Literature DB >> 30982110

Dissection of the genetic variation and candidate genes of lint percentage by a genome-wide association study in upland cotton.

Chengxiang Song1,2, Wei Li1, Xiaoyu Pei1, Yangai Liu1, Zhongying Ren1, Kunlun He1, Fei Zhang1, Kuan Sun1, Xiaojian Zhou1, Xiongfeng Ma3, Daigang Yang4.   

Abstract

KEY MESSAGE: A genome-wide associated study identified six novel QTLs for lint percentage. Two candidate genes underlying this trait were also detected. Increasing lint percentage (LP) is a core goal of cotton breeding. To better understand the genetic basis of LP, a genome-wide association study (GWAS) was conducted using 276 upland cotton accessions planted in multiple environments and genotyped with a CottonSNP63K array. After filtering, 10,660 high-quality single-nucleotide polymorphisms (SNPs) were retained. Population structure, principal component and neighbor-joining phylogenetic tree analyses divided the accessions into two subpopulations. These results along with linkage disequilibrium decay indicated accessions were not highly structured and exhibited weak relatedness. GWAS uncovered 23 polymorphic SNPs and 15 QTLs significantly associated with LP, with six new QTLs identified. Two candidate genes, Gh_D05G0313 and Gh_D05G1124, both contained one significant SNP, highly expressed during ovule and fiber development stages, implying that the two genes may act as the most promising regulators of LP. Furthermore, the phenotypic value of LP was found to be positively correlated with the number of favorable SNP alleles. These favorable alleles for LP identified in the study may be useful for improving lint yield.

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Year:  2019        PMID: 30982110     DOI: 10.1007/s00122-019-03333-0

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  57 in total

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Journal:  Genetics       Date:  2004-01       Impact factor: 4.562

3.  PowerMarker: an integrated analysis environment for genetic marker analysis.

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Journal:  Bioinformatics       Date:  2005-02-10       Impact factor: 6.937

4.  A unified mixed-model method for association mapping that accounts for multiple levels of relatedness.

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Journal:  Nat Genet       Date:  2005-12-25       Impact factor: 38.330

5.  Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

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6.  Toward sequencing cotton (Gossypium) genomes.

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Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
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10.  Recent advances in cotton genomics.

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Journal:  Int J Plant Genomics       Date:  2008
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  13 in total

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Authors:  S Anjan Gowda; Navin Shrestha; Taylor M Harris; Vasu Kuraparthy; Anne Z Phillips; Hui Fang; Shilpa Sood; Kuang Zhang; Fred Bourland; Rebecca Bart
Journal:  Theor Appl Genet       Date:  2022-10-08       Impact factor: 5.574

Review 3.  Genome-wide association study reveals novel quantitative trait loci and candidate genes of lint percentage in upland cotton based on the CottonSNP80K array.

Authors:  Yu Chen; Yang Gao; Pengyun Chen; Juan Zhou; Chuanyun Zhang; Zhangqiang Song; Xuehan Huo; Zhaohai Du; Juwu Gong; Chengjie Zhao; Shengli Wang; Jingxia Zhang; Furong Wang; Jun Zhang
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4.  Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races.

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5.  Detection of Stable Elite Haplotypes and Potential Candidate Genes of Boll Weight Across Multiple Environments via GWAS in Upland Cotton.

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7.  Genome-wide association reveals genetic variation of lint yield components under salty field conditions in cotton (Gossypium hirsutum L.).

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Journal:  G3 (Bethesda)       Date:  2020-02-06       Impact factor: 3.154

9.  Genome-wide association study reveals the genetic basis of fiber quality traits in upland cotton (Gossypium hirsutum L.).

Authors:  Wei Liu; Chengxiang Song; Zhongying Ren; Zhiqiang Zhang; Xiaoyu Pei; Yangai Liu; Kunlun He; Fei Zhang; Junjie Zhao; Jie Zhang; Xingxing Wang; Daigang Yang; Wei Li
Journal:  BMC Plant Biol       Date:  2020-08-27       Impact factor: 4.215

10.  Co-expression network and comparative transcriptome analysis for fiber initiation and elongation reveal genetic differences in two lines from upland cotton CCRI70 RIL population.

Authors:  Xiao Jiang; Liqiang Fan; Pengtao Li; Xianyan Zou; Zhen Zhang; Senmiao Fan; Juwu Gong; Youlu Yuan; Haihong Shang
Journal:  PeerJ       Date:  2021-07-21       Impact factor: 2.984

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