项目名称: iPSC形成过程中表观遗传调控网络的探索
项目编号: No.31471250
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 生物科学
项目作者: 陆晨琪
作者单位: 复旦大学
项目金额: 75万元
中文摘要: 诱导多能干细胞(iPSC)在再生医学和人类疾病个性化治疗中意义重大,然而iPSC形成机制的不明确特别是表观遗传调控缺乏系统阐释,大大阻碍了其临床安全应用。表观遗传因子通常是相互协作而非独立行使功能,因此在网络层面系统研究iPSC形成的表观遗传调控机制极其重要。我们之前的研究发现模块结构是研究复杂网络的重要窗口,也是复杂网络维持稳定性和适应性的基础。本项目将构建新算法从iPSC高通量数据中推测表观遗传因子的因果关系,结合生物信息学预测结果,优化现有构图算法推导iPSC形成过程的表观遗传调控网络;通过网络模块结构分析,获得对iPSC形成的关键调控模块以及控制该模块的关键表观遗传修饰和调控因子,并在此基础上尝试优化现有iPSC的诱导方案和质量差异的鉴定方法。本项目的完成,将加深对iPSC形成和细胞命运决定中表观遗传调控机制的认识,为高质量iPSC早日安全应用临床提供帮助。
中文关键词: 诱导多能干细胞;复杂网络;模块结构;表观遗传调控;转录调控网络
英文摘要: Induced pluripotent stem cells (iPSC) play a critical role in regenerative medicine and personal treatment of human diseases. However, the mechanism of iPSC formation is not clear, especially the lack of systematic interpretation of epigenetic regulation, greatly hindered its clinical safety applications. Epigenetic factors are usually coordinated rather than the independently functions in the cell. So, study of epigenetic regulatory mechanisms at network level in iPSC formation system is extremely important. Our previous study found that the modular structure is an important window for the study of complex networks, and a key point to maintain the stability and adaptability for complex network. This project will establish a new algorithm for high-throughput data to deduce causal relationship between epigenetic factors; by combining with bioinformatics prediction, optimize algorithms to derive composition epigenetic regulatory networks in iPSC formation process; through network module structure analysis, access to critical regulatory modules for iPSC formation and key epigenetic modification and regulatory factors which controlling this module; and try to optimize the existing iPSC induction and quality identification methods. Completion of this project will deepen the understanding of epigenetic regulatory mechanisms in iPSC formation and cell fate decisions, and may help secure and high quality iPSC earlier to clinical application.
英文关键词: Induced pluripotent stem cells;Complex network;Module structure;Epigenetic regulation;Transcriptional regulation network