title: A probabilistic approach to learn chromatin architecture and accurate inference of the NF-κB/RelA regulatory network using ChIP-Seq.
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.
authors.affiliation: Department of Internal Medicine, The University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 77555-1060, USA, Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 77555-1060, USA, Institute for Translational Sciences, The University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 77555-1060, USA, Institute of Informatics, University of Warsaw, Banacha 2, 02-097, Warsaw, Poland and Sealy Center for Molecular Medicine, The University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 77555-1060, USA.
authors.forename: Jun
authors.initials: J
authors.lastname: Yang
authors.forename: Abhishek
authors.initials: A
authors.lastname: Mitra
authors.forename: Norbert
authors.initials: N
authors.lastname: Dojer
authors.forename: Shuhua
authors.initials: S
authors.lastname: Fu
authors.forename: Maga
authors.initials: M
authors.lastname: Rowicka
authors.forename: Allan R
authors.initials: AR
authors.lastname: Brasier
mesh_terms: D020087:Alu Elements; D001665:Binding Sites; D045744:Cell Line, Tumor; D002843:Chromatin / Q000235:genetics / Q000378:metabolism*; D042002:Chromatin Assembly and Disassembly; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D053263:Gene Regulatory Networks; D015894:Genome, Human; D006801:Humans; D015233:Models, Statistical; D058977:Molecular Sequence Annotation; D016328:NF-kappa B / Q000032:analysis* / Q000235:genetics; D059372:Nucleotide Motifs; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017423:Sequence Analysis, RNA; D051996:Transcription Factor RelA / Q000235:genetics / Q000378:metabolism
chemical_list: D002843:Chromatin; D016328:NF-kappa B; C498143:RELA protein, human; D051996:Transcription Factor RelA