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

Yang J, Mitra A, Dojer N, Fu S, Rowicka M, Brasier AR - Nucleic Acids Res. (2013)

Bottom Line: 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.

View Article: PubMed Central - PubMed

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.

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.

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Validation of TANK as an NF-κB/RelA target. (A) Ingenuity pathway network of NF-κB family members identified in the 20% of significant peaks. Each node is a gene; edges indicate protein–protein interactions (solid lines) and activation (directed arrow). Abbreviations are BCL3, B cell CLL/lymphoma 3; BCR, B-cell receptor; NFKID, IκB-Δ; NFKBIZ, IκB-ζ; TNFSF15, TNF secreted ligand 15 kDa; NFKBIA, IκBα, IKBKB, Inhibitor of IκB kinase β; IKBKE, IκBε; TANK, TRAF family member associated NF-κB activator; TRAF, TNF-associated factor. (B) Top panel, location of NF-κB/RelA peaks on the TANK gene. Shown are TANK gene 5′-UTR, TSS and TANK exons as small green boxes. Bottom panel, NF-κB/RelA peaks (green). (C) Validation of NF-κB/RelA and AP1 binding. XChIP was performed on control or TNF-stimulated A549 cells. Chromatin was immunoprecipitated using RelA or AP1 Abs as indicated. Shown is fold enrichment of TANK promoter sequences by Q-gPCR. (D) Induction of TANK mRNA expression. A549 cells were stimulated with TNF, and TANK mRNA quantified by Q-RT-PCR. Shown is fold change in normalized TANK mRNA as a function of time. (E) Validation of NF-κB dependence on TANK expression. HeLatTA/FLAG-IκBα Mut cells were plated in parallel in the absence (−Dox) or presence (+Dox) of doxycyline (Dox, 2 μg/ml) and stimulated with TNF. TANK mRNA abundance was determined by Q-RT-PCR. (F) AP1 knockdown effect on TANK expression. A549 cells were transfected by lentiviral control shRNA (pLOK.1) or c-Jun shRNA and the pooled puromycin-resistant cells were further treated by TNF and analyzed TANK expression by Q-RT-PCR. Shown is normalized fold change mRNA expression.
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gkt493-F6: Validation of TANK as an NF-κB/RelA target. (A) Ingenuity pathway network of NF-κB family members identified in the 20% of significant peaks. Each node is a gene; edges indicate protein–protein interactions (solid lines) and activation (directed arrow). Abbreviations are BCL3, B cell CLL/lymphoma 3; BCR, B-cell receptor; NFKID, IκB-Δ; NFKBIZ, IκB-ζ; TNFSF15, TNF secreted ligand 15 kDa; NFKBIA, IκBα, IKBKB, Inhibitor of IκB kinase β; IKBKE, IκBε; TANK, TRAF family member associated NF-κB activator; TRAF, TNF-associated factor. (B) Top panel, location of NF-κB/RelA peaks on the TANK gene. Shown are TANK gene 5′-UTR, TSS and TANK exons as small green boxes. Bottom panel, NF-κB/RelA peaks (green). (C) Validation of NF-κB/RelA and AP1 binding. XChIP was performed on control or TNF-stimulated A549 cells. Chromatin was immunoprecipitated using RelA or AP1 Abs as indicated. Shown is fold enrichment of TANK promoter sequences by Q-gPCR. (D) Induction of TANK mRNA expression. A549 cells were stimulated with TNF, and TANK mRNA quantified by Q-RT-PCR. Shown is fold change in normalized TANK mRNA as a function of time. (E) Validation of NF-κB dependence on TANK expression. HeLatTA/FLAG-IκBα Mut cells were plated in parallel in the absence (−Dox) or presence (+Dox) of doxycyline (Dox, 2 μg/ml) and stimulated with TNF. TANK mRNA abundance was determined by Q-RT-PCR. (F) AP1 knockdown effect on TANK expression. A549 cells were transfected by lentiviral control shRNA (pLOK.1) or c-Jun shRNA and the pooled puromycin-resistant cells were further treated by TNF and analyzed TANK expression by Q-RT-PCR. Shown is normalized fold change mRNA expression.

Mentions: Our GO molecular functions enrichment analysis and top-scoring molecular pathways identified by the IPA knowledge base indicated that at least 15 genes in the NF-κB pathway itself were identified as NF-κB/RelA targets. A characteristic of the NF-κB/RelA pathway is that it is under negative autoregulatory control, where its activation induces negative feedback regulators, including the IκB family of inhibitors (BCL3, IκB-α, -β, -γ, -ε) and NF-κB-1 and 2. However, our analysis identified additional sites of autoregulation, including the TRAF family member associated NF-κB activator (TANK), and IκB kinase β (IKKβ; Figure 6A).


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

Yang J, Mitra A, Dojer N, Fu S, Rowicka M, Brasier AR - Nucleic Acids Res. (2013)

Validation of TANK as an NF-κB/RelA target. (A) Ingenuity pathway network of NF-κB family members identified in the 20% of significant peaks. Each node is a gene; edges indicate protein–protein interactions (solid lines) and activation (directed arrow). Abbreviations are BCL3, B cell CLL/lymphoma 3; BCR, B-cell receptor; NFKID, IκB-Δ; NFKBIZ, IκB-ζ; TNFSF15, TNF secreted ligand 15 kDa; NFKBIA, IκBα, IKBKB, Inhibitor of IκB kinase β; IKBKE, IκBε; TANK, TRAF family member associated NF-κB activator; TRAF, TNF-associated factor. (B) Top panel, location of NF-κB/RelA peaks on the TANK gene. Shown are TANK gene 5′-UTR, TSS and TANK exons as small green boxes. Bottom panel, NF-κB/RelA peaks (green). (C) Validation of NF-κB/RelA and AP1 binding. XChIP was performed on control or TNF-stimulated A549 cells. Chromatin was immunoprecipitated using RelA or AP1 Abs as indicated. Shown is fold enrichment of TANK promoter sequences by Q-gPCR. (D) Induction of TANK mRNA expression. A549 cells were stimulated with TNF, and TANK mRNA quantified by Q-RT-PCR. Shown is fold change in normalized TANK mRNA as a function of time. (E) Validation of NF-κB dependence on TANK expression. HeLatTA/FLAG-IκBα Mut cells were plated in parallel in the absence (−Dox) or presence (+Dox) of doxycyline (Dox, 2 μg/ml) and stimulated with TNF. TANK mRNA abundance was determined by Q-RT-PCR. (F) AP1 knockdown effect on TANK expression. A549 cells were transfected by lentiviral control shRNA (pLOK.1) or c-Jun shRNA and the pooled puromycin-resistant cells were further treated by TNF and analyzed TANK expression by Q-RT-PCR. Shown is normalized fold change mRNA expression.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3753626&req=5

gkt493-F6: Validation of TANK as an NF-κB/RelA target. (A) Ingenuity pathway network of NF-κB family members identified in the 20% of significant peaks. Each node is a gene; edges indicate protein–protein interactions (solid lines) and activation (directed arrow). Abbreviations are BCL3, B cell CLL/lymphoma 3; BCR, B-cell receptor; NFKID, IκB-Δ; NFKBIZ, IκB-ζ; TNFSF15, TNF secreted ligand 15 kDa; NFKBIA, IκBα, IKBKB, Inhibitor of IκB kinase β; IKBKE, IκBε; TANK, TRAF family member associated NF-κB activator; TRAF, TNF-associated factor. (B) Top panel, location of NF-κB/RelA peaks on the TANK gene. Shown are TANK gene 5′-UTR, TSS and TANK exons as small green boxes. Bottom panel, NF-κB/RelA peaks (green). (C) Validation of NF-κB/RelA and AP1 binding. XChIP was performed on control or TNF-stimulated A549 cells. Chromatin was immunoprecipitated using RelA or AP1 Abs as indicated. Shown is fold enrichment of TANK promoter sequences by Q-gPCR. (D) Induction of TANK mRNA expression. A549 cells were stimulated with TNF, and TANK mRNA quantified by Q-RT-PCR. Shown is fold change in normalized TANK mRNA as a function of time. (E) Validation of NF-κB dependence on TANK expression. HeLatTA/FLAG-IκBα Mut cells were plated in parallel in the absence (−Dox) or presence (+Dox) of doxycyline (Dox, 2 μg/ml) and stimulated with TNF. TANK mRNA abundance was determined by Q-RT-PCR. (F) AP1 knockdown effect on TANK expression. A549 cells were transfected by lentiviral control shRNA (pLOK.1) or c-Jun shRNA and the pooled puromycin-resistant cells were further treated by TNF and analyzed TANK expression by Q-RT-PCR. Shown is normalized fold change mRNA expression.
Mentions: Our GO molecular functions enrichment analysis and top-scoring molecular pathways identified by the IPA knowledge base indicated that at least 15 genes in the NF-κB pathway itself were identified as NF-κB/RelA targets. A characteristic of the NF-κB/RelA pathway is that it is under negative autoregulatory control, where its activation induces negative feedback regulators, including the IκB family of inhibitors (BCL3, IκB-α, -β, -γ, -ε) and NF-κB-1 and 2. However, our analysis identified additional sites of autoregulation, including the TRAF family member associated NF-κB activator (TANK), and IκB kinase β (IKKβ; Figure 6A).

Bottom Line: 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.

View Article: PubMed Central - PubMed

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.

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.

Show MeSH
Related in: MedlinePlus