基于多组学数据整合的肿瘤相关长非编码RNA优化筛选和调控机制研究

项目名称： 基于多组学数据整合的肿瘤相关长非编码RNA优化筛选和调控机制研究

项目编号： No.31471220

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 遗传学与生物信息学、细胞生物学

项目作者： 刘长宁

作者单位： 中国科学院西双版纳热带植物园

项目金额： 90万元

中文摘要： 长非编码RNA是一类具有调控功能的RNA分子，在多种信号通路及代谢调控途径中发挥重要功能，同肿瘤发生、发展及转移密切相关。由于长非编码RNA在序列、结构和表达调控上的多样性和特殊性，单纯依靠传统生物学手段研究长非编码RNA功能及其与肿瘤的关系存在很多困难。本项目将针对多种人类常见肿瘤，通过整合RNA-Seq, ChIP-Seq, RIP-seq, ChIA-PET, CNV/SNV等多组学数据，发展一套全面可靠鉴定肿瘤相关长非编码RNA的计算流程，构建由肿瘤相关转录因子，miRNA，蛋白质以及长非编码RNA参与的多元分子联合调控网络。进一步我们计划利用一系列分子生物学实验手段，通过鉴定长非编码RNA在肿瘤细胞中的表达状况、亚细胞定位、上下游结合靶点，来验证我们构建的调控网络模型并深入研究长非编码RNA的分子作用机制。

中文关键词： 长非编码RNA；基因表达调控；肿瘤；多组学数据整合

英文摘要： In recent years, long non-coding RNA (lncRNA), a class of regulatory RNA molecules, was proven to play an important role in a variety of signaling and metabolism pathways, moreover, to have a potent correlation with tumor occurrence, development and metastasis. Considering the diversity and particularity of lncRNA in sequence, structure and expression, there might be some handicaps to discover the relationship between lncRNA and tumor if only relying on the traditional biological methods. Hence, for seeking the tumor-related lncRNA more effectively, this study will develop a systematical and dependable computing method by integrating a variety of high-throughput data, such as RNA-Seq, ChIP-Seq, RIP-seq, ChIA-PET and CNV/SNV. Meanwhile, we will construct a multicomponent regulatory network including tumor-related transcription factor, miRNA, protein and lncRNA. Finally, we will carry out a train of molecular experiments to detect lncRNA's expression level, subcellular location, binding targets on upstream and downstream and so on, to confirm our network model and identify the regulatory mechanism of lncRNA.

英文关键词： Long noncoding RNA;Regulation of gene expression;Tumor;Multiple omics data integration