Identification of candidate genes associated with resistance to aflatoxin production in peanut through genetic mapping and transcriptome analysis
文献类型: 外文期刊
作者: Huai, Dongxin;Huang, Li;Xue, Xiaomeng;Yu, Bolun;Ding, Yingbin;Jin, Gaorui;Liu, Hao;Pandey, Manish K.;Sudini, Hari Kishan;Luo, Huaiyong;Zhou, Xiaojing;Liu, Nian;Chen, Weigang;Yan, Liying;Chen, Yuning;Wang, Xin;Wang, Qianqian;Kang, Yanping;Wang, Zhihui;Chen, Xiaoping;Jiang, Huifang;Lei, Yong;Liao, Boshou
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关键词: 无
期刊名称: THEORETICAL AND APPLIED GENETICS
ISSN: 0040-5752
年卷期: 2025 年 138 卷 4 期
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收录情况: SCIE(2025版) ; ; EI(2025版)
摘要: Key message Two major QTLs qAftA07and qAftB06.2 for peanut aflatoxin production resistance were identified and candidate genes for them were predicted.AbstractPeanut (Arachis hypogaea L.) is a globally significant oil and economic crop, serving as a primary source of edible oil and protein. Aflatoxin contamination is a main risk factor for peanut food safety and industry development worldwide. The most cost-economic and effective control strategy entails the exploration and utilization of natural resistance in peanut, alongside the development of resistant varieties. However, the underlying mechanism of resistance to aflatoxin production (AP) in peanuts remains elusive. In this study, a RIL population derived from a cross between Zhonghua 10 (susceptible) and ICG 12625 (resistant), was used to identify quantitative trait loci (QTLs) for AP resistance. Overall, seven QTLs associated with AP resistance were mapped on five chromosomes, explaining 6.83-17.86% of phenotypic variance (PVE). Notably, only two major QTLs, namely qAftA07and qAftB06.2, were consistently detected across different environments with 6.83-16.52% PVE. To predict the candidate genes for AP resistance in qAftA07and qAftB06.2, the transcriptome analysis of seeds from parental lines inoculated with Aspergillus flavus were conducted. A total of 175 and 238 candidate genes were respectively identified in qAftA07 and qAftB06.2, encompassing genes with non-synonymous genomic variations as well as differentially expressed genes. Combined with the weighted gene co-expression network analysis, 10 and 11 genes in qAftA07 and qAftB06.2 were characterized showing a high correlation with aflatoxin content, thereby representing the most promising candidate genes within these two QTLs. These results provide valuable insights for future map-based cloning studies targeting candidate genes associated with AP resistance in peanut.
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