基于生物网络的复杂疾病相关lncRNA基因多角度挖掘技术研究

The cause of complex disease is a complex process involving in the coordination of many biological factors. Recent studies have suggested that regulatory relationships between long non-coding RNAs (lncRNAs) and other biological molecules are closely associated with complex diseases. However, there is little known about their possible regulatory mechanisms in complex diseases between lncRNAs and other biological molecules. In the subject, we attempt to propose a systematically analyzing strategy to identify the regulatory relationships, reconstruct the regulatory networks and explore the composite regulatory patterns between lncRNAs and other biological molecules for complex diseases, by integrating multi-dimensional high-throughput biological data, such as genomics, transcriptomics, proteomics, phenomics, functional genomics and next-generation sequencing data, etc. Then, we will develop novel computational methods for mining specific disease-related lncRNAs based on different biological networks. These results not only provide a basis for the drug development, clinical diagnosis and treatment, but also promote a better understanding of the underlying mechanisms of human complex diseases.

研究表明lncRNA与其他生物分子协同调控关系的紊乱与复杂疾病的发生发展密切相关。但是lncRNA与其他生物分子间调控作用的具体机制以及与复杂疾病的关联关系研究仍处于初步探索阶段。本课题将利用信息融合技术整合分析已有的基因组、转录组、蛋白质组、表型组、功能组和新一代测序数据重点研究lncRNA基因的靶的发现与识别、lncRNA基因与多种生物分子复杂协同调控网络的重建和复杂疾病相关的lncRNA与多种生物分子之间的协同作用网络，研究协同调控作用的潜在机制和疾病lncRNA 的拓扑特征, 从复杂生物网络和系统生物学角度建立适用于不同水平网络的lncRNA和人类复杂疾病关联关系的生物信息学挖掘策略，并应用于乳腺癌、前列腺癌和恶性胶质瘤等癌症数据，挖掘出疾病特异的候选lncRNA。该研究不仅可以为癌症在内的许多复杂疾病的诊断和治疗提供新的依据和靶点，同时对于阐明复杂疾病的分子机制具有重要意义。

长链非编码RNA（long non-coding RNA）是近年发现的一类长度超过200个碱基的功能性非编码RNA分子，能够通过与DNA、RNA和蛋白质相互作用，在表观遗传水平、转录水平和转录后水平调控基因的表达，在基因调控网络中扮演着十分重要的角色，在多个层面上参与细胞分化和个体发育等重要生命过程的调控，并与人类复杂疾病的发生发展密切相关。利用生物信息学方法来系统地预测复杂疾病相关lncRNA基因研究仍处于起步阶段。本项目从生物网络为出发点，整合多种组学数据开发多角度的计算策略识别复杂疾病相关lncRNA基因，为生物实验学家和临床医生在功能机制研究、临床诊断治疗和药物研发等方面提供一定的指导作用。