A genome-wide association study reveals a rich genetic architecture of flour color-related traits in bread wheat

Zhai, S., Liu, J., Xu, D., Wen, W., Yan, J., Zhang, P., Wan, Y., Cao, S., Hao, Y., Xia, X., Ma, W.ORCID: 0000-0002-1264-866X and He, Z. (2018) A genome-wide association study reveals a rich genetic architecture of flour color-related traits in bread wheat. Frontiers in Plant Science, 9 . Article 1136.

Abstract

Flour color-related traits, including brightness (L*), redness (a*), yellowness (b*) and yellow pigment content (YPC), are very important for end-use quality of wheat. Uncovering the genetic architecture of these traits is necessary for improving wheat quality by marker-assisted selection (MAS). In the present study, a genome-wide association study (GWAS) was performed on a collection of 166 bread wheat cultivars to better understand the genetic architecture of flour color-related traits using the wheat 90 and 660 K SNP arrays, and 10 allele-specific markers for known genes influencing these traits. Fifteen, 28, 25, and 32 marker–trait associations (MTAs) for L*, a*, b*, and YPC, respectively, were detected, explaining 6.5–20.9% phenotypic variation. Seventy-eight loci were consistent across all four environments. Compared with previous studies, Psy-A1, Psy-B1, Pinb-D1, and the 1B•1R translocation controlling flour color-related traits were confirmed, and four loci were novel. Two and 11 loci explained much more phenotypic variation of a* and YPC than phytoene synthase 1 gene (Psy1), respectively. Sixteen candidate genes were predicted based on biochemical information and bioinformatics analyses, mainly related to carotenoid biosynthesis and degradation, terpenoid backbone biosynthesis and glycolysis/gluconeogenesis. The results largely enrich our knowledge of the genetic basis of flour color-related traits in bread wheat and provide valuable markers for wheat quality improvement. The study also indicated that GWAS was a powerful strategy for dissecting flour color-related traits and identifying candidate genes based on diverse genotypes and high-throughput SNP arrays.

Item Type:	Journal Article
Murdoch Affiliation(s):	School of Veterinary and Life Sciences
Publisher:	Frontiers
Copyright:	© 2018 Zhai, Liu, Xu, Wen, Yan, Zhang, Wan, Cao, Hao, Xia, Ma and He.
URI:	http://researchrepository.murdoch.edu.au/id/eprint/41722

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