In silico and wet lab approaches to study transcriptional regulation

Abstract

Gene expression is a complicated process with multiple types of regulation, including binding of proteins termed transcription factors. This thesis looks at transcription factors and transcription factor binding site discovery through computational predictions and wet lab work to better elucidate their role in transcriptional regulation. This includes bioinformatics tools to extrapolate transcription factors common to a set of co-regulated sequences, such as genes differentially expressed in a microarray or next-generation sequencing experiment. It also includes a working pipeline to analyze next-generation sequencing data, used in the following projects: Next-generation sequencing of chromatin-immunoprecipitated CBP and p300 (two highly homologous transcription factors) bound DNA was performed to analyze their (different) roles in cell cycle regulation. Next-generation sequencing of RNA from differentiating muscle cells was also done to identify differential gene expression during myogenesis, as well as identify novel promoter regions (a common target of transcription factors). Taken together, computational and wet lab tools can enhance our knowledge of transcriptional regulation, as described by several applications to enhance our knowledge of myogenic and cell-cycle regulation in this thesis.