多性状全基因组关联分析新方法的探索

项目名称： 多性状全基因组关联分析新方法的探索

项目编号： No.31301229

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 农业科学

项目作者： 张瑾

作者单位： 南京农业大学

项目金额： 23万元

中文摘要： 由于人工选择的品种群体构建时间短、SNP标记密度高和利用历史重组机会多，致使近年来关联分析在植物遗传研究中应用较为广泛。但是，目前的分析方法一般采用单性状分析，假阳性率较高，功效有待提高。研究已表明，多性状联合分析能提高遗传分析功效与精度，剖析复杂性状的一因多效。在已提出品种群体数量性状上位性关联分析和抗性性状多QTL检测新方法的前期工作基础上，本项目将研究多性状联合遗传分析的参数估计算法；进而构建多性状联合的全基因组关联分析技术平台，经Monte Carlo计算机模拟研究验证后，研制相应的计算机软件包；用于286个大豆品种群体籽粒大小与形状性状的多性状全基因组关联分析，揭示这些相关性状的遗传基础是一因多效还是基因连锁。预计发表SCI论文2篇，研制软件1套。

中文关键词： 多性状；关联分析；多基因；参数估计；品种群体

英文摘要： In the past several years genome-wide association study has been widely adopted in the genetic analysis of complex traits in plants owing to short time in the construction of mapping population, high density of SNP markers, and excessive recombinant in the breeding of crop cultivar. However, almost all the current methodologies are available only for a single quantitative trait. This results in high false positive rate and low power in the detection of quantitative trait loci (QTL). As we know, multi-trait joint analysis can increase the power and precision, and distinguish pleiotropic QTL from multiple linked QTL. Based on epistatic association study for quantitative traits and multi-QTL mapping for resistance traits in crop cultivars, in this study we will investigate the algorithm of parameter estimation for multi-trait joint analysis, and its purpose is to set up the technologic platform of multi-trait genome-wide association study. Once the new method is validated by Monte Carlo simulation experiments, the corresponding software will be developed. The validated method and software will be used to carry out multi-trait genome-wide association studies for seed size and shape traits in 286 soybean cultivars. If doing so, the QTL cluster for the above traits in our previous studies may be identified. In other w

英文关键词： Multiple trait；Association study；Polygenic；Parameter estimation；Cultivar population