数字农科院2.0

Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection

文献类型： 外文期刊

作者： Jing Huang;Na Guo;Yinghui Li;Jutao Sun;Guanjun Hu;Haipeng Zhang;Yanfei Li;Xing Zhang,Jinming Zhao;Han Xing;Lijuan Qiu

作者机构：

关键词： Soybean mini core collection;Phytophthora sojae;Resistance evaluation;Association mapping;Genetic diversity

期刊名称： BMC GENETICS

ISSN： 1471-2156

年卷期： 2016 年 17 卷

页码：

收录情况： JCR（2021版）

摘要： Background: Phytophthora root and stem rot (PRR) caused by Phytophthora sojae is one of the most serious diseases affecting soybean (Glycine max (L.) Merr.) production all over the world. The most economical and environmentally-friendly way to control the disease is the exploration and utilization of resistant varieties. Results: We screened a soybean mini core collection composed of 224 germplasm accessions for resistance against eleven P. sojae isolates. Soybean accessions from the Southern and Huanghuai regions, especially the Hubei, Jiangsu, Sichuan and Fujian provinces, had the most varied and broadest spectrum of resistance. Based on gene postulation, Rps1b, Rps1c, Rps4, Rps7 and novel resistance genes were identified in resistant accessions. Consequently, association mapping of resistance to each isolate was performed with 1,645 single nucleotide polymorphism (SNP) markers. A total of 14 marker-trait associations for Phytophthora resistance were identified. Among them, four were located in known PRR resistance loci intervals, five were located in other disease resistance quantitative trait locus (QTL) regions, and five associations unmasked novel loci for PRR resistance. In addition, we also identified candidate genes related to resistance. Conclusion: This is the first P. sojae resistance evaluation conducted using the Chinese soybean mini core collection, which is a representative sample of Chinese soybean cultivars. The resistance reaction analyses provided an excellent database of resistant resources and genetic variations for future breeding programs. The SNP markers associated with resistance will facilitate marker-assisted selection (MAS) in breeding programs for resistance to PRR, and the candidate genes may be useful for exploring the mechanism underlying P. sojae resistance.

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[1]Additional file 4: of Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Guo, Na,Guanjun Hu,Jutao Sun,Huang, Jing,Yinghui Li,Xing, Han,Yanfei Li,Jinming Zhao,Zhang, Xing,Lijuan Qiu,Haipeng Zhang

[2]Additional file 2: of Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Xing, Han,Zhang, Xing,Yanfei Li,Jutao Sun,Guanjun Hu,Haipeng Zhang,Huang, Jing,Guo, Na,Jinming Zhao,Lijuan Qiu,Yinghui Li

[3]Additional file 6: of Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Zhang, Xing,Huang, Jing,Guanjun Hu,Haipeng Zhang,Xing, Han,Lijuan Qiu,Yanfei Li,Jutao Sun,Jinming Zhao,Yinghui Li,Guo, Na

[4]Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Zhang, Xing,Guanjun Hu,Xing, Han,Lijuan Qiu,Jinming Zhao,Jutao Sun,Yinghui Li,Haipeng Zhang,Huang, Jing,Guo, Na,Yanfei Li

[5]Additional file 5: of Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Yanfei Li,Yinghui Li,Lijuan Qiu,Jinming Zhao,Guo, Na,Guanjun Hu,Jutao Sun,Xing, Han,Zhang, Xing,Haipeng Zhang,Huang, Jing

[6]Additional file 1: of Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Yanfei Li,Lijuan Qiu,Jutao Sun,Xing, Han,Jinming Zhao,Huang, Jing,Guo, Na,Haipeng Zhang,Yinghui Li,Zhang, Xing,Guanjun Hu

[7]Additional file 3: of Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection. Xing, Han,Zhang, Xing,Huang, Jing,Guanjun Hu,Haipeng Zhang,Yanfei Li,Lijuan Qiu,Guo, Na,Yinghui Li,Jutao Sun,Jinming Zhao

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