Genome-wide association study of resistance to PstS2 and Warrior races of Puccinia striiformis f. sp. tritici (stripe rust) in bread wheat landraces

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants' defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

A major yellow rust resistance QTL on chromosome 6A shows increased frequency in recent Norwegian spring wheat cultivars and breeding lines

KEY MESSAGE

A major yellow rust resistance QTL, QYr.nmbu.6A, contributed consistent adult plant resistance in field trials across Europe, China, Kenya and Mexico. Puccinia striiformis f. sp. tritici, causing wheat yellow rust (YR), is one of the most devastating biotrophic pathogens affecting global wheat yields. Owing to the recent epidemic of the PstS10 race group in Europe, yellow rust has become a reoccurring disease in Norway since 2014. As all stage resistances (ASR) (or seedling resistances) are usually easily overcome by pathogen evolution, deployment of durable adult plant resistance (APR) is crucial for yellow rust resistance breeding. In this study, we assessed a Nordic spring wheat association mapping panel (n = 301) for yellow rust field resistance in seventeen field trials from 2015 to 2021, including nine locations in six countries across four different continents. Nine consistent QTL were identified across continents by genome-wide association studies (GWAS). One robust QTL on the long arm of chromosome 6A, QYr.nmbu.6A, was consistently detected in nine out of the seventeen trials. Haplotype analysis of QYr.nmbu.6A confirmed significant QTL effects in all tested environments and the effect was also validated using an independent panel of new Norwegian breeding lines. Increased frequency of the resistant haplotype was found in new varieties and breeding lines in comparison to older varieties and landraces, implying that the resistance might have been selected for due to the recent changes in the yellow rust pathogen population in Europe.

The Keys to Controlling Wheat Rusts: Identification and Deployment of Genetic Resistance

Rust diseases are among the major constraints for wheat production worldwide due to the emergence and spread of highly destructive races of Puccinia. The most common approach to minimize yield losses due to rust is to use cultivars that are genetically resistant. Modern wheat cultivars, landraces, and wild relatives can contain undiscovered resistance genes, which typically encode kinase or nucleotide-binding site leucine rich repeat (NLR) domain containing receptor proteins. Recent research has shown that these genes can provide either resistance in all growth stages (all-stage resistance; ASR) or specially in later growth stages (adult-plant resistance; APR). ASR genes are pathogen and race-specific, meaning can function against selected races of the Puccinia fungus due to the necessity to recognize specific avirulence molecules in the pathogen. APR genes are either pathogen-specific or multipathogen resistant but often race-nonspecific. Prediction of resistance genes through rust infection screening alone remains complex when more than one resistance gene is present. However, breakthroughs during the past half century such as the single-nucleotide polymorphism-based genotyping techniques and resistance gene isolation strategies like mutagenesis, resistance gene enrichment, and sequencing (MutRenSeq), mutagenesis and chromosome sequencing (MutChromSeq), and association genetics combined with RenSeq (AgRenSeq) enables rapid transfer of resistance from source to modern cultivars. There is a strong need for combining multiple genes for better efficacy and longer-lasting resistance. Hence, techniques like gene cassette creation speeds up the gene combination process, but their widespread adoption and commercial use is limited due to their transgenic nature.

Genetic Basis of Resistance to Warrior (-) Yellow Rust Race at the Seedling Stage in Current Central and Northern European Winter Wheat Germplasm

To evaluate genetic variability and seedling plant response to a dominating Warrior (-) race of yellow rust in Northern and Central European germplasm, we used a population of 229 winter wheat cultivars and breeding lines for a genome-wide association study (GWAS). A wide variation in yellow rust disease severity (based on infection types 1-9) was observed in this panel. Four breeding lines, TS049 (from Austria), TS111, TS185, and TS229 (from Germany), and one cultivar, TS158 (KWS Talent), from Germany were found to be resistant to Warrior (-) FS 53/20 and Warrior (-) G 23/19. The GWAS identified five significant SNPs associated with yellow rust on chromosomes 1B, 2A, 5B, and 7A for Warrior (-) FS 53/20, while one SNP on chromosome 5B was associated with disease for Warrior (-) G 23/19. For Warrior (-) FS 53/20, we discovered a new QTL for yellow rust resistance associated with the marker Kukri_c5357_323 on chromosome 1B. The resistant alleles G and T at the marker loci Kukri_c5357_323 on chromosome 1B and Excalibur_c17489_804 on chromosome 5B showed the largest effects (1.21 and 0.81, respectively) on the severity of Warrior (-) FS 53/20 and Warrior (-) G 23/19. Our results provide the basis for knowledge-based resistance breeding in the face of the enormous impact of the Warrior (-) race on wheat production in Europe.

Comparison of linear and semi-parametric models incorporating genomic, pedigree, and associated loci information for the prediction of resistance to stripe rust in an Austrian winter wheat breeding program

We used a historical dataset on stripe rust resistance across 11 years in an Austrian winter wheat breeding program to evaluate genomic and pedigree-based linear and semi-parametric prediction methods. Stripe rust (yellow rust) is an economically important foliar disease of wheat (Triticum aestivum L.) caused by the fungus Puccinia striiformis f. sp. tritici. Resistance to stripe rust is controlled by both qualitative (R-genes) and quantitative (small- to medium-effect quantitative trait loci, QTL) mechanisms. Genomic and pedigree-based prediction methods can accelerate selection for quantitative traits such as stripe rust resistance. Here we tested linear and semi-parametric models incorporating genomic, pedigree, and QTL information for cross-validated, forward, and pairwise prediction of adult plant resistance to stripe rust across 11 years (2008-2018) in an Austrian winter wheat breeding program. Semi-parametric genomic modeling had the greatest predictive ability and genetic variance overall, but differences between models were small. Including QTL as covariates improved predictive ability in some years where highly significant QTL had been detected via genome-wide association analysis. Predictive ability was moderate within years (cross-validated) but poor in cross-year frameworks.

Genome-wide association study and genomic prediction of resistance to stripe rust in current Central and Northern European winter wheat germplasm

We found two loci on chromosomes 2BS and 6AL that significantly contribute to stripe rust resistance in current European winter wheat germplasm. Stripe or yellow rust, caused by the fungus Puccinia striiformis Westend f. sp. tritici, is one of the most destructive wheat diseases. Sustainable management of wheat stripe rust can be achieved through the deployment of rust resistant cultivars. To detect effective resistance loci for use in breeding programs, an association mapping panel of 230 winter wheat cultivars and breeding lines from Northern and Central Europe was employed. Genotyping with the Illumina® iSelect® 25 K Infinium® single nucleotide polymorphism (SNP) genotyping array yielded 8812 polymorphic markers. Structure analysis revealed two subpopulations with 92 Austrian breeding lines and cultivars, which were separated from the other 138 genotypes from Germany, Norway, Sweden, Denmark, Poland, and Switzerland. Genome-wide association study for adult plant stripe rust resistance identified 12 SNP markers on six wheat chromosomes which showed consistent effects over several testing environments. Among these, two marker loci on chromosomes 2BS (RAC875_c1226_652) and 6AL (Tdurum_contig29607_413) were highly predictive in three independent validation populations of 1065, 1001, and 175 breeding lines. Lines with the resistant haplotype at both loci were nearly free of stipe rust symptoms. By using mixed linear models with those markers as fixed effects, we could increase predictive ability in the three populations by 0.13-0.46 compared to a standard genomic best linear unbiased prediction approach. The obtained results facilitate an efficient selection for stripe rust resistance against the current pathogen population in the Northern and Central European winter wheat gene pool.

Exploring the Genetic Diversity and Population Structure of Wheat Landrace Population Conserved at ICARDA Genebank

Landraces are considered a valuable source of potential genetic diversity that could be used in the selection process in any plant breeding program. Here, we assembled a population of 600 bread wheat landraces collected from eight different countries, conserved at the ICARDA's genebank, and evaluated the genetic diversity and the population structure of the landraces using single nucleotide polymorphism (SNP) markers. A total of 11,830 high-quality SNPs distributed across the genomes A (40.5%), B (45.9%), and D (13.6%) were used for the final analysis. The population structure analysis was evaluated using the model-based method (STRUCTURE) and distance-based methods [discriminant analysis of principal components (DAPC) and principal component analysis (PCA)]. The STRUCTURE method grouped the landraces into two major clusters, with the landraces from Syria and Turkey forming two clusters with high proportions of admixture, whereas the DAPC and PCA analysis grouped the population into three subpopulations mostly according to the geographical information of the landraces, i.e., Syria, Iran, and Turkey with admixture. The analysis of molecular variance revealed that the majority of the variation was due to genetic differences within the populations as compared with between subpopulations, and it was the same for both the cluster-based and distance-based methods. Genetic distance analysis was also studied to estimate the differences between the landraces from different countries, and it was observed that the maximum genetic distance (0.389) was between the landraces from Spain and Palestine, whereas the minimum genetic distance (0.013) was observed between the landraces from Syria and Turkey. It was concluded from the study that the model-based methods (DAPC and PCA) could dissect the population structure more precisely when compared with the STRUCTURE method. The population structure and genetic diversity analysis of the bread wheat landraces presented here highlight the complex genetic architecture of the landraces native to the Fertile Crescent region. The results of this study provide useful information for the genetic improvement of hexaploid wheat and facilitate the use of landraces in wheat breeding programs.

QTL Mapping of Adult Plant Resistance to Stripe Rust in a Doubled Haploid Wheat Population

Stripe rust caused by Puccinia striiformis Westend. f. sp. tritici. is a major bread wheat disease worldwide with yield losses of up to 100% under severe disease pressure. The deployment of resistant cultivars with adult plant resistance to the disease provides a long-term solution to stripe rust of wheat. An advanced line from the International Winter Wheat Improvement Program (IWWIP) 130675 (Avd/Vee#1//1-27-6275/Cf 1770/3/MV171-C-17466) showed a high level of adult plant resistance to stripe rust in the field. To identify the adult plant resistance genes in this elite line, a mapping population of 190 doubled haploid (DH) lines was developed from a cross between line 130675 and the universal stripe rust-susceptible variety Avocet S. The DH population was evaluated at precision wheat stripe rust phenotyping platform, in Izmir during 2019, 2020, and 2021 cropping seasons under artificial inoculations. Composite interval mapping (CIM) identified two stable QTLs QYr.rcrrc-3B.1, and QYr.rcrrc-3B.2, which were detected in multiple years. In addition to these two QTLs, five more QTLs, QYr.rcrrc-1B, QYr.rcrrc-2A, QYr.rcrrc-3A, QYr.rcrrc-5A, and QYr.rcrrc-7D, were identified, which were specific to the cropping year (environment). All QTLs were derived from the resistant parent, except QYr.rcrrc-3A. The significant QTLs explained 3.4-20.6% of the phenotypic variance. SNP markers flanking the QTL regions can be amenable to marker-assisted selection. The best DH lines with high yield, end-use quality, and stripe rust resistance can be used for further selection for improved germplasm. SNP markers flanking the QTL regions can aid in identifying such lines.

Quantitative trait loci for yellow rust resistance in spring wheat doubled haploid populations developed from the German Federal ex situ genebank genetic resources

Novel resistance sources to the pathogen Puccinia striiformis f. sp. tritici, which causes yellow rust (stripe rust), a widespread devastating foliar disease in wheat (Triticum aestivum L.), are in demand. Here, we tested two doubled haploid (DH) spring wheat populations derived from the genetic resources for resistance to yellow rust in field trials in Germany and Egypt. Additionally, we performed tests for all-stage resistance (seedling resistance). We performed linkage mapping based on 15k Infinium SNP chip genotyping data that resulted in 3,567 and 3,457 polymorphic markers for DH Population 1 (103 genotypes) and DH Population 2 (148 genotypes), respectively. In DH Population 1, we identified a major and consistent quantitative trait locus (QTL) on chromosome 1B that explained up to 28 and 39% of the phenotypic variation in the field and seedling tests, respectively. The favorable allele was contributed by the line 'TRI-5645', a landrace from Iran, and is most probably the yellow rust resistance (Yr) gene Yr10. In DH Population 2, the favorable allele of a major QTL on chromosome 6B was contributed by the line 'TRI-5310', representing the variety 'Eureke' from France. This QTL was mainly effective in the German environments and explained up to 36% of the phenotypic variation. In Egypt, however, only a moderate resistance QTL was identified in the field tests and no resistance QTL was observed in the seedling tests. Our results demonstrate the usefulness of genetic resources to identify novel sources of resistance to yellow rust, including the "Warrior" race PstS10.

Genomic signatures of selection for resistance to stripe rust in Austrian winter wheat

We combined quantitative and population genetic methods to identify loci under selection for adult plant resistance to stripe rust in an Austrian winter wheat breeding population from 2008 to 2018. Resistance to stripe rust, a foliar disease caused by the fungus P. striiformis f. sp. tritici, in wheat (Triticum aestivum L.) is both qualitatively and quantitatively controlled. Resistance genes confer complete, race-specific resistance but are easily overcome by evolving pathogen populations, while quantitative resistance is controlled by many small- to medium-effect loci that provide incomplete yet more durable protection. Data on resistance loci can be applied in marker-assisted selection and genomic prediction frameworks. We employed genome-wide association to detect loci associated with stripe rust and selection testing to identify regions of the genome that underwent selection for stripe rust resistance in an Austrian winter wheat breeding program from 2008 to 2018. Genome-wide association mapping identified 150 resistance loci, 62 of which showed significant evidence of selection over time. The breeding population also demonstrated selection for resistance at the genome-wide level.

Importance of Landraces in Cereal Breeding for Stress Tolerance

The renewed focus on cereal landraces is a response to some negative consequences of modern agriculture and conventional breeding which led to a reduction of genetic diversity. Cereal landraces are still cultivated on marginal lands due to their adaptability to unfavourable conditions, constituting an important source of genetic diversity usable in modern plant breeding to improve the adaptation to abiotic or biotic stresses, yield performance and quality traits in limiting environments. Traditional agricultural production systems have played an important role in the evolution and conservation of wide variability in gene pools within species. Today, on-farm and ex situ conservation in gene bank collections, together with data sharing among researchers and breeders, will greatly benefit cereal improvement. Many efforts are usually made to collect, organize and phenotypically and genotypically analyse cereal landrace collections, which also utilize genomic approaches. Their use in breeding programs based on genomic selection, and the discovery of beneficial untapped QTL/genes/alleles which could be introgressed into modern varieties by MAS, pyramiding or biotechnological tools, increase the potential for their better deployment and exploitation in breeding for a more sustainable agricultural production, particularly enhancing adaptation and productivity in stress-prone environments to cope with current climate changes.

Comparison of Genomic Prediction Methods for Yellow, Stem, and Leaf Rust Resistance in Wheat Landraces from Afghanistan

Wheat rust diseases, including yellow rust (Yr; also known as stripe rust) caused by Puccinia striiformis Westend. f. sp. tritici, leaf rust (Lr) caused by Puccinia triticina Eriks. and stem rust (Sr) caused by Puccinia graminis Pres f. sp. tritici are major threats to wheat production all around the globe. Durable resistance to wheat rust diseases can be achieved through genomic-assisted prediction of resistant accessions to increase genetic gain per unit time. Genomic prediction (GP) is a promising technology that uses genomic markers to estimate genomic-assisted breeding values (GBEVs) for selecting resistant plant genotypes and accumulating favorable alleles for adult plant resistance (APR) to wheat rust diseases. To evaluate GP we compared the predictive ability of nine different parametric, semi-parametric and Bayesian models including Genomic Unbiased Linear Prediction (GBLUP), Ridge Regression (RR), Least Absolute Shrinkage and Selection Operator (LASSO), Elastic Net (EN), Bayesian Ridge Regression (BRR), Bayesian A (BA), Bayesian B (BB), Bayesian C (BC) and Reproducing Kernel Hilbert Spacing model (RKHS) to estimate GEBV’s for APR to yellow, leaf and stem rust of wheat in a panel of 363 bread wheat landraces of Afghanistan origin. Based on five-fold cross validation the mean predictive abilities were 0.33, 0.30, 0.38, and 0.33 for Yr (2016), Yr (2017), Lr, and Sr, respectively. No single model outperformed the rest of the models for all traits. LASSO and EN showed the lowest predictive ability in four of the five traits. GBLUP and RR gave similar predictive abilities, whereas Bayesian models were not significantly different from each other as well. We also investigated the effect of the number of genotypes and the markers used in the analysis on the predictive ability of the GP model. The predictive ability was highest with 1000 markers and there was a linear trend in the predictive ability and the size of the training population. The results of the study are encouraging, confirming the feasibility of GP to be effectively applied in breeding programs for resistance to all three wheat rust diseases.

Genetic Diversity and Population Structure Analysis of Triticum aestivum L. Landrace Panel from Afghanistan

Landraces are a potential source of genetic diversity and provide useful genetic resources to cope with the current and future challenges in crop breeding. Afghanistan is located close to the centre of origin of hexaploid wheat. Therefore, understanding the population structure and genetic diversity of Afghan wheat landraces is of enormous importance in breeding programmes for the development of high-yielding cultivars as well as broadening the genetic base of bread wheat. Here, a panel of 363 bread wheat landraces collected from seven north and north-eastern provinces of Afghanistan were evaluated for population structure and genetic diversity using single nucleotide polymorphic markers (SNPs). The genotyping-by-sequencing of studied landraces after quality control provided 4897 high-quality SNPs distributed across the genomes A (33.75%), B (38.73%), and D (27.50%). The population structure analysis was carried out by two methods using model-based STRUCTURE analysis and cluster-based discriminant analysis of principal components (DAPC). The analysis of molecular variance showed a higher proportion of variation within the sub-populations compared with the variation observed as a whole between sub-populations. STRUCTURE and DAPC analysis grouped the majority of the landraces from Badakhshan and Takhar together in one cluster and the landraces from Baghlan and Kunduz in a second cluster, which is in accordance with the micro-climatic conditions prevalent within the north-eastern agro-ecological zone. Genetic distance analysis was also studied to identify differences among the Afghan regions; the strongest correlation was observed for the Badakhshan and Takhar (0.003), whereas Samangan and Konarha (0.399) showed the highest genetic distance. The population structure and genetic diversity analysis highlighted the complex genetic variation present in the landraces which were highly correlated to the geographic origin and micro-climatic conditions within the agro-climatic zones of the landraces. The higher proportions of admixture could be attributed to historical unsupervised exchanges of seeds between the farmers of the central and north-eastern provinces of Afghanistan. The results of this study will provide useful information for genetic improvement in wheat and is essential for association mapping and genomic prediction studies to identify novel sources for resistance to abiotic and biotic stresses.