Deciphering the genetic basis of resistance to soybean cyst nematode combining IBD and association mapping

文献类型： 外文期刊

第一作者： Tian, Yu

作者： Tian, Yu;Li, Delin;Wang, Xueqing;Zhang, Hao;Li, Hongjie;Li, Ying-hui;Qiu, Li-juan;Wang, Jiajun;Luan, Xiaoyan;Liu, Xinlei;Yu, Lijie;Guo, Changhong;Reif, Jochen C.

作者机构：

期刊名称：THEORETICAL AND APPLIED GENETICS （ 影响因子：5.4； 五年影响因子：5.7 ）

ISSN： 0040-5752

年卷期： 2023 年 136 卷 3 期

页码：

收录情况： SCI

摘要： Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most devastating pathogens for soybean production worldwide. The cultivar Zhongpin03-5373 (ZP), derived from SCN-resistant progenitor parents, Peking, PI 437654 and Huipizhi Heidou, is an elite line with high resistance to SCN race3. In the current study, a pedigree variation map was generated for ZP and its ten progenitors using 3,025,264 high-quality SNPs identified from an average of 16.2 x re sequencing for each genome. Through identity by decent (IBD) tracking, we showed the dynamic change of genome and detected important IBD fragments, which revealed the comprehensively artificial selection of important traits during ZP breeding process. A total of 2,353 IBD fragments related to SCN resistance including SCN-resistant genes rhg1, rhg4 and NSFRAN07 were identified based on the resistant-related genetic paths. Moreover, 23 genomic regions underlying resistance to SCN race3 were identified by genome-wide association study (GWAS) in 481 re-sequenced cultivated soybeans. Ten common loci were found by both IBD tracking and GWAS analysis. Haplotype analysis of 16 potential candidate genes suggested a causative SNP (C/T, - 1065) located in the promoter of Glyma.08G096500 and encoding a predicted TIFY5b-related protein on chr8 was highly correlated with SCN race3 resistance. Our results more thoroughly elucidated the dynamics of genomic fragments during ZP pedigree breeding and the genetic basis of SCN resistance, which will provide useful information for gene cloning and the development of resistant soybean cultivars using a marker-assisted selection approach.

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