Incorporating Genome-Wide Association Mapping Results Into Genomic Prediction Models for Grain Yield and Yield Stability in CIMMYT Spring Bread Wheat

Frontiers in Plant Science

Jesse Poland¹  Ravi Singh²  Suchismita Mondal²  Susanne Dreisigacker²  Deepmala Sehgal²  Umesh Rosyara² 

[1] Department of Plant Pathology, Kansas State University, Manhattan, KS, United States;Global Wheat Program, International Maize and Wheat Improvement Center, Texcoco, Mexico;

关键词: Triticum aestivum;    GBS;    GWAS;    haplotypes;    genomic selection;   

DOI  :  10.3389/fpls.2020.00197

来源: DOAJ

【 摘 要 】

Untangling the genetic architecture of grain yield (GY) and yield stability is an important determining factor to optimize genomics-assisted selection strategies in wheat. We conducted in-depth investigation on the above using a large set of advanced bread wheat lines (4,302), which were genotyped with genotyping-by-sequencing markers and phenotyped under contrasting (irrigated and stress) environments. Haplotypes-based genome-wide-association study (GWAS) identified 58 associations with GY and 15 with superiority index Pi (measure of stability). Sixteen associations with GY were “environment-specific” with two on chromosomes 3B and 6B with the large effects and 8 associations were consistent across environments and trials. For Pi, 8 associations were from chromosomes 4B and 7B, indicating ‘hot spot’ regions for stability. Epistatic interactions contributed to an additional 5–9% variation on average. We further explored whether integrating consistent and robust associations identified in GWAS as fixed effects in prediction models improves prediction accuracy. For GY, the model accounting for the haplotype-based GWAS loci as fixed effects led to up to 9–10% increase in prediction accuracy, whereas for Pi this approach did not provide any advantage. This is the first report of integrating genetic architecture of GY and yield stability into prediction models in wheat.

【 授权许可】

Unknown