结合甲基化DNA的转录因子识别及其调控功能研究

More and more recent studies indicated that transcription factors (TFs) can bind to methylated DNA sequences. It is critical to recognize such methylation-dependent binding TFs and understand the regulatory activity of interactions between TFs and methylated DNA sequences, which may uncover the biological functions related to DNA methylation. While the next generation sequencing technology widely used in genome studies, a vast amount of data have been generated by many incorporated groups, e.g. ENCODE, TCGA. Those data can be used to predict more methylation-dependent DNA-binding TFs, and further explore their biological functions. However, it also brings a challenge to integrate and analyze the data from diverse sources. .In this study, we will conduct comprehensive analysis on high-throughput data from different cell lines to distinguish novel TFs binding to methylated DNA sequences by developing the bioinformatics methodology in gene feature selection. We will categorize identified TFs specific to methylation-dependent binding activities and their target genes into different groups, suggesting different enriched biological functions and pathways in each gene set. Based on our findings, the new database, including the information of specific binding sequences and binding sites of TFs, will be built and progressively distributed to our research community. We will collaborate with experiment groups in stem cell study to validate our discovery. The study may also bring new evidence on the methylation-related regulatory network. We expect our research consequences will become significant expansion of knowledge of epigenetic regulation of transcription, leading to a better understanding of the link between DNA methylation and chromatin structures. Thus, successful completion of this project will help to significantly improve insight into mechanism of some diseases, or even provide clear clues to the drug discovery and new therapy treatments.

最近的研究表明一些转录因子可以结合甲基化DNA，识别这些转录因子、研究转录因子-甲基化DNA的相互作用关系是理解甲基化功能的关键问题。随着测序技术在基因组研究中的广泛应用，ENCODE、TCGA等大型研究计划产生了海量生物数据，如何对这些数据进行整合及分析，准确地预测可结合甲基化DNA的转录因子并分析其生物功能是亟需解决的前沿问题。因此，本项目拟发展生物信息学方法，整合分析每种细胞相关的高通量数据，识别可以结合甲基化DNA的转录因子，分析其基因组特征与生物功能；研发结合甲基化DNA的转录因子识别及分析系统，构建甲基化DNA相关的转录因子及其结合位点数据库；在胚胎干细胞上对生物信息分析结果开展生物学实验验证。本项目的研究成果将有助于增进表观遗传学对基因转录调控的认识、加深DNA甲基化对染色质结构变化调控机制的理解，为生命科学家探索某些疾病致病机理、新的治疗方案或药物靶点的研究提供线索。

随着高通量测序和芯片技术的快速发展，基因组学的研究逐渐步入了后基因组时代，包括DNA修饰、RNA编辑、组蛋白修饰及染色质结构重塑等表观遗传学逐步成为基因调控领域的研究热点。DNA甲基化作为最早发现的表观遗传机制，随着海量数据的积累，使得研究DNA甲基化与转录因子相互作用及基因调控功能成为可能。本课题围绕转录因子与DNA甲基化相互作用关系开展研究，以发现转录因子与DNA甲基化相互作用规律及生物功能为目标，利用现有的开源数据及自主研发的技术，针对高通量的DNA甲基化数据和转录因子结合DNA的信息等构建了多种生物信息分析方法，主要开展以下四个方面的研究：（1）首先设计了识别DNA甲基化状态算法，并在胚胎干细胞等多个细胞系中预测结合甲基化DNA的转录因子；（2）分析转录因子与DNA甲基化互作的基因组特性，识别高甲基化结合位点的染色质状态，推断生物功能；（3）课题组整合相关研究成果，研发与DNA甲基化相关的转录因子分析系统与数据库系统MeDReaders；（4）针对目前缺少多对多的DNA与转录因子相互作用的高通量检测技术的问题，自主研发了首个可同时检测多种表观遗传修饰与多种转录因子相互作用的技术─DAPPL（Digital Affinity Profiling via Proximity Ligation），构建了一系列生物信息学分析算法，分析了不同修饰形式对转录因子与DNA相互作用的影响。本项目的研究成果将有助于增进在表观遗传学层面对基因转录调控的认识、加深DNA甲基化对染色质结构变化调控机制的理解，为生命科学家探索某些疾病致病机理、新的治疗方案或药物靶点的研究提供线索。