人类不同细胞类型之间染色质状态动态变化及其对转录水平影响的研究

Transcription is a pivotal regulation process during gene expression, and it includes a series of regulatory components and regulatory factors. Mounting evidences have proved that chromatin modification can be regarded as the proxy of gene transcription activation. It becomes more and more important to describe the dynamic changes of chromatin states, and how these changes can influence gene transcription among different human cell lines. In this study, we attempt to compare the dynamic chromatin states among different human cell lines using whole genome epigenetic modification and transcription factor binding site data through machine learning methods. By this way, we can get better understanding about the causal relationship among the epigenetic modifications can transcription regulatory factors, and reveal the scenario of chromatin dynamic changes. Our work also attempts to pave a new way for the further disease analysis caused by chromatin states disorders at transcription level.

在基因表达中，转录调控是非常重要而复杂的过程，其中包括一系列的调控元件和作用因子。越来越多的研究证据表明，染色质修饰可以被看作基因转录调控功能及活性的重要标记。因此，如何更好的描绘人类不同细胞类型中染色质状态的动态变化，以及这些变化所产生的对基因表达的影响对于我们更清楚的理解人类细胞转录调控机制是至关重要的。本研究拟利用人类不同细胞类型的全基因组表观遗传学修饰数据以及转录因子结合位点数据，通过机器学习方法来深入挖掘和预测人类不同细胞类型的染色质的状态特征，以及不同细胞类型之间染色质状态的动态变化。通过该研究，可以更好的把表观遗传学修饰过程跟转录调控过程中各个作用元件的功能紧密联系，较为完整的描绘出基因转录过程中染色质状态的动态变化规律。本研究旨在为将来进一步研究疾病过程中染色质状态的异常变化所带来的基因表达紊乱提供一个新的研究思路。