Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome-wide association study using high-density SNPs

文献类型： 外文期刊

第一作者： Huang, Cong

作者： Huang, Cong;Nie, Xinhui;Shen, Chao;Zhao, Wenxia;Zhang, Xianlong;Lin, Zhongxu;Nie, Xinhui;You, Chunyuan;Li, Wu

作者机构：

关键词： cotton;yield;fibre quality;single-nucleotide polymorphism;population structure;genome-wide association study

期刊名称：PLANT BIOTECHNOLOGY JOURNAL （ 影响因子：9.803； 五年影响因子：9.555 ）

ISSN： 1467-7644

年卷期： 2017 年 15 卷 11 期

页码：

收录情况： SCI

摘要： Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton-producing and cotton-consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome-wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high-density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11975 quantified polymorphic single-nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty-eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high-resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.

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