癌基因 Ras 诱导细胞衰老过程基因动态调控网络的分析与建模

Cellular senescence is an important tumor-suppressor mechanism that prevents the propagation of damaged cells, and is also closely related to organismal aging and age-related degenerative diseases. The aberrant activation of oncogene Ras could induce cellular senescence in human fibroblast cells. The Ras-induced senescence is a dynamic process which takes about seven days to enter a stable senescence state. Multiple regulatory mechanisms were found to be involved in this process, and during which the cell morphology, gene expression pattern and epigenetic profiles change dramatically. However the detailed dynamic properties of the gene regulatory network during this process were poorly understood. In this study, we will use an interdisciplinary strategy by taking the advantage of bioinformatics modeling, and the new emerging high throughput DNA sequencing technology and synthetic biology experiment approaches to study the dynamics of the gene regulatory network during the Ras-induced senescence process. We will focus on developing new approaches to construct multi-factor and multi-layer gene regulatory networks, tracing the dynamics of the core-regulatory genes and microRNAs, analyzing the robustness and dynamic property of the regulatory networks, and identifying the tipping point of the network state and critical transition genes, to better understand the gene regulatory mechanism during cellular senescence process. And a new interdisciplinary methodology to systematically study the dynamic gene regulatory mechanism of important biological processes will be developed.

细胞衰老是一种重要的抑癌机制，同时与个体衰老和多种老年病的发生密切相关。癌基因Ras异常活化会诱导正常增殖的人成纤维细胞进入细胞衰老状态。这是一个持续约7天的动态过程，涉及到多种基因调控因素，期间细胞在形态、基因表达和表观基因组状态等方面发生一系列变化，最终不可逆地脱离细胞周期，进入稳定的细胞衰老状态。本课题综合利用信息科学的理论与方法，通过高通量组学和合成生物学等的新兴实验手段，针对细胞衰老过程的基因动态调控网络开展计算与实验紧密结合的系统研究。从多层次基因调控网络构建、核心调控基因动力学特性观测、动态调控网络建模与分析、网络状态转换临界点和标志物识别等方面，探究癌基因Ras诱导细胞衰老过程的基因调控规律，并为从交叉学科角度研究重要生物过程的基因动态调控规律探索新的方法策略。

本项目综合多种高通量基因组学技术，对人成纤维细胞衰老过程的基因调控规律进行了系统研究，取得以下成果：1. 构建了细胞衰老基因网络，并发表了人类细胞衰老基因数据库HCSGD；2. 通过时间序列RNA-seq技术观测了细胞衰老过程基因网络动态调控变化，对基因动态调控网络进行了分析与建模；3. 通过CRISPR和RNAi干扰解析了细胞衰老调控网络的关键基因；4.对细胞衰老过程的染色质结构变化进行了实验和计算分析，建立了发表了染色质相互作用的预测模型和分析软件，发现了细胞衰老过程染色质的结构变化规律；5.比较了不同抗衰老策略在物种间的异同。