Literature DB >> 32652678

Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (Gossypium hirsutum L.).

Libei Li1,2, Chi Zhang1,2, Jianqin Huang1, Qibao Liu1,2, Hengling Wei2, Hantao Wang2, Guoyuan Liu2, Lijiao Gu2, Shuxun Yu1,2.   

Abstract

Although upland cotton (Gossypium hirsutism L.) originated in the tropics, this early maturity cotton can be planted as far north as 46°N in China due to the accumulation of numerous phenotypic and physiological adaptations during domestication. However, how the genome of early maturity cotton has been altered by strong human selection remains largely unknown. Herein, we report a cotton genome variation map generated by the resequencing of 436 cotton accessions. Whole-genome scans for sweep regions identified 357 putative selection sweeps covering 4.94% (112 Mb) of the upland cotton genome, including 5184 genes. These genes were functionally related to flowering time control, hormone catabolism, ageing and defence response adaptations to environmental changes. A genome-wide association study (GWAS) for seven early maturity traits identified 307 significant loci, 22.48% (69) of which overlapped with putative selection sweeps that occurred during the artificial selection of early maturity cotton. Several previously undescribed candidate genes associated with early maturity were identified by GWAS. This study provides insights into the genetic basis of early maturity in upland cotton as well as breeding resources for cotton improvement.
© 2020 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Entities:  

Keywords:  early maturity; flowering time; genome-wide association analysis; upland cotton

Year:  2020        PMID: 32652678      PMCID: PMC7769233          DOI: 10.1111/pbi.13446

Source DB:  PubMed          Journal:  Plant Biotechnol J        ISSN: 1467-7644            Impact factor:   9.803


  69 in total

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10.  Identification of favorable SNP alleles and candidate genes for traits related to early maturity via GWAS in upland cotton.

Authors:  Junji Su; Chaoyou Pang; Hengling Wei; Libei Li; Bing Liang; Caixiang Wang; Meizhen Song; Hantao Wang; Shuqi Zhao; Xiaoyun Jia; Guangzhi Mao; Long Huang; Dandan Geng; Chengshe Wang; Shuli Fan; Shuxun Yu
Journal:  BMC Genomics       Date:  2016-08-30       Impact factor: 3.969

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  16 in total

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

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2.  Characterization and Functional Analysis of GhNAC82, A NAM Domain Gene, Coordinates the Leaf Senescence in Upland Cotton (Gossypium hirsutum L.).

Authors:  Chenlei Wang; Tengyu Li; Qibao Liu; Libei Li; Zhen Feng; Shuxun Yu
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Review 4.  Genetic Diversity, QTL Mapping, and Marker-Assisted Selection Technology in Cotton (Gossypium spp.).

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7.  Insights Into MicroRNA-Mediated Regulation of Flowering Time in Cotton Through Small RNA Sequencing.

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Journal:  Front Plant Sci       Date:  2022-03-31       Impact factor: 6.627

8.  Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (Gossypium hirsutum L.).

Authors:  Libei Li; Chi Zhang; Jianqin Huang; Qibao Liu; Hengling Wei; Hantao Wang; Guoyuan Liu; Lijiao Gu; Shuxun Yu
Journal:  Plant Biotechnol J       Date:  2020-08-01       Impact factor: 9.803

9.  Uncovering Novel Genomic Regions and Candidate Genes for Senescence-Related Traits by Genome-Wide Association Studies in Upland Cotton (Gossypium hirsutum L.).

Authors:  Qibao Liu; Libei Li; Zhen Feng; Shuxun Yu
Journal:  Front Plant Sci       Date:  2022-01-05       Impact factor: 5.753

10.  QTL and candidate gene identification of the node of the first fruiting branch (NFFB) by QTL-seq in upland cotton (Gossypium hirsutum L.).

Authors:  Jingjing Zhang; Xiaoyun Jia; Xiaohao Guo; Hengling Wei; Meng Zhang; Aimin Wu; Shuaishuai Cheng; Xiaoqian Cheng; Shuxun Yu; Hantao Wang
Journal:  BMC Genomics       Date:  2021-12-06       Impact factor: 3.969

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