Literature DB >> 32894321

A high-density genetic map and multiple environmental tests reveal novel quantitative trait loci and candidate genes for fibre quality and yield in cotton.

Qishen Gu1, Huifeng Ke1, Zhengwen Liu1, Xing Lv1, Zhengwen Sun1, Man Zhang1, Liting Chen1, Jun Yang1, Yan Zhang1, Liqiang Wu1, Zhikun Li1, Jinhua Wu1, Guoning Wang1, Chengsheng Meng1, Guiyin Zhang1, Xingfen Wang2, Zhiying Ma3.   

Abstract

KEY MESSAGE: A high-density linkage map of an intraspecific RIL population was constructed using 6187 bins to identify QTLs for fibre quality- and yield-related traits in upland cotton by whole-genome resequencing. Good fibre quality and high yield are important production goals in cotton (Gossypium hirsutum L.), which is a leading natural fibre crop worldwide. However, a greater understanding of the genetic variants underlying fibre quality- and yield-related traits is still required. In this study, a large-scale population including 588 F7 recombinant inbred lines, derived from an intraspecific cross between the upland cotton cv. Nongdamian13, which exhibits high quality, and Nongda601, which exhibits a high yield, was genotyped by using 232,946 polymorphic single-nucleotide polymorphisms obtained via a whole-genome resequencing strategy with 4.3-fold genome coverage. We constructed a high-density bin linkage map containing 6187 bin markers spanning 4478.98 cM with an average distance of 0.72 cM. We identified 58 individual quantitative trait loci (QTLs) and 25 QTL clusters harbouring 94 QTLs, and 119 previously undescribed QTLs controlling 13 fibre quality and yield traits across eight environments. Importantly, the QTL counts for fibre quality in the Dt subgenome were more than two times that in the At subgenome, and chromosome D02 harboured the greatest number of QTLs and clusters. Furthermore, we discovered 24 stable QTLs for fibre quality and 12 stable QTLs for yield traits. Four novel major stable QTLs related to fibre length, fibre strength and lint percentage, and seven previously unreported candidate genes with significantly differential expression between the two parents were identified and validated by RNA-seq. Our research provides valuable information for improving the fibre quality and yield in cotton breeding.

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Year:  2020        PMID: 32894321     DOI: 10.1007/s00122-020-03676-z

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


  11 in total

1.  Analysis of transcriptome data and quantitative trait loci enables the identification of candidate genes responsible for fiber strength in Gossypium barbadense.

Authors:  Yajie Duan; Qin Chen; Quanjia Chen; Kai Zheng; Yongsheng Cai; Yilei Long; Jieyin Zhao; Yaping Guo; Fenglei Sun; Yanying Qu
Journal:  G3 (Bethesda)       Date:  2022-08-25       Impact factor: 3.542

2.  Genome-wide association study reveals that GhTRL1 and GhPIN8 affect cotton root development.

Authors:  Ziqian Cui; Shaodong Liu; Changwei Ge; Qian Shen; Siping Zhang; Huijuan Ma; Ruihua Liu; Xinhua Zhao; Ruida Liu; Pengzhen Li; Hongchen Wang; Qidi Wu; Chaoyou Pang; Jing Chen
Journal:  Theor Appl Genet       Date:  2022-08-14       Impact factor: 5.574

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

Authors:  Zhen Feng; Libei Li; Minqiang Tang; Qibao Liu; Zihan Ji; Dongli Sun; Guodong Liu; Shuqi Zhao; Chenjue Huang; Yanan Zhang; Guizhi Zhang; Shuxun Yu
Journal:  Front Plant Sci       Date:  2022-06-13       Impact factor: 6.627

4.  Identification of candidate genes involved in salt stress response at germination and seedling stages by QTL mapping in upland cotton.

Authors:  Anhui Guo; Ying Su; Hushuai Nie; Bin Li; Xingkun Ma; Jinping Hua
Journal:  G3 (Bethesda)       Date:  2022-05-30       Impact factor: 3.542

5.  A stable QTL qSalt-A04-1 contributes to salt tolerance in the cotton seed germination stage.

Authors:  Qishen Gu; Huifeng Ke; Chenchen Liu; Xing Lv; Zhengwen Sun; Zhengwen Liu; Wei Rong; Jun Yang; Yan Zhang; Liqiang Wu; Guiyin Zhang; Xingfen Wang; Zhiying Ma
Journal:  Theor Appl Genet       Date:  2021-04-29       Impact factor: 5.699

6.  Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum.

Authors:  Xiao Jiang; Juwu Gong; Jianhong Zhang; Zhen Zhang; Yuzhen Shi; Junwen Li; Aiying Liu; Wankui Gong; Qun Ge; Xiaoying Deng; Senmiao Fan; Haodong Chen; Zhengcheng Kuang; Jingtao Pan; Jincan Che; Shuya Zhang; Tingting Jia; Renhui Wei; Quanjia Chen; Shoujun Wei; Haihong Shang; Youlu Yuan
Journal:  Front Plant Sci       Date:  2021-12-16       Impact factor: 5.753

7.  Identification of yield-related genes through genome-wide association: case study of weeping forsythia, an emerging medicinal crop.

Authors:  Yong Li; Qiong Wu; Hong-Li Liu; Nan-Cai Pei; Yan-Xia He; Jine Quan
Journal:  Genes Genomics       Date:  2021-11-12       Impact factor: 2.164

8.  Quantitative Trait Locus Analysis and Identification of Candidate Genes Affecting Seed Size and Shape in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense.

Authors:  Luyao Wu; Bing Jia; Wenfeng Pei; Li Wang; Jianjiang Ma; Man Wu; Jikun Song; Shuxian Yang; Yue Xin; Li Huang; Pan Feng; Jinfa Zhang; Jiwen Yu
Journal:  Front Plant Sci       Date:  2022-03-22       Impact factor: 5.753

Review 9.  Inheritance, QTLs, and Candidate Genes of Lint Percentage in Upland Cotton.

Authors:  Hao Niu; Qun Ge; Haihong Shang; Youlu Yuan
Journal:  Front Genet       Date:  2022-03-31       Impact factor: 4.772

10.  Construction of a high-density genetic map and identification of QTLs related to agronomic and physiological traits in an interspecific (Gossypium hirsutum × Gossypium barbadense) F2 population.

Authors:  Zhanfeng Si; Shangkun Jin; Jiedan Chen; Sen Wang; Lei Fang; Xiefei Zhu; Tianzhen Zhang; Yan Hu
Journal:  BMC Genomics       Date:  2022-04-15       Impact factor: 4.547

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