基于林木动态数量性状的GWAS云计算平台及其在杨树中的应用

项目名称： 基于林木动态数量性状的GWAS云计算平台及其在杨树中的应用

项目编号： No.31470675

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 农业科学

项目作者： 王忠

作者单位： 北京林业大学

项目金额： 95万元

中文摘要： 全基因组关联分析（GWAS）在医学和农业领域蓬勃发展，有了广泛的应用。而在林业领域，由于研究人员较少，林木基因组资源少，对于复杂的动态数量性状的GWAS关联分析还未取得成果。本项目拟扩展和改进医学领域的GWAS统计模型，构建一个能够关联林木动态数量性状的GWAS分析平台。这个分析平台包括边际效应，全基因组范围联合效应，基因范围内联合效用和单倍型效应等4个统计模型，用以检测SNP的显著水平和分析多种互作效应。通过扩充生物过程函数和协方差矩阵，更好地拟合动态数量性状，提高分析的精度和生物学意义。参考iPlant等云计算平台，将拟完成的统计软件和GWAS数据分析的工作流整合到面向林木GWAS分析的云计算平台。本研究还通过对美洲黒杨杂交群体的GWAS数据分析，力图解答影响杨树生长的几个关键问题和定位与此有关的遗传机制。

中文关键词： 统计模型；关联分析；全基因组关联分析；云计算；杨树

英文摘要： Genome-wide association study (GWAS) has been applied to wide applications in medicine and agriculture. In the forestry field, it has not been fruitful for GWAS association analysis of complex dynamic quantitative traits because of fewer researchers and fewer trees genomic resources. The project intends to expand and improve the GWAS statistical models applied in medicine to build a GWAS analysis platform for dynamic quantitative traits. It provides four kinds of statistical model to detect significant SNPs and several interaction effects, including marginal effect models, joint genome-wide effect models, joint gene-based effect models and haplotype effect models. We try to improve the computational accuracy and biological significance through the expansion of biological process functions and covariance matrices for better fitting of the dynamic quantitative traits. Finally all statistical software and analysis workflows will be integrated into the cloud computing platform of GWAS for forestry dynamic quantitative traits according to iPlant collaborative. The study also tries to answer several key issues with poplar growth and explain the genetic mechanisms through the data analysis of a hybrid population of Populus deltoides.

英文关键词： Statistical model;Association study;Genome-wide association study;Cloud computing;Populus