A probabilistic approach to learn chromatin architecture and accurate inference of the NF-κB/RelA regulatory network using ChIP-Seq

Jun Yang, Abhishek Mitra, Norbert Dojer, Shuhua Fu, Malgorzata Rowicka-Kudlicka, Allan R. Brasier

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Using nuclear factor-κB (NF-κB) ChIP-Seq data, we present a framework for iterative learning of regulatory networks. For every possible transcription factor-binding site (TFBS)-putatively regulated gene pair, the relative distance and orientation are calculated to learn which TFBSs are most likely to regulate a given gene. Weighted TFBS contributions to putative gene regulation are integrated to derive an NF-κB gene network. A de novo motif enrichment analysis uncovers secondary TFBSs (AP1, SP1) at characteristic distances from NF-κB/RelA TFBSs. Comparison with experimental ENCODE ChIP-Seq data indicates that experimental TFBSs highly correlate with predicted sites. We observe that RelA-SP1-enriched promoters have distinct expression profiles from that of RelA-AP1 and are enriched in introns, CpG islands and DNase accessible sites. Sixteen novel NF-κB/RelA-regulated genes and TFBSs were experimentally validated, including TANK, a negative feedback gene whose expression is NF-κB/RelA dependent and requires a functional interaction with the AP1 TFBSs. Our probabilistic method yields more accurate NF-κB/RelA-regulated networks than a traditional, distance-based approach, confirmed by both analysis of gene expression and increased informativity of Genome Ontology annotations. Our analysis provides new insights into how co-occurring TFBSs and local chromatin context orchestrate activation of NF-κB/RelA sub-pathways differing in biological function and temporal expression patterns.

Original languageEnglish (US)
Pages (from-to)7240-7259
Number of pages20
JournalNucleic Acids Research
Volume41
Issue number15
DOIs
StatePublished - Aug 2013

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Chromatin
Genes
Transcription Factors
Binding Sites
Gene Expression
CpG Islands
Deoxyribonucleases
Gene Regulatory Networks
Introns
Learning
Genome

ASJC Scopus subject areas

  • Genetics

Cite this

A probabilistic approach to learn chromatin architecture and accurate inference of the NF-κB/RelA regulatory network using ChIP-Seq. / Yang, Jun; Mitra, Abhishek; Dojer, Norbert; Fu, Shuhua; Rowicka-Kudlicka, Malgorzata; Brasier, Allan R.

In: Nucleic Acids Research, Vol. 41, No. 15, 08.2013, p. 7240-7259.

Research output: Contribution to journalArticle

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