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利用元QTL分析解析陆地棉多病害抗性的基因组区域和候选基因

Unraveling genomic regions and candidate genes for multiple disease resistance in upland cotton using meta-QTL analysis.

作者信息

Huo Wen-Qi, Zhang Zhi-Qiang, Ren Zhong-Ying, Zhao Jun-Jie, Song Cheng-Xiang, Wang Xing-Xing, Pei Xiao-Yu, Liu Yan-Gai, He Kun-Lun, Zhang Fei, Li Xin-Yang, Li Wei, Yang Dai-Gang, Ma Xiong-Feng

机构信息

Zhengzhou Research Base, National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450001, China.

National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.

出版信息

Heliyon. 2023 Jul 27;9(8):e18731. doi: 10.1016/j.heliyon.2023.e18731. eCollection 2023 Aug.

Abstract

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 discovery 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.

摘要

黄萎病、枯萎病和根结线虫病是影响棉花生产的主要病害。然而,由于棉花遗传背景不一致,许多已报道的棉花抗性数量性状位点(QTL)尚未应用于农业生产实践。整合现有的棉花遗传资源有助于发现参与抗病性的重要基因组区域和候选基因。在此,对过去二十年中31项研究的487个抗病QTL进行了改进和全面的元QTL分析。构建了一个遗传总长度为3006.59厘摩、包含8650个标记的一致性连锁图谱。共发现28个元QTL(MQTL),其中9个MQTL被确定与多种病害抗性相关。基于公开的转录组数据预测了候选基因,并在与抗病性相关的途径中富集。本研究采用基于元QTL、已知基因和转录组学整合的方法,揭示了对多种病害抗性的主要基因组区域和推定的候选基因,为棉花育种中高抗病性的分子标记辅助选择提供了新的依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/896d/10412778/65be7290aa3b/gr1.jpg

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