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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Hard Winter Wheat Genetics Research » Research » Publications at this Location » Publication #336017

Research Project: Genetic Improvement of Hard Winter Wheat to Biotic and Abiotic Stresses

Location: Hard Winter Wheat Genetics Research

Title: Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

item Guttieri, Mary
item FRELS, KATHERINE - University Of Minnesota
item BAENZIGER, P STEPHEN - University Of Nebraska
item GROGAN, SARAH - Colorado State University
item BYRNE, PATRICK - Colorado State University
item LIU, SHUYU - Texas A&M University
item CARVER, BRETT - Oklahoma State University

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 11/14/2016
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter wheat genotypes grown in Texas, Oklahoma, Colorado, and Nebraska. Trials included drought-affected, moisture-sufficient rain-fed, and irrigated environments. Average grain weight at the 8 locations ranged from 25.4 to 35.6 mg kernel-1. Genome-wide association scans were conducted by fitting a multi-locus mixed model (MLMM) for kernel weight at each environment and over all eight environments using the extended Bayesian Information Criteria for model selection. SNP associations with kernel weight varied among the environments; associations of kernel weight with 6BS, 5BL, and 5DS SNPs were most common. In high-yield environments, associations with 7AL SNPs were important. In the multi-location analysis, associations of kernel weight with 6BS, 5DL, 1AL, and 1BL SNPs were most significant. Genotype x environment interaction was evaluated using Finlay-Wilkinson regression with a Bayesian method for simultaneous estimation of environmental and genotype parameters that incorporated genetic marker information. Genotype effect (g ^) and environmental response (b ^) were positively correlated. SNP associations with b ^ were identified by MLMM analysis, and the most significant SNP association was with a 6AS SNP. Genomic regions associated with environmental response also were generally associated with kernel weight. The rare alleles at 7AL SNPs were favorable for kernel weight and had favorable environmental stability, thus they may be most useful for breeding.