Association mapping and gene–gene interaction for stem rust resistance in CIMMYT spring wheat germplasm

Abstract

The recent emergence of wheat stem rust Ug99 and evolution of new races within the lineage threatens global wheat production because they overcome widely deployed stem rust resistance (Sr) genes that had been effective for many years. To identify loci conferring adult plant resistance to races of Ug99 in wheat, we employed an association mapping approach for 276 current spring wheat breeding lines from the International Maize and Wheat Improvement Center (CIMMYT). Breeding lines were genotyped with Diversity Array Technology (DArT) and microsatellite markers. Phenotypic data was collected on these lines for stem rust race Ug99 resistance at the adult plant stage in the stem rust resistance screening nursery in Njoro, Kenya in seasons 2008, 2009 and 2010. Fifteen marker loci were found to be significantly associated with stem rust resistance. Several markers appeared to be linked to known Sr genes, while other significant markers were located in chromosome regions where no Sr genes have been previously reported. Most of these new loci colocalized with QTLs identified recently in different biparental populations. Using the same data and Q + K covariate matrices, we investigated the interactions among marker loci using linear regression models to calculate P values for pairwise marker interactions. Resistance marker loci including the Sr2 locus on 3BS and the wPt1859 locus on 7DL had significant interaction effects with other loci in the same chromosome arm and with markers on chromosome 6B. Other resistance marker loci had significant pairwise interactions with markers on different chromosomes. Based on these results, we propose that a complex network of gene-gene interactions is, in part, responsible for resistance to Ug99. Further investigation may provide insight for understanding mechanisms that contribute to this resistance gene network.

Genetic analysis of rust resistance genes in global wheat cultivars: an overview

“…Among these genes, at least 27 genes, including Sr2 (Yr30), Sr13, Sr21, Sr22, Sr24, Sr25, Sr26, Sr27, Sr28, Sr32, Sr33, Sr35, Sr36, Sr37, Sr39, Sr40, Sr42, Sr44, Sr45, Sr46, Sr47, Sr51, Sr52, Sr53, Sr55 (Lr67/Yr46/ Pm46), Sr57 (Lr34/Yr18/Pm38), and Sr58 (Lr46/Yr29/Pm39), are effective or partially effective against the Ug99 race group [91][92][93][94][95][96][97][98][99][100]. Among these 27 genes, Sr2, Sr13, Sr22, Sr25, Sr26, Sr35, Sr39 and Sr40 were reported to be the most effective against Ug99 [87,[101][102][103]. A brief description of the details of these genes is given in Table 4.…”

Mapping QTL for agronomic traits in breeding populations

“…The most promising approach to detect epistatic QTL appears to be a full two-dimensional scan for all possible pairwise interactions. Such scans are nowadays computationally feasible and have successfully been used to detect epistatic interactions in family mapping (e.g., Buckler et al 2009;Liu et al 2011;Steinhoff et al 2012;Würschum et al 2012c), and in population mapping (e.g., Li et al 2010;Massman et al 2011;Reif et al 2011;Würschum et al 2011a, b;Yu et al 2011).…”

Genome-wide association mapping for resistance to leaf rust, stripe rust and tan spot in wheat reveals potential candidate genes

“…GWAS provides a much finer resolution than linkage mapping because it accounts for greater allelic diversity at a given locus and exploits the ancestral recombination events that have occurred in an existing diversity panel at the population level (Yu and Buckler 2006). It has been successfully used to dissect several complex traits in wheat (Breseghello and Sorrells 2006; Crossa et al 2007; Yu et al 2011; Juliana et al 2015). However, several novel quantitative trait loci (QTL) identified in GWAS studies in wheat have not been validated and functionally characterized which have limited their use in breeding programs.…”