Abstract

Both histone modifications and microRNAs (miRNAs) play pivotal role in gene expression regulation. Although numerous studies have been devoted to explore the gene regulation by miRNA and epigenetic regulations, their coordinated actions have not been comprehensively examined. In this work, we systematically investigated the combinatorial relationship between miRNA and epigenetic regulation by taking advantage of recently published whole genome-wide histone modification data and high quality miRNA targeting data. The results showed that miRNA targets have distinct histone modification patterns compared with non-targets in their promoter regions. Based on this finding, we proposed a machine learning approach to fit predictive models on the task to discern whether a gene is targeted by a specific miRNA. We found a considerable advantage in both sensitivity and specificity in diverse human cell lines. Finally, we found that our predicted miRNA targets are consistently annotated with Gene Ontology terms. Our work is the first genome-wide investigation of the coordinated action of miRNA and histone modification regulations, which provide a guide to deeply understand the complexity of transcriptional regulation.

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