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Journal of Integrative Agriculture  2025, Vol. 24 Issue (10): 3772-3788    DOI: 10.1016/j.jia.2024.03.008
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Identification of novel QTLs for resistance to late leaf spot in peanut by SNP array and QTL-seq analyses

Guanghui Chen1, Li Sheng2, Lijun Wu1, Liang Yin1, Shuangling Li1, Hongfeng Wang1, Xiao Jiang1, Heng Wang3, Yanmao Shi1, Fudong Zhan1, Xiaoyuan Chi1, Chunjuan Qu1#, Yan Ren1#, Mei Yuan1#

1 Key Laboratory of Peanut Biology, Genetic & Breeding, Ministry of Agriculture and Rural Affairs/Shandong Peanut Research Institute, Qingdao 266100, China

2 Qingdao Academy of Agricultural Sciences, Qingdao 266100, China

3 Rizhao Agricultural Technology Service Center, Rizhao 276800, China

 Highlights 
An environmental stable major quantitative trait locus (QTL) conferring resistance to late leaf spot disease (LLS) was identified on chromosome (Chr) 02 from peanut germplasm Mi-2.
A structural variation (SV) exists on Chr02 of the resistant parent, and the presence of this structural variation can significantly enhance the average resistance level in peanut.
Numerous NBS-LRR disease resistance genes are affected by this SV, potentially leading to their loss or replacement by chromosomal segments from other regions.
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摘要  
晚斑病(LLS)是导致花生减产的重要病害之一。花生存在多种抗晚斑病的种质资源,鉴定晚斑病抗性QTL并开发相关分子标记对花生抗晚斑病品种选育具有重要意义。本研究利用抗病种质Mi-2与感病品种SunOleic97R构建重组自交系群体,并通过48K SNP芯片对其中173个单株进行基因分型,构建了一个包含1475个SNP标记、20个连锁群的高密度遗传图谱。通过该遗传图谱进行晚斑病抗性QTL分析,共检测到11个QTL。其中,一个主效QTL qLLS.LG02在所有六个环境中都能检测到,其表型贡献率在15.57%到31.09%之间。此外,利用QTL-seq技术进行了晚斑病抗性QTL分析,通过G prime算法检测到14个晚斑病抗性QTL。其中,qLLS02qLLS03的物理位置与通过连锁图鉴定到的qLLS.LG02qLLS.LG03相重叠。对通过QTL-seq检测到的14个QTL区间的基因进行功能注释分析,发现这些QTL区间共有163个NBS-LRR类抗病基因(R基因),占花生基因组中所有R基因的22.86%,R基因的富集倍数为4.26,p值为5.19e-57。在抗性亲本Mi-2的QTL qLLS02区间,存在一个包含81个NBS-LRR基因的5Mb结构变异区间。针对该结构变异,本研究开发了一个PCR诊断标记,检测结果显示该结构变异可能导致该区间的基因缺失或被替换为其他基因,该结构变异可以提高花生晚斑病的抗性。该研究对花生晚斑病抗病育种具有重要意义。


Abstract  

Late leaf spot disease (LLS) is one of the most important diseases that cause severe yield losses in peanut.  Peanut has various sources of resistance to LLS, so the identification of resistant quantitative trait loci (QTLs) and the development of related molecular markers are of great importance for the breeding of LLS-resistant peanut.  In this study, 173 individual lines of a recombinant inbred line (RIL) population and the 48K SNP array for genotyping were used to construct a high-density genetic map with 1,475 bin markers and 20 linkage groups.  A total of 11 QTLs were obtained through QTL analysis using the constructed genetic map.  Among them, the stable major QTL qLLS.LG02 was identified on linkage group 2 in all six environments, with the phenotypic variation explained (PVE) ranging from 15.57 to 31.09%.  QTL-seq technology was also employed for a QTL analysis of LLS resistance.  As a result, 14 QTL loci related to LLS resistance were identified using the G prime algorithm.  Notably, the physical positions of qLLS02 and qLLS03 coincided with those of qLLS.LG02 and qLLS.LG03, respectively.  Gene annotation analysis within the 14 QTL intervals from QTL-seq revealed a total of 163 nucleotide-binding site–leucine-rich repeat (NBS-LRR) disease resistance genes, accounting for 22.86% of all resistance (R) genes in the peanut genome and showing a 4.26-fold enrichment with a P-value of 5.19e–57.  Within the QTL region qLLS02 of the resistant parent Mi-2, there was a 5 Mb structural variation (SV) interval containing 81 NBS-LRR genes.  A PCR diagnostic marker was developed, and validation data suggested that this SV might lead to gene deletion or replacement with other genes.  This SV has the potential to enhance peanut resistance to LLS.  The results of this study have significant implications for improving peanut breeding for LLS resistance through the development of associated molecular markers.

Keywords:  late leaf spot       SNP array        QTL-seq        disease resistance gene        structural variation        quantitative trait locus (QTL)  
Received: 17 October 2023   Online: 02 March 2024   Accepted: 29 December 2023
Fund: 
This research was funded by the Key Research and Development Program of Shandong Province, China (2022LZGC007 and 2018GNC110036), the Natural Science Foundation of Shandong Province, China (ZR2024MC038 and ZR2020QC121), the Taishan Scholar Project Funding, China (tsqn201812121), the Agricultural Scientific and Technological Innovation Project of Shandong Academy of Agricultural Sciences, China (CXGC2024G20, CXGC2023A06, CXGC2022A03, and CXGC2022F33), the Science and Technology for People’s Livelihood Project of Qingdao, China (20-3-4-26-nsh), the China Agriculture Research System (CARS-13), the National Natural Science Foundation of China (32072107), and the Major Scientific and Technological Project in Xinjiang, China (2022A02008-3) .
About author:  Guanghui Chen, E-mail: ghchen@sdpeanut.ac.cn; #Correspondence Mei Yuan, E-mail: yuanbeauty@126.com; Yan Ren, E-mail: renyan@sdpeanut.ac.cn; Chunjuan Qu, E-mail: 2891240615@qq.com

Cite this article: 

Guanghui Chen, Li Sheng, Lijun Wu, Liang Yin, Shuangling Li, Hongfeng Wang, Xiao Jiang, Heng Wang, Yanmao Shi, Fudong Zhan, Xiaoyuan Chi, Chunjuan Qu, Yan Ren, Mei Yuan. 2025. Identification of novel QTLs for resistance to late leaf spot in peanut by SNP array and QTL-seq analyses. Journal of Integrative Agriculture, 24(10): 3772-3788.

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