Date of Award
Fall 2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computational Biology and Bioinformatics
First Advisor
Gerstein, Mark
Abstract
Regulation of gene expression is one of the most important and fundamental aspects of biological systems. The intricate regulation could be observed in different aspects, including the variations in individual genes, dynamic interactions between multiple genes, and complicated regulatory relationships between expression and other properties such as methylation level. Therefore, studying gene regulation at all these multiple scales is crucial. Transcription factors (TFs) are a special group of proteins that recognize specific DNA sequences and control gene expression by DNA binding. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) had been developed to identify genome-wide protein–DNA interactions. It has become the standard assay to detect TF binding sites and provides a powerful approach to studying the regulation of genes. In this dissertation, we performed several ChIP-seq-centered gene regulatory analyses, focusing on different levels. Firstly, we aimed to improve our understanding of each gene's TF binding by introducing a new method to infer better TF binding motifs. Secondly, we modeled the underlying regulatory relationships between genes with a Bayesian network and showed that this simple network outperformed traditional biological networks. Finally, as a part of the integrative analysis on a large-scale multi-tissue personal epigenomes resource, we identified a core list of TF binding motifs that were sensitive to allele-specific events and demonstrated their importance in predicting the allele-specific gene expressions.
Recommended Citation
Gao, Jiahao, "Multi-Scale Gene Regulation Analysis With ChIP-Seq and Beyond" (2023). Yale Graduate School of Arts and Sciences Dissertations. 1123.
https://elischolar.library.yale.edu/gsas_dissertations/1123
