Estimating the effects of transcription factors binding and histone modifications on gene expression levels in human cells

• DOI: 10.18632/oncotarget.16988
• Publication Date: 2017-04-10T00:15:59Z
• Authors: Lu-Qiang Zhang; Qian-Zhong Li
• Keywords: 0301 basic medicine; Support Vector Machine; 9. Industry and infrastructure; Gene Expression; DNA-Directed RNA Polymerases; Cell Line; Histone Code; Histones; Research Paper: Chromosome; 03 medical and health sciences; Cell Line, Tumor; Animals; Humans; Regression Analysis; K562 Cells; 10. No inequality; Protein Processing, Post-Translational; Algorithms; Embryonic Stem Cells; Protein Binding; Transcription Factors

Transcription factors and histone modifications are vital for the regulation of gene expression. Hence, to estimate the effects of transcription factors binding and histone modifications on gene expression, we construct a statistical model for the genome-wide 15 transcription factors binding data, 10 histone modifications profiles and DNase-I hypersensitivity data in three mammalian. Remarkably, our results show POLR2A and H3K36me3 can highly and consistently predict gene expression in three cell lines. And H3K4me3, H3K27me3 and H3K9ac are more reliable predictors than other histone modifications in human embryonic stem cells. Moreover, genome-wide statistical redundancies exist within and between transcription factors and histone modifications, and these phenomena may be caused by the regulation mechanism. In further study, we find that even though transcription factors and histone modifications offer similar effects on expression levels of genome-wide genes, the effects of transcription factors and histone modifications on predictive abilities are different for genes in independent biological processes.