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.
Highlights
Bread wheat (Triticum aestivum L., 2n = 6x = 42, AABBDD), with global production of 761.5 million tons, is a staple food source for over 2.5 billion people worldwide and an important crop for food security (FAO, 2020)
grain yield (GY) showed significant (P < 0.001) and positive correlations with plant height (PH) in 26 elite yield trials (EYTs) × environment combinations, while the correlations with days to heading (DH) were positive in irrigated environments and negative in stress environments (MD, severe drought (SD), and heat stress (HS)) across years
Much research exploring the genetic architecture of yield and yield-associated traits has been reported in wheat using genome-wide association study (GWAS), the identification of more stable key determinants of GY remain relatively unexplored, largely due to the complexity of the trait and small panel sizes used in previous studies leading to the so-called “large p small n” or “short-fat data” problem (Diao and Vidyashankar, 2013)
Summary
Improvement of grain yield (GY) is an arduous task for the global plant-breeding community due to low heritability and intractable “genotype × environment” interactions associated with it, under stress. Low-cost genotyping platforms that generate thousands to millions of data points are available for all agronomically important crops, providing effective means for crop genetic research studies (Ganal et al, 2012). The resulting high-density genomic data have opened up new possibilities for untangling the genetic architecture of complex traits by genome-wide association study (GWAS) and to perform other genomic studies, for instance, the analysis of selective sweeps within or across species (Afzal et al, 2019; Liu et al, 2019). With genome resolution reaching megabase-scale level in wheat, it is envisioned that genomicsassisted breeding can be escalated to a scale that was not possible previously (Keeble-Gagnère et al, 2018)
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