Unraveling genomic regions and candidate genes for multiple disease resistance in upland cotton using meta-QTL analysis
文献类型： 外文期刊
作者： Huo, Wen-Qi 1 ; Zhang, Zhi-Qiang 1 ; Ren, Zhong-Ying 2 ; Zhao, Jun-Jie 2 ; Song, Cheng-Xiang 2 ; Wang, Xing-Xing 2 ; Pei, Xiao-Yu 2 ; Liu, Yan-Gai 2 ; He, Kun-Lun 2 ; Zhang, Fei 2 ; Li, Xin-Yang 2 ; Li, Wei 1 ; Yang, Dai-Gang 1 ; Ma, Xiong-Feng 1 ;
作者机构： 1.Zhengzhou Univ, Sch Agr Sci, Natl Key Lab Cotton Biobreeding & Integrated Utili, Zhengzhou Res Base, Zhengzhou 450001, Peoples R China
2.Chinese Acad Agr Sci, Inst Cotton Res, Natl Key Lab Cotton Biobreeding & Integrated Utili, Anyang 455000, Peoples R China
3.Chinese Acad Agr Sci, Western Agr Res Ctr, Changji 831100, Peoples R China
关键词： Cotton; Quantitative trait loci; Meta-QTL; Disease resistance; Genomic region
期刊名称：HELIYON （ 影响因子：4.0； 五年影响因子：4.1 ）
ISSN：
年卷期： 2023 年 9 卷 8 期
页码：
收录情况： SCI
摘要： Verticillium wilt (VW), Fusarium wilt (FW) and Root-knot nematode (RKN) are the main diseases affecting cotton production. However, many reported quantitative trait loci (QTLs) for cotton resistance have not been used for agricultural practices because of inconsistencies in the cotton genetic background. The integration of existing cotton genetic resources can facilitate the dis-covery of important genomic regions and candidate genes involved in disease resistance. Here, an improved and comprehensive meta-QTL analysis was conducted on 487 disease resistant QTLs from 31 studies in the last two decades. A consensus linkage map with genetic overall length of 3006.59 cM containing 8650 markers was constructed. A total of 28 Meta-QTLs (MQTLs) were discovered, among which nine MQTLs were identified as related to resistance to multiple diseases. Candidate genes were predicted based on public transcriptome data and enriched in pathways related to disease resistance. This study used a method based on the integration of Meta-QTL, known genes and transcriptomics to reveal major genomic regions and putative candidate genes for resistance to multiple diseases, providing a new basis for marker-assisted selection of high disease resistance in cotton breeding.
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