Literature DB >> 35570221

Genome-wide association study reveals novel quantitative trait loci and candidate genes of lint percentage in upland cotton based on the CottonSNP80K array.

Yu Chen1, Yang Gao1,2, Pengyun Chen3, Juan Zhou1, Chuanyun Zhang1, Zhangqiang Song1, Xuehan Huo1, Zhaohai Du1, Juwu Gong3, Chengjie Zhao1, Shengli Wang1, Jingxia Zhang1, Furong Wang4, Jun Zhang5.   

Abstract

KEY MESSAGE: Thirty-four SNPs corresponding with 22 QTLs for lint percentage, including 13 novel QTLs, was detected via GWAS. Two candidate genes underlying this trait were also identified. Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop cultivated worldwide. Lint percentage (LP, %) is one of the important yield components, and increasing LP is a core goal of cotton breeding improvement. However, the genetic and molecular mechanisms underlying LP in upland cotton remain unclear. Here, we performed a genome-wide association study (GWAS) for LP based on 254 upland cotton accessions in four environments as well as the best linear unbiased predictors using the high-density CottonSNP80K array. In total, 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened, and 34 SNPs within 22 quantitative trait loci (QTLs) were significantly associated with LP. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2), and 50 hub genes were identified through GO enrichment and weighted gene co-expression network analysis. Two candidate genes (Gh_D01G0162 and Gh_D07G0463), which may participate in early fiber development to affect the number of fiber protrusions and LP, were also identified. Their genetic variation and expression were verified by linkage disequilibrium blocks, haplotypes, and quantitative real-time polymerase chain reaction, respectively. The weighted gene interaction network analysis showed that the expression of Gh_D07G0463 was significantly correlated with that of Gh_D01G0162. These identified SNPs, QTLs and candidate genes provide important insights into the genetic and molecular mechanisms underlying variations in LP and serve as a foundation for LP improvement via marker-assisted breeding.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Year:  2022        PMID: 35570221     DOI: 10.1007/s00122-022-04111-1

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.574


  46 in total

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Journal:  Theor Appl Genet       Date:  2017-01-31       Impact factor: 5.699

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Journal:  Nature       Date:  2003-03-27       Impact factor: 49.962

9.  Identification of Introgressed Alleles Conferring High Fiber Quality Derived From Gossypium barbadense L. in Secondary Mapping Populations of G. hirsutum L.

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Journal:  Front Plant Sci       Date:  2018-07-18       Impact factor: 5.753

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Journal:  Front Plant Sci       Date:  2019-01-09       Impact factor: 5.753

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  1 in total

1.  Identification of Candidate Genes for Lint Percentage and Fiber Quality Through QTL Mapping and Transcriptome Analysis in an Allotetraploid Interspecific Cotton CSSLs Population.

Authors:  Peng Yang; Xiaoting Sun; Xueying Liu; Wenwen Wang; Yongshui Hao; Lei Chen; Jun Liu; Hailun He; Taorui Zhang; Wanyu Bao; Yihua Tang; Xinran He; Mengya Ji; Kai Guo; Dexin Liu; Zhonghua Teng; Dajun Liu; Jian Zhang; Zhengsheng Zhang
Journal:  Front Plant Sci       Date:  2022-04-29       Impact factor: 6.627

  1 in total

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