Genome Wide Association Study of Seedling and Adult Plant Leaf Rust Resistance in Elite Spring Wheat Breeding Lines

Abstract

Leaf rust is an important disease, threatening wheat production annually. Identification of resistance genes or QTLs for effective field resistance could greatly enhance our ability to breed durably resistant varieties. We applied a genome wide association study (GWAS) approach to identify resistance genes or QTLs in 338 spring wheat breeding lines from public and private sectors that were predominately developed in the Americas. A total of 46 QTLs were identified for field and seedling traits and approximately 20–30 confer field resistance in varying degrees. The 10 QTLs accounting for the most variation in field resistance explained 26–30% of the total variation (depending on traits: percent severity, coefficient of infection or response type). Similarly, the 10 QTLs accounting for most of the variation in seedling resistance to different races explained 24–34% of the variation, after correcting for population structure. Two potentially novel QTLs (QLr.umn-1AL, QLr.umn-4AS) were identified. Identification of novel genes or QTLs and validation of previously identified genes or QTLs for seedling and especially adult plant resistance will enhance understanding of leaf rust resistance and assist breeding for resistant wheat varieties. We also developed computer programs to automate field and seedling rust phenotype data conversions. This is the first GWAS study of leaf rust resistance in elite wheat breeding lines genotyped with high density 90K SNP arrays.

QTL Analysis of Spike Morphological Traits and Plant Height in Winter Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

“…The recently developed iSelect 9K and 90K arrays (Cavanagh et al, 2013; Wang et al, 2014) designed to characterize genetic variation in hexaploid wheat populations have extensive applications in QTL mapping (Wu et al, 2015b), genome-wide association studies (GWAS) (Gao et al, 2016), genomic selection (He et al, 2016), and establishment of heterotic groups (Zhao et al, 2015). In the present study, we constructed a dense genetic linkage map for the Y8679/J411 RIL population, using 10,816 polymorphic SNP markers from an iSelect 90K array and 174 polymorphic SSR markers.…”

Mining Centuries Old In situ Conserved Turkish Wheat Landraces for Grain Yield and Stripe Rust Resistance Genes

“…Therefore, to avoid potential risk of type II error, a threshold was determined by obtaining p -values within the bottom 0.1 percentile of the distribution. This approach has been used in a few recent GWA studies in wheat (Zegeye et al, 2014; Gao et al, 2016). Based on this approach, a threshold p -value of 0.001 and 0.0001 corresponded to the bottom 0.1 percentile of the distribution for grain yield and yield components and for stripe rust resistance, respectively.…”

A genome‐wide association study for partial resistance to southern corn rust in tropical maize

“…In traditional linkage mapping, biparental populations are developed to identify QTLs associated with the phenotype; on the other hand, GWAS use ancestral recombination in natural populations to find marker‐phenotype associations based on linkage disequilibrium (Zhu, Gore, Buckler, & Yu, ). GWAS generally have better mapping resolution than biparental mapping and have become more widely available to plant researchers (Gao, Kathryn Turner, Chao, Kolmer, & Anderson, ). In maize, GWAS have been used successfully to study agronomic traits (Farfan et al, ; Tian et al, ), quality traits (Owens et al, ; Suwarno, Pixley, Palacios‐Rojas, Kaeppler, & Babu, ), pest resistance (Samayoa, Malvar, Olukolu, Holland, & Butrón, ) and disease resistance (Coan et al, ; Gowda et al, ; Zila et al, ).…”