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为探寻与大豆油份含量、蛋白含量相关的关键位点,本研究选取中国东北地区92份大豆主栽品种及常用种质资源品种群体基于蛋白含量和油份含量的Meta分析,进行基于数学模型的类群划分评价,估测样本群体的结构,应用简单线性模型分析与大豆油份含量、蛋白含量相关的的位点。结果表明,通过多次迭代测试,当K=5时,即该资源群体可以分为5个亚群时,为最稳定的分类结果,并在显著水平下(p<0.05)贡献率大于1%的标记中,得到与大豆油份含量相关标记有Sat_412,Sat_195,Satt317,Sat_187,Sat_195,Satt255,Satt713,Satt468,Satt267,Satt686,Sat_294和AZ302047,对油分含量的总贡献率为39.54%。蛋白质含量相关标记有Satt683,Sat_311,Satt578,Satt181,Satt317,Satt700,Satt713,Satt255,Sat_242和Satt720对蛋白质含量总贡献率为48.39%。这些重要的标记位点为大豆油份含量和蛋白含量的分子辅助育种提供重要基础。
In order to explore key points related to soybean oil content and protein content, this study selected 92 soybean major cultivars and common germplasm resources in Northeast China based on Meta analysis of protein content and oil content, based on mathematical model Of the taxonomic assessment, estimating the structure of the sample population, using simple linear model analysis of soybean oil content, protein content-related sites. The results show that the result of multiple iteration tests shows that when K = 5, the resource group can be divided into five subgroups, which is the most stable classification result, and the contribution rate is significantly higher than 1% under the significant level (p <0.05) The results showed that Sat_412, Sat_195, Satt317, Sat_187, Sat_195, Satt255, Satt713, Satt468, Satt267, Satt686, Sat_294 and AZ302047 were all related to the content of soybean oil, and the total contribution to oil content was 39.54%. The protein content related markers Satt683, Sat_311, Satt578, Satt181, Satt317, Satt700, Satt713, Satt255, Sat_242 and Satt720 contributed to the total protein content of 48.39%. These important marker sites provide an important basis for molecular-assisted breeding of soybean oil content and protein content.