基于非编码RNA调控网络的复杂疾病致病模式发现研究

Complex disease is one of the cores of life science and related disciplines. Its occurrence and progress have been proved to be closely related to regulatory interaction of non-coding RNAs (ncRNAs). Mining pathogenesis regulations from extremely complicated ncRNA regulatory interactions is a challenging, foresight and urgent problem for complex disease analysis. As the succeeding project of the just accomplished one supported by the National Natural Science Foundation of China (major program) under Grant 91130006, this project focuses on methodology study of pathogenesis pattern discovery and intervention of complex disease based on disease-associated ncRNA interaction networks which needs be mined from sequence and expression data of different types of ncRNAs. To avoid extraordinary computation and storage, and notice the highly intra-connection characteristic of ncRNA modules in the network, we adopt a dynamic search strategy of taking a step by step approach to accomplish the construction of only the disease-associated pathogenesis ncRNA regulatory network for discovery of pathogenesis pattern. What follows is a deep analysis of the network on its topology property, graph spectrum property, controllability property etc. for functionality analysis of the discovered pathogenesis pattern. Based on analysis results, intervention scheme is studied for controlling the progress of the disease. All these will be beneficial to systematic and comprehensive understanding of the mechanism of and intervention to complex disease.

复杂疾病是生命科学及相关学科的核心研究内容之一，与非编码RNA(ncRNA)密切相关：其发生和恶化是ncRNA之间复杂调控的结果。从ncRNA之间高度复杂的调控关系中挖掘导致疾病的ncRNA调控关系，极具挑战性。本项目在2015年1月提交结题报告的国家自然科学重大研究计划培育项目成果基础上，针对新一代测序ncRNA数据和表达数据，研究致病ncRNA调控模式、并对相关ncRNA及其调控模式发现理论与方法研究。为规避建立ncRNA网络基础上致病ncRNA子网搜索所导致的计算和存储复杂性问题，鉴于疾病相关ncRNA功能模块具有内部封闭性的特点，提出步步为营的致病ncRNA调控网络动态构建技术，即从某个起点出发、通过不断搜索的动态过程，实现网络构建，并对网络的图谱特性、可控制性等拓扑特性深度分析，提出致病模式发现方案，为全面、系统了解复杂疾病的发生、发展机理和对复杂疾病实施有效控制提供有力依据。

本项目紧紧围绕非编码RNA与复杂疾病致病模式，分几个层次展开研究：全基因组SNP，SCNA层次；miRNA层次；miRNA-mRNA相关关系层次等；此外还研究了piRNA/lncRNA预测。研究内容包括复杂疾病致病miRNA的调控网络模块研究、泛癌miRNA协作关系研究、piRNA的识别、lncRNA预测研究、miRNA-mRNA交互作用及与复杂疾病关系的研究、体细胞拷贝数变异与复杂疾病的关联性研究、复杂疾病的致病位点研究等。涉及的复杂疾病包括老年性黄斑退化症(AMD)、各种神经系统疾病（神经分裂症，孤独症，多动症）以及12种典型癌症（包括膀胱癌、乳腺癌、肺癌、结肠癌、肾癌、白血病、子宫内膜癌、直肠癌等）。