Grain Protein Content Stability and Genomic Selection for Predicting the Grain Protein Content in Wheat
Primary Author: Karansher Sandhu
Faculty Sponsor: Arron Carter
Primary College/Unit: Agricultural, Human and Natural Resource Sciences
Category: Agricultural and Natural Resource Sciences
Grain protein content (GPC) is controlled by a complex genetic system, yet it is an important quality determinant for hard red spring wheat as it has a positive effect on bread and pasta quality. GPC is highly variable among genotypes and is also variable across different environments. Thus, understanding the genetic control of wheat GPC and identifying genotypes with less variation under different environments, is an important breeding goal. The objectives of this research were to identify wheat families having less variation for GPC across environments and identify quantitative trait loci (QTL) controlling the stability of GPC. We used 650 recombinant inbred lines from the spring wheat nested association mapping (NAM) population derived from 26 diverse founder parents each crossed to one common parent, ‘Berkut’. The population was phenotyped for three years (2014-16). Genomic prediction (GP) models were developed to predict GPC and GPC stability. The GPC was highly variable between these families across environments. We selected seven families that had less variation of GPC. The stability index of each genotype was obtained by Finlay-Wilkinson regression. Genome-wide association study (GWAS) identified eight significant QTLs using a Bonferroni correction of 0.05. This study also demonstrated that genome-wide trait prediction with ridge regression/best linear unbiased estimates reached up to r = 0.69. Overall, this study helped in the identification of QTLs controlling the stability of GPC. The genomic prediction accuracies suggest that genomic selection can be used to select breeding lines having higher protein content and improve genetic gain more rapidly.