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Identification of candidate genes controlling fiber quality traits in upland cotton through integration of meta-QTL, significant SNP and transcriptomic data

机译:通过整合Meta-QTL,重要的SNP和转录组数据来鉴定旱麻棉中纤维质量性状的候选基因

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摘要

Background:Meta-analysis of quantitative trait locus(QTL)is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies.The combination of meta-QTL intervals,significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.Results:In our study,884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1,as a result,74 meta-QTLs were identified,including 19 meta-QTLs for fiber length;18 meta-QTLs for fiber strength;11 meta-QTLs for fiber uniformity;11 meta-QTLs for fiber elongation;and 15 meta-QTLs for micronaire.Combined with 8589 significant single nucleotide polymorphisms associated with fiber quality traits collected from 15 studies,297 candidate genes were identified in the meta-QTL intervals,20 of which showed high expression levels specifically in the developing fibers.According to the function annotations,some of the 20 key candidate genes are associated with the fiber development.Conclusions:This study provides not only stable QTLs used for marker-assisted selection,but also candidate genes to uncover the molecular mechanisms for cotton fiber development.

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  • 来源
    《棉花研究(英文版)》 |2020年第4期|324-335|共12页
  • 作者单位

    Key Laboratory of Oasis Ecology Agricultural of Xinjiang Production and Construction Coprs Agricultural College Shihezi University Shihezi 832000 Xinjiang China;

    Key Laboratory of Oasis Ecology Agricultural of Xinjiang Production and Construction Coprs Agricultural College Shihezi University Shihezi 832000 Xinjiang China;

    Hubei Key Laboratory of Agricultural Bioinformatics College of Informatics Huazhong Agricultural University Wuhan 430070 Hubei China;

    Key Laboratory of Oasis Ecology Agricultural of Xinjiang Production and Construction Coprs Agricultural College Shihezi University Shihezi 832000 Xinjiang China;

    Hubei Key Laboratory of Agricultural Bioinformatics College of Informatics Huazhong Agricultural University Wuhan 430070 Hubei China;

    Key Laboratory of Oasis Ecology Agricultural of Xinjiang Production and Construction Coprs Agricultural College Shihezi University Shihezi 832000 Xinjiang China;

    National Key Laboratory of Crop Genetic Improvement College of Plant Science and Technology Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement College of Plant Science and Technology Huazhong Agricultural University Wuhan 430070 Hubei China;

    Key Laboratory of Oasis Ecology Agricultural of Xinjiang Production and Construction Coprs Agricultural College Shihezi University Shihezi 832000 Xinjiang China;

    National Key Laboratory of Crop Genetic Improvement College of Plant Science and Technology Huazhong Agricultural University Wuhan 430070 Hubei China;

    Research Institute of Economic Crops Xinjiang Academy of Agricultural Sciences Urumqi 830091 China;

    Key Laboratory of Oasis Ecology Agricultural of Xinjiang Production and Construction Coprs Agricultural College Shihezi University Shihezi 832000 Xinjiang China;

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  • 入库时间 2022-08-19 04:49:05
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