全基因组重测序数据高维SNP相互作用研究

项目名称： 全基因组重测序数据高维SNP相互作用研究

项目编号： No.61472158

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 计算机科学学科

项目作者： 梁艳春

作者单位： 吉林大学

项目金额： 80万元

中文摘要： 本项目拟充分利用当前用于全基因组关联分析的基因重测序数据，通过采用基于信息熵的群智能启发搜索、基于多聚类的数据压缩、基于LASSO的高维特征选择等策略来挖掘全基因组数据中的高维SNP（核苷酸多态性）相互作用，再使用基于最大化信息熵的方法对其评估，剔除由于传递性导致的间接相互作用。研究由于SNP导致的蛋白结构变化、表面结合位点与docking相关信息，通过映射相关基因，融合基因注释和Pathway信息，在序列上检查启动子motif和小RNA靶基因，并在此基础上研究蛋白相互作用网络中拓扑结构变化。将获得的高维相互作用进行系统生物学层面的信息验证和机理阐述，进行农作物分子育种和复杂人类疾病研究。本项目将提出和研发一套全基因组的高维SNP相互作用挖掘软件和并行计算平台，通过机理与数据的结合与分析，揭示相应性状和复杂疾病相关的分子遗传和代谢机理，为分子育种设计、基因组复杂性状的分子遗传改良提供范例。

中文关键词： 全基因组关联分析；高维相互作用；计算智能；信息熵；多聚类

英文摘要： The project will fully use the existing genome resequencing data obtained from the Genome Wide Association Study, use the entropy based swarm intelligence heuristic search, data extraction on multiple-clustering, LASSO based high dimensional feature selection to obtain the SNP high-way interaction in whole genome level. Then the entropy maximization strategy will be used to evaluate and validate the obtained candidate high-way interaction, where several transition-based interactions will be pruned. Then the SNPs are mapped into genes in genome. The project will work on incorporating the information of gene ontology, pathway, upstream operon motif, small RNA target gene, and the structure variants caused by SNP, binding-site and docking. All the useful information is unified in the framework of protein interaction network topology variants. The high-way SNP interactions could be validated and illustrated in molecular mechanism in system biology point of view. Then the cropsbreeding and human complex diseases as the experiments datasets will be studied. This project will study and develop a whole set of high-way SNP interaction software and parallel computational platform in whole genome level. Mechanism and data will be incorporated and analyzed. Traits and complex diseases relevant molecular inheritance and metabolism mechanism will be illustrated. The project could also benefit to crops molecular breeding design and complex genome complex traits molecular improvements.

英文关键词： Genome wide association study;High-way interaction;Computational intelligence;Information entropy;Multiple clustering