Literature DB >> 28628238

A genome-wide association study of 23 agronomic traits in Chinese wheat landraces.

Yaxi Liu1, Yu Lin1, Shang Gao1, Zhanyi Li1, Jian Ma1, Mei Deng1, Guoyue Chen1, Yuming Wei1, Youliang Zheng1.   

Abstract

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 DArT-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.
© 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  DArT-seq markers; Triticum aestivum; agronomic traits; association mapping; population structure; wheat landrace

Mesh:

Year:  2017        PMID: 28628238     DOI: 10.1111/tpj.13614

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  32 in total

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