Deciphering the Gene Regulatory Networks during Embryonic Stem Cell Differentiation

Abstract

With the development of sequencing technologies, genomics, and the advent of the era of big data, bioinformatics has become more and more important. One very important research area is the regulation of gene expression, which has become one of the hot research fields in bioinformatics. Transcription factors are important transcriptional regulators. In the process of gene expression, A key step is binding of transcription factors in gene expression by combining with a specific DNA sequence to regulate gene expression and inhibit or enhance its role. The difference between these specific DNA sequences is important for understanding gene regulation. With the rapid development of high-throughput sequencing technology, ChIP-seq, which combines chromatin immunoprecipitation technology and next-generation sequencing, provides massive data for transcription factor binding site across the genome. HiChIP, as a protein-centric chromatin conformation analysis method, is concerned because of its sensitive and efficient characteristics. In this project, we are working on the early demobilization of embryonic stem cells, in which ZIC3, Otx2, etc. play an important regulatory role. We are starting from analyzing HiChIP data on ZIC3 but mainly on calling peaks on HiChIP data, and ground tools to analysis HiChIP data. To integrate the chromatin binding properties of transcription factors with other chromatin markers. This report is based on the work done on HiChIP data during the early differentiation of stem cells, and has compared the methods required to reach the peak of this data. In addition, this project verified the output by using ground truth from histone mark ChIP-seq data (H3K27ac) and did the motif analysis from some of the output peaks.