基因表达调控的进化是生物物种进化的重要驱动力，ENCODE计划和高通量测序技术的不断发展，使得转录因子调控网络的重建成为分子生物学和分子医学研究的热点。目前对转录调控网络进化的研究多集中于不同物种间调控网络的比较分析，鲜有从转录因子基因家族角度进行系统研究。本课题利用生物信息学和分子进化的方法，研究人类转录因子基因家族调控网络进化的模式。以前期整合的转录因子基因家族信息库为基础，选择TP53, PAX, USF等代表性转录因子基因家族，通过序列水平、表达水平、互作和调控网络水平，定量分析转录因子倍增基因的功能分化，并结合基因家族系统进化树推断转录因子倍增基因祖先节点的调控网络状态，研究基因家族调控网络的进化规律；针对在疾病细胞中调控网络出现异常的转录因子，通过实验分析其与疾病的关系。本研究将为阐述人类转录调控网络的功能和进化提供理论依据，并为探索转录因子调控网络与人类疾病的相关性奠定基础。

Differences in gene regulation are a major driving force for species evolution. With the development of ENCODE project and high-throughput sequencing, reconstructing the regulatory circuitries of human transcription factors (TFs) attracted great interest of researchers in molecular biology and molecular medicine. Currently, a lot of research have been conducted on the evolution of gene regulation between species rather than between TF gene families. In this study, we plan to study the evolutionary patterns of gene regulatory networks of human TF gene families. Based on our database of human TF gene families, we choose representative gene families such as TP53, PAX, and USF. We will quantitative analysis the functional and expressional divergences between duplicate TF genes for these TF gene families by computing the divergence at the levels of sequence, expression, protein-protein interaction, regulatory network. In order to analyse the evolutionary patterns of regulatory networks, we will infer the ancestral regulatory networks based on the phylogenetic tree of each TF gene family. Moreover, we will experimentally test the relationship between TF regulatory networks and human diseases, for those TFs who have abnormal regulatory networks in a specific cell line. Our research will lead us better understand the function and evolution of gene regulation, and will also benefit the research of the role of TF regulatory networks in human diseases.