Identifying Loci Conferring Resistance to Leaf and Stripe Rusts in a Spring Wheat Population (Triticum aestivum) via Genome-Wide Association Mapping

Genome-wide QTL mapping for stripe rust resistance in spring wheat line PI 660122 using the Wheat 15K SNP array

Introduction

Stripe rust is a global disease of wheat. Identification of new resistance genes is key to developing and growing resistant varieties for control of the disease. Wheat line PI 660122 has exhibited a high level of stripe rust resistance for over a decade. However, the genetics of stripe rust resistance in this line has not been studied. A set of 239 recombinant inbred lines (RILs) was developed from a cross between PI 660122 and an elite Chinese cultivar Zhengmai 9023.

Methods

The RIL population was phenotyped for stripe rust response in three field environments and genotyped with the Wheat 15K single-nucleotide polymorphism (SNP) array.

Results

A total of nine quantitative trait loci (QTLs) for stripe rust resistance were mapped to chromosomes 1B (one QTL), 2B (one QTL), 4B (two QTLs), 4D (two QTLs), 6A (one QTL), 6D (one QTL), and 7D (one QTL), of which seven QTLs were stable and designated as QYrPI660122.swust-4BS, QYrPI660122.swust-4BL, QYrPI660122.swust-4DS, QYrPI660122.swust-4DL, QYrZM9023.swust-6AS, QYrZM9023.swust-6DS, and QYrPI660122.swust-7DS. QYrPI660122.swust-4DS was a major all-stage resistance QTL explaining the highest percentage (10.67%-20.97%) of the total phenotypic variation and was mapped to a 12.15-cM interval flanked by SNP markers AX-110046962 and AX-111093894 on chromosome 4DS.

Discussion

The QTL and their linked SNP markers in this study can be used in wheat breeding to improve resistance to stripe rust. In addition, 26 lines were selected based on stripe rust resistance and agronomic traits in the field for further selection and release of new cultivars.

Physiological specialization of Puccinia triticina and genome-wide association mapping provide insights into the genetics of wheat leaf rust resistance in Iran

Leaf rust caused by Puccinia triticina Erikss. (Pt) is the most widely distributed and important wheat disease worldwide. The objective of the present study was to determine the frequency of Iranian Pt races, their virulence to key resistance genes and map quantitative trait loci (QTL) for resistance to different Pt races from 185 globally diverse wheat genotypes using a genome-wide association study (GWAS) approach. The virulence pattern of the 33 Pt isolates from various wheat-growing areas of Iran on 55 wheat differentials showed that the FKTPS and FKTTS were relatively frequent pathotypes among the 18 identified races. The weighted average frequency of virulence on the resistance genes Lrb, Lr3bg, Lr14b, Lr16, Lr24, Lr3ka, Lr11 and Lr20 were high (> 90%). However, low virulence on the resistant genes Lr2a, Lr9, Lr19, Lr25, Lr28 and Lr29 indicates that these genes are still effective against the pathogen population in Iran at present. GWAS on a panel of 185 wheat genotypes against 10 Pt races resulted into 62 significant marker-trait associations (MTAs) belonged to 34 quantitative trait loci (QTL) across 16 chromosomes. Among them, 10 QTLs on chromosomes 1A, 1B, 3B, 3D, 4A, 6D, 7A and 7D were identified as potential novel QTLs, of which four QTLs (QLr.iau-3B-2, QLr.iau-7A-2, QLr.iau-7A-3 and QLr.iau-7D-2) are more interesting, as they are associated with resistance to two or more Pt races. The known and novel QTLs associated with different Pt races found here, can be used in future wheat breeding programs to recombine different loci for durable resistance against leaf rust races.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Association Analysis Identifies New Loci for Resistance to Chinese Yr26-Virulent Races of the Stripe Rust Pathogen in a Diverse Panel of Wheat Germplasm

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most destructive fungal diseases of wheat worldwide. The expanding Yr26-virulent Pst race (V26) group overcomes almost all currently deployed resistance genes in China and has continued to accumulate new virulence. Investigating the genetic architecture of stripe rust resistance in common wheat is an important basis for a successful utilization of resistance in breeding programs. A panel of 410 exotic wheat germplasms was used for characterizing new stripe rust resistance loci. This panel was genotyped using high-density wheat 660K single-nucleotide polymorphism (SNP) array, and phenotypic evaluation of seedlings for stripe rust resistance was performed using multiple Pst races. Thirty-five loci conferring resistance were identified through genome-wide association mapping, and explained phenotypic variances ranged from 53 to 75%. Of these, 14 were colocated in the proximity of the known loci, including cataloged Yr genes Yr9, Yr10, Yr26, Yr33, Yr47, Yr56, Yr57, Yr64, Yr67, Yr72, and Yr81 and three temporarily designated as YrCen, YrNP63, and YrRC detected in our quantitative trait locus (QTL) mapping studies. Seven of them (Yr9, Yr10, Yr24/26, Yr81, YrCEN, YrNP63, and YrRC) were confirmed by molecular detection or genetic analysis. New loci that were identified to be different from reported Yr genes need further confirmation. Nine QTL with significantly large phenotypic effect on resistance to all tested races were considered as major loci for effective resistance. The identified loci enrich our stripe rust resistance gene pool, and the linked SNPs should be useful for marker-assisted selection in breeding programs.