Open AccessPopulation structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome‐wide association study using high‐density SNP s
Author(s) -
Huang Cong,
Nie Xinhui,
Shen Chao,
You Chunyuan,
Li Wu,
Zhao Wenxia,
Zhang Xianlong,
Lin Zhongxu
Publication year - 2017
Publication title -
plant biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.525
H-Index - 115
eISSN - 1467-7652
pISSN - 1467-7644
DOI - 10.1111/pbi.12722
Subject(s) - biology , quantitative trait locus , genome wide association study , single nucleotide polymorphism , lint , snp , genetic association , genetic architecture , population , snp genotyping , genetics , trait , gene , genotype , agronomy , demography , sociology , computer science , programming language
Summary 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 Cotton SNP 63K 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 11 975 quantified polymorphic single‐nucleotide polymorphisms ( SNP s). 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 SNP s 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 QTL s 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 SNP s in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.