Signal transducers and activators of transcription-1 (STAT1) regulates microRNA transcription in interferon γ-stimulated HeLa cells

Guohua Wang, Yadong Wang, Mingxiang Teng, Denan Zhang, Lang Li, Yunlong Liu

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Background: Constructing and modeling the gene regulatory network is one of the central themes of systems biology. With the growing understanding of the mechanism of microRNA biogenesis and its biological function, establishing a microRNA-mediated gene regulatory network is not only desirable but also achievable. Methodology: In this study, we propose a bioinformatics strategy to construct the microRNA-mediated regulatory network using genome-wide binding patterns of transcription factor(s) and RNA polymerase II (RPol II), derived using chromatin immunoprecipitation following next generation sequencing (ChIP-seq) technology. Our strategy includes three key steps, identification of transcription start sites and promoter regions of primary microRNA transcripts using RPol II binding patterns, selection of cooperating transcription factors that collaboratively function with the transcription factors targeted by ChIP-seq assay, and construction of the network that contains regulatory cascades of both transcription factors and microRNAs. Principal Findings: Using CAMDA (Critical Assessment of Massive Data Analysis) 2009 data set that includes ChIP-seq data on RPol II and STAT1 (signal transducers and activators of transcription 1) in HeLa S3 cells in control condition and with interferon γ stimulation, we first identified promoter regions of 83 microRNAs in HeLa cells. We then identified two potential STAT1 collaborating factors, AP-1 and C/EBP (CCAAT enhancer-binding proteins), and further established eight feedback network elements that may regulate cellular response during interferon γ stimulation. Conclusions: This study offers a bioinformatics strategy to provide testable hypotheses on the mechanisms of microRNA-mediated transcriptional regulation, based upon genome-wide protein-DNA interaction data derived from ChIP-seq experiments.

Original languageEnglish (US)
Article numbere11794
JournalPloS one
Issue number7
StatePublished - 2010

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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