Logo image
A genome-wide association study reveals a rich genetic architecture of flour color-related traits in bread wheat
Journal article   Peer reviewed

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

S. Zhai, J. Liu, D. Xu, W. Wen, J. Yan, P. Zhang, Y. Wan, S. Cao, Y. Hao, X. Xia, …
Frontiers in Plant Science, Vol.9, Article 1136
2018
pdf
genome wide.pdfDownloadView
Published (Version of Record) Open Access
url
Free to Read *No subscription requiredView

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.

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#13 Climate Action
#15 Life on Land

Source: InCites

Metrics

73 File views/ downloads
92 Record Views

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
International collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.4 Crop Science
3.4.96 QTL
Web Of Science research areas
Plant Sciences
ESI research areas
Plant & Animal Science
Logo image