Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat

Abstract

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011–2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5–21.1%, 3.7–14.7%, 3.5–20.6%, and 4.4– 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

Selection signatures in the CIMMYT International Elite Spring and Semi‐arid Wheat Yield Trials

“…This genomic region that showed an increase in frequency over time in trials was also identified by Sehgal et al. (2020) using haplotype‐based GWAS. Monitoring and additional pyramiding of these QTL offer breeders new opportunities for further improvement facilitating marker‐assisted or genomic selection.…”

“…However, phenotypic data (especially from the initial years) have shown to be highly unbalanced. Therefore, we plotted allele frequency changes of recent GWAS results for grain yield derived from an extensive data set of CIMMYT advanced lines (Sehgal et al., 2020). In both yield trials, for more than half of the QTL (57% and 67% for the SAWYT and ESWYT, respectively) the favorable allele increased in frequency over time.…”

Genetic Dissection of Grain Zinc and Iron Concentration, Protein Content, Test Weight and Thousand Kernel Weight in Wheat (Triticum Aestivum L.) through Genome Wide Association Study

“…Similar LD pattern was reported by [53] (5.98 Mb) in a set of Chinese wheat landraces. In contrast, [54] reported that the whole genome LD decay was faster and it was at the distance of 2 Mb in a set of CIMMYT spring bread wheat lines. In addition, [67] found that the whole genome LD decay distance was about 3 Mb.…”

Genetic Architecture and QTL Selection Response For Kernza Perennial Grain Domestication Traits

“…Plots were created using the qqman R package (Turner 2017). For each significant marker, marker effects were determined using the lmekin function from the coxme R package (Therneau 2020) following the analysis of Sehgal et al (2020). Percent variance explained (PVE) was calculated following methods by Broman and Sen (2009 pg.…”