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A genome‐wide association study of 23 agronomic traits in Chinese wheat landraces
Author(s) -
Liu Yaxi,
Lin Yu,
Gao Shang,
Li Zhanyi,
Ma Jian,
Deng Mei,
Chen Guoyue,
Wei Yuming,
Zheng Youliang
Publication year - 2017
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.13614
Subject(s) - biology , quantitative trait locus , candidate gene , genetics , genetic marker , phenotypic trait , linkage disequilibrium , genetic association , marker assisted selection , genome wide association study , gene , genotype , phenotype , single nucleotide polymorphism
Summary Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro‐ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome‐wide association study was conducted for these traits using 52 303 DA rT‐seq markers to identify marker‐trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus ( QTL ), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty‐five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN ‐B1 and vrn‐B3 and the photoperiod response genes Ppd and PRR . Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker‐assisted selection in wheat.