD) with three progenitor species comprising the genome.

Theses progenitors and other related species in the Triticeae family are sources of genetic defense for abiotic and biotic stressors. Wheat diseases represent a significant threat to yield and production, including fungal pathogens such as stem rust (Puccinia graminis f.sp. tritici (Pgt)), stripe rust (Puccinia striiformis f.sp. tritici (Pst)), and powdery mildew (Blumeria graminis f.sp. tritici (Bgt)). Incorporating disease resistance genes from hexaploid wheat, progenitor species, or closely related species such as

Thinopyrum elongatum and Secale cereal have been the most effective method of reducing the impacts from such diseases.

Stem rust (Sr), stripe rust(Yr), and powdery mildew (Pm) resistance genes can provide either broad or race-specific resistance to these pathogens but are susceptible to being overcome when disease pressure is high or resistance is based on a single gene. The alien introgression t1RS·1BL consisting of the short of rye chromosome 1R translocated onto the long arm of wheat chromosome 1B has been widely utilized in wheat breeding due to useful abiotic and biotic tolerance traits including the resistance genes Sr31, Yr9, and Pm8 (Singh et al. 1994, McIntosh and Yamazaki 2008; Zeller 1973). Yr9 and Pm8 were useful sources of resistance to stripe rust and powdery mildew until regional virulence developed in

1986 and 1992 respectively (Singh et al. 2004; Lutz et al. 1992).

In 1998, a new race of stem rust appeared in Uganda termed Ug99 which had developed virulence to Sr31 (Pretorius et al. 2000). Sr31 provided durable resistance to stem rust worldwide for decades preceding the emergence of Ug99 and was the main source of resistance in many cultivars developed for stem rust prone regions. The loss of Sr31 effectiveness combined with the broad virulence

of the subsequently emerged Ug99 race group means that the majority of wheat grown around the world

is susceptible to these highly virulent Pgt races (Singh et al. 2015, 2008). Sr31 provided strong broad

resistance and its breakdown highlights the importance of identifying new sources of resistance and

pyramiding or stacking multiple resistance genes in a single cultivar to increase the durability of

resistance (Pretorius et al. 2000). As a result, new research efforts have focused on identifying new Sr genes that provide Ug99 resistance.

There have been 65 Sr genes or alleles identified in common wheat with only 27 having some or complete resistance to the Ug99 race group (Yu et al. 2014). Many of the Ug99 effective Sr genes are on alien translocations that have yield penalty associated with them which limits their incorporation for cultivar development. An additional nine genes such as SrCad, SrTmp, and SrTA10187 confer resistance to Ug99 but have not been fully characterized and formally designated (Wiersma et al. 2016; Kassa et al.

2016; Hiebert et al. 2016). The majority of Sr genes confer race-specific resistance and can potentially lose effectiveness as new mutations give rise to virulent races of the pathogen. Sr24 and Sr36 are major resistance genes which were overcome by the Ug99 race group shortly after deployment (Jin et al. 2008,

2009).

In contrast, broad resistance is effective against all races and provides quantitative resistance that is less effective than major resistance but more durable. When this type of resistance is apparent in mature adult plants, it is referred to as adult plant resistance (APR). Five APR quantitative trait loci (QTL) have been identified in wheat: Sr2, Sr55, Sr56, Sr57, and Sr58 (Yu et al. 2014). APR genes are insufficient to

inhibit infection at seedling stages but slow the infection and spread in mature plants (Ellis et al. 2014).

The combination of APR and major resistance genes is a strategy for the development of resistant

cultivars that will be durable to the Ug99 race group. Screening facilities set up in Kenya and Ethiopia in

the mid-2000s have facilitated the identification and testing of germplasm from around the world against

Ug99 stem rust, which has only been detected in 13 countries in Africa and the Middle East (Singh et al.

2015). There has historically been significant variation of stem rust resistance between market classes of

wheat, however, new virulences to Sr24, Sr36, SrTmp, and Sr1RS over the past two decades have made

winter wheats nearly as vulnerable as spring wheats to the Ug99 race group in African nursery screenings.

From 2006 to 2014, the percentage of the total wheat material screened in Njoro, Kenya displaying

resistance to Ug99 races steadily increased to roughly 20% having good resistance and another 20%

having some resistance (Singh et al. 2015).

The objective of the present study was to identify the genetic source of APR resistance displayed

to Ug99 races in Njoro, Kenya and develop markers to trace this resistance in soft red winter wheat

germplasm. Resistance to stripe rust and powdery mildew was also evaluated in the population and

included in linkage mapping analysis. This biparental population identified significant QTL for stem rust

as well as for stripe rust and powdery mildew which will help to characterize resistance currently

established in Eastern U.S. cultivars.

Material and Methods Plant Materials The soft red winter wheat experimental line MD01W28-08-11 (pedigree AGS 2000/USG 3209) developed by J. Costa, USDA-ARS and University of Maryland, exhibited a moderate reaction to stem rust in a screening nursery in Njoro, Kenya in 2009. In order to further evaluate the resistance,

MD01W28-08-11 was crossed with the stem rust susceptible soft red winter cultivar Coker 9553

(pedigree 89M-4035A/Pioneer 2580; PI 643092). The Ug99-resistant parent MD01W28-08-01 has the

1RS.1BL translocation while the susceptible parent Coker 9553 does not and neither parent possesses

Lr34/Pm38/Yr18, Sr36/Pm6, Sr38/Yr17/Lr37, SrAmigo, and Sr24. F1 seed from the cross were sent to

Heartland Plant Innovations (HPI, Manhattan, KS) for doubled haploid population development using the

maize pollination method. Seeds from the population of 279 doubled haploid lines, hereafter referred to as

the CM population, were increased by USDA-ARS at Raleigh, NC.

Stem Rust Assessment MD01W28-08-11, Coker 9553, and the CM population were evaluated for stem rust reaction in the field at the Kenya Agricultural and Livestock Research Organization (KALRO) in Njoro, Kenya in

2015 and 2016. In each year, all of the lines were vernalized for 6 weeks at 4°C, then transplanted to the field in hill plots, spaced approximately 30cm apart. Each CM line was planted once and the parents were replicated twice. The susceptible control cultivar, Jagger (PI 593688, Sears et al. 1997), was included every 50 plots in the nursery to monitor the level of infection. In both years, a mixture of stem rust susceptible, local spring wheat cultivars were planted in a continuous strip directly adjacent to each hill plot to provide adequate rust inoculum. No hill plot was more than 10cm away from the spreader. Plants in the spreaders were inoculated at booting and heading growth stages by injecting urediniospores directly into stems in order to promote infection and spore production. The inoculum in both years included the original Ug99 race TTKSK (avirulence/virulence of Sr36, Tmp, 24/Sr5, 21, 9e, 7b, 11, 6, 8a, 9g, 9b, 30,

17, 9a, 9d, 10, 31, 38, McN), TTKST (TTKSK with virulence to Sr24), and TTKTK (TTKST with virulence to Tmp).

Stem rust evaluations were conducted twice in 2015 and four times in 2016. Only one rating chosen for optimal discrimination between phenotypes was used each year for QTL analyses. In both years lines were evaluated using a two-part rating for infection type (IT) and severity. Infection types were classified as, in increasing severity, R, RMR, MRR, MR, MRMS, MSMR, MS, MSS, SMS, and S

(R:resistant, S:susceptible, M:moderately). Severity was assessed as percent symptomatic plant area, with

0 indicating immunity and 100 indicating full susceptibility and complete coverage (CIMMYT 1986).

The two-part rating was used to create two separate ratings for subsequent QTL analysis. First, a composite score was created by assigning infection type values of 0.1, 0.5, and 0.9. Resistant phenotypes

(R-MSMR) are given a value of 0.1, moderately susceptible (MS) phenotypes 0.5, and susceptible (MSS-

S) phenotypes 0.9. This asymmetric transformation was modified from the scale used in Bajgain et al.

2015 in order to emphasize the APR characteristic captured in “resistant” infection type scores. Severity

scores were then multiplied by the weighted infection type to obtain a single numerical value representing

the two-part ratings. A second score was also created using just the infection type with R-0, RMR-1, MR-

2, MRR-2, MRMS-3, MSMR-3, MS-6, MSS-7, SMS-8, and S-9. This transformation was also used to emphasize resistant phenotypes. Both composite and infection type scales were used for linkage mapping of stem rust resistance.

Stripe Rust Assessment The same experiments rated for stem rust were also evaluated for stripe rust in 2015 and 2016 in

Njoro, Kenya. Stripe rust in this nursery can be severe and is best evaluated earlier in the growing season than stem rust. In Njoro, stripe rust typically fades as temperatures rise and the plants develop past heading. Infection was by naturally occurring stripe rust, and the predominant race in east Africa in both years was PstS6 (RustTracker.org). There was a single rating taken in 2015 of infection types only, and

three ratings taken in 2016, two of which were a 2-part rating of severity and infection type (CIMMYT

1986). The 2015 IT rating was converted to a 0-9 scale (see stem rust IT conversion above) and one rating from 2016 was converted to a composite scale in the same manner as the stem rust composite score conversion described previously.

In the 2014-2015 growing season in North Carolina, the parents and CM population were evaluated for stripe rust at the North Carolina Department of Agriculture & Consumer Services

(NCDA&CS) and North Carolina State University (NCSU) Upper Mountain Research Station at Laurel

Springs, NC. A single replicate of each entry with the parents repeated four times randomly throughout was planted in one-meter head rows. The stripe rust susceptible controls NC-Neuse (PI 633037, Murphy et al., 2004) and CG514W were included every 80 head rows. Stripe rust spreader CG514W was planted in 1.5-meter wide, four row drill strips after every three drill strips of head rows, resulting in each head row no greater than two meters away from a spreader row. In mid-March and mid-April of 2015, stripe rust infected (primarily race PstV52) and sporulating plants of NC-Neuse were transplanted within the established CG514W spreader every 15 meters to infect the spreader. The parents and CM lines were

evaluated for stripe rust on an ordinal 0-9 scale when the parents were at soft dough. All the plants in the

spreader and the controls were rated 100S when the CM population and parents were evaluated.

Powdery Mildew Assessment Parents and CM lines were evaluated for powdery mildew reaction in 2014 and 2016 at the

NCSU Lake Wheeler Field Lab at Raleigh, NC. In 2014, a single replication with interspersed parents repeated four times was planted in one-meter rows. The cultivar Trego (PI 612576, Martin et al., 2001)

was included every 80 rows as a susceptible control and was also used as a spreader. Powdery mildew

spreader Trego was planted in 1.5m wide, four row drill strips after every three drill strips of meter rows,

resulting in each head row no greater than two meters away from a spreader row. Powdery mildew

severity was determined using a 0-to-9 scale where the percent of the leaf covered with mildew is determined on the upper 4 leaves (flag to F-3), and a higher numerical rating indicates greater severity on the leaves (Large and Doling 1962). The 2016 evaluation was conducted identical to 2014 with a second replication included. A single score was obtained by averaging the two replications for 2016.

QTL Map construction Tissue was collected from 14-day old seedlings of the parents and the CM population and frozen at -80°C in 96 well strip tubes. Tissue was macerated with steel beads using a GenoGrinder2000 (SPEX

Certipreps, Metuchen, NJ) and DNA was extracted using LGC Sbeadex DNA isolation kits (LGC

Genomics, UK). GBS libraries were prepared using the two-enzyme method described in Poland et al.

(2012). Reads were aligned to the IWGSC RefSeq1.0 assembly using the Burrows-Wheeler aligner

(BWA) version 0.7.10 and SNP identified using TASSEL5 version 5.2.33. SNP data were filtered to remove taxa with more than 90% missing data and sites with more than 10% missing data, minor allele frequency less than 10%, and more than 1% heterozygosity. This produced 3,156 SNP sites used in linkage map construction. KASP assays associated in previous studies of soft red winter wheat with stripe rust resistance on chromosome 4B (Brown-Guedira, unpublished) and powdery mildew resistance on chromosomes 2B and 6B (Sarinelli 2017; Table 1) were evaluated on the parents and population and

incorporated into the linkage map. KASP assays associated with stem rust resistance on chromosome 6D

were also evaluated but the parents were monomorphic and these assays were therefore not included in

the linkage map (Kassa et al. 2016).

All map construction and analysis was done in the R statistical programming packages “QTL”

and “ASMap” (Broman et al. 2003; Taylor and Butler 2017). Marker ordering was done with the

minimum-spanning tree algorithm (argument: mstmap(…)) in ASMap to order markers within, but not

between, pre-established linkage groups accounting for physical ordering established by BWA and

IWGSC RefSeq1.0 chromosome assignments. The Kosambi map function was used to calculate genetic

map distances. Individuals were identified and removed in r/qtl due to abnormal number of double

crossovers and high genetic similarity so that 248 CM individuals were retained in the final linkage map.

QTL’s from the CM population were declared using the scanone argument in r/qtl to obtain LOD

scores for all SNP positions. After calculating QTL genotype probabilities using calc.genoprob, the

expectation-maximization (EM) argument was used with 5,000 permutations. This determined genome-

wide LOD thresholds used for declaring QTL and their significance.

Results Phenotypic analysis A majority of the CM population showed some level of stem rust susceptibility and the high disease pressure of the Njoro screening facility allowed variation in IT’s to be observed. Coker 9553 was extremely susceptible to stem rust with average composite scores of 49.5 and 85.5 in 2015 and 2016, respectively (Figure 1C). All ITs for Coker 9553 checks were MSS to S for both years (Fig. 1A).

MD01W28-08-11 was resistant in 2015 and 2016 with average composite scores of 14.75 and 19.25, respectively and ITs of MR to MRMS for both years (Figs. 1A and 1C. The CM population showed a normal distribution for severity scores in both years and a right-skewed distribution for infection type with SMS and S most common in both years. Conversion to a composite numerical score resulted in

discrete scores (22 bins) which separated by 0.5 at low infection types and 9.0 at high infection types reflected in the x-axis (Fig. 1C).

Coker 9553 was moderately resistant to stripe rust in Njoro 2015 and 2016 with average scores of

5.75 (IT scale) and 13.5 (composite score) (Figure 2A and B). It was highly resistant in Laurel Springs

2015 with an average score of 0 (ordinal scale) (Fig. 2C). MD01W28-08-11 was highly susceptible in

Njoro evaluations with average scores of 8.5 (IT scale, 2015) and 24.75 (composite score, 2016) and in

Laurel Springs 2015 with an average score of 8.5 (ordinal scale). The CM population displayed a bimodal distribution in the Njoro, 2016 and Laurel Springs, 2015 environments for stripe rust phenotype. Njoro,

2015 had a slight bimodal distribution that skewed toward the MR infection type.

Coker 9553 was highly resistant to powdery mildew in both Raleigh 2014 and 2016 evaluations with an average ordinal score of 0.5 and 0, respectively (Figure 3). MD01W28-08-11 was moderately susceptible in both 2014 and 2016 environments with an average score of 5.75 and 4.50, respectively. The

CM population displayed left-skewed distribution with a majority of phenotypes scored as 0 in both years. Transgressive segregation indicates that both Coker 9553 and MD01W28-08-11 likely possess favorable alleles for powdery mildew resistance.

Linkage map The linkage map constructed in r/qtl using 248 double haploid individuals consisted of 3057 markers located to 1249 unique loci (Table 2). The total map length was 2428 cM with an average density

2.5 cM between loci. The D genome had the least amount of coverage for each chromosome with 25 markers (16 loci) located on chromosome 3D, 23 markers (12 loci) on 5D and only four marker loci on chromosome 4D (Table 2). Physical distances were assigned to GBS markers using the IWGSC RefSeq

V.1.0 reference sequence. Physical distances agreed with the genetic position determined by interval mapping for the majority of markers (Supplementary Table 2).

Stem Rust QTL Two QTL for stem rust reaction were detected in Njoro located on the short arm of chromosome

6D and the long arm of chromosome 2B and an additional QTL was detected on the long arm of chromosome 4B in Njoro, 2016 only (Table 3, Figure 5). For all QTL, resistance was contributed by

MD01W28-08-11.

The 6D QTL, designated QSr.nc-6D, was stable and significant in both years with composite and

IT rating methods (Figure 6). The 1.0-step LOD interval for QSr.nc-6D for each evaluation were located at the most distal part of the 6DS spanning from 0.0-4.9 cM with the peak LOD score was at 4.5 cM.

QSr.nc-6D explained 12-13% of the composite scale variation but only 6-7% for IT (Table 3). The QTL peak on 2B was identified using the IT scale in both 2015 and 2016 and is designated QSr.nc-2B (Table

3). The QTL had a 1.0-step LOD interval that spans approximately the same 15 cM region of 2B in both years, and the maximum LOD peaks for QSr.nc-2B in 2015 and 2016 were located 0.8 cM apart (Table

3). A QTL peak on 4BL was identified in 2016 for both composite and IT scales but not in 2015. Both rating scales identified identical 10 cM 1.0-step LOD intervals for QSr.nc-4B.

Stripe Rust QTL A QTL on chromosome 4BL was identified in all three environments for stripe rust (Table 3).

Designated QYr.nc-4B, the QTL was highly significant in Njoro 2015, 2016, and Laurel Springs 2015 explaining 13%, 39%, and 74% of phenotypic variation, respectively. The 1.0-step LOD score interval was the largest for Njoro, 2015, followed by Njoro, 2016, and Laurel Springs, 2015 which did not have any secondary loci within the interval. There were 34 GBS markers spanning a physical distance of

100Mbp mapped to the QYr.nc-4B peak position at 61.7 cM (Supplementary Figure 1). The KASP

markers previously associated with resistance to stripe rust in a genome-wide association study (GWAS) of soft winter wheat, Yr_4B_001 and Yr_4B_002, were also located under the QTL peak at the 61.7 cM on the linkage map. QYr.nc-4B was contributed by the stripe rust resistant parent Coker 9553. This is

notable since the similar interval corresponding to QSr.nc-4B stem rust resistance was contributed by

MD01W28-08-11.

Powdery Mildew QTL QTL for powdery mildew resistance located on the long arms of chromosomes 2B and 6B (Figure

5) were highly significant in both years when the population was evaluated at Raleigh, NC. The 2B QTL had peaks in 2014 and 2016 which were 0.5 cM apart and was designated QPm.nc-2B (Table 3).

Resistance at QPm.nc-2B was contributed by Coker 9553. The 6B QTL was designated QPm.nc-6B and

peaks in 2014 and 2016 were located 4 cM apart (Table 3). QPm.nc-6B was highly significant in both

2014 and 2016, accounting for 43% and 10% of variation, respectively, and resistance was contributed by

MD01W28-08-11 despite being the more susceptible parent.

KASP markers developed from GBS SNP significantly associated with powdery mildew

resistance in a GWAS of southeastern germplasm (Sarinelli 2017) were also associated with resistance in

the CM population. The KASP marker PM_2B_005 was located within the QPm.nc-2B interval and

KASP marker Pm_6B_002 was located at the peak position of QPm.nc-6B for 2016 (Figure 5).

Discussion It is important to understand the genetic basis of disease resistance to pathogens such as rusts and powdery mildew in order to develop markers and track resistance throughout breeding populations and programs. This expedites the breeding process by allowing breeders and pathologists to characterize resistance in the absence of pathogens. Highlighting the need for molecular markers, the CM population was part of the 2016 LSU stem rust nursery but adverse planting and weather conditions made scoring for rust impossible. Validated markers would allow resistance in similar populations to be assessed by genotyping when phenotypic reactions are unavailable for environmental reasons or absence of the pathogen. Development of markers closely linked with resistance genes can also help breeders to develop cultivars with durable multi-genic resistance to highly variable pathogens.

Soft winter wheats from the eastern growing region have higher resistance to stem rust than other

U.S. market classes due in part to more diversity of Sr genes (Olson, Brown-Guedira, Marshall, Jin, et al.

2010). These resistance genes include Sr31 as well as Sr24, Sr36, and Sr1RSAmigo which have been overcome by the Ug99 race group or TRTTF (Pretorius et al. 2000; Jin et al. 2008, 2009; Singh et al.

2015). It is therefore important to characterize other sources of resistance in soft winter wheats in order to determine the level of resistance in developed cultivars and produce durably resistant cultivars. Coker

9553 as well as MD01W28-08-11 and its parents, AGS2000 and USG3209, have been widely used in the development of many commercial soft red winter wheat cultivars having stem rust, stripe rust, and powdery mildew resistance. Identifying markers linked with these resistance genes via linkage mapping allows for characterization of sources for resistance already in commercial use.

Coker 9553 is adapted for the southeastern U.S. and has had durable resistance to stripe rust,

moderate resistance to leaf rust and powdery mildew, and lacked noticeable resistance to stem rust. Stem

rust is not a significant pathogen in North Carolina and phenotyping for Pgt was limited to evaluations

done in collaborative screening done in Njoro, Kenya and the USDA-ARS Cereal Disease Lab at St. Paul,

MN. Coker 9553 was postulated to contain Lr11 (personal correspondence, Jim Kolmer) but no other

disease resistance genes including the 1RS:1BL translocation were detected via DNA marker evaluation

of the 2009 and 2010 Mason-Dixon Collaborative testing nursery. Seedling testing of Coker 9553 showed

that it was fully susceptible to Ug99 races TTKSK, TTKST, and TTTSK

(https://www.ars.usda.gov/midwest-area/stpaul/cereal-disease-lab/docs/germplasm-evaluation/uniform-

southern-soft-red-winter-wheat/). MD01W28-08-11 was notable for Ug99 stem rust resistance in Kenyan

screenings and APR characteristic but susceptible to stripe rust and powdery mildew in all environments.

Seedling testing of MD01W28-08-11 had seedling infections types of 2+/3, 2+, and 2+ when evaluated

with TTKSK, TTKST, and TTTSK, respectively (https://www.ars.usda.gov/midwest-area/stpaul/cereal-

disease-lab/docs/germplasm-evaluation/uniform-southern-soft-red-winter-wheat/). Similar infection types

were observed for the AGS 2000 parent of MD01W28-08-11.

Stem Rust Five distinct LOD peaks were identified in the stem rust analysis but only one was consistent across both environments and rating system. QSr.nc-6D was consistently identified in IT and composite analysis with a single LOD peak at 4.5 cM (Table 3). It was also the most significant QTL in the composite rating scale in both years, explaining 13% of the phenotypic variation and having the largest additive effect. The QSr.nc-4B QTL was detected only in 2016 with both rating scales and although the

peak marker positions were separated by 4 cM, this QTL is likely linked to a single causal gene. QSr.nc-

4B marker interval spanned the physical region from 519Mb to 620Mb on chromosome 4B, including the

centromere, typically a region of low recombination (Supplementary Figure 1). However, the QTL peaks

were located on the long arm of 4B. The stable presence of QSr.nc-4B in each rating scheme of 2016

suggests that this QTL was a significant source of stem rust resistance in Njoro 2016 but not 2015. The

peaks identified as QSr.nc-2B mapped close together and had overlapping LOD intervals (Table 3). These

distinct peaks are likely linked to the same gene on 2B and only surpassed the significance threshold

using the infection type rating in either year.

QSr.nc-6D QSr.nc-6D lies near the proximal end of the short arm of chromosome 6D in a region with sparse marker coverage. There were 13 markers identified at 4.5 cM spanning a physical region 6,228,361bp to

7,115,065bp. Sr5, Sr42, SrTmp, SrCad, and SrTA10187 are Pgt resistance genes located on the terminal part of the short arm of 6D where QSr.nc-6D was identified (Wiersma et al. 2016; Gao et al. 2015;

McIntosh et al. 1995; Olson et al. 2013; Hiebert et al. 2016). Sr5 is not effective against the Ug99 race group, indicating that this is not the source of resistance in MD01W28-08-11. The origin of SrTA10187 is

Ae. tauschii and was introgressed only recently to T. aestivum, suggesting this also is not the source of resistance in MD01W28-08-11(Olson et al. 2013). Norin 40 is a Japanese cultivar and was the original source of Sr42 (Ghazvini et al. 2012). The winter wheat cultivar Triumph 64 was the source of SrTmp

(Mcvey and Hamilton 1985). The source of SrCad was “Peace” and “AC Cadillac”, Canadian hard spring cultivars (Hiebert et al. 2011).

Sr42, SrTmp, and SrCad have varying Ug99 race group resistance profiles indicating separate genes or allelic variants are at play (Wiersma et al. 2016; Hiebert et al. 2016; Jin et al. 2007). Hiebert et al. (2016) showed these genes have different functional resistance profiles to TTKSK, TRTTF, and North American races RKQSC, QCCJB and QTHJF. The resistance of SrTmp was overcome in 2013 by race TKTTF and more notably by TTKTK which was present both years in Njoro (Newcomb et al. 2016; Patpour et al.

2016). SrCad and Sr42 maintained resistance to races present in Njoro. It was also demonstrated that

Sr42, SrTmp, and SrCad co-segregated in three separate mapping populations. This points to different causal sources of resistance which may be tightly linked resistance genes or an allelic relationship (Singh et al. 2015; Hiebert et al. 2016).

KASP markers developed by Kassa et al. (2016), which segregate with Sr42, SrTmp, and SrCad as shown by Hiebert et. al., (2016), were tested on the CM population (Table 1). These markers spanned from 5,065,772bp (contig166262_kwm997, positions determined in relation to the IWGSC refSeq1.0) to

5,731,420bp (6DS_2105488_5581_kwm907), a more proximal region of 6DS than QSr.nc-6D. These markers were monomorphic between Coker 9553 and MD01W28-08-11 (data not shown) and therefore not included in the constructed linkage map. This does not preclude QSr.nc-6D from being related to these Sr genes. The KASP markers were developed and validated with hard spring Canadian lines (the parents of the mapping populations used in the identification of SrCad) and have had mixed results on soft winter wheats in southeastern U.S. lines (personal communication, Jared Smith, Kassa et al. 2016).

While these markers are useful for predicting the presence of Sr42, SrTmp, and SrCad in certain material, differentiation among putative genes from diverse backgrounds remains difficult. Further validation of these markers and the development of new unique SNP markers will allow for a more accurate prediction and differentiation of these genes in the future.

The CM population was only evaluated in the field under nursery conditions with three known

Pgt races present. To better characterize the resistance present in MD01W28-08-11, the CM population should be phenotyped with seedling virulence tests of other Pgt races such as TRTTF, and North

American races RKQSC, QCCJB and QTHJF for a direct comparison to the resistance analyzed by

Hiebert et al (2016). Similarly, development of KASP markers from SNPs identified in CM population

would help to compare QSr.nc-6D with Sr42, SrCad, SrTmp, and SrTA10187 if tested on other mapping populations. Further examination with different markers from the discussed publications applied to the

CM population may shed light on this region of the 6D chromosome. Understanding this source of resistance which is likely present in other soft red winter cultivars will allow better assessment of the established Ug99 resistance in North America. Finally, markers would also be useful for marker assisted selection of a Ug99-effective Sr QTL for future cultivar release.

QSr.nc-6D was the most stable source of resistance in each QTL analysis scheme but the presence of additional 2B and 4B QTL indicate the field resistance to Ug99 observed in Njoro may be due to other genetic or environmental factors. Sr36 is a T. timopheevi derived major resistance gene on the long arm of chromosome 2B which provides complete resistance to TTKSK, TTKST, and TTKTK. Both parents were negative for the KASP assay Sr36_8085 (data not shown) further indicating this is not the resistance in MD01W28-08-11. Physiological traits are a possible explanation given the identification of

QSr.nc-2B only appeared on the IT scale and shared similar map positions to LOD peaks from maturity data. Winter wheats were artificially vernalized before planting at Njoro, which can result in extreme phenotypes for maturity and affect stem rust reactions. However, the population segregated for heading dates in Raleigh and QTL analysis with this maturity data indicated that MD01W28-08-11 possesses the photoperiod gene Ppd-B1 on chromosome 2B (data not shown). This maturity QTL was located near

QSr.nc-2B with overlapping intervals. The absence of a significant effect on 2B in composite rating scales, segregation at Ppd-B1, and absence of Sr36 indicate that QSr.nc-2B may be a physiological artifact that is compensated for by incorporating severity ratings in the composite score.

Stripe Rust Stripe rust evaluations revealed a single highly significant QTL on chromosome 4B contributed from Coker 9553. Njoro 2015, 2016, and Laurel Springs 2015 were evaluated with an infection type,

35 composite, and ordinal scale respectively and consistently identified QYr.nc-4B (Table 3). Nearly complete resistance seen in Laurel Springs suggests one race or only avirulent races were present in 2015.

There may be more than one reason for moderate infection types and stripe rust phenotype in the Njoro environments. Heavy stripe rust populations were present in both years and may have contained more than one race. The added presence of Ug99 stem rust from heavy artificial inoculation may have also obscured the full impact of stripe rust. Nevertheless, a high significance of QYr.nc-4B in all three environments points at a valuable source of stripe rust resistance in Coker 9553, a cultivar well adapted for the southeastern U.S. where it has been grown and used for crossing since its release in 2006. An unpublished study postulated the presence of a candidate Yr gene on 4B in Coker 9553 located near to the

SSR marker Xbarc163 (Christopher 2011). A QTL for stripe rust resistance was identified in the soft red winter cultivar USG3555 (Griffey et al. 2009) on 4BL(Christopher et al. 2013). Interestingly, both

USG3555 and Coker 9553 share USG3209 as a parent. Stripe rust QTL QYr.nc-4B from Coker 9553 coincided closely with stem rust resistance QTL QSr.nc-4B from MD01W28-08-11 (Figure 4). High significance in each evaluation with only one QTL indicated stripe rust resistance in this population was monogenic and qualitative while stem rust resistance was more quantitative in nature. Whether these are markers tightly linked to two different rust resistance genes that are in repulsion or allelic variants is unclear. The confidence intervals for the QTL spanned a large physical distance of 137Mb that represented only 2.4cM of recombination in the linkage map (Supplementary Figure 1). This suggests that these QTL are located in a region of low recombination, which complicates analysis of their relationship.

It is also possible that resistance to early stripe rust infection resulted in higher stem rust severity later in the season. Although the low level of recombination observed in the QYr.nc-4B region may hamper efforts at fine mapping, the resulting high levels of linkage disequilibrium can facilitate the use of the linked markers for tracking this resistance source in breeding material. Co-location of three KASP markers for the GBS SNPs identified by GWAS (Table 1), Yr_4B_001 (located at 570,472,978 bp in 4B in the IWGSC refSeq1.0), Yr_4B_002 (577,008,759 bp), and Yr_4B_003 (588,905,418bp) with QYr.nc-

4B makes it a good candidate for marker assisted selection.

Powdery Mildew The peaks associated with both powdery mildew resistance QTL on the long arms of chromosomes 2B and 6B are located in close proximity and likely represent a single causal resistance gene present on each chromosome. Despite Coker 9553 being substantially more resistant to powdery mildew than MD01W28-08-11 in Raleigh 2014 and 2015, significant QTL for resistance were identified from both parents of the CM population.

The 2014 and 2016 peaks for QPm.nc-2B suggest a single gene from the more resistant parent

Coker 9553 (Table 3). QPm.nc-2B was more significant in 2016. In the GWAS conducted by Sarinelli et al. (2017), significant marker trait associations for Pm resistance were identified for nine GBS SNP on

2B, eight of which segregated in the CM population. Many of the GWAS SNPs were located in genetic bins with significant effect in the CM population. Marker PM_2B_005, located at 716,180,576 on chromosome 2B in the IWGSC RefSeq1.0 draft reference genome, was identified in both the GWAS and this study. Marker PM_2B_005 was completely linked to QPm.nc-2B peak marker S2B_714,502,978. A

QTL was also located in this region by Hao et al. (2015) in the RIL mapping population derived from the

cross of Pioneer Brand 26R61 and AGS 2000.

QPm.nc-6B originated from MD01W28-08-11 and was highly significant both years (Table 3).

Sarinelli et al. (2017) reported eight GBS SNP significant for Pm resistance on 6B in a southeastern U.S.

GWAS that were determined to be co-located with the Pm54 gene mapped by Hao et al. (2015) . Three of

these SNP were associated with QPm.nc-6B in the CM mapping population. The most significant SNP in

the GWAS, S6B_695007016, and the closely associated S6B_695676537 (for which PM_6B_002 KASP

assay was developed) both were closely linked with QPm.nc-6B in the present study. This further

supports that these QTL may be further tracked and monitored in soft winter breeding populations where

it is likely they are already present and providing resistance.

Conclusion It is likely that these regions contain important resistance genes that will complement the growing list of known stem rust, stripe rust, and powdery mildew resistance. The high correlation between the present mapping population and markers found in a diverse panel of regional soft wheats by association mapping supports the notion that these genes are widely deployed in the region and providing significant, unquantified resistance. These findings reinforce previous work done on stripe rust and powdery mildew while shedding light on stem rust resistance on chromosome 6DS, and the use of markers developed from these populations will be valuable to wheat breeders.

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-CHAPTER III- Ug99 and Multi-Disease Resistance Genotyping of Winter Wheat Breeding Germplasm

Introduction Plant pathogens are major contributors to yield losses in cereal crops such as common bread wheat, T. aestivum. Half of the world’s caloric intake is derived from cereals and 30% of cereal production in 2016/17 was T. aestivum, leading rice and coarse grains (FAO 2017; Awika 2011). The steady increase in wheat production over the last century is due in large part to improved varieties with superior agronomic and disease resistance traits. Stem rust of wheat (Puccinia graminis f.sp. tritici (Pgt))

has historically been a major pathogen in the United States and around the world causing epidemics in the

first half of the 20th century (Kolmer et al. 2007). The impact of stem rust was reduced in the U.S. by the removal of its alternate host (Barberis spp.) and development of resistant varieties. The USDA

implemented a barberry eradication program in 1918 after two epidemics occurred in the U.S. the

previous decade (Roelfs 1982). By 1972, 17 states across the Midwest and Eastern U.S. had removed

98% of barberry bushes in eradication zones thereby removing overwintering sites and the source of

sexual recombination of P. graminis (Roelfs 1982). This was attributed with the reduction in the number

of new virulent races and amount of initial inoculum of stem rust (Kolmer et al. 2007). The adoption of

wheat varieties with stem rust resistance genes (Sr) have likewise reduced the amount of susceptible hosts

for the pathogen. The resistance genes Sr6, Sr24, Sr31, Sr36, and SrTmp have provided resistance to

various races of Pgt in hard winter and soft red winter wheats in the U.S (Kolmer et al. 2007). The rye

(Secale cereale) translocation 1BL.1RS contains Sr31 which has been particularly effective and durable to P. graminis throughout the world. Sr31 was widely distributed in germplasm by the International

Maize and Wheat Improvement Center (CIMMYT) and helped lead to a global reduction in stem rust incidence. With exception of epidemics in 1950-1954, only a few localized stem rust outbreaks have threatened wheat crops in the U.S (Kolmer et al. 2007). As a result of this control, wheat breeding programs have relied on established and single source resistance for stem rust when developing new cultivars.

In 1999, a new race of stem rust emerged in Uganda with resistance to Sr31. The original race is referred to as Ug99 (Pretorius et al. 2000). The nomenclature was later updated to include a 5th differential set to reflect the novel virulence to Sr31 to TTKSK. There have been 13 race variants of Ug99 comprising the Ug99 race group detected as of 2014 (Fetch et al. 2016). The evolving nature of the Ug99 race group and propensity to overcome major resistance genes deployed in countries with the pathogen have highlighted the vulnerability of wheat worldwide. Ug99 screening facilities have been phenotyping germplasm reaction to local stem rust races in Njoro, Kenya and Debre Zeit, Ethiopia since 2005 and

2007, respectively. Over 400,000 accessions from up to 32 countries have been assessed for their vulnerability to Ug99 races (Singh et al. 2015). It is estimated that between 80% and 95% of the world’s germplasm is susceptible to Ug99 or a member of its race group (Singh et al. 2011, 2008, 2015). At least

27 of the 65 numerically designated stem rust genes have been phenotypically shown to have some resistance to Ug99 race group, as well as a number of temporarily designated resistance genes with incomplete characterization (Yu et al. 2014). Singh et al. (2015) highlighted Sr22, Sr25, Sr26, Sr33, Sr35,

Sr54, and Sr50 as the most promising race-specific sources of resistance provided they are deployed in concert with each other or with other supporting genes such as adult plant resistance (APR) genes.

The ability of P. graminis f.sp. tritici to develop new virulence to resistance genes has led to an effort to increase the durability of resistance in cultivars by stacking multiple resistance genes in one genetic background. APR genes, which typically confer additive, non race-specific resistance and are typically not highly effective when deployed alone, can extend the period over which race-specific genes are able to persist. Sr2 lies on the short arm of chromosome 2B and is the most effective and widely used

APR gene (McIntosh et al. 1995; Singh et al. 2015). Three pleiotropic (Sr55, Sr57, and Sr58) and a fourth

(Sr56) APR genes have been identified but do not provide the same level of resistance as Sr2 (Bansal et al.. 2014; Herrera-Foessel et al. 2014; Singh et al. 2015; and Yu et al. 2014).

In the United States, wheat breeders focus their variety development on traits important to growers in their region such as yield, grain quality, growth habit and local races of pathogens. Important

wheat pathogens in the southeastern U.S. include Stagonospora nodorum blotch (Parastagonospora

nodorum (SNB)), barley yellow dwarf virus (BYDV), Fusarium head blight (Fusarium graminearum

(FHB)), and leaf rust (Puccinia triticina (Lr)). The Small Grains Research Program located in Raleigh

N.C. develops germplasm with a number of traits important to the southeastern U.S. including stem,

stripe,and leaf rust, FHB, BYDV, powdery mildew, and SNB resistance in adapted, agronomically

superior backgrounds. The use of molecular markers facilitates the identification and combination of

resistance genes despite the absence of pathogens such as Ug99 stem rust.

In this study, single-head selections from 78 F6 lines, 47 F4 populations, and 16 F3 populations of winter wheat were screened for the presence of selected stem rust, and leaf rust genes as well as Fhb1,

Bdv2 and the toxin sensitivity gene Tsn1. This will validate the presence of multiple disease resistance

genes and facilitate incorporation of effective Ug99 resistance into U.S. cultivars.

Material and Methods Germplasm Panel A diverse set of lines were selected for marker analysis and obtained directly from David

Marshall, USDA-ARS, Raleigh, N.C. (Table 4). 149 lines were included in the germplasm panel, each with between 2 and 60 head selections, for a total of 2021 individual head entries. Selections of each line were made based on plant phenotype, disease resistance, and segregation in field evaluations in Raleigh and threshed separately. Two seeds from each head were kept for DNA extraction and the remainder was packaged for head row planting in the 2017-2018 field season in Raleigh, N.C. All genotyped entries (line and head) could be traced to a head row in the field. Marker panels applied to separate lines were determined by pedigree and postulated resistance which would require validation. Entries were derived from F4 or F5 headrow selections or from first year yield trial selections of equal or higher advanced generations.

Seven crosses (ARS16W0645, ARS16W0650, ARS16W0652, ARS16W0684, ARS16W0701,

ARS16W0703, and ARS16W0705) derived from Pakistani spring and U.S. winter wheats were

selectively genotyped for the APR gene Lr34/Yr18/Sr57 and the absence of Tsn1. The Pakistani wheat

parents were developed from CIMMYT lines and progeny of their cross to U.S. winter wheats were part

of the Wheat Production Enhancement Program (WPEP) for Pakistan selected here for genotyping.

Three crosses (ARS16W0727, ARS16W0180 and ARS16W0181) derived from Kenyan spring and U.S. winter wheat varieties were selectively genotyped for APR genes Sr2, Fhb1 and Lr34/Yr18/Sr57

as well as the absence of Tsn1. Kingbird-2, a CIMMYT derived spring variety, was the Kenyan parent in

each cross and showed stem rust APR in Ug99 screens.

Thirteen lines (ARS16W0612 ARS16W0604, ARS16W00605, ARS16W0616, ARS16W00624

ARS16W0459, ARS16W0464, ARS16W0768, ARS16W0772, ARS16W0773, ARS16W0891,

ARS16W059 and ARS16W0030) derived from international winter wheats crossed to U.S. winter wheats.

These were selectively genotyped for Sr2, Sr22, Sr35, Sr36, Lr34, and the absence of Tsn1. The exotic

parents of each line displayed good overall phenotype and resistance in the International Winter Wheat

Stem Rust Resistance Nursery (IWWSRRN) and crosses were made to introduce resistance into ARS

germplasm.

The majority of lines in the germplasm panel contained U.S. wheats (Kansas, Louisiana,

Oklahoma, Westbred, Inc.) crossed to North Carolina and USDA-ARS lines or crosses between USDA-

ARS lines. These were genotyped for Sr, Lr, Fhb, Tsn and BYDV resistance combinations.

Marker Analysis Tissue was extracted from 14 day old seedlings and frozen overnight at -80°C in 96 well strip tubes. Tissue was macerated with steel beads using a GenoGrinder2000 (SPEX Certipreps, Metuchen, NJ) and DNA was extracted using LGC Sbeadex DNA isolation kits (LGC Genomics, UK). DNA was diluted with ddH2O to a 1:9 average working concentration of 3ng/µl for molecular analysis.

Nine markers (Sr2, Sr22, Sr26, Sr35, Sr36, Sr40, Lr34, Fhb1, and Tsn1) were assessed using

Kompetitive Allele Specific PCR (KASP) (Kbioscience, Hoddesdon, UK) protocols (He, Holme, and

Anthony 2014). PCR mastermix consisted of 2µL of 2X Reaction Mix and 0.055µL of primer mix added to 2µL of genomic template DNA (3ng/µl) for total reaction volume of 4.055µL on 384-well plates.

Thermocycling conditions for KASP markers (“Touchdown-33” protocol) are as follows: initial denaturation at 94°C for 15 minutes, 10 cycles of 94°C for 20 seconds and 65-57°C for 60 seconds

(dropping 0.8°C per cycle), followed by 23 cycles of 94°C for 20 seconds and 57°C for 60 seconds.

FRET reads were analyzed with PHERAstar-FSX microplate reader (BMG, Ortenberg, Germany) and

KlusterCaller software(LGC, Middlesex, UK). Three successive, additional cycles were ran at 94°C for

20 seconds and 57°C for 60 seconds, with FRET reads after each, until appropriate resolution was reached. Protocols were adapted from publications and personal communications with developing labs and are summarized at maswheat.ucdavis.edu (Table 5)(Periyannan et al. 2011; Saintenac et al. 2013; R.

Mago et al. 2011; Lagudah et al. 2009; Bernardo et al. 2012).

Sr32 and Sr39/Lr35 were assessed using PCR-based markers. Sr32 used two dominant PCR markers, csSr32#1 and csSr32#2. Thermocycling parameters for csSr32#1 were as follows: initial denaturation at 95°C for 30 seconds, 30 cycles of 95°C for 30 seconds, 58°C for 30 seconds, and 72°C for

40 seconds, followed by 72°C for 5 minutes. Thermocycling parameters for csSr32#2 was as follows: initial denaturation at 95°C for 30 seconds, 30 cycles of 95°C for 30 seconds, 60°C for 40 seconds, and

72°C for 50 seconds, followed by 72°C for 5 minutes. Sr39/Lr35 used two dominant PCR markers,

Sr39_22r and BE5007005. Thermocycling parameters for Sr39_22r was as follows: initial denaturation at

94°C for 5 minutes, 30 cycles of 92°C for 30 seconds, 58°C for 30 seconds, and 72°C for 40 seconds, followed by 72°C for 10 minutes. Thermocycling parameters for BE500705 was as follows: initial denaturation at 94°C for 3 minutes, 30 cycles of 92°C for 30 seconds, 56°C for 30 seconds, and 72°C for

40 seconds, followed by 72°C for 10 minutes. Amplification products were resolved on 1X agarose gel and a 100bp DNA ladder was used (TrackIt, Invitrogen, CA). Protocols were adapted from publications summarized at www.maswheat.ucdavis.edu (Table 6)(Mago et al. 2009 and 2013).

Sr42, Sr54, and Bdv2 were assessed using simple sequence repeat (SSR) markers. Sr42 was

genotyped with two co-dominant markers, cfd49F and gpw5182. Sr54 was genotyped with two co-

dominant markers cfd270 and wmc170. Bydv2 was genotyped with the co-dominant marker Bdv2 All

markers used PCR mastermix consisting of 1.2µL 10X PCR buffer w/ MgCl2 (15 mM), 0.96µL 2.5mM

dNTP mix, 0.6µL primer mix, 0.09µL Taq polymerase, 7.15µL of H2O, and 2µL template DNA (6ng/µl).

Sr42 markers used 60anneal thermal cycling conditions. Sr54 markers cfd270 and wmc170 used 60anneal

and 61anneal, respectively. Bdv3 used 50anneal thermal cycling conditions. PCR product fragment sizes

were assessed with an Applied Biosystems 3730xI DNA Analyzer (ABI, Life Technologies, CA).

Protocols were adapted from www.maswheat.ucdavis.edu and personal communication with Gina Brown-

Guedira (Table 6). (Ghazvini et al. 2012; Kumssa et al. 2015; Ghazvini et al. 2013).

Lr57 was genotyped using a PCR-based cleaved amplified polymorphic sequence (CAPS)

marker, Lr57/Yr40-MAS-CAPS16F. PCR mastermix consisting of 2.5µL CutSmart buffer, 2.5µL 2.5mM

dNTP mix, 1.0µL Lr57/Yr40-MAS-CAPS16F primer, 0.75µL Taq polymerase, 15.25µL of H2O, and 3µL template DNA (25ng/µl). Thermocycling conditions were 54anneal. PCR product digestion was performed with 5µL PCR product, 0.1µL Alu1 restriction enzyme, 1.0µL restriction buffer (New England

Biolabs, MA), 0.1µL BSA, and 3.8µL H2O on a thermal cycler at 37°C for 2.5 hours. Digestion product was resolved on 1X agrarose gel. Protocol was adapted from Kuraparthy et. al. (Table 6) (Kuraparthy et al. 2009).

Results and Discussion A total of 2021 entries were selected for disease resistance genotyping. 95 entries (4.5%) had poor germination and no tissue was collected for genotyping. Only one line for which two head selections were included as entries was not genotyped due to both entries having poor germination.

Selected genotyping groups There were 75 entries from the seven WPEP derieved lines were which genotyped for the presence of Lr34/Yr18/Sr57. 40 entries of these were also genotyped for the absence of Tsn1. These lines

were developed as part of a USAID funded project to introduce Pakistani spring wheat germplasm to U.S.

winter wheats. Genotyping for the slow-rusting gene Lr34 and the susceptibility marker Tsn1 would

verify the presence of a valuable broad-spectrum rust resistance gene and/or the absence of a

susceptibility gene for two diseases, tan spot (Pyrenophora tritici-repentis) and Parastagonospora

nodorum. Of the 75 entries genotyped for Lr34, 72 (96%) were positive for the marker, two were

heterozygotes, and one had poor germination. Of the 40 entries genotyped for Tsn1, three (8%) were

positive for the susceptibility marker, 36 (90%) were negative for the marker, and one had poor

germination. The majority of entries (88%) genotyped for Lr34 and Tsn1 are positive and negative

respectively, indicating these crosses will be a useful resource for disease resistance with the intermediate

baking qualities of a spring by winter hybrid.

There were 42 entries from the three Kingbird-2 derived lines which were genotyped for the

presence of Sr2, Lr34/Yr18/Sr57, and Fhb1. Seven entries in two lines of the were also genotyped for the

absence of Tsn1. Kingbird-2 is a U.S. winter by CIMMYT spring cross that was adapted for the growing

conditions of east Africa. The lines studied here represent diverse germplasm crosses for a number of

known and unknown disease resistance genes. For the APR gene Sr2, 21 of the 42 entries (50%) were

positive for the marker, two entries were heterozygotes, 17 entries were negative for the marker, and two

entries had poor germination. Two lines were positive for the resistance marker in all entries while the

third line had roughly half of the 35 entries positive for Sr2. For the slow-rusting gene Lr34, four entries

(10%) were positive for the marker, one entry was heterozygous, four entries were missing data (null

calls), two entries had poor germination, and 31 entries were negative for the marker. None of the entries

were positive for the Fhb1 marker with two having poor germination. For the seven entries genotyped for

Tsn1, one entry (14%) was positive for the susceptibility marker, one entry had poor germination, and

five were negative. There was mixed results for these Kingbird-2 by ARS crosses, with one line

containing the majority of the entries which lacked Lr34 and Fhb1 but partially containing Sr2. The two lines that totaled 7 entries were more uniform, possessing the rust markers and lacking the Tsn1

susceptibility marker. None contained Fhb1. There were three entries with at least two favorable resistance combinations and three entries with at least three favorable combinations. There are other known genes in the pedigree of the ARS lines such as Sr25 and Pm35 so the apparent lack of resistance only reflects those genes genotyped. These lines will have further phenotyping to confirm the genotypic analysis as well as characterize further resistance.

There were 141 entries from 13 lines were genotyped for Lr34/Yr18/Sr57 and 110 entries from

eight of these lines were also genotyped for the absence of Tsn1. All 13 lines genotyped have a winter

wheat parent selected from the International Winter Wheat Stem Rust Resistance Nursery (IWWSRRN)

for their APR characteristics in Kenya and their agronomic and disease resistance phenotype in Raleigh.

These lines were crossed to U.S. soft wheats in order to incorporate their APR characteristics and increase

genetic diversity and were selectively genotyped. Certain IWWSRRN parents had known resistance for

rusts and powdery mildew or contained the 1RS.1BL rye translocation but these were not genotyped for.

Of the 141 entries genotyped for Lr34, 125 entries (89%) were positive for the marker, one was

heterozygous, two had poor germination, four were missing data (null calls), and the remaining nine

entries were negative for the marker. Five lines, each with two selections for analysis, had no positive

calls for the marker. Of the 110 entries genotyped for Tsn1, five entries (5%) were positive for the

susceptibility marker, two entries had poor germination, and 103 were negative for the marker. 95 entries

(86%) contain the Lr34 combination with the absence of Tsn1 and therefore will be a source of multi-

disease resistance. All four of the lines containing the ARS line UX0830-10 lacked the presence of the

Lr34 marker but were not genotyped for Tsn1. This should be taken into consideration in future crossing

decisions.

The remaining entries included in the marker genotyping panel do not fit into categories by

common parentage or characteristics as previously discussed lines have, but were selected for their rust

APR as well as their agronomic phenotypes. These entries were derived from U.S. crosses, public and

private in development, and their discussion will be organized by individual marker rather than by line.

Break down of each resistance marker’s representation will include all entries genotyped, including those

previously highlighted, in order to characterize the entire marker panel.

Discussion by gene Sr2 has been a valuable source of rust resistance and APR since the mid-twentieth century. It has been selected for and against due to its useful APR phenotype and sometimes undesirable pseudo-black chaff characteristic. The gene was introgressed from Triticum dicoccum to bread wheat and is associated with Lr27 on chromosome 3B (McIntoshet al. 1995). Sr2 was the only recognized stem rust APR gene for decades. A KASP marker developed for the detection of Sr2 in 2011 was used for genotyping (Mago et al. 2011). There were 26 lines totaling 442 entries selected for genotyping for Sr2. 183 entries (41%) had positive calls for the marker. There were 15 entries with poor germination and 16 with heterozygous calls; the remaining 228 entries were negative. Two lines were uniformly positive, three lines uniformly negative calls, and the remainder segregated for the Sr2 KASP marker.

Sr22, transferred from Triticum monococcum and mapped to chromosome 7A, has been a useful resource in the effort against Ug99 (Khan et al. 2005; Singh et al. 2015). It became a more attractive source of resistance after reduction of the translocated segment removed portions of the deleterious genomic material associated with Sr22 (Olson et al. 2010). A KASP marker developed for the qualitative resistance gene was developed in 2011 and used to genotype 19 lines in the present study (Periyannan et al. 2011). Of the 435 entries, 91 (21%) were positive for the marker and 266 were negative. There were

19 heterozygous calls, 31 null calls, and 28 with poor germination. Five lines were uniformly negative for the Sr22 marker and none had more than 50% positive calls.

Sr26 is an Agropyron elongatum-derived gene from the translocation 6AS.6AL-6Ae#1L on chromosome 6A (Knott 1961). It is a highly promising source of resistance to Ug99 and the race group due to the high degree of resistance provided (major resistance) and limited presence in germplasm worldwide (Singh et al. 2015; Liu et al. 2010). A KASP marker was developed for Sr26 and used to genotype three lines in the present study (personal communication, Guihua Bai, KSU). There were 66

entries with no positive or heterozygous calls for the marker. There were three entries with poor

germination as well as three null calls but there is no reason to expect that the marker for Sr26 is present

in these entries based on its absence in the rest of the selected entries. The lack of Sr26 presence in U.S. wheat is partially due to its delayed availability as well as a 9% decrease in yield reported in lines containing the gene (The et al. 1988; Dubcovsky and Soria, n.d.).

Sr32 is a widely effective stem rust resistance gene that was translocated from Aegilops speltoides and resides on chromosome 2D (Mago et al. 2013; McIntosh et al. 1995). Sr32 carried a large portion of deleterious genomic material on the translocation and its deployment in cultivars has been limited. Two

PCR-based markers were developed by Mago et. al. (2013) and were used to genotype two lines with two entries each. For the SSR marker csSr32#1, two of four entries amplified a 184bp band as expected

(Figure 6). However, there was no amplification of any size for the SSR marker csSr32#2. One entry had poor germination. The presence of Sr32 could not be validated without a positive result for both markers and the two entries were classified as absent in these lines. Similarly, an association mapping study attempted to use the same PCR marker but noted that the results were inconclusive (Bajgain et al. 2015)

Sr35 was transferred from T. monococcum to hexaploid wheat and has provided resistant to moderately resistant phenotypes against Ug99 (Zhang et al. 2010). Sr35 is a promising source of resistance due to its effectiveness against TTKST and TTTSK, Ug99 races that have overcome Sr24 and

Sr36 respectively (Singh et al. 2015). Sr35 resides on chromosome 3A and a KASP marker was used to genotype 34 lines in the present study (Saintenac et al. 2013, personal communication, Eduard Akhunov,

KSU). There were 22 out of 297 entries (7%) which were positive for the Sr35 marker. There were seven entries with poor germination which could not be genotyped. Within lines that had positive calls, there was limited representation of Sr35 with 2-50% of entries reporting positive calls.

Sr36 was transferred from Triticum timopheevi and provides resistance to TTKSK but variable resistance to the Ug99 race group (Singh et al. 2015). Sr36 is a common Pgt resistance gene in U.S. cultivars. It was overcome by the race TTTSK in 2007 which remains present at low population levels in

eastern Africa (Jin et al. 2009). Sr36 remains a useful tool in regions where it is effective provided it is

used in combination with other resistance genes. A combination of a Sr36 marker and TaSus marker is

used to confirm the presence of the Pgt resistance gene but not the closely linked sucrose synthase gene

which causes false positives. A total of 386 entries from 34 lines were selected for genotyping with the

marker combination. 333 entries (86%) had positive calls for the Sr36 marker and negative calls for the

TaSus marker, indicating that these entries contained the desirable resistance allele. There was one which

was heterozygous, eight had poor germination, and one entry was a null. The remaining 43 entries were

negative for the Sr36 resistance marker combination. The majority of Sr36-tested lines contained positive calls which rarely segregated within lines.

Sr39/Lr35 is an Ae. speltoides derived resistance gene that was transferred to hexaploid wheat

chromosome 2B in 1990 (Kerber and Dyck 1990). The gene provides seedling stem rust resistance and

APR to leaf rust. Sr39 is effective to Ug99 and the race group, and a two-marker diagnostic combination

developed for its’ detection makes the multi-disease resistance gene an attractive candidate for MAS

(Mago et al. 2013). The dominant resistance marker Sr39_22r is used in concert with the dominant

susceptibility marker BE500705 to identify the reduced translocated segment. Both markers are PCR-

based and were applied to seven lines with 21 total entries. No amplification was observed on resolved

gels for the resistance marker Sr39#22r, while 16 entries had amplification for the susceptible allele

associated marker. Amplification did not occur at the expected 166bp size for the susceptible allele, but at

~275bp. Four entries had poor germination and one entry was null, with no amplification on either

marker. It was concluded that none of the lines genotyped contained Sr39/Lr35.

Sr40 is an Ug99 effective resistance gene that was transferred from T. timopheevii (syn T.

araraticum) to hexaploid wheat in 1993 (Wu et al. 2009; Dyck 1992). Sr40 is associated with deleterious

linkage drag on chromosome 2B and has not been widely deployed despite its’ efficacy (Wu et al. 2009;

Singh et al. 2015). A KASP marker was developed for the resistance gene (personal communication, Paul

St. Amand, KSU) and used to genotype 6 lines with 29 total entries. None of the genotyped entries had

positive calls, with one heterozygous call and two entries with no germination. The heterozygous call

derived from a line with 19 entries otherwise uniformly negative. It is notable that Sr40 has mapped close

to Sr39 and an earlier survey of U.S. hard winter wheat found that Sr39_22r accurately tracked the gene

(Bernardo et al. 2013). Further comparative examination with KASP marker Sr40-Seg2-SNP1 could

reveal discrepancies between the two protocols.

Sr42 is a Ug99 effective resistance gene first identified in the Japanese wheat cultivar Norin40

(Ghazvini et al. 2012). Sr42 is one five resistance genes (Sr5, Sr42, SrTmp, SrCad, SrTa10187) located on the short arm of chromosome 6D with functionally different resistance profiles but unknown physical locations in relation to one another (Hiebert et al. 2016; Olson et al. 2013; Kassa et al. 2016). Sr42 is resistant to races TTTSK and TTKST making it a useful tool against Ug99 (Singh et al. 2015). Two imperfect PCR-based markers, cfd49F and gpw5182, predict the presence of Sr42 but are unable to distinguish between SrCad and other 6D resistance genes (Ghazvini et al. 2012; Hiebert et al. 2011; personal communication, Colin Hiebert). One line with 29 entries was genotyped for Sr42 however none produced both expected resistance products. Five entries produced a heterozygous call for cfd49F with peaks at 163bp (resistant) as well as 184 and 186(susceptible). All entries had peaks at 160bp (resistant) for the gpw5182 marker (Figure 7). Without single peaks for both markers at the expected resistant allele size, four entries which produced a heterozygous call and resistant call for their respective markers were classified as heterozygous in the final interpretation. The remaining 24 entries were negative for the gene and one entry had poor germination.

Sr54 is a relatively uncharacterized resistance gene that was also first identified in Norin40

(Ghazvini et al. 2012 and 2013). The resistance gene is located on chromosome 2D and does not provide

Ug99 effective resistance. Two PCR-based markers were developed in order to screen for the presence of the gene (Ghazvini et al. 2013; personal communication, Colin Hiebert). There was one family with 29 entries genotyped for Sr54. Seven entries had a single peak for the cfd270 resistant allele (216bp) and the

remaining entries had peaks at the susceptible allele (214bp) (Figure 8). There were 17 entries with single

resistant allele peaks for wmc170 (210bp) and nine heterozygotes with a second susceptible allele peak

(198bp). One entry had a single resistant allele peak for both markers and was the only Sr54 positive

result, with nine entries heterozygous for Sr54. Further characterization of this gene will help shed light

on its’ efficacy in MAS and marker ambiguity.

Lr34/Yr18/Sr57/Pm18 is a multi-disease resistance gene that provides slow-rusting APR to stem rust. The pleiotropic gene has been extremely durable with no virulence reported to date to leaf or stripe rust (Keller et al. 2012). Lr34 has also been associated with tolerance to barley yellow dwarf virus. It was first identified in the cultivar Frontana and has been associated with leaf-tip necrosis, a morphological marker (Dyck et al. 1966; Singh 1992). Two KASP markers were developed by Lagudah et. al. (2009) that identify the resistance gene on chromosome 7D and differentiate it from the Jagger allele that produces a false positive (a mutation causes a premature stop codon in the resistance gene). There were

100 lines totaling 1075 entries that were genotyped for Lr34, the most common genotyped resistance gene in the panel. 475 entries (44%) reported positive calls for marker with 40 entries being heterozygous, 31 entries having poor germination, and 75 null calls. Only five entries were positive for the false positive

Jagger allele.

Lr57/Yr40 is another pleiotropic resistance gene that was introgressed from Aegilops geniculata into bread wheat (Kuraparthy et al. 2007). Residing on chromosome 5D, Lr57/Yr40 is resistant to most

U.S. leaf and stripe rust races. A cleaved amplified polymorphic sequence marker was reported in

Kuraparthy et al. (2009) and used to genotype two lines with a total of 15 entries. There were eight entries which had expected amplification band sizes, all from one of the two lines (Figure 9). There was one entry with poor germination.

Fhb1 provides resistance to scab (Fusarium graminearum) and was first identified in the cultivar

Sumai 3 (Pumphrey et al. 2007). Fhb1 is the most effective known genetic source of resistance and prevents the spread of symptoms within the spikelet where yield effects are greatest. Fhb1 resides on chromosome 3B (Bernardo et al. 2012). A KASP marker combination was developed by Bernardo et al.

(2012) to accurately track the resistance gene (personal communication, Lynda Whitcher, Jared Smith).

Marker “snp3BS-8” is used to determine the presence of the gene with a positive KASP call while marker

“Fhb1” confirms the true positives with a negative KASP call. A total of 369 entries from 20 lines were

genotyped with 100 entries (27%) positive for the gene Fhb1, 25 and 22 entries reporting heterozygous

and possibly heterozygous respectively, and 13 entries with poor germination. Entries ambiguous for the

marker snp3BS-8 (classified as “Y:X?”, due to poor separation of clusters) were reported as “Fhb1het?”

in order to capture the uncertainty in the KASP reaction. The Fhb1 KASP marker used to confirm

snp3BS-8 was positive for 18 lines and therefore false positives. Only entries that were clearly positive

for snp3BS-8 and negative for Fhb1 were confirmed positive for the resistance gene.

Barley yellow dwarf virus is a major pathogen in the U.S. and North Carolina and spread by

aphid and insect vectors. The Bdv2 resistance allele was introgressed from Thinopyrum intermedium onto

group 7 homologues (Banks et al. 1995; Sharma et al. 1995). P29 derived lines and the majority of TC

derived lines possess Bdv2 on chromosome 7D. There are few effective control options for BYDV and

mainly rely on Bdv2, the main and most significant source of resistance. A PCR-based SSR protocol was

developed by Herb Ohm (2005) and adapted (personal communication, Jared Smith) for use in the current

study. There were ten lines with 320 total entries genotyped for Bdv2, 96 entries (30%) of which had a

single resistant allele peak (200bp) (Figure 10). 12 entries were heterozygous with a second susceptible

peak (185bp), 21 entries had poor germination, and 11 entries had null calls (no amplification). One line

had no positive calls and the remaining lines segregated for the resistance translocation.

The Tsn1 gene, unlike other screened genes, indicates sensitivity to the Ptr ToxA toxin produced

by tan spot (Pyrenophora tritici-repentis) and Stagonospora nodorum ). While it is not the only toxin produced by the pathogens, ToxA is a major virulence factor that causes extensive necrosis and yield loss

(Faris and Friesen 2005; Friesen et al. 2003). A KASP marker was developed by Gina B. Guedira

(personal communication) which predicts the presence of the sensitivity gene on chromosome 5B. There were 19 lines with 169 entries genotyped in the present study. There were 12 entries (7%) positive for the

marker and seven entries having no germination. 150 entries lacked the sensitive allele indicating a higher

level of resistance to both pathogens than those with positive calls.

Combined resistance Fifteen disease resistance genes in total were assessed for their presence in a diverse set of germplasm. While many of the breeding lines were selectively genotyped for a single resistance gene, many lines suspected of multiple sources of resistance were targeted for multiple resistance genes. Sr2,

Sr35, Sr36, Lr34, Fhb1, and Tsn1 were the most commonly used markers and revealed a number of lines

with disease resistance combinations. 5, 62, and 92 entries combined Sr2 with the absence of Tsn1, Lr34,

and Fhb1 respectively. 7, 36, 83, and 139 entries had combinations of Lr34 with Sr35, Fhb1, Sr36, and the absence of Tsn1 respectively. 17 entries combine the major resistance genes Sr35 and Sr36. Beyond these lines with two-gene combinations, there are 33 Sr2+Lr34+Fhb1 entries and 5 Sr35+Sr36+Lr34 entries. Sr2 and Lr34 are important APR and slow-rusting genes that retard the ability of pathogens to overcome other resistance genes when in pyramid combinations. These lines and entries will be a useful germplasm tool for developing durably resistant cultivars. This is of vital importance in the effort against the Ug99 race-group which has proven difficult to breed for due to its propensity to evolve and develop new pathotypes virulent to resistance genes.

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Table 1: Sequence information of powdery mildew, stripe rust, and stem rust associated KASP markers; bolded markers were incorporated in Coker9553/MD01W28-08-11 linkage map, 6D markers were excluded; a positions determined by IWGSC_refseqv1.0; b resistant allele.

KASP MARKER LG PHYSICAL SNP FORWARD PRIMER (5'-3') ALTERNATIVE ALLELE PRIMERB COMMON PRIMER SOURCE POSITION A (BP) PM_2B_005 2B 730676924 [T/C] Pm_2B_005_ALT- Pm_2B_005_ALC- CGGACGGATGTAGTGG Sarinelli et al. GAAGGTGACCAAGTTCATGCTGATACAC GAAGGTCGGAGTCAACGGATTGATACACT CTCGTA 2017 TGCTACGTACGTACCA GCTACGTACGTACCG PM_6B_002 6B 695676537 [A/G] Pm_6B_002_ALA- Pm_6B_002_ALG- TGCATCCTGCTTCCAT Sarinelli et al. 2017 GAAGGTGACCAAGTTCATGCTGCATGTA GAAGGTCGGAGTCAACGGATTCATGTATA CTCCCTTT TAGTGACATGTGACTCTCT GTGACATGTGACTCTCC YR_4B_001 4B 570472978 [T/C] Yr_4B_001_ALC- Yr_4B_001_ALT- GCTGACTACAGTACCC Brown- GAAGGTCGGAGTCAACGGATTGACCTCG GAAGGTGACCAAGTTCATGCTCGACCTCG CTGCGA Guedira ACCTCCGCTCTG ACCTCCGCTCTA YR_4B_002 4B 577008759 [G/C] Yr_4B_002_ALG- Yr_4B_002_ALC- TAGTTAAACCTGAGAA Brown- GAAGGTGACCAAGTTCATGCTCCTCTGC GAAGGTCGGAGTCAACGGATTCCTCTGCA AAAGGTGCTGCTT Guedira AGGATCCTATCTAGC GGATCCTATCTAGG YR_4B_003 4B 588905418 [C/T] Yr_4B_003_ALT- Yr_4B_003_ALC- GGCCCAATGACCGGAT Brown- GAAGGTCGGAGTCAACGGATTACGGCGC GAAGGTGACCAAGTTCATGCTCGGCGCTG ACGAAAATT Guedira TGCAGATTACCATTTA CAGATTACCATTTG

6DS_2105488_558 6D 5731420 [A/T] TAG1- TAG2- GTGAATTCGAGAAGGT Hiebert et al. 1_KWM907 ATCTTGCTAGTTCATGAGCTACTACAT ATCTTGCTAGTTCATGAGCTACTACAA TACAATTAAGCATA 2016 CONTIG11536236 6D 5150113 [A/G] TAG1- TAG2-CCATGTACAAAGCTGTACGAGTTAG CACCCTCGGTATAACT Hiebert et al. _557_KWM999 ACCATGTACAAAGCTGTACGAGTTAA ATGCCTAGTA 2016 CONTIG11536236 6D 5150112 [T/G] TAG1- TAG2-CTCGGTATAACTATGCCTAGTAGAG GTTTGGAAGACTTGGC Hiebert et al. _558_KWM1000 CCTCGGTATAACTATGCCTAGTAGAT ACCATGTACAA 2016 CONTIG166262_ 6D 5065772 [A/C] TAG1- TAG2- GCTTCCGGCACCCGTC Hiebert et al. KWM997 CCTCATCGTAGTTTTCTTCTTCTATGTA CTCATCGTAGTTTTCTTCTTCTATGTC CCAA 2016 CONTIG3539676_ 6D 5198455 [G/A] TAG1- TAG2- TCACTAAGCTCAAGAT Hiebert et al. KWM994 TAACTTGGATCTTGACGTCTTTGATG CTTTAACTTGGATCTTGACGTCTTTGATA TCGTCGCGA 2016 KUKRI_REP_C68 6D 5178439 [A/G] TAG1-TCAGGGATCTTGACCGCTA TAG2-TCAGGGATCTTGACCGCTG TGAGCACCTCGGTAAG Hiebert et al. 823_696_KWM98 TTGT 2016 7

Table 2: Summary of Coker9553/MD01W28-08-11 genetic map including GBS and KASP markers.

Chromosome Number Length, Average Max of cM Spacing, Spacing, Markers cM cM 1A 52 40.0 0.8 5.0 1B 62 90.3 1.5 23.1 1D 32 79.6 2.6 23.8 2A 94 234.8 2.5 23.5 2B 130 130.3 1.0 17.2 2D 42 160.0 3.9 25.5 3A 103 209.3 2.1 35.6 3B 122 175.0 1.4 21.8 3D 16 69.0 4.6 19.0 4A 73 196.2 2.7 31.7 4B 45 87.8 2.0 25.4 4D 4 16.9 5.6 6.9 5A 124 189.1 1.5 23.4 5B 66 143.3 2.2 24.7 5D 12 56.6 5.1 19.8 6A 74 133.5 1.8 25.9 6B 57 142.4 2.5 26.9 6D 20 68.6 3.6 25.5 7A 51 76.1 1.5 22.4 7B 42 74.3 1.8 17.8 7D 28 55.0 2.0 26.1 overall 1249 2428.0 2.5 22.4

Table 3: Position and effect of QTL for stem rust, stripe rust, and powdery mildew resistance based on interval mapping analysis of double haploid Coker9553/MD01W28-08-11 population; * P<0.05, ** P<0.01, *** P<0.001, *** P<0.0001; a Scoring method used for linkage mapping analysis summarized in material and methods; infection type (0-9); composite (converted IT * severity); and ordinal (0-9) system; b Marker interval based on 1.0-step LOD score; c Percent of phenotypic variation associated with the QTL; d Positive or negative values indicate the allele was inherited from MD01W28-08-11 and Coker9553, respectively; ePhysical position (bp) on chromosome of most significant marker on IWGSC_refseqv1.0 map.

PEAK ADDITIV QTL POSITION R2(%) E PEAK POSITION, ENVIRONMENT RATINGA QTL NAME LG INTERVALB (CM) PEAK LOD C EFFECTD PHYSICAL (BP)E STEM RUST

2015 NJORO Composite QSr.nc-6D 6D 0.0-4.85 4.5 6.74**** 13.3 31% 6,274,316

Infection Type QSr.nc-6D 6D 0.0-4.85 4.5 3.8** 6.38 12% 6,274,316

QSr.nc-2B 2B 42.3-57.4 50.0 4.95**** 8.52 14% 63,135,770

2016 NJORO Composite QSr.nc-6D 6D 0.0-4.85 4.5 7.58**** 12.53 30% 6,274,316

QSr.nc-4B 4B 54.8-65.57 61.7 4.68** 7.47 24% 550,333,527

Infection Type QSr.nc-6D 6D 0.0-4.85 4.5 4.45** 7.01 12% 6,274,316

QSr.nc-4B 4B 54.8-65.57 65.6 3.27* 6.61 11% 635,685,764

QSr.nc-2B 2B 42.3-57.8 50.8 4.23** 7.42 12% 66,011,112 STRIPE RUST

2015 NJORO Infection Type QYr.nc-4B 4B 59.3-61.7 61.7 6.57**** 12.96 -37% 550,333,527

2016 NJORO Composite QYr.nc-4B 4B 59.7-61.7 61.7 25.1**** 39.03 -65% 550,333,527

2015 LAUREL SPRINGS Ordinal QYr.nc-4B 4B 61.7 61.7 68.5**** 73.54 -79% 550,333,527 POWDERY MILDEW

2014 RALEIGH Ordinal QPm.nc-2B 2B 75.6-81.2 80.1 3.52* 4.99 -47% 717,229,729

QPm.nc-6B 6B 113.7 113.7 31.22**** 42.86 86% 696,099,425

2016 RALEIGH Ordinal QPm.nc-2B 2B 78.5-80.1 79.7 10.26**** 18.27 -58% 714,502,978

QPm.nc-6B 6B 105.6-113.7 109.6 4.83*** 9.5 45% 691,945,269

Table 4: Line designations and pedigree of genotyped selections. Line USDA-ARS- Generation Number of Raleigh Cross Pedigree of Seed Selections Designation Number Genotyped Genotyped

ARS16W0006 WX04ARS0327 KS2016-U2/WX03ARS0404-X1 F14 2

ARS16W0030 WX06ARS129 ZG33-82/KW90-PB-H2019 F12 25

ARS16W0103 WX09ARS163 ARS05-0423/ARS05-0163 F9 18

ARS16W0180 NA* KS05HW14-1*2/Kingbird-2 F7 2

ARS16W0181 NA* KS05HW14-1*2/Kingbird-2 F7 5

ARS16W0201 WX04ARS0327 KS2016-U2/WX03ARS0404-X1 F14 2

ARS16W0202 WX04ARS0327 KS2016-U2/WX03ARS0404-X1 F14 2

ARS16W0204 WX04ARS0393 LA9528CA78-1-2-B/WX03ARS0178 F14 2

ARS16W0407 WX09ARS349 ARS05-0005/ARS05-1044 F9 2

ARS16W0459 WX11ARS0070 ARS09-092/Gondvana F7 23

ARS16W0464 WX11ARS0107 UX0830-10-12-X1/Gondvana F7 2

ARS16W0469 WX11ARS0259 NuEast/U5931-3-1 F7 2

ARS16W0595 WX10ARS206 ARS07-0606/Krasnodarskaya 99 F8 2

ARS16W0604 WX10ARS219 ARS07-1231/ACC050150 F8 33

ARS16W0605 WX10ARS219 ARS07-1231/ACC050150 F8 42

ARS16W0612 WX10ARS226 ARS05-0074/ACC040347 F8 2

ARS16W0616 WX10ARS235 ARS05-0074/ACC060040 F8 2

ARS16W0624 WX10ARS236 ARS07-0558/ACC060040 F8 2

ARS16W0645 WX11ARS0006 AAS-2009/X10ARS071-3-8 F7 36

ARS16W0650 WX11ARS0006 AAS-2009/X10ARS071-3-8 F7 22

ARS16W0652 WX11ARS0006 AAS-2009/X10ARS071-3-8 F7 2

ARS16W0684 WX11ARS0023 Farid 2006/ARS05-1044 F7 9

ARS16W0701 WX11ARS0049 Shahkar-95/ARS09-077 F7 2

ARS16W0703 WX11ARS0049 Shahkar-95/ARS09-077 F7 2

ARS16W0705 WX11ARS0049 Shahkar-95/ARS09-077 F7 2

ARS16W0727 WX11ARS0071 ARS09-112/Kingbird-2 F7 35

ARS16W0759 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 29

ARS16W0761 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

Table 4: Line designations and pedigree of genotyped selections. Line USDA-ARS- Generation Number of Raleigh Cross Pedigree of Seed Selections Designation Number Genotyped Genotyped

ARS16W0762 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

ARS16W0763 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

ARS16W0764 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

ARS16W0765 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

ARS16W0766 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

ARS16W0767 WX11ARS0106 UX0830-4-1-X1/ARS09-331 F7 2

ARS16W0768 WX11ARS0107 UX0830-10-12-X1/Gondvana F7 2

ARS16W0772 WX11ARS0107 UX0830-10-12-X1/Gondvana F7 2

ARS16W0773 WX11ARS0107 UX0830-10-12-X1/Gondvana F7 2

ARS16W0779 WX11ARS0108 UX0830-24-7-X1/ARS09-025 F7 2

ARS16W0798 WX11ARS0135 NuEast/ARS09-013 F7 2

ARS16W0863 WX11ARS0250 NuEast/U5928-1-5 F7 2

ARS16W0866 WX11ARS0251 NuEast/U5938-10-5 F7 4

ARS16W0867 WX11ARS0253 NuEast/U5924-10-1 F7 2

ARS16W0868 WX11ARS0255 NuEast/U5950-11-2 F7 2

ARS16W0874 WX11ARS0258 NuEast/U5954-1-5 F7 2

ARS16W0875 WX11ARS0261 NuEast/U5942-10-1 F7 2

ARS16W0876 WX11ARS0266 NuEast/UX0830-24-7-X1 F7 2

ARS16W0878 WX11ARS0274 NuEast/UX0875-6-X1 F7 2

ARS16W0879 WX11ARS0274 NuEast/UX0875-6-X1 F7 2

ARS16W0880 WX11ARS0274 NuEast/UX0875-6-X1 F7 2

ARS16W0891 WX11ARS0289 Appalachian White/Gondvana F7 2

ARS16W0941 WX11ARS0326 Appalachian White/ARS09-331 F7 2

ARS16W0946 WX11ARS0338 Appalachian White/ARS09-443 F7 2

ARS16W1015 WX11ARS0416 Appalachian White/U5947-1-3 F7 2

ARS16W1016 WX11ARS0416 Appalachian White/U5947-1-3 F7 2

ARS16W1019 WX11ARS0416 Appalachian White/U5947-1-3 F7 4

ARS16W1021 WX11ARS0416 Appalachian White/U5947-1-3 F7 2

Table 4: Line designations and pedigree of genotyped selections. Line USDA-ARS- Generation Number of Raleigh Cross Pedigree of Seed Selections Designation Number Genotyped Genotyped

ARS16W1024 WX11ARS0418 Appalachian White/U5938-10-5 F7 2

ARS16W1025 WX11ARS0423 Appalachian White/U5952-5-4 F7 2

ARS16W1026 WX11ARS0423 Appalachian White/U5952-5-4 F7 2

ARS16W1027 WX11ARS0423 Appalachian White/U5952-5-4 F7 1

ARS16W1028 WX11ARS0424 Appalachian White/U5954-1-5 F7 9

ARS16W1030 WX11ARS0424 Appalachian White/U5954-1-5 F7 2

ARS16W1031 WX11ARS0429 Appalachian White/UX0830-10-6-X1 F7 2

ARS16W1032 WX11ARS0429 Appalachian White/UX0830-10-6-X1 F7 2

ARS16W1035 WX11ARS0429 Appalachian White/UX0830-10-12-X1 F7 4

ARS16W1036 WX11ARS0429 Appalachian White/UX0830-10-12-X1 F7 14

ARS16W1041 WX11ARS0462 ARS05-1044/ARS09-013 F7 2

ARS16W1045 WX11ARS0472 ARS05-1044/ARS09-095 F7 2

ARS16W1048 WX11ARS0472 ARS05-1044/ARS09-095 F7 2

ARS16W1055 WX11ARS0496 ARS05-1044/ARS09-442 F7 22

ARS16W1060 WX11ARS0523 ARS05-1044/WX03ARS1052-23 F7 2

ARS16W1079 WX11ARS0574 ARS05-1044/U5938-10-5 F7 2

ARS16W1081 WX11ARS0575 ARS05-1044/U5941-1-6 F7 19

ARS16W1150 WX11ARS0995 ARS05-0401/KS11WGGRC53-O F7 2

ARS16W1152 WX11ARS0995 ARS05-0401/KS11WGGRC53-O F7 13

ARS16W1175 WX03ARS0466 LA9415D104-5-2/TX94D7206 F14 2

none WX13ARS012 WX09ARS008-X2/NC08-140 F5 42

none WX13ARS015 WX09ARS009-X1/NC08-140 F5 23

none WX13ARS034 WX09ARS038-X2/NC08-140 F5 15

none WX13ARS146 WX09ARS260-X1/WX09ARS078-X1 F5 38

none WX13ARS163 WX09ARS418-X1/NC08-140 F5 50

none WX13ARS166 WX10ARS256-2-X2/NC08-140 F5 38

none WX13ARS173 WX10ARS048-X1/UX0830-24-7-X1 F5 18

none WX13ARS175 WX10ARS094-X1/UX0875-9-2-X1 F5 44

Table 4: Line designations and pedigree of genotyped selections. Line USDA-ARS- Generation Number of Raleigh Cross Pedigree of Seed Selections Designation Number Genotyped Genotyped

none WX13ARS176 WX10ARS094-X1/UX0875-9-2-X2 F5 50

none WX13ARS187 ARS10-211-X3/NC08-140 F5 45

none WX13ARS192 WX09ARS300-X1/UX0873-25-1-X1 F5 25

none WX13ARS193 ARS10-323-X1/NC08-140 F5 33

none WX13ARS199 ARS10-587-X1/UX0830-10-12-X1 F5 50

none WX13ARS200 ARS10-587-X1/UX0875-2-13-X1 F5 36

none WX13ARS202 ARS11-0042-X1/UX0830-22-5-X2 F5 29

none WX13ARS258 UX0830-4-7-X1/WX09ARS139-X2 F5 22

none WX13ARS259 UX0830-10-4-X1/WX09ARS247-X2 F5 24

none WX13ARS260 UX0830-10-12-X1/WX09ARS023-X2 F5 32

none WX13ARS261 UX0830-10-12-X1/WX09ARS139-X2 F5 21

none WX13ARS262 UX0830-10-12-X1/WX09ARS141-X2 F5 26

none WX13ARS263 UX0830-14-16-X1/WX09ARS034-X1 F5 9

none WX13ARS265 UX0830-14-16-X1/WX09ARS143-X2 F5 18

none WX13ARS268 UX0830-22-5-X2/WX09ARS042-X2 F5 15

none WX13ARS269 UX0830-22-5-X2/WX09ARS065-X2 F5 15

none WX13ARS270 UX0830-22-5-X2/WX09ARS233-X1 F5 15

none WX13ARS273 UX0830-24-7-X1/WX09ARS072-X1 F5 5

none WX13ARS274 UX0873-18-5-X1/WX09ARS231-X2 F5 21

none WX13ARS275 UX0873-18-5-X1/ARS11-0076-X1 F5 14

none WX13ARS278 UX0873-20-6-X1/ARS11-0657-X1 F5 16

none WX13ARS279 UX0873-25-1-X1/WX09ARS010-X2 F5 31

none WX13ARS282 UX0875-2-13-X1/WX09ARS077-X2 F5 30

none WX13ARS283 UX0875-9-2-X1/WX09ARS132-X2 F5 23

none WX13ARS284 UX0875-9-2-X2/WX09ARS023-X2 F5 22

none WX13ARS285 UX0875-9-2-X2/WX09ARS034-X1 F5 24

none WX13ARS287 UX0875-9-2-X2/WX09ARS233-X1 F5 25

none WX13ARS288 UX0875-9-2-X2/ARS11-0042-X1 F5 28

Table 4: Line designations and pedigree of genotyped selections. Line USDA-ARS- Generation Number of Raleigh Cross Pedigree of Seed Selections Designation Number Genotyped Genotyped

none WX13ARS291 NC08-140/WX09ARS009-X1 F5 25

none WX13ARS292 NC08-140/WX09ARS400-X1 F5 27

none WX13ARS293 NC08-140/ARS10-291-X1 F5 22

none WX13ARS399 WX09ARS053-X1/UX1520-4-7-X1 F5 15

none WX13ARS400 WX09ARS053-X1/UX1521-1-3-X1 F5 24

none WX13ARS401 WX09ARS053-X1/UX1522-5-1-X1 F5 25

none WX13ARS402 ARS05-1044/UX1162-4-37-31 F5 12

none WX13ARS403 ARS05-1044/UX1162-4-37-31 F5 10

none WX13ARS404 ARS05-1044/UX1162-4-37-31 F5 6

none WX13ARS405 ARS05-1044/UX1162-4-37-43 F5 9

none WX13ARS406 ARS05-1044/UX1162-4-37-43 F5 8

none WX14ARS060 WX09ARS052-X1/UX1162-4-56-123 F4 20

none WX14ARS061 WX09ARS052-X1/UX1193-13-02 F4 19

none WX14ARS062 WX09ARS052-X1/UX1325-08 F4 22

none WX14ARS089 ARS11-0376-30/UX1162-4-36-04 F4 16

none WX14ARS090 ARS11-0376-30/UX1325-06 F4 25

none WX14ARS093 ARS11-0418-13/UX1325-06 F4 19

none WX14ARS114 ARS11-0827-10/UX1195-01-10 F4 20

none WX14ARS120 WX04ARS0740-16-05-03-13-06/UX1162-4-36-66 F4 16

none WX14ARS121 WX04ARS0740-16-05-03-13-06/UX1162-4-56-101 F4 23

none WX14ARS124 WX05ARS0280-18-01-05-06/UX1162-4-36-24 F4 24

none WX14ARS151 WX09ARS140-X1/UX1107-5-02 F4 22

none WX14ARS153 WX09ARS140-X1/UX1193-13-02 F4 28

none WX14ARS155 WX09ARS140-X2/UX1105-13-10 F4 30

none WX14ARS157 WX09ARS140-X2/UX1183-07-06 F4 19

none WX14ARS163 WX09ARS225-X1/UX1352-04 F4 29

none WX14ARS166 WX09ARS256-X2/UX1162-4-56-45 F4 23

*NA=Not available. Cross made by USDA-ARS in Manhattan, KS.

Table 5: Primer sequences for KASP assays used in germplasm screening and associated controls.

Locus LG Marker Name Allele 1 Sequence Allele 2 Common Controls (KASP name)

Stem Rust

Sr2 3B Sr2_ger93p GAAGGTGACCAAGTTCATGCTGTGC GAAGGTCGGAGTCAACGGATTGT CTCAAATGGTCGAGCACAAG Inia66 (+), Pastor (-), Sonora64 GAGACATCCAACACTCAC GCGAGACATCCAACACTCAT CTCTA (neg)

Sr22 7A Sr22_A GAAGGTGACCAAGTTCATGCTTTACT GAAGGTCGGAGTCAACGGATTTA TGAATGGATGCATCAATGCA Sr22TB (+) CAATTACTTCCATAAGTTCCTACT CTCAATTACTTCCATAAGTTCCTA TGCACAT CA

Sr26 6A Sr26_S GAAGGTGACCAAGTTCATGCTCAAG GAAGGTCGGAGTCAACGGATTAC Allele 1 common: Avocet (+) CCACAAGGTGCCCAGC TATCATGCACCGGGCAATGC CTCCTGTCCGGTGATTGTATG GTT

Allele 2 common: GGCTTCTACGTAAGCCTACG TAGAT

Sr35 3A NL9ce GAAGGTCGGAGTCAACGGATTAG CCATGGTTTTGATCAGAGCAT G2919 (+) ACTGTCCAGTTTGTACATATTACT GGGTA AAT

Sr36/Pm6 2B Sr36_8085 GAAGGTGACCAAGTTCATGCTACCC GAAGGTCGGAGTCAACGGATTCA CAGCGTAGTGCGCGCGGCTT Neuse(+), NCD16001-F12(+), AGCCGCTTGAGGCG CCCAGCCGCTTGAGGCT NCD16001-D1(+)

2B TaSus2-2B GAAGGTGACCAAGTTCATGCTGCGG GAAGGTCGGAGTCAACGGATTGC ACTGCTGAGTACAATGCCGC NCD16001-F12(+), NCD16001- TGTCCTTGAGCTTCTCA GGTGTCCTTGAGCTTCTCG GATCCCA G12(-), NCD16001-D1(-)

Sr40 2B Sr40-Seg2-SNP1 GAAGGTGACCAAGTTCATGCTAGTC GAAGGTCGGAGTCAACGGATTAG TATTGCGATAACAGTGCTTCT US665-60 (+) CAACCACAGCCTTTGCAGCATC TCCAACCACAGCCTTTGCAGCATG TAG

Leaf Rust

Lr34/Yr15/Pm38 7D Lr34 GAAGGTGACCAAGTTCATGCTCTGG GAAGGTCGGAGTCAACGGATTCT CGCATGACAATAAGTTTCACT Jagger(+), Chinese Spring(+), TATGCCATTTAACATAATCATGAA GGTATGCCATTTAACATAATCATG CATGCAAA AT NCD16001-A1(-)

7D Lr34jagger GAAGGTGACCAAGTTCATGCTTGTA GAAGGTCGGAGTCAACGGATTAT GATCATTATCTGACCTGTGCG Jagger(+), NCD16001-A7(+), ATGTATCGTGAGAGATTTGCAG TGTAATGTATCGTGAGAGATTTGC AATGAATA AT NCD16001-D5(-)

Fusarium Head Blight

Fhb1 3B snp3BS-8 GAAGGTGACCAAGTTCATGCTCACA GAAGGTCGGAGTCAACGGATTCA CAAAGCAGCCTTAGGTCAAT VAG17001-B1 (+) TGCATTTGCAAGGTTGTTATCC CATGCATTTGCAAGGTTGTTATCG AGTTTGAAA

3B Fhb1 Sequence pending publication Sequence pending publication Sequence pending publication VAG17001-B1 (-)

Tan Spot

5B Tsn1_A GAAGGTCGGAGTCAACGGATTCT CTGCCCTTCACTTAGCCTGTC Jagger(+), NCD16001-D12(+), ATTCGTAATCGTGCCTTCCGG AC NCD16001-D1(-)

Table 6: Primer sequences for gel, ABI, and CAPS based markers used in germplasm screening.

Locus LG Marker Name Forward Sequence Reverse Sequence

Gel-based markers Sr32 2D csSr32#1 GGTTTGGTGGCAACTCAG GT CATAAGCCAAAGAGGCACCA

csSr32#2 CAAATGAATAGAAAAACCCGTGCT CACACACTGTTTTCCGTTGC Sr39/Lr35 2B Sr39_22r AGAGAAGATAAGCAGTAAACATG TGCTGTCATGAGAGGAACTCTG

BE500706 ATCTGTGGCAGTGTGCTCCT TCCTGCAAATGCTTGTCGTT

ABI-based markers Sr42 6D cfd49F TGAGTTCTTCTGGTGAGGCA GAATCGGTTCACAAGGGAAA

gpw5182 TCCACTTCACTAACAAACACGG AAAAGCTGTATAGGCAGTTCGC Sr54 2D wmc41 TCCCTCTTCCAAGCGCGGATAG GGAGGAAGATCTCCCGGAGCAG

cfd270 AGCATGTGTGTCTCCTCGTG CTCCTCACTCCTCGTCTTGG BYDV 7D Bdv3 CTTAACTTCATTGTTGATCTTA CGACGAATTCCCAGCTAAACTAGACT

CAPS-based markers Lr57 5D Lr57/Yr40-MAS- CTCGTCAACACCCATCTCCT ACGTTGGTCTCGGTCATCTC CAPS16F

Supplementary Table 3.1: Germplasm source and genotyped markers.

Principal Marker Germplasm Source Bdv2 NC08-140 Fhb1 UX1105-13-10, UX1107-5-02, UX1162-4-36-04, UX1162-4-36-24, UX1162-4- 36-66, UX1162-4-37-31, UX1162-4-37-43, UX1162-4-56-45, UX1162-4-56-101, UX1162-4-56-123, UX1183-7-6, UX1193-13-02, UX1195-01-10, UX1520-4-7- X1, UX1521-1-3-X1, UX1522-5-1-X1

Lr34 AAS-2009, ACC040347, ACC050150, ACC060040, ARS05-0163, ARS05-0401, ARS05-1044, ARS09-013, ARS09-025, ARS09-092, ARS09-443, ARS11-0376-30, ARS11-0827-10, Farid-2006, Gondvana, Kingbird-2, Krasnodarskaya 99, Shahkar- 95, TX94D7206, U5931-3-1, U5938-10-5, UX0830-4-7-X1, UX0830-10-4-X1, UX0830-10-6-X1, UX0830-10-12-X1, UX0830-22-5-X2, UX0830-24-7-X1, UX1105-13-10, UX1107-5-02, UX1162-4-56-101, UX1162-4-56-123, UX1183-7-6, UX1193-13-02, UX1195-01-10, UX1520-4-7-X1, UX1521-1-3-X1, UX1522-5-1-X1, WX03ARS0404-17-10-3, WX04ARS0740-16-05-03-13-06, WX05ARS0280-18-01- 05-06, WX09ARS034-X1, WX09ARS052-X1, WX09ARS139-X2, WX09ARS140- X1, WX09ARS140-X2, WX09ARS143-X2, WX09ARS256-X2, WX09ARS260-2- X1, WX10ARS048-1-X1, ZG33-82

Lr57 KS11WGGRC53-O

Sr2 ACC060040, Kingbird-2, TX94D7206, UX1105-13-10, UX1107-5-02, UX1162- 4-36-04, UX1162-4-36-24, UX1162-4-36-66, UX1162-4-37-31, UX1162-4-37- 43, UX1162-4-56-45, UX1162-4-56-101, UX1162-4-56-123, UX1183-7-6, UX1193-13-02, UX1195-01-10, UX1520-4-7-X1, UX1521-1-3-X1, UX1522-5-1- X1, WX03ARS0178-9-14-3

Sr22Tb U5924-10-1, UX0873-18-5-X1, UX0873-20-6-X1, UX0873-25-1-X1, UX0875-2- 13-X1, UX0875-6-X1, UX0875-9-2-X1, UX0875-9-2-X2, WX09ARS078-1-X1

Sr26 UX1325-06, UX1325-08

Sr32 U5928-1-5, U5950-11-2

Sr35 U5931-3-1, U5938-10-5, U5952-5-4, U5954-1-5, UX0830-4-7-X1, UX0830-10- 4-X1, UX0830-10-6-X1, UX0830-10-12-X1, UX0830-14-16-X1, UX0830-22-5- X2, UX0830-24-7-X1

Sr36 ARS05-0074, ARS05-0401, ARS07-0606, ARS07-1231, ARS09-013, ARS09- 025, ARS09-077, ARS09-092, ARS09-095, ARS10-587-X1, ARS11-0042-X1, UX0873-20-6-X1, UX0873-25-1-X1, UX0875-2-13-X1, UX0875-6-X1, WX04ARS0740-16-05-03-13-06, WX09ARS023-X2, WX09ARS034-X1, WX09ARS038-1-X2, WX09ARS042-X2, WX09ARS053-X1, WX09ARS065- X2, WX09ARS072-X1, WX09ARS139-X2, WX09ARS141-X2, WX09ARS143- X2, WX09ARS233-X1, WX09ARS247-X2, WX10ARS071-3-8, WX10ARS094- 1-X1, WX10ARS048-X1

Supplementary Table 3.1: Germplasm source and genotyped markers.

Principal Marker Germplasm Source Sr39 U5938-10-5, U5954-1-5 Sr40 U5941-1-6, U5942-10-1, U5947-1-3 Sr42 UX1352-04 Sr54 UX1352-04

Tsn1 (absence) ARS05-0401, ARS05-1044, ARS07-0046, ARS07-0558, ARS07-0606, ARS07- 1182, ARS07-1231, ARS09-013, ARS09-077, Gondvana, Kingbird-2, KW90- PB-H2019, WX04ARS0740-16-05-03-13-06, WX05ARS0280-18-01-05-06, WX09ARS053-X1, WX09ARS140-X1, WX09ARS140-X2

Figure 1: Distribution of stem rust infection type ratings, severity ratings, and composite scores on the double haploid Coker9553/MD01W28-08-11 population in 2015 (black) and 2016 (shaded) in Njoro, Kenya. A) Infection type ratings varying from MR-S (moderately resistant - susceptible) B) Severity ratings (5 indicating 5% affected leaf area, 90 indicating 90% complete susceptibility) C) Composite score calculated by converted (0.1, 0.5, 0.9) infection type * severity; Arrows indicate parent phenotype as averaged in each year; MD, MD01W28-08-11; CK, Coker 9553.

Figure 2: Distribution of stripe rust infection type ratings, severity ratings, and composite scores on the double haploid Coker9553/MD01W28-08-11 population in Njoro, 2015 and 2016 and Laurel Springs, 2015. A) Infection type ratings for Njoro, 2015 varying from R-S (resistant - susceptible) B) Composite scores for Njoro, 2016 calculated by converted (0.1, 0.5, 0.9) infection type * severity C) Ordinal scores for Laurel Springs, 2015 (0-9); Arrows indicate parent averaged phenotype within environment; MD, MD01W28-08-11; CK, Coker9553.

Figure 3: Distribution of powdery mildew ratings on the double haploid Coker9553/MD01W28-08-11 population in Raleigh, 2014 and Raleigh, 2016. Ordinal score ratings (0-9) for A) 2014 Raleigh and B) 2016 Raleigh; Arrows indicate parent averaged phenotype within environment; MD, MD01W28-08-11; CK, Coker 9553.

Figure 4: Genetic map of QTL linked with stem rust, stripe rust, and powdery mildew on chromosomes 2BS, 2BL, 4B, 6B, and 6D of the double haploid Coker9553/MD01W28-08-11 population; black vertical bars indicate 1.0-step LOD interval of significant QTL; GBS marker name right of chromosome with co- located markers excluded; genetic position (cM) left of chromosome.

Figure 5: Quantitative trait loci (QTL) for adult plant resistance to stem rust identified on chromosome 6DS in Coker9553/MD01W28-08-11 in Njoro 2015 and 2016; Composite and infection type (IT) rating scales used in linkage analysis are shown for each year.

Figure 6: PCR amplification of csSr32#1 marker for Sr32; Lane 1 and 4, amplification at 184bp; Lane A, 100bp ladder.

Figure 7: PCR amplified DNA fragment peaks for codominant markers cfd49Fd (top) and gpw5182 (bottom) for detection of Sr42; cfd149F heterozygous; gpw5182 homozygous resistant; size standard above peaks.

Figure 8: PCR amplified DNA fragment peaks for codominant markers cfd270 (top and middle) and wmc170 (bottom) for detection of Sr54; Top, susceptible 214bp fragment; middle, resistant 216bp fragment; bottom, resistant 210bp fragment; size standard above peaks.

Figure 9: PCR amplification of CAPS marker Lr57/Yr40-MAS-CAPS16F; lane 1, resistant amplification of 450bp band; lane A, 100bp DNA ladder.

Figure 10: PCR amplified DNA fragment peaks for marker BYDV2; top, susceptible fragment 185bp peak; bottom, resistant fragment 200bp peak; size standard above peaks.

Supplementary Figure 2.1: GBS markers identified on chromosome 4B are plotted by their physical position relative to the IWGSC RefSeq v.1.0 reference map and the genetic map location; markers identified as QYr.nc-4B are indicated by brackets.

Supplementary Figure 2.2: GBS identified markers of CM population plotted by their genetic position (cM, Y axis) and physical position relative to IWGSC RefSeq v.1.0 reference map (bp, X axis); rows grouped by chromosome group, columns grouped by genome; ie top-left panel shows chromosome 1A.