摘要
为研究MLM混合线性模型在大豆全基因组关联分析中应用的可行性,以便精确寻找影响表型性状差异的主要基因标记位点范围,帮助检测分析个体在全基因组水平范围内遗传变异的多态性,采用混合线性模型,引入固定效应和随机效应来分解和计算基因组与多性状之间的相关性,对大豆全基因组数据与对应的表型性状进行关联分析。根据模型计算结果得出P值并展示有效基因位点图,不同性状与对应有效基因标记关联性显著突出。通过设定的模拟有效基因位点检验混合线性模型关联分析的遗传评估力,结果高出一般线形模型的效率,验证该方法在大豆全基因组关联分析上具有可行性,可为其它物种进行关联分析研究提供借鉴。
To study the feasibility of Mixed Linear Model(MLM) on soybean genome wide association study, in order to accurately identify the main gene marker loci that affect phenotypic traits by correlation analysis between soybean genome-wide data and the corresponding phenotypic traits, this study detected and analyzed the polymorphism of individual genetic variation at the genome-wide level. The main analysis method was to decompose and calculate genotype data. The effects were divided into two parts: Fixed and random. The statistical correlation of mixed linear models is introduced. According to the calculated results of the model, the P value and the display contrast figure can be used to find the effective gene loci intuitively, and the significant relationship between different traits and gene markers can be analyzed intuitively. The genetic evaluation power of hybrid linear model association analysis was tested by simulated effective gene loci, which was more efficient than the general linear model. The innovation of this method in soybean genome association study was validated, and it was worth using for reference by other species for association analysis.
作者
唐友
王永江
张继成
许薇
TANG You;WANG Yong-jiang;ZHANG Ji-cheng;XU Wei(Electrical and Information Engineering College,JiLin Agricultural Science and Technology University, Jilin 132101,China;College of Electrical and Information,Northeast Agricultural University,Harbin 150030,China)
出处
《大豆科学》
CAS
CSCD
北大核心
2019年第2期212-216,235,共6页
Soybean Science
基金
吉林农业科技学院博士(人才)科研启动基金(2018-5008)
关键词
混合线性模型
大豆
基因组
关联分析
遗传评估力
Mixed Linear Model(MLM)
Soybean
Genome-wide
Association study
Genetic assessment
