Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton

文献类型： 外文期刊

第一作者： Shi, Yuzhen

作者： Shi, Yuzhen;Liu, Aiying;Li, Junwen;Li, Shaoqi;Zhang, Jinfeng;Ma, Liujun;He, Rui;Song, Weiwu;Guo, Lixue;Lu, Quanwei;Xiang, Xianghui;Gong, Wankui;Gong, Juwu;Ge, Qun;Shang, Haihong;Deng, Xiaoying;Pan, Jingtao;Yuan, Youlu;Zhang, Jinfa

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期刊名称：THEORETICAL AND APPLIED GENETICS （ 影响因子：5.699； 五年影响因子：5.565 ）

ISSN： 0040-5752

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收录情况： SCI

摘要： Key message Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum x G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.

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