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Biological insights of transcription factor through analyzing ChIP-Seq data Kaida, Ning

Abstract

ChIP-Seq is a technology for detecting in vivo transcription factor binding sites or histone modification sites on a genome wide scale. How to utilize the large scale data and find out biological insights is a challenging question for us. Here, we analyzed three ChIP-Seq data sets for human HeLa cell, includ ing data of a transcription factor called STAT1, data of RNA polymerase II (Po12), and data of histone monomethylation (Mel). With these data sets, we looked into the spacial relationship between STAT1 binding sites, Po12 binding sites, Mel flanked regions and the gene transcription start sites; we checked the intersection of locations of STAT1 binding sites, Po12 bind ing sites and Mel flanked regions; we did de novo motif discovery for the sequences around the STAT1 binding sites, and predicted several transcription factors whose binding sites may form cis-regulatory module with STAT1 binding site; we put the STAT1-centered sequences into different categories based on their spacial relationship with Po12 binding sites and Mel flanked regions, and found that the de novo discovered motifs’ occurrence rates are different in sequences of different categories; we also analyzed the ChIP-Seq data along with gene expression data, and found that STAT1 binding may be related with genes’ differential expression under IFN-gamma stimulation. We suggest that further ChIP-Seq experiment be carried out for TFs corresponding to the de novo predicted motifs, and that gene expression be characterized for the IFN-gamma stimulated HeLa cell on the whole genome scale.

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Attribution-NonCommercial-NoDerivs 3.0 Unported

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