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Bang I, Khanh Nong L, Young Park J, Thi Le H, Mok Lee S, Kim D. ChEAP: ChIP-exo analysis pipeline and the investigation of Escherichia coli RpoN protein-DNA interactions. Comput Struct Biotechnol J 2022; 21:99-104. [PMID: 36544470 PMCID: PMC9735260 DOI: 10.1016/j.csbj.2022.11.053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/25/2022] [Accepted: 11/25/2022] [Indexed: 12/03/2022] Open
Abstract
Genome-scale studies of the bacterial regulatory network have been leveraged by declining sequencing cost and advances in ChIP (chromatin immunoprecipitation) methods. Of which, ChIP-exo has proven competent with its near-single base-pair resolution. While several algorithms and programs have been developed for different analytical steps in ChIP-exo data processing, there is a lack of effort in incorporating them into a convenient bioinformatics pipeline that is intuitive and publicly available. In this paper, we developed ChIP-exo Analysis Pipeline (ChEAP) that executes the one-step process, starting from trimming and aligning raw sequencing reads to visualization of ChIP-exo results. The pipeline was implemented on the interactive web-based Python development environment - Jupyter Notebook, which is compatible with the Google Colab cloud platform to facilitate the sharing of codes and collaboration among researchers. Additionally, users could exploit the free GPU and CPU resources allocated by Colab to carry out computing tasks regardless of the performance of their local machines. The utility of ChEAP was demonstrated with the ChIP-exo datasets of RpoN sigma factor in E. coli K-12 MG1655. To analyze two raw data files, ChEAP runtime was 2 min and 25 s. Subsequent analyses identified 113 RpoN binding sites showing a conserved RpoN binding pattern in the motif search. ChEAP application in ChIP-exo data analysis is extensive and flexible for the parallel processing of data from various organisms.
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Affiliation(s)
- Ina Bang
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Linh Khanh Nong
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Joon Young Park
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Hoa Thi Le
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Sang- Mok Lee
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Donghyuk Kim
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea,Schools of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea,Corresponding author at: School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.
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2
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Bal E, Kumar R, Hadigol M, Holmes AB, Hilton LK, Loh JW, Dreval K, Wong JCH, Vlasevska S, Corinaldesi C, Soni RK, Basso K, Morin RD, Khiabanian H, Pasqualucci L, Dalla-Favera R. Super-enhancer hypermutation alters oncogene expression in B cell lymphoma. Nature 2022; 607:808-815. [PMID: 35794478 PMCID: PMC9583699 DOI: 10.1038/s41586-022-04906-8] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 05/25/2022] [Indexed: 12/16/2022]
Abstract
Diffuse large B cell lymphoma (DLBCL) is the most common B cell non-Hodgkin lymphoma and remains incurable in around 40% of patients. Efforts to sequence the coding genome identified several genes and pathways that are altered in this disease, including potential therapeutic targets1-5. However, the non-coding genome of DLBCL remains largely unexplored. Here we show that active super-enhancers are highly and specifically hypermutated in 92% of samples from individuals with DLBCL, display signatures of activation-induced cytidine deaminase activity, and are linked to genes that encode B cell developmental regulators and oncogenes. As evidence of oncogenic relevance, we show that the hypermutated super-enhancers linked to the BCL6, BCL2 and CXCR4 proto-oncogenes prevent the binding and transcriptional downregulation of the corresponding target gene by transcriptional repressors, including BLIMP1 (targeting BCL6) and the steroid receptor NR3C1 (targeting BCL2 and CXCR4). Genetic correction of selected mutations restored repressor DNA binding, downregulated target gene expression and led to the counter-selection of cells containing corrected alleles, indicating an oncogenic dependency on the super-enhancer mutations. This pervasive super-enhancer mutational mechanism reveals a major set of genetic lesions deregulating gene expression, which expands the involvement of known oncogenes in DLBCL pathogenesis and identifies new deregulated gene targets of therapeutic relevance.
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Affiliation(s)
- Elodie Bal
- Institute for Cancer Genetics, Columbia University, New York, NY, USA
| | - Rahul Kumar
- Institute for Cancer Genetics, Columbia University, New York, NY, USA
- Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, India
| | - Mohammad Hadigol
- Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Antony B Holmes
- Institute for Cancer Genetics, Columbia University, New York, NY, USA
| | - Laura K Hilton
- Centre for Lymphoid Cancer, BC Cancer Research Centre, Vancouver, British Columbia, Canada
| | - Jui Wan Loh
- Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Kostiantyn Dreval
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Jasper C H Wong
- Centre for Lymphoid Cancer, BC Cancer Research Centre, Vancouver, British Columbia, Canada
| | - Sofija Vlasevska
- Institute for Cancer Genetics, Columbia University, New York, NY, USA
| | | | - Rajesh Kumar Soni
- Proteomics and Macromolecular Crystallography Shared Resource, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Katia Basso
- Institute for Cancer Genetics, Columbia University, New York, NY, USA
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA
| | - Ryan D Morin
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada
- Genome Sciences Center, BC Cancer Research Institute, Vancouver, British Columbia, Canada
| | - Hossein Khiabanian
- Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
- Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Laura Pasqualucci
- Institute for Cancer Genetics, Columbia University, New York, NY, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA.
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA.
| | - Riccardo Dalla-Favera
- Institute for Cancer Genetics, Columbia University, New York, NY, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA.
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA.
- Department of Genetics & Development, Columbia University, New York, NY, USA.
- Department of Microbiology & Immunology, Columbia University, New York, NY, USA.
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3
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Scaffold association factor B (SAFB) is required for expression of prenyltransferases and RAS membrane association. Proc Natl Acad Sci U S A 2020; 117:31914-31922. [PMID: 33257571 DOI: 10.1073/pnas.2005712117] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Inhibiting membrane association of RAS has long been considered a rational approach to anticancer therapy, which led to the development of farnesyltransferase inhibitors (FTIs). However, FTIs proved ineffective against KRAS-driven tumors. To reveal alternative therapeutic strategies, we carried out a genome-wide CRISPR-Cas9 screen designed to identify genes required for KRAS4B membrane association. We identified five enzymes in the prenylation pathway and SAFB, a nuclear protein with both DNA and RNA binding domains. Silencing SAFB led to marked mislocalization of all RAS isoforms as well as RAP1A but not RAB7A, a pattern that phenocopied silencing FNTA, the prenyltransferase α subunit shared by farnesyltransferase and geranylgeranyltransferase type I. We found that SAFB promoted RAS membrane association by controlling FNTA expression. SAFB knockdown decreased GTP loading of RAS, abrogated alternative prenylation, and sensitized RAS-mutant cells to growth inhibition by FTI. Our work establishes the prenylation pathway as paramount in KRAS membrane association, reveals a regulator of prenyltransferase expression, and suggests that reduction in FNTA expression may enhance the efficacy of FTIs.
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4
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Meyer SN, Scuoppo C, Vlasevska S, Bal E, Holmes AB, Holloman M, Garcia-Ibanez L, Nataraj S, Duval R, Vantrimpont T, Basso K, Brooks N, Dalla-Favera R, Pasqualucci L. Unique and Shared Epigenetic Programs of the CREBBP and EP300 Acetyltransferases in Germinal Center B Cells Reveal Targetable Dependencies in Lymphoma. Immunity 2019; 51:535-547.e9. [PMID: 31519498 DOI: 10.1016/j.immuni.2019.08.006] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 06/03/2019] [Accepted: 08/06/2019] [Indexed: 12/22/2022]
Abstract
Inactivating mutations of the CREBBP and EP300 acetyltransferases are among the most common genetic alterations in diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL). Here, we examined the relationship between these two enzymes in germinal center (GC) B cells, the normal counterpart of FL and DLBCL, and in lymphomagenesis by using conditional GC-directed deletion mouse models targeting Crebbp or Ep300. We found that CREBBP and EP300 modulate common as well as distinct transcriptional programs implicated in separate anatomic and functional GC compartments. Consistently, deletion of Ep300 but not Crebbp impaired the fitness of GC B cells in vivo. Combined loss of Crebbp and Ep300 completely abrogated GC formation, suggesting that these proteins partially compensate for each other through common transcriptional targets. This synthetic lethal interaction was retained in CREBBP-mutant DLBCL cells and could be pharmacologically targeted with selective small molecule inhibitors of CREBBP and EP300 function. These data provide proof-of-principle for the clinical development of EP300-specific inhibitors in FL and DLBCL.
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Affiliation(s)
- Stefanie N Meyer
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Claudio Scuoppo
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA
| | - Sofija Vlasevska
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Elodie Bal
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Antony B Holmes
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Mara Holloman
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | | | - Sarah Nataraj
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Romain Duval
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Thomas Vantrimpont
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Katia Basso
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA
| | - Nigel Brooks
- Cell Centric, Chesterford Research Park, Little Chesterford, Cambridge, CB10 1XL, UK
| | - Riccardo Dalla-Favera
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA; Department of Genetics & Development, Columbia University, New York, NY 10032, USA; Department of Microbiology & Immunology, Columbia University, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA
| | - Laura Pasqualucci
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA.
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5
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Berger S, Pachkov M, Arnold P, Omidi S, Kelley N, Salatino S, van Nimwegen E. Crunch: integrated processing and modeling of ChIP-seq data in terms of regulatory motifs. Genome Res 2019; 29:1164-1177. [PMID: 31138617 PMCID: PMC6633267 DOI: 10.1101/gr.239319.118] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 05/14/2019] [Indexed: 01/10/2023]
Abstract
Although ChIP-seq has become a routine experimental approach for quantitatively characterizing the genome-wide binding of transcription factors (TFs), computational analysis procedures remain far from standardized, making it difficult to compare ChIP-seq results across experiments. In addition, although genome-wide binding patterns must ultimately be determined by local constellations of DNA-binding sites, current analysis is typically limited to identifying enriched motifs in ChIP-seq peaks. Here we present Crunch, a completely automated computational method that performs all ChIP-seq analysis from quality control through read mapping and peak detecting and that integrates comprehensive modeling of the ChIP signal in terms of known and novel binding motifs, quantifying the contribution of each motif and annotating which combinations of motifs explain each binding peak. By applying Crunch to 128 data sets from the ENCODE Project, we show that Crunch outperforms current peak finders and find that TFs naturally separate into "solitary TFs," for which a single motif explains the ChIP-peaks, and "cobinding TFs," for which multiple motifs co-occur within peaks. Moreover, for most data sets, the motifs that Crunch identified de novo outperform known motifs, and both the set of cobinding motifs and the top motif of solitary TFs are consistent across experiments and cell lines. Crunch is implemented as a web server, enabling standardized analysis of any collection of ChIP-seq data sets by simply uploading raw sequencing data. Results are provided both in a graphical web interface and as downloadable files.
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Affiliation(s)
- Severin Berger
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
| | - Mikhail Pachkov
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
| | - Phil Arnold
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
| | - Saeed Omidi
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
| | - Nicholas Kelley
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
| | - Silvia Salatino
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
| | - Erik van Nimwegen
- Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland
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6
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Duy C, Teater M, Garrett-Bakelman FE, Lee TC, Meydan C, Glass JL, Li M, Hellmuth JC, Mohammad HP, Smitheman KN, Shih AH, Abdel-Wahab O, Tallman MS, Guzman ML, Muench D, Grimes HL, Roboz GJ, Kruger RG, Creasy CL, Paietta EM, Levine RL, Carroll M, Melnick AM. Rational Targeting of Cooperating Layers of the Epigenome Yields Enhanced Therapeutic Efficacy against AML. Cancer Discov 2019; 9:872-889. [PMID: 31076479 DOI: 10.1158/2159-8290.cd-19-0106] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 04/17/2019] [Accepted: 05/07/2019] [Indexed: 02/06/2023]
Abstract
Disruption of epigenetic regulation is a hallmark of acute myeloid leukemia (AML), but epigenetic therapy is complicated by the complexity of the epigenome. Herein, we developed a long-term primary AML ex vivo platform to determine whether targeting different epigenetic layers with 5-azacytidine and LSD1 inhibitors would yield improved efficacy. This combination was most effective in TET2 mut AML, where it extinguished leukemia stem cells and particularly induced genes with both LSD1-bound enhancers and cytosine-methylated promoters. Functional studies indicated that derepression of genes such as GATA2 contributes to drug efficacy. Mechanistically, combination therapy increased enhancer-promoter looping and chromatin-activating marks at the GATA2 locus. CRISPRi of the LSD1-bound enhancer in patient-derived TET2 mut AML was associated with dampening of therapeutic GATA2 induction. TET2 knockdown in human hematopoietic stem/progenitor cells induced loss of enhancer 5-hydroxymethylation and facilitated LSD1-mediated enhancer inactivation. Our data provide a basis for rational targeting of cooperating aberrant promoter and enhancer epigenetic marks driven by mutant epigenetic modifiers. SIGNIFICANCE: Somatic mutations of genes encoding epigenetic modifiers are a hallmark of AML and potentially disrupt many components of the epigenome. Our study targets two different epigenetic layers at promoters and enhancers that cooperate to aberrant gene silencing, downstream of the actions of a mutant epigenetic regulator.This article is highlighted in the In This Issue feature, p. 813.
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Affiliation(s)
- Cihangir Duy
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York.
| | - Matt Teater
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York
| | - Francine E Garrett-Bakelman
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York.,Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia.,Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Tak C Lee
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York
| | - Cem Meydan
- Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York
| | - Jacob L Glass
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Meng Li
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York
| | - Johannes C Hellmuth
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York
| | | | | | - Alan H Shih
- Memorial Sloan Kettering Cancer Center, New York, New York
| | | | | | - Monica L Guzman
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York
| | - David Muench
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - H Leighton Grimes
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Gail J Roboz
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York
| | | | | | | | - Ross L Levine
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Martin Carroll
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
| | - Ari M Melnick
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, New York. .,Department of Pharmacology, Weill Cornell Medicine, New York, New York
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7
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Gayvert K, Elemento O. Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity. Methods Mol Biol 2019; 1903:179-184. [PMID: 30547442 DOI: 10.1007/978-1-4939-8955-3_10] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Inhibition of oncogenes and reactivation of tumor suppressors are well-established goals in anticancer drug development. Unfortunately many oncogenes and tumor suppressors are not classically druggable, in that they lack a targetable enzymatic activity and associated binding pockets that small molecule drugs can be directed to. This is especially relevant for transcription factors, which have long been thought to be undruggable. To address this gap, we have developed and described CRAFTT, a broadly applicable computational drug-repositioning approach for targeting transcription factors. CRAFTT combines transcription factor target gene sets with drug-induced expression profiling to identify small molecules that can perturb transcription factor activity. Network analysis is then used to derive a modulation index (MI) and prioritize predictions.
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Affiliation(s)
- Kaitlyn Gayvert
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, USA
| | - Olivier Elemento
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
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8
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Brescia P, Schneider C, Holmes AB, Shen Q, Hussein S, Pasqualucci L, Basso K, Dalla-Favera R. MEF2B Instructs Germinal Center Development and Acts as an Oncogene in B Cell Lymphomagenesis. Cancer Cell 2018; 34:453-465.e9. [PMID: 30205047 PMCID: PMC6223119 DOI: 10.1016/j.ccell.2018.08.006] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 05/15/2018] [Accepted: 08/08/2018] [Indexed: 12/30/2022]
Abstract
The gene encoding the MEF2B transcription factor is mutated in germinal center (GC)-derived B cell lymphomas, but its role in GC development and lymphomagenesis is unknown. We demonstrate that Mef2b deletion reduces GC formation in mice and identify MEF2B transcriptional targets in GC, with roles in cell proliferation, apoptosis, GC confinement, and differentiation. The most common lymphoma-associated MEF2B mutant (MEF2BD83V) is hypomorphic, yet escapes binding and negative regulation by components of the HUCA complex and class IIa HDACs. Mef2bD83V expression in mice leads to GC enlargement and lymphoma development, a phenotype that becomes fully penetrant in combination with BCL2 de-regulation, an event associated with human MEF2B mutations. These results identify MEF2B as a critical GC regulator and a driver oncogene in lymphomagenesis.
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Affiliation(s)
- Paola Brescia
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Christof Schneider
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Antony B Holmes
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Qiong Shen
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA
| | - Shafinaz Hussein
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Laura Pasqualucci
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA; The Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA
| | - Katia Basso
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA.
| | - Riccardo Dalla-Favera
- Institute for Cancer Genetics, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA; Department of Microbiology and Immunology, Columbia University, New York, NY 10032, USA; Department of Genetics and Development, Columbia University, New York, NY 10032, USA; The Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA.
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9
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Qiao Y, Kang K, Giannopoulou E, Fang C, Ivashkiv LB. IFN-γ Induces Histone 3 Lysine 27 Trimethylation in a Small Subset of Promoters to Stably Silence Gene Expression in Human Macrophages. Cell Rep 2018; 16:3121-3129. [PMID: 27653678 DOI: 10.1016/j.celrep.2016.08.051] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Revised: 06/14/2016] [Accepted: 08/16/2016] [Indexed: 01/21/2023] Open
Abstract
The mechanisms by which IFN-γ activates expression of interferon-stimulated genes that have inflammatory and host defense functions are well understood. In contrast, little is known about how IFN-γ represses gene expression. By using transcriptomic and epigenomic analysis, we found that stable repression of a small group of genes by IFN-γ is associated with recruitment of the histone methyltransferase EZH2 and deposition of the negative mark histone 3 lysine 27 trimethylation (H3K27me3) at their promoters. Repressed genes included MERTK, PPARG, and RANK, which have anti-inflammatory functions and promote osteoclast differentiation. Gene repression and H3K27me3 persisted after IFN-γ signaling was terminated, and these silenced genes were no longer responsive to glucocorticoids, IL-4, and M-CSF. These results identify cytokine-induced H3K27 trimethylation as a mechanism that stabilizes gene silencing in macrophages. IFN-γ-induced macrophage activation is thus reinforced by a chromatin-based mechanism that blocks anti-inflammatory and opposing pathways.
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Affiliation(s)
- Yu Qiao
- Arthritis and Tissue Degeneration Program and David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, NY 10021, USA
| | - Kyuho Kang
- Arthritis and Tissue Degeneration Program and David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, NY 10021, USA
| | - Eugenia Giannopoulou
- Arthritis and Tissue Degeneration Program and David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, NY 10021, USA; Department of Biological Sciences, New York City College of Technology, City University of New York, Brooklyn, NY 11201, USA
| | - Celeste Fang
- Arthritis and Tissue Degeneration Program and David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, NY 10021, USA
| | - Lionel B Ivashkiv
- Arthritis and Tissue Degeneration Program and David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, NY 10021, USA; Department of Medicine, Weill Cornell Medical College and Graduate Program in Immunology and Microbial Pathogenesis, Weill Cornell Graduate School of Medical Sciences, New York, NY 10065, USA.
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10
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Namous H, Peñagaricano F, Del Corvo M, Capra E, Thomas DL, Stella A, Williams JL, Marsan PA, Khatib H. Integrative analysis of methylomic and transcriptomic data in fetal sheep muscle tissues in response to maternal diet during pregnancy. BMC Genomics 2018; 19:123. [PMID: 29409445 PMCID: PMC5801776 DOI: 10.1186/s12864-018-4509-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 01/29/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Numerous studies have established a link between maternal diet and the physiological and metabolic phenotypes of their offspring. In previous studies in sheep, we demonstrated that different maternal diets altered the transcriptome of fetal tissues. However, the mechanisms underlying transcriptomic changes are poorly understood. DNA methylation is an epigenetic mark regulating transcription and is largely influenced by dietary components of the one-carbon cycle that generate the methyl group donor, SAM. Therefore, in the present study, we tested whether different maternal diets during pregnancy would alter the DNA methylation and gene expression patterns in fetal tissues. RESULTS Pregnant ewes were randomly divided into two groups which received either hay or corn diet from mid-gestation (day 67 ± 5) until day 131 ± 1 when fetuses were collected by necropsy. A total of 1516 fetal longissimus dorsi (LD) tissues were used for DNA methylation analysis and gene expression profiling. Whole genome DNA methylation using methyl-binding domain enrichment analysis revealed 60 differentially methylated regions (DMRs) between hay and corn fetuses with 39 DMRs more highly methylated in the hay fetuses vs. 21 DMRs more highly methylated in the corn fetuses. Three DMRs (LPAR3, PLIN5-PLIN4, and the differential methylation of a novel lincRNA) were validated using bisulfite sequencing. These DMRs were associated with differential gene expression. Additionally, significant DNA methylation differences were found at the single CpG level. Integrative methylome and transcriptome analysis revealed an association between gene expression and inter-/intragenic methylated regions. Furthermore, intragenic DMRs were found to be associated with expression of neighboring genes. CONCLUSIONS The findings of this study imply that maternal diet from mid- to late-gestation can shape the epigenome and the transcriptome of fetal tissues, and putatively affect phenotypes of the lambs.
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Affiliation(s)
- Hadjer Namous
- Department of Animal Sciences, University of Wisconsin, 1675 Observatory Drive, Madison, WI 53706 USA
| | - Francisco Peñagaricano
- Department of Animal Sciences, University of Florida Genetics Institute, University of Florida, Florida, USA
| | - Marcello Del Corvo
- Institute of Zootechnics and PRONUTRIGEN Research Center, Faculty of Agricultural, Food and Environmental Sciences, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Emanuele Capra
- Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Lodi, Italy
| | - David L. Thomas
- Department of Animal Sciences, University of Wisconsin, 1675 Observatory Drive, Madison, WI 53706 USA
| | - Alessandra Stella
- Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Lodi, Italy
| | - John L. Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, Australia
| | - Paolo Ajmone Marsan
- Institute of Zootechnics and PRONUTRIGEN Research Center, Faculty of Agricultural, Food and Environmental Sciences, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Hasan Khatib
- Department of Animal Sciences, University of Wisconsin, 1675 Observatory Drive, Madison, WI 53706 USA
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11
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Analyzing DNA Methylation Patterns During Tumor Evolution. Methods Mol Biol 2018. [PMID: 29344884 DOI: 10.1007/978-1-4939-7493-1_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
Epigenetic modifications play a key role in cellular development and tumorigenesis. Recent large-scale genomic studies have shown that mutations in players of the epigenetic machinery and concomitant perturbation of epigenomic patterning are frequent events in tumors. Among epigenetic marks, DNA methylation is one of the best studied. Hyper- and hypo-methylation events of specific regulatory elements (such as promoters and enhancers) are sometimes thought to be correlated with expression of nearby genes. High-throughput bisulfite converted sequencing is currently the technology of choice for studying DNA methylation in base-pair resolution and on whole-genome scale. Such broad and high-resolution coverage investigations of the epigenome provide unprecedented opportunities to analyze DNA methylation patterns, which are correlated with tumorigenesis, tumor evolution, and tumor progression. However, few computational pipelines are available to the public to perform systematic DNA methylation analysis. Utilizing open source tools, we here describe a comprehensive computational methodology to thoroughly analyze DNA methylation patterns during tumor evolution based on bisulfite converted sequencing data, including intra-tumor methylation heterogeneity.
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12
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Teater M, Dominguez PM, Redmond D, Chen Z, Ennishi D, Scott DW, Cimmino L, Ghione P, Chaudhuri J, Gascoyne RD, Aifantis I, Inghirami G, Elemento O, Melnick A, Shaknovich R. AICDA drives epigenetic heterogeneity and accelerates germinal center-derived lymphomagenesis. Nat Commun 2018; 9:222. [PMID: 29335468 PMCID: PMC5768781 DOI: 10.1038/s41467-017-02595-w] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 12/13/2017] [Indexed: 12/22/2022] Open
Abstract
Epigenetic heterogeneity is emerging as a feature of tumors. In diffuse large B-cell lymphoma (DLBCL), increased cytosine methylation heterogeneity is associated with poor clinical outcome, yet the underlying mechanisms remain unclear. Activation-induced cytidine deaminase (AICDA), an enzyme that mediates affinity maturation and facilitates DNA demethylation in germinal center (GC) B cells, is required for DLBCL pathogenesis and linked to inferior outcome. Here we show that AICDA overexpression causes more aggressive disease in BCL2-driven murine lymphomas. This phenotype is associated with increased cytosine methylation heterogeneity, but not with increased AICDA-mediated somatic mutation burden. Reciprocally, the cytosine methylation heterogeneity characteristic of normal GC B cells is lost upon AICDA depletion. These observations are relevant to human patients, since DLBCLs with high AICDA expression manifest increased methylation heterogeneity vs. AICDA-low DLBCLs. Our results identify AICDA as a driver of epigenetic heterogeneity in B-cell lymphomas with potential significance for other tumors with aberrant expression of cytidine deaminases. In diffuse large B-cell lymphoma (DLBCL) increased epigenetic heterogeneity in the form of cytosine methylation is known to link to a poor clinical outcome. Here, the authors show that AICDA, an enzyme required for DLBCL pathogenesis, increases cytosine methylation heterogeneity.
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Affiliation(s)
- Matt Teater
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, 10021, USA.,Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Pilar M Dominguez
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, 10021, USA
| | - David Redmond
- Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Zhengming Chen
- Division of Biostatistics and Epidemiology, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Daisuke Ennishi
- Centre for Lymphoid Cancer, British Columbia Cancer Agency, Vancouver, BC V5Z 4E6, Canada
| | - David W Scott
- Centre for Lymphoid Cancer, British Columbia Cancer Agency, Vancouver, BC V5Z 4E6, Canada
| | - Luisa Cimmino
- Department of Pathology, Laura and Isaac Perlmutter Cancer Center, and The Helen L. and Martin S. Kimmel Center for Stem Cell Biology, NYU School of Medicine, New York, NY, 10016, USA
| | - Paola Ghione
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, 10021, USA.,Division of Hematology, Department of Experimental Medicine and Oncology, University of Turin, 10124, Turin, Italy
| | - Jayanta Chaudhuri
- Immunology Program, Memorial Sloan-Kettering Cancer Center, Gerstner Sloan-Kettering Graduate School, New York, NY, 10021, USA
| | - Randy D Gascoyne
- Department of Pathology, British Columbia Cancer Agency, Vancouver, BC V5Z 4E6, Canada
| | - Iannis Aifantis
- Department of Pathology, Laura and Isaac Perlmutter Cancer Center, and The Helen L. and Martin S. Kimmel Center for Stem Cell Biology, NYU School of Medicine, New York, NY, 10016, USA
| | - Giorgio Inghirami
- Pathology and Laboratory Medicine Department, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Olivier Elemento
- Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10021, USA. .,Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.
| | - Ari Melnick
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, 10021, USA.
| | - Rita Shaknovich
- Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, 10021, USA. .,Cancer Genetics, Inc., Rutherford, NJ, 07070, USA.
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13
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Jalili V, Matteucci M, Morelli MJ, Masseroli M. MuSERA: Multiple Sample Enriched Region Assessment. Brief Bioinform 2017; 18:367-381. [PMID: 27013647 DOI: 10.1093/bib/bbw029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Indexed: 11/14/2022] Open
Abstract
Enriched region (ER) identification is a fundamental step in several next-generation sequencing (NGS) experiment types. Yet, although NGS experimental protocols recommend producing replicate samples for each evaluated condition and their consistency is usually assessed, typically pipelines for ER identification do not consider available NGS replicates. This may alter genome-wide descriptions of ERs, hinder significance of subsequent analyses on detected ERs and eventually preclude biological discoveries that evidence in replicate could support. MuSERA is a broadly useful stand-alone tool for both interactive and batch analysis of combined evidence from ERs in multiple ChIP-seq or DNase-seq replicates. Besides rigorously combining sample replicates to increase statistical significance of detected ERs, it also provides quantitative evaluations and graphical features to assess the biological relevance of each determined ER set within its genomic context; they include genomic annotation of determined ERs, nearest ER distance distribution, global correlation assessment of ERs and an integrated genome browser. We review MuSERA rationale and implementation, and illustrate how sets of significant ERs are expanded by applying MuSERA on replicates for several types of NGS data, including ChIP-seq of transcription factors or histone marks and DNase-seq hypersensitive sites. We show that MuSERA can determine a new, enhanced set of ERs for each sample by locally combining evidence on replicates, and prove how the easy-to-use interactive graphical displays and quantitative evaluations that MuSERA provides effectively support thorough inspection of obtained results and evaluation of their biological content, facilitating their understanding and biological interpretations. MuSERA is freely available at http://www.bioinformatics.deib.polimi.it/MuSERA/.
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14
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Verma N, Pan H, Doré LC, Shukla A, Li QV, Pelham-Webb B, Teijeiro V, González F, Krivtsov A, Chang CJ, Papapetrou EP, He C, Elemento O, Huangfu D. TET proteins safeguard bivalent promoters from de novo methylation in human embryonic stem cells. Nat Genet 2017; 50:83-95. [PMID: 29203910 PMCID: PMC5742051 DOI: 10.1038/s41588-017-0002-y] [Citation(s) in RCA: 140] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 10/25/2017] [Indexed: 12/22/2022]
Abstract
The TET enzymes oxidize 5-methylcytosine to 5-hydroxymethylcytosine, which can lead to DNA demethylation. However, direct connections between TET-mediated DNA demethylation and transcriptional output are difficult to establish due to challenges of distinguishing global versus locus-specific effects. Here we show that TET1/2/3 triple knockout (TKO) human embryonic stem cells (hESCs) exhibit prominent bivalent promoter hypermethylation without an overall corresponding gene expression decrease in the undifferentiated state. Focusing on the bivalent PAX6 locus, we find increased DNMT3B binding is associated with promoter hypermethylation, which precipitates a neural differentiation defect and failure of PAX6 induction during differentiation. dCas9-mediated locus-specific demethylation and global inactivation of DNMT3B in TKO hESCs partially reverses the hypermethylation at the PAX6 promoter and improves differentiation to neuroectoderm. Taken together with further genome-wide methylation and TET1 and DNMT3B ChIP-Seq analysis, we conclude that the TET proteins safeguard bivalent promoters from de novo methylation to ensure robust lineage-specific transcription upon differentiation.
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Affiliation(s)
- Nipun Verma
- Developmental Biology Program, Sloan Kettering Institute, New York, NY, USA.,Weill Graduate School of Medical Sciences at Cornell University/The Rockefeller University/Sloan Kettering Institute Tri-Institutional MD-PhD Program, New York, NY, USA
| | - Heng Pan
- Department of Physiology and Biophysics, Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA.,Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medical College, New York, NY, USA
| | - Louis C Doré
- Department of Chemistry, Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, Howard Hughes Medical Institute, University of Chicago, Chicago, IL, USA
| | - Abhijit Shukla
- Developmental Biology Program, Sloan Kettering Institute, New York, NY, USA
| | - Qing V Li
- Developmental Biology Program, Sloan Kettering Institute, New York, NY, USA.,Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Bobbie Pelham-Webb
- Weill Graduate School of Medical Sciences at Cornell University/The Rockefeller University/Sloan Kettering Institute Tri-Institutional MD-PhD Program, New York, NY, USA
| | - Virginia Teijeiro
- Developmental Biology Program, Sloan Kettering Institute, New York, NY, USA.,Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medical College, New York, NY, USA
| | - Federico González
- Developmental Biology Program, Sloan Kettering Institute, New York, NY, USA.,Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
| | - Andrei Krivtsov
- Cancer Biology and Genetics Program, Sloan Kettering Institute, New York, NY, USA
| | - Chan-Jung Chang
- Department of Oncological Sciences and Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eirini P Papapetrou
- Department of Oncological Sciences and Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chuan He
- Department of Chemistry, Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, Howard Hughes Medical Institute, University of Chicago, Chicago, IL, USA
| | - Olivier Elemento
- Department of Physiology and Biophysics, Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA.
| | - Danwei Huangfu
- Developmental Biology Program, Sloan Kettering Institute, New York, NY, USA.
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15
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Steube A, Schenk T, Tretyakov A, Saluz HP. High-intensity UV laser ChIP-seq for the study of protein-DNA interactions in living cells. Nat Commun 2017; 8:1303. [PMID: 29101361 PMCID: PMC5670203 DOI: 10.1038/s41467-017-01251-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 08/31/2017] [Indexed: 01/10/2023] Open
Abstract
Genome-wide mapping of transcription factor binding is generally performed by chemical protein–DNA crosslinking, followed by chromatin immunoprecipitation and deep sequencing (ChIP-seq). Here we present the ChIP-seq technique based on photochemical crosslinking of protein–DNA interactions by high-intensity ultraviolet (UV) laser irradiation in living mammalian cells (UV-ChIP-seq). UV laser irradiation induces an efficient and instant formation of covalent “zero-length” crosslinks exclusively between nucleic acids and proteins that are in immediate contact, thus resulting in a “snapshot” of direct protein–DNA interactions in their natural environment. Here we show that UV-ChIP-seq, applied for genome-wide profiling of the sequence-specific transcriptional repressor B-cell lymphoma 6 (BCL6) in human diffuse large B-cell lymphoma (DLBCL) cells, produces sensitive and precise protein–DNA binding profiles, highly enriched with canonical BCL6 DNA sequence motifs. Using this technique, we also found numerous previously undetectable direct BCL6 binding sites, particularly in condensed, inaccessible areas of chromatin. Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) can map transcription factor binding to a given genome. Here, Steube and colleagues devise a ChIP-seq technique based on photochemical crosslinking by high-intensity ultraviolet laser irradiation, and describe its utility.
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Affiliation(s)
- Arndt Steube
- Department of Cell and Molecular Biology, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knöll Institute (HKI), Jena, 07745, Germany. .,Department of Internal Medicine IV, Jena University Hospital, Friedrich Schiller University, Jena, 07747, Germany. .,Friedrich Schiller University, Jena, 07737, Germany.
| | - Tino Schenk
- Friedrich Schiller University, Jena, 07737, Germany. .,Department of Hematology and Medical Oncology, Clinic of Internal Medicine II, Jena University Hospital, Jena, 07747, Germany. .,Institute of Molecular Cell Biology, Center for Molecular Biomedicine Jena (CMB), Jena University Hospital, Jena, 07745, Germany.
| | - Alexander Tretyakov
- Department of Cell and Molecular Biology, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knöll Institute (HKI), Jena, 07745, Germany
| | - Hans Peter Saluz
- Department of Cell and Molecular Biology, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knöll Institute (HKI), Jena, 07745, Germany. .,Friedrich Schiller University, Jena, 07737, Germany.
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16
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Lavender CA, Shapiro AJ, Burkholder AB, Bennett BD, Adelman K, Fargo DC. ORIO (Online Resource for Integrative Omics): a web-based platform for rapid integration of next generation sequencing data. Nucleic Acids Res 2017; 45:5678-5690. [PMID: 28402545 PMCID: PMC5449597 DOI: 10.1093/nar/gkx270] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 04/05/2017] [Indexed: 11/14/2022] Open
Abstract
Established and emerging next generation sequencing (NGS)-based technologies allow for genome-wide interrogation of diverse biological processes. However, accessibility of NGS data remains a problem, and few user-friendly resources exist for integrative analysis of NGS data from different sources and experimental techniques. Here, we present Online Resource for Integrative Omics (ORIO; https://orio.niehs.nih.gov/), a web-based resource with an intuitive user interface for rapid analysis and integration of NGS data. To use ORIO, the user specifies NGS data of interest along with a list of genomic coordinates. Genomic coordinates may be biologically relevant features from a variety of sources, such as ChIP-seq peaks for a given protein or transcription start sites from known gene models. ORIO first iteratively finds read coverage values at each genomic feature for each NGS dataset. Data are then integrated using clustering-based approaches, giving hierarchical relationships across NGS datasets and separating individual genomic features into groups. In focusing its analysis on read coverage, ORIO makes limited assumptions about the analyzed data; this allows the tool to be applied across data from a variety of experiments and techniques. Results from analysis are presented in dynamic displays alongside user-controlled statistical tests, supporting rapid statistical validation of observed results. We emphasize the versatility of ORIO through diverse examples, ranging from NGS data quality control to characterization of enhancer regions and integration of gene expression information. Easily accessible on a public web server, we anticipate wide use of ORIO in genome-wide investigations by life scientists.
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Affiliation(s)
- Christopher A Lavender
- Integrative Bioinformatics, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Andrew J Shapiro
- Program Operations Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Adam B Burkholder
- Integrative Bioinformatics, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Brian D Bennett
- Integrative Bioinformatics, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Karen Adelman
- Epigenetics and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA.,Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - David C Fargo
- Office of Scientific Computing, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
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17
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Frattini S, Capra E, Lazzari B, McKay SD, Coizet B, Talenti A, Groppetti D, Riccaboni P, Pecile A, Chessa S, Castiglioni B, Williams JL, Pagnacco G, Stella A, Crepaldi P. Genome-wide analysis of DNA methylation in hypothalamus and ovary of Capra hircus. BMC Genomics 2017. [PMID: 28645321 PMCID: PMC5481934 DOI: 10.1186/s12864-017-3866-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND DNA methylation is a frequently studied epigenetic modification due to its role in regulating gene expression and hence in biological processes and in determining phenotypic plasticity in organisms. Rudimentary DNA methylation patterns for some livestock species are publically available: among these, goat methylome deserves to be further explored. RESULTS Genome-wide DNA methylation maps of the hypothalamus and ovary from Saanen goats were generated using Methyl-CpG binding domain protein sequencing (MBD-seq). Analysis of DNA methylation patterns indicate that the majority of methylation peaks found within genes are located gene body regions, for both organs. Analysis of the distribution of methylated sites per chromosome showed that chromosome X had the lowest number of methylation peaks. The X chromosome has one of the highest percentages of methylated CpG islands in both organs, and approximately 50% of the CpG islands in the goat epigenome are methylated in hypothalamus and ovary. Organ-specific Differentially Methylated Genes (DMGs) were correlated with the expression levels. CONCLUSIONS The comparison between transcriptome and methylome in hypothalamus and ovary showed that a higher level of methylation is not accompanied by a higher gene suppression. The genome-wide DNA methylation map for two goat organs produced here is a valuable starting point for studying the involvement of epigenetic modifications in regulating goat reproduction performance.
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Affiliation(s)
- Stefano Frattini
- Department of Veterinary Science, University of Milan, Milan, Italy
| | - Emanuele Capra
- Institute of Agricultural Biology and Biotechnology, National Research Council UOS of Lodi, Lodi, Italy
| | - Barbara Lazzari
- Institute of Agricultural Biology and Biotechnology, National Research Council UOS of Lodi, Lodi, Italy.,PTP Science Park, Lodi, Italy
| | - Stephanie D McKay
- Department of Animal & Veterinary Sciences, University of Vermont, Burlington, VT, USA
| | - Beatrice Coizet
- Department of Veterinary Science, University of Milan, Milan, Italy
| | - Andrea Talenti
- Department of Veterinary Science, University of Milan, Milan, Italy
| | - Debora Groppetti
- Department of Veterinary Science, University of Milan, Milan, Italy
| | - Pietro Riccaboni
- Department of Veterinary Science, University of Milan, Milan, Italy
| | | | - Stefania Chessa
- Institute of Agricultural Biology and Biotechnology, National Research Council UOS of Lodi, Lodi, Italy
| | - Bianca Castiglioni
- Institute of Agricultural Biology and Biotechnology, National Research Council UOS of Lodi, Lodi, Italy
| | - John L Williams
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, 5371, Australia
| | - Giulio Pagnacco
- Department of Veterinary Science, University of Milan, Milan, Italy
| | - Alessandra Stella
- Institute of Agricultural Biology and Biotechnology, National Research Council UOS of Lodi, Lodi, Italy.,PTP Science Park, Lodi, Italy
| | - Paola Crepaldi
- Department of Veterinary Science, University of Milan, Milan, Italy.
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18
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Glass JL, Hassane D, Wouters BJ, Kunimoto H, Avellino R, Garrett-Bakelman FE, Guryanova OA, Bowman R, Redlich S, Intlekofer AM, Meydan C, Qin T, Fall M, Alonso A, Guzman ML, Valk PJM, Thompson CB, Levine R, Elemento O, Delwel R, Melnick A, Figueroa ME. Epigenetic Identity in AML Depends on Disruption of Nonpromoter Regulatory Elements and Is Affected by Antagonistic Effects of Mutations in Epigenetic Modifiers. Cancer Discov 2017; 7:868-883. [PMID: 28408400 DOI: 10.1158/2159-8290.cd-16-1032] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 10/20/2016] [Accepted: 04/07/2017] [Indexed: 11/16/2022]
Abstract
We performed cytosine methylation sequencing on genetically diverse patients with acute myeloid leukemia (AML) and found leukemic DNA methylation patterning is primarily driven by nonpromoter regulatory elements and CpG shores. Enhancers displayed stronger differential methylation than promoters, consisting predominantly of hypomethylation. AMLs with dominant hypermethylation featured greater epigenetic disruption of promoters, whereas those with dominant hypomethylation displayed greater disruption of distal and intronic regions. Mutations in IDH and DNMT3A had opposing and mutually exclusive effects on the epigenome. Notably, co-occurrence of both mutations resulted in epigenetic antagonism, with most CpGs affected by either mutation alone no longer affected in double-mutant AMLs. Importantly, this epigenetic antagonism precedes malignant transformation and can be observed in preleukemic LSK cells from Idh2R140Q or Dnmt3aR882H single-mutant and Idh2R140Q/Dnmt3aR882H double-mutant mice. Notably, IDH/DNMT3A double-mutant AMLs manifested upregulation of a RAS signaling signature and displayed unique sensitivity to MEK inhibition ex vivo as compared with AMLs with either single mutation.Significance: AML is biologically heterogeneous with subtypes characterized by specific genetic and epigenetic abnormalities. Comprehensive DNA methylation profiling revealed that differential methylation of nonpromoter regulatory elements is a driver of epigenetic identity, that gene mutations can be context-dependent, and that co-occurrence of mutations in epigenetic modifiers can result in epigenetic antagonism. Cancer Discov; 7(8); 868-83. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 783.
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Affiliation(s)
- Jacob L Glass
- Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.,Department of Medicine, Hematology/Oncology Division, Weill Medical College of Cornell University, New York, New York
| | - Duane Hassane
- Institute of Computational Biomedicine, Weill Medical College of Cornell University, New York, New York
| | - Bas J Wouters
- Department of Medicine, Hematology/Oncology Division, Weill Medical College of Cornell University, New York, New York.,Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Hiroyoshi Kunimoto
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Roberto Avellino
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Francine E Garrett-Bakelman
- Department of Medicine, Hematology/Oncology Division, Weill Medical College of Cornell University, New York, New York.,Department of Medicine, University of Virginia, Charlottesville, Virginia.,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia
| | - Olga A Guryanova
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Robert Bowman
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Shira Redlich
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Andrew M Intlekofer
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Cem Meydan
- Department of Medicine, University of Virginia, Charlottesville, Virginia
| | - Tingting Qin
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Mame Fall
- Epigenomics Core Facility, Weill Medical College of Cornell University, New York, New York
| | - Alicia Alonso
- Epigenomics Core Facility, Weill Medical College of Cornell University, New York, New York
| | - Monica L Guzman
- Department of Medicine, Hematology/Oncology Division, Weill Medical College of Cornell University, New York, New York
| | - Peter J M Valk
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Craig B Thompson
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ross Levine
- Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.,Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York.,Center for Epigenetics Research, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Olivier Elemento
- Institute of Computational Biomedicine, Weill Medical College of Cornell University, New York, New York
| | - Ruud Delwel
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands.
| | - Ari Melnick
- Department of Medicine, Hematology/Oncology Division, Weill Medical College of Cornell University, New York, New York.
| | - Maria E Figueroa
- Department of Human Genetics and Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida.
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19
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Common nonmutational NOTCH1 activation in chronic lymphocytic leukemia. Proc Natl Acad Sci U S A 2017; 114:E2911-E2919. [PMID: 28314854 DOI: 10.1073/pnas.1702564114] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Activating mutations of NOTCH1 (a well-known oncogene in T-cell acute lymphoblastic leukemia) are present in ∼4-13% of chronic lymphocytic leukemia (CLL) cases, where they are associated with disease progression and chemorefractoriness. However, the specific role of NOTCH1 in leukemogenesis remains to be established. Here, we report that the active intracellular portion of NOTCH1 (ICN1) is detectable in ∼50% of peripheral blood CLL cases lacking gene mutations. We identify a "NOTCH1 gene-expression signature" in CLL cells, and show that this signature is significantly enriched in primary CLL cases expressing ICN1, independent of NOTCH1 mutation. NOTCH1 target genes include key regulators of B-cell proliferation, survival, and signal transduction. In particular, we show that NOTCH1 transactivates MYC via binding to B-cell-specific regulatory elements, thus implicating this oncogene in CLL development. These results significantly extend the role of NOTCH1 in CLL pathogenesis, and have direct implications for specific therapeutic targeting.
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Zhang J, Vlasevska S, Wells VA, Nataraj S, Holmes AB, Duval R, Meyer SN, Mo T, Basso K, Brindle PK, Hussein S, Dalla-Favera R, Pasqualucci L. The CREBBP Acetyltransferase Is a Haploinsufficient Tumor Suppressor in B-cell Lymphoma. Cancer Discov 2017; 7:322-337. [PMID: 28069569 DOI: 10.1158/2159-8290.cd-16-1417] [Citation(s) in RCA: 142] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Revised: 01/05/2017] [Accepted: 01/06/2017] [Indexed: 01/12/2023]
Abstract
Inactivating mutations of the CREBBP acetyltransferase are highly frequent in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL), the two most common germinal center (GC)-derived cancers. However, the role of CREBBP inactivation in lymphomagenesis remains unclear. Here, we show that CREBBP regulates enhancer/super-enhancer networks with central roles in GC/post-GC cell fate decisions, including genes involved in signal transduction by the B-cell receptor and CD40 receptor, transcriptional control of GC and plasma cell development, and antigen presentation. Consistently, Crebbp-deficient B cells exhibit enhanced response to mitogenic stimuli and perturbed plasma cell differentiation. Although GC-specific loss of Crebbp was insufficient to initiate malignant transformation, compound Crebbp-haploinsufficient/BCL2-transgenic mice, mimicking the genetics of FL and DLBCL, develop clonal lymphomas recapitulating the features of the human diseases. These findings establish CREBBP as a haploinsufficient tumor-suppressor gene in GC B cells and provide insights into the mechanisms by which its loss contributes to lymphomagenesis.Significance: Loss-of-function mutations of CREBBP are common and early lesions in FL and DLBCL, suggesting a prominent role in lymphoma initiation. Our studies identify the cellular program by which reduced CREBBP dosage facilitates malignant transformation, and have direct implications for targeted lymphoma therapy based on drugs affecting CREBBP-mediated chromatin acetylation. Cancer Discov; 7(3); 322-37. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 235.
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Affiliation(s)
- Jiyuan Zhang
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Sofija Vlasevska
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Victoria A Wells
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Sarah Nataraj
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Antony B Holmes
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Romain Duval
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Stefanie N Meyer
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Tongwei Mo
- Institute for Cancer Genetics, Columbia University, New York, New York
| | - Katia Basso
- Institute for Cancer Genetics, Columbia University, New York, New York.,Department of Pathology and Cell Biology, Columbia University, New York, New York
| | - Paul K Brindle
- Department of Biochemistry, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Shafinaz Hussein
- Department of Pathology and Laboratory Medicine, NorthWell Health, Staten Island University Hospital, Staten Island, New York
| | - Riccardo Dalla-Favera
- Institute for Cancer Genetics, Columbia University, New York, New York.,Department of Pathology and Cell Biology, Columbia University, New York, New York.,Department of Genetics and Development, Columbia University, New York, New York.,Department of Microbiology and Immunology, Columbia University, New York, New York.,Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York
| | - Laura Pasqualucci
- Institute for Cancer Genetics, Columbia University, New York, New York. .,Department of Pathology and Cell Biology, Columbia University, New York, New York.,Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York
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21
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Jiang Y, Ortega-Molina A, Geng H, Ying HY, Hatzi K, Parsa S, McNally D, Wang L, Doane AS, Agirre X, Teater M, Meydan C, Li Z, Poloway D, Wang S, Ennishi D, Scott DW, Stengel KR, Kranz JE, Holson E, Sharma S, Young JW, Chu CS, Roeder RG, Shaknovich R, Hiebert SW, Gascoyne RD, Tam W, Elemento O, Wendel HG, Melnick AM. CREBBP Inactivation Promotes the Development of HDAC3-Dependent Lymphomas. Cancer Discov 2017; 7:38-53. [PMID: 27733359 PMCID: PMC5300005 DOI: 10.1158/2159-8290.cd-16-0975] [Citation(s) in RCA: 176] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 10/11/2016] [Accepted: 10/11/2016] [Indexed: 12/18/2022]
Abstract
Somatic mutations in CREBBP occur frequently in B-cell lymphoma. Here, we show that loss of CREBBP facilitates the development of germinal center (GC)-derived lymphomas in mice. In both human and murine lymphomas, CREBBP loss-of-function resulted in focal depletion of enhancer H3K27 acetylation and aberrant transcriptional silencing of genes that regulate B-cell signaling and immune responses, including class II MHC. Mechanistically, CREBBP-regulated enhancers are counter-regulated by the BCL6 transcriptional repressor in a complex with SMRT and HDAC3, which we found to bind extensively to MHC class II loci. HDAC3 loss-of-function rescued repression of these enhancers and corresponding genes, including MHC class II, and more profoundly suppressed CREBBP-mutant lymphomas in vitro and in vivo Hence, CREBBP loss-of-function contributes to lymphomagenesis by enabling unopposed suppression of enhancers by BCL6/SMRT/HDAC3 complexes, suggesting HDAC3-targeted therapy as a precision approach for CREBBP-mutant lymphomas. SIGNIFICANCE Our findings establish the tumor suppressor function of CREBBP in GC lymphomas in which CREBBP mutations disable acetylation and result in unopposed deacetylation by BCL6/SMRT/HDAC3 complexes at enhancers of B-cell signaling and immune response genes. Hence, inhibition of HDAC3 can restore the enhancer histone acetylation and may serve as a targeted therapy for CREBBP-mutant lymphomas. Cancer Discov; 7(1); 38-53. ©2016 AACR.See related commentary by Höpken, p. 14This article is highlighted in the In This Issue feature, p. 1.
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Affiliation(s)
- Yanwen Jiang
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York
| | - Ana Ortega-Molina
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Huimin Geng
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, California
| | - Hsia-Yuan Ying
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
| | - Katerina Hatzi
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Sara Parsa
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Dylan McNally
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
| | - Ling Wang
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
| | - Ashley S Doane
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York
| | - Xabier Agirre
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
- Area de Oncología, Centro de Investigación Médica Aplicada (CIMA), Universidad de Navarra, Pamplona, Spain
| | - Matt Teater
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York
| | - Cem Meydan
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York
| | - Zhuoning Li
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
| | - David Poloway
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York
| | - Shenqiu Wang
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Daisuke Ennishi
- Centre for Lymphoid Cancer, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - David W Scott
- Centre for Lymphoid Cancer, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Kristy R Stengel
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee
| | | | | | - Sneh Sharma
- Laboratory of Cellular Immunobiology, Division of Hematologic Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - James W Young
- Laboratory of Cellular Immunobiology, Division of Hematologic Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, Weill Cornell Medicine; The Rockefeller University, New York, New York
| | - Chi-Shuen Chu
- Laboratory of Biochemistry and Molecular Biology, The Rockefeller University, New York, New York
| | - Robert G Roeder
- Laboratory of Biochemistry and Molecular Biology, The Rockefeller University, New York, New York
| | | | - Scott W Hiebert
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Randy D Gascoyne
- Centre for Lymphoid Cancer, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Wayne Tam
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Olivier Elemento
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York
| | - Hans-Guido Wendel
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, New York.
| | - Ari M Melnick
- Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, New York.
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Abstract
Chromatin immunoprecipitation followed by sequencing is an invaluable assay for identifying the genomic binding sites of transcription factors. However, transcription factors rarely bind chromatin alone but often bind together with other cofactors, forming protein complexes. Here, we describe a computational method that integrates multiple ChIP-seq and RNA-seq datasets to discover protein complexes and determine their role as activators or repressors. This chapter outlines a detailed computational pipeline for discovering and predicting binding partners from ChIP-seq data and inferring their role in regulating gene expression. This work aims at developing hypotheses about gene regulation via binding partners and deciphering the combinatorial nature of DNA-binding proteins.
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23
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Qin Q, Mei S, Wu Q, Sun H, Li L, Taing L, Chen S, Li F, Liu T, Zang C, Xu H, Chen Y, Meyer CA, Zhang Y, Brown M, Long HW, Liu XS. ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline. BMC Bioinformatics 2016; 17:404. [PMID: 27716038 PMCID: PMC5048594 DOI: 10.1186/s12859-016-1274-4] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2016] [Accepted: 09/21/2016] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Transcription factor binding, histone modification, and chromatin accessibility studies are important approaches to understanding the biology of gene regulation. ChIP-seq and DNase-seq have become the standard techniques for studying protein-DNA interactions and chromatin accessibility respectively, and comprehensive quality control (QC) and analysis tools are critical to extracting the most value from these assay types. Although many analysis and QC tools have been reported, few combine ChIP-seq and DNase-seq data analysis and quality control in a unified framework with a comprehensive and unbiased reference of data quality metrics. RESULTS ChiLin is a computational pipeline that automates the quality control and data analyses of ChIP-seq and DNase-seq data. It is developed using a flexible and modular software framework that can be easily extended and modified. ChiLin is ideal for batch processing of many datasets and is well suited for large collaborative projects involving ChIP-seq and DNase-seq from different designs. ChiLin generates comprehensive quality control reports that include comparisons with historical data derived from over 23,677 public ChIP-seq and DNase-seq samples (11,265 datasets) from eight literature-based classified categories. To the best of our knowledge, this atlas represents the most comprehensive ChIP-seq and DNase-seq related quality metric resource currently available. These historical metrics provide useful heuristic quality references for experiment across all commonly used assay types. Using representative datasets, we demonstrate the versatility of the pipeline by applying it to different assay types of ChIP-seq data. The pipeline software is available open source at https://github.com/cfce/chilin . CONCLUSION ChiLin is a scalable and powerful tool to process large batches of ChIP-seq and DNase-seq datasets. The analysis output and quality metrics have been structured into user-friendly directories and reports. We have successfully compiled 23,677 profiles into a comprehensive quality atlas with fine classification for users.
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Affiliation(s)
- Qian Qin
- Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai, China
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Shenglin Mei
- Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai, China
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Qiu Wu
- Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai, China
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Hanfei Sun
- Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai, China
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Lewyn Li
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA USA
| | - Len Taing
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA USA
| | - Sujun Chen
- Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai, China
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Fugen Li
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA USA
| | - Tao Liu
- Department of Biochemistry, University at Buffalo, Buffalo, NY USA
| | - Chongzhi Zang
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA USA
| | - Han Xu
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA USA
| | - Yiwen Chen
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA USA
| | - Clifford A. Meyer
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA USA
| | - Yong Zhang
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Myles Brown
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA USA
- Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute and Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA
| | - Henry W. Long
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA USA
| | - X. Shirley Liu
- Shanghai Key laboratory of tuberculosis, Shanghai Pulmonary Hospital, Shanghai, China
- Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA USA
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24
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Jammula S, Pasini D. EpiMINE, a computational program for mining epigenomic data. Epigenetics Chromatin 2016; 9:42. [PMID: 27708717 PMCID: PMC5043526 DOI: 10.1186/s13072-016-0095-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Accepted: 09/20/2016] [Indexed: 11/10/2022] Open
Abstract
Background In epigenetic research, both the increasing ease of high-throughput sequencing and a greater interest in genome-wide studies have resulted in an exponential flooding of epigenetic-related data in public domain. This creates an opportunity for exploring data outside the limits of any specific query-centred study. Such data have to undergo standard primary analyses that are accessible with multiple well-stabilized programs. Further downstream analyses, such as genome-wide comparative, correlative and quantitative analyses, are critical in deciphering key biological features. However, these analyses are only accessible for computational researchers and completely lack platforms capable of handling, analysing and linking multiple interdisciplinary datasets with efficient analytical methods. Results Here, we present EpiMINE, a program for mining epigenomic data. It is a user-friendly, stand-alone computational program designed to support multiple datasets, for performing genome-wide correlative and quantitative analysis of ChIP-seq and RNA-seq data. Using data available from the ENCODE project, we illustrated several features of EpiMINE through different biological scenarios to show how easy some known observations can be verified. These results highlight how these approaches can be helpful in identifying novel biological features. Conclusions EpiMINE performs different kinds of genome-wide quantitative and correlative analyses, using ChIP-seq- and RNA-seq-related datasets. Its framework enables it to be used by both experimental and computational researchers. EpiMINE can be downloaded from https://sourceforge.net/projects/epimine/. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0095-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- SriGanesh Jammula
- Department of Experimental Oncology, European Institute of Oncology, Via Adamello 16, 20139 Milan, Italy
| | - Diego Pasini
- Department of Experimental Oncology, European Institute of Oncology, Via Adamello 16, 20139 Milan, Italy
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25
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Bunting KL, Soong TD, Singh R, Jiang Y, Béguelin W, Poloway DW, Swed BL, Hatzi K, Reisacher W, Teater M, Elemento O, Melnick AM. Multi-tiered Reorganization of the Genome during B Cell Affinity Maturation Anchored by a Germinal Center-Specific Locus Control Region. Immunity 2016; 45:497-512. [PMID: 27637145 PMCID: PMC5033726 DOI: 10.1016/j.immuni.2016.08.012] [Citation(s) in RCA: 101] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2015] [Revised: 06/14/2016] [Accepted: 06/24/2016] [Indexed: 12/11/2022]
Abstract
During the humoral immune response, B cells undergo a dramatic change in phenotype to enable antibody affinity maturation in germinal centers (GCs). Using genome-wide chromosomal conformation capture (Hi-C), we found that GC B cells undergo massive reorganization of the genomic architecture that encodes the GC B cell transcriptome. Coordinate expression of genes that specify the GC B cell phenotype-most prominently BCL6-was achieved through a multilayered chromatin reorganization process involving (1) increased promoter connectivity, (2) formation of enhancer networks, (3) 5' to 3' gene looping, and (4) merging of gene neighborhoods that share active epigenetic marks. BCL6 was an anchor point for the formation of GC-specific gene and enhancer loops on chromosome 3. Deletion of a GC-specific, highly interactive locus control region upstream of Bcl6 abrogated GC formation in mice. Thus, large-scale and multi-tiered genomic three-dimensional reorganization is required for coordinate expression of phenotype-driving gene sets that determine the unique characteristics of GC B cells.
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Affiliation(s)
- Karen L Bunting
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA; Department of Pharmacology, Weill Cornell Medical College, New York, NY 10065, USA
| | - T David Soong
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Rajat Singh
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA; Department of Immunology and Microbial Pathogenesis, Weill Cornell Medical College, New York, NY 10065, USA
| | - Yanwen Jiang
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA
| | - Wendy Béguelin
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - David W Poloway
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Brandon L Swed
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Katerina Hatzi
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - William Reisacher
- Department of Otorhinolaryngology, Weill Cornell Medical College/New York Presbyterian Hospital, New York, NY 10065, USA
| | - Matt Teater
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Olivier Elemento
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA.
| | - Ari M Melnick
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA; Department of Pharmacology, Weill Cornell Medical College, New York, NY 10065, USA.
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Georgiou G, van Heeringen SJ. fluff: exploratory analysis and visualization of high-throughput sequencing data. PeerJ 2016; 4:e2209. [PMID: 27547532 PMCID: PMC4957989 DOI: 10.7717/peerj.2209] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 06/13/2016] [Indexed: 01/07/2023] Open
Abstract
Summary. In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org. Availability. fluff is implemented in Python and runs on Linux. The source code is freely available for download at https://github.com/simonvh/fluff.
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Affiliation(s)
- Georgios Georgiou
- Radboud University, Molecular Developmental Biology , Nijmegen , The Netherlands
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27
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Deignan L, Pinheiro MT, Sutcliffe C, Saunders A, Wilcockson SG, Zeef LAH, Donaldson IJ, Ashe HL. Regulation of the BMP Signaling-Responsive Transcriptional Network in the Drosophila Embryo. PLoS Genet 2016; 12:e1006164. [PMID: 27379389 PMCID: PMC4933369 DOI: 10.1371/journal.pgen.1006164] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2016] [Accepted: 06/10/2016] [Indexed: 12/24/2022] Open
Abstract
The BMP signaling pathway has a conserved role in dorsal-ventral axis patterning during embryonic development. In Drosophila, graded BMP signaling is transduced by the Mad transcription factor and opposed by the Brinker repressor. In this study, using the Drosophila embryo as a model, we combine RNA-seq with Mad and Brinker ChIP-seq to decipher the BMP-responsive transcriptional network underpinning differentiation of the dorsal ectoderm during dorsal-ventral axis patterning. We identify multiple new BMP target genes, including positive and negative regulators of EGF signaling. Manipulation of EGF signaling levels by loss- and gain-of-function studies reveals that EGF signaling negatively regulates embryonic BMP-responsive transcription. Therefore, the BMP gene network has a self-regulating property in that it establishes a balance between its activity and that of the antagonistic EGF signaling pathway to facilitate correct patterning. In terms of BMP-dependent transcription, we identify key roles for the Zelda and Zerknüllt transcription factors in establishing the resulting expression domain, and find widespread binding of insulator proteins to the Mad and Brinker-bound genomic regions. Analysis of embryos lacking the BEAF-32 insulator protein shows reduced transcription of a peak BMP target gene and a reduction in the number of amnioserosa cells, the fate specified by peak BMP signaling. We incorporate our findings into a model for Mad-dependent activation, and discuss its relevance to BMP signal interpretation in vertebrates. Embryogenesis involves the patterning of many different cell fates by a limited number of types of signals. One way that these signals promote a particular cell fate is through the induction of a complex, yet highly reproducible, gene expression programme that instructs changes in the cell. For example, there is a conserved role for BMP signals in specifying cell fates during dorsal-ventral axis patterning. Here, we have used genomics approaches to identify the gene expression programme implemented in response to BMP signaling during axis patterning in the Drosophila embryo. Part of the gene network downstream of BMP signaling includes members of the EGF signaling pathway, with our data highlighting reciprocal interactions between these two pathways. We have also determined genome-wide binding of BMP-responsive transcription factors to gain new insights into how the BMP gene network is activated. Our data reveal roles for specific transcription factors and insulator binding proteins, with the latter traditionally associated with the separation of transcriptional domains. Overall, our data will provide a platform for exploiting the tractability of the Drosophila embryo to determine which features of the network are critical drivers of BMP-induced cell fate changes during embryogenesis.
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Affiliation(s)
- Lisa Deignan
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Marco T. Pinheiro
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Catherine Sutcliffe
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Abbie Saunders
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Scott G. Wilcockson
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Leo A. H. Zeef
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Ian J. Donaldson
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Hilary L. Ashe
- Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
- * E-mail:
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28
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The transcriptional repressor Hes1 attenuates inflammation by regulating transcription elongation. Nat Immunol 2016; 17:930-7. [PMID: 27322654 PMCID: PMC4955730 DOI: 10.1038/ni.3486] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2016] [Accepted: 05/05/2016] [Indexed: 12/15/2022]
Abstract
Most of the known regulatory mechanisms that curb inflammatory gene expression target pre-transcription-initiation steps, and evidence for post-initiation regulation of inflammatory gene expression remains scarce. We found that the transcriptional repressor Hes1 suppressed production of CXCL1, a chemokine that is crucial for recruiting neutrophils. Hes1 negatively regulated neutrophil recruitment in vivo in a manner that was dependent on macrophage-produced CXCL1, and it attenuated the severity of inflammatory arthritis. Mechanistically, inhibition of Cxcl1 expression by Hes1 did not involve modification of transcription initiation. Instead, Hes1 inhibited signal-induced recruitment of the positive transcription-elongation complex P-TEFb and thereby prevented phosphorylation of RNA polymerase II at Ser2 and productive elongation. Thus, our results identify Hes1 as a homeostatic suppressor of inflammatory responses that exerts its suppressive function by regulating transcription elongation.
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Fish L, Pencheva N, Goodarzi H, Tran H, Yoshida M, Tavazoie SF. Muscleblind-like 1 suppresses breast cancer metastatic colonization and stabilizes metastasis suppressor transcripts. Genes Dev 2016; 30:386-98. [PMID: 26883358 PMCID: PMC4762424 DOI: 10.1101/gad.270645.115] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Post-transcriptional deregulation is a defining feature of metastatic cancer. While many microRNAs have been implicated as regulators of metastatic progression, less is known about the roles and mechanisms of RNA-binding proteins in this process. We identified muscleblind-like 1 (MBNL1), a gene implicated in myotonic dystrophy, as a robust suppressor of multiorgan breast cancer metastasis. MBNL1 binds the 3' untranslated regions (UTRs) of DBNL (drebrin-like protein) and TACC1 (transforming acidic coiled-coil containing protein 1)-two genes that we implicate as metastasis suppressors. By enhancing the stability of these genes' transcripts, MBNL1 suppresses cell invasiveness. Consistent with these findings, elevated MBNL1 expression in human breast tumors is associated with reduced metastatic relapse likelihood. Our findings delineate a post-transcriptional network that governs breast cancer metastasis through RNA-binding protein-mediated transcript stabilization.
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Affiliation(s)
- Lisa Fish
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, New York 10065, USA
| | - Nora Pencheva
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, New York 10065, USA
| | - Hani Goodarzi
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, New York 10065, USA
| | - Hien Tran
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, New York 10065, USA
| | - Mitsukuni Yoshida
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, New York 10065, USA
| | - Sohail F Tavazoie
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, New York 10065, USA
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30
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Liu Y, Giannopoulou EG, Wen D, Falciatori I, Elemento O, Allis CD, Rafii S, Seandel M. Epigenetic profiles signify cell fate plasticity in unipotent spermatogonial stem and progenitor cells. Nat Commun 2016; 7:11275. [PMID: 27117588 PMCID: PMC4853422 DOI: 10.1038/ncomms11275] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2016] [Accepted: 03/09/2016] [Indexed: 11/29/2022] Open
Abstract
Spermatogonial stem and progenitor cells (SSCs) generate adult male gametes. During in vitro expansion, these unipotent murine cells spontaneously convert to multipotent adult spermatogonial-derived stem cells (MASCs). Here we investigate this conversion process through integrative transcriptomic and epigenomic analyses. We find in SSCs that promoters essential to maintenance and differentiation of embryonic stem cells (ESCs) are enriched with histone H3-lysine4 and -lysine 27 trimethylations. These bivalent modifications are maintained at most somatic promoters after conversion, bestowing MASCs an ESC-like promoter chromatin. At enhancers, the core pluripotency circuitry is activated partially in SSCs and completely in MASCs, concomitant with loss of germ cell-specific gene expression and initiation of embryonic-like programs. Furthermore, SSCs in vitro maintain the epigenomic characteristics of germ cells in vivo. Our observations suggest that SSCs encode innate plasticity through the epigenome and that both conversion of promoter chromatin states and activation of cell type-specific enhancers are prominent features of reprogramming. Spermatogonial stem cells (SSCs) spontaneously convert to multipotent adult spermatogonial-derived stem cells (MASCs). Here, the authors reveal the dynamics of bivalent histone H3-lysine4 and -lysine27 methylation signatures at somatic gene promoters in SSCs and ESC-like promoter chromatin states in MASCs.
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Affiliation(s)
- Ying Liu
- Department of Medicine, Division of Regenerative Medicine, Ansary Stem Cell Institute, Weill Cornell Medical College, 1300 York Avenue, New York, New York 10065, USA.,Chromatin Biology and Epigenetics, The Rockefeller University, New York, New York 10065, USA
| | - Eugenia G Giannopoulou
- Biological Sciences Department, New York City College of Technology, City University of New York, Brooklyn, New York 11201, USA.,Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, New York 10021, USA
| | - Duancheng Wen
- Ronald O. Perelman and Claudia Cohen Center for Reproductive Medicine, Weill Cornell Medical College, New York, New York 10065, USA
| | - Ilaria Falciatori
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge CB2 0RE, UK
| | - Olivier Elemento
- HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York 10065, USA.,Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA
| | - C David Allis
- Chromatin Biology and Epigenetics, The Rockefeller University, New York, New York 10065, USA
| | - Shahin Rafii
- Department of Medicine, Division of Regenerative Medicine, Ansary Stem Cell Institute, Weill Cornell Medical College, 1300 York Avenue, New York, New York 10065, USA
| | - Marco Seandel
- Department of Surgery, Weill Cornell Medical College, New York, New York 10065, USA
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31
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Zhang J, Dominguez-Sola D, Hussein S, Lee JE, Holmes AB, Bansal M, Vlasevska S, Mo T, Tang H, Basso K, Ge K, Dalla-Favera R, Pasqualucci L. Disruption of KMT2D perturbs germinal center B cell development and promotes lymphomagenesis. Nat Med 2015; 21:1190-8. [PMID: 26366712 PMCID: PMC5145002 DOI: 10.1038/nm.3940] [Citation(s) in RCA: 311] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Accepted: 08/11/2015] [Indexed: 12/12/2022]
Abstract
Mutations in the gene encoding the KMT2D (or MLL2) methyltransferase are highly recurrent and occur early during tumorigenesis in diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL). However, the functional consequences of these mutations and their role in lymphomagenesis are unknown. Here we show that FL- and DLBCL-associated KMT2D mutations impair KMT2D enzymatic activity, leading to diminished global H3K4 methylation in germinal-center (GC) B cells and DLBCL cells. Conditional deletion of Kmt2d early during B cell development, but not after initiation of the GC reaction, results in an increase in GC B cells and enhances B cell proliferation in mice. Moreover, genetic ablation of Kmt2d in mice overexpressing Bcl2 increases the incidence of GC-derived lymphomas resembling human tumors. These findings suggest that KMT2D acts as a tumor suppressor gene whose early loss facilitates lymphomagenesis by remodeling the epigenetic landscape of the cancer precursor cells. Eradication of KMT2D-deficient cells may thus represent a rational therapeutic approach for targeting early tumorigenic events.
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Affiliation(s)
- Jiyuan Zhang
- Institute for Cancer Genetics, Columbia University, New York, New York, USA
| | - David Dominguez-Sola
- Institute for Cancer Genetics, Columbia University, New York, New York, USA.,Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Shafinaz Hussein
- Institute for Cancer Genetics, Columbia University, New York, New York, USA
| | - Ji-Eun Lee
- Laboratory of Endocrinology and Receptor Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Antony B Holmes
- Institute for Cancer Genetics, Columbia University, New York, New York, USA
| | - Mukesh Bansal
- Department of Systems Biology, Columbia University, New York, New York, USA
| | - Sofija Vlasevska
- Institute for Cancer Genetics, Columbia University, New York, New York, USA
| | - Tongwei Mo
- Institute for Cancer Genetics, Columbia University, New York, New York, USA
| | - Hongyan Tang
- Institute for Cancer Genetics, Columbia University, New York, New York, USA
| | - Katia Basso
- Institute for Cancer Genetics, Columbia University, New York, New York, USA.,Department of Pathology and Cell Biology, Columbia University, New York, New York, USA
| | - Kai Ge
- Laboratory of Endocrinology and Receptor Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Riccardo Dalla-Favera
- Institute for Cancer Genetics, Columbia University, New York, New York, USA.,Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.,Department of Genetics &Development, Columbia University, New York, New York, USA.,Department of Microbiology &Immunology, Columbia University, New York, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York, USA
| | - Laura Pasqualucci
- Institute for Cancer Genetics, Columbia University, New York, New York, USA.,Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York, USA
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32
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Alarcón CR, Goodarzi H, Lee H, Liu X, Tavazoie S, Tavazoie SF. HNRNPA2B1 Is a Mediator of m(6)A-Dependent Nuclear RNA Processing Events. Cell 2015; 162:1299-308. [PMID: 26321680 DOI: 10.1016/j.cell.2015.08.011] [Citation(s) in RCA: 1044] [Impact Index Per Article: 116.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Revised: 03/10/2015] [Accepted: 07/08/2015] [Indexed: 01/14/2023]
Abstract
N(6)-methyladenosine (m(6)A) is the most abundant internal modification of messenger RNA. While the presence of m(6)A on transcripts can impact nuclear RNA fates, a reader of this mark that mediates processing of nuclear transcripts has not been identified. We find that the RNA-binding protein HNRNPA2B1 binds m(6)A-bearing RNAs in vivo and in vitro and its biochemical footprint matches the m(6)A consensus motif. HNRNPA2B1 directly binds a set of nuclear transcripts and elicits similar alternative splicing effects as the m(6)A writer METTL3. Moreover, HNRNPA2B1 binds to m(6)A marks in a subset of primary miRNA transcripts, interacts with the microRNA Microprocessor complex protein DGCR8, and promotes primary miRNA processing. Also, HNRNPA2B1 loss and METTL3 depletion cause similar processing defects for these pri-miRNA precursors. We propose HNRNPA2B1 to be a nuclear reader of the m(6)A mark and to mediate, in part, this mark's effects on primary microRNA processing and alternative splicing. PAPERCLIP.
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Affiliation(s)
- Claudio R Alarcón
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, NY 10065, USA
| | - Hani Goodarzi
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, NY 10065, USA
| | - Hyeseung Lee
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, NY 10065, USA
| | - Xuhang Liu
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, NY 10065, USA
| | - Saeed Tavazoie
- Department of Biochemistry and Molecular Biophysics and Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Sohail F Tavazoie
- Laboratory of Systems Cancer Biology, Rockefeller University, New York, NY 10065, USA.
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33
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Multiplexing of ChIP-Seq Samples in an Optimized Experimental Condition Has Minimal Impact on Peak Detection. PLoS One 2015; 10:e0129350. [PMID: 26066343 PMCID: PMC4466019 DOI: 10.1371/journal.pone.0129350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2014] [Accepted: 05/07/2015] [Indexed: 11/19/2022] Open
Abstract
Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience, with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed peak detection analyses to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection, and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million single-end reads each and still detect over 90% of all peaks found when using a full lane for sample (~181 million reads). Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and, therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal.
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34
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Ceballos-Chávez M, Subtil-Rodríguez A, Giannopoulou EG, Soronellas D, Vázquez-Chávez E, Vicent GP, Elemento O, Beato M, Reyes JC. The chromatin Remodeler CHD8 is required for activation of progesterone receptor-dependent enhancers. PLoS Genet 2015; 11:e1005174. [PMID: 25894978 PMCID: PMC4403880 DOI: 10.1371/journal.pgen.1005174] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2014] [Accepted: 03/25/2015] [Indexed: 01/01/2023] Open
Abstract
While the importance of gene enhancers in transcriptional regulation is well established, the mechanisms and the protein factors that determine enhancers activity have only recently begun to be unravelled. Recent studies have shown that progesterone receptor (PR) binds regions that display typical features of gene enhancers. Here, we show by ChIP-seq experiments that the chromatin remodeler CHD8 mostly binds promoters under proliferation conditions. However, upon progestin stimulation, CHD8 re-localizes to PR enhancers also enriched in p300 and H3K4me1. Consistently, CHD8 depletion severely impairs progestin-dependent gene regulation. CHD8 binding is PR-dependent but independent of the pioneering factor FOXA1. The SWI/SNF chromatin-remodelling complex is required for PR-dependent gene activation. Interestingly, we show that CHD8 interacts with the SWI/SNF complex and that depletion of BRG1 and BRM, the ATPases of SWI/SNF complex, impairs CHD8 recruitment. We also show that CHD8 is not required for H3K27 acetylation, but contributes to increase accessibility of the enhancer to DNaseI. Furthermore, CHD8 was required for RNAPII recruiting to the enhancers and for transcription of enhancer-derived RNAs (eRNAs). Taken together our data demonstrate that CHD8 is involved in late stages of PR enhancers activation. A lot of research has been devoted during the last decades to understand the mechanisms that control gene promoters activity, however, much less is known about enhancers. Only recently, the use of genome-wide chromatin immunoprecipitation techniques has revealed the existence of more than 400,000 enhancers in the human genome. We are starting to understand the importance of these regulatory elements and how they are activated or repressed. In this work we discover that the chromatin remodeler CHD8 is recruited to Progesteron Receptor-dependent enhancers upon hormone treatment. CHD8 is required for late steps in the activation of these enhancers, including transcription of the enhancers and synthesis of eRNA (long noncoding RNAs derived form the enhancers).
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Affiliation(s)
- María Ceballos-Chávez
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
| | - Alicia Subtil-Rodríguez
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
- * E-mail: (ASR); (JCR)
| | - Eugenia G. Giannopoulou
- Biological Sciences Department, New York City College of Technology, City University of New York, Brooklyn, New York, New York, United States of America
- Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, New York, United States of America
| | - Daniel Soronellas
- Centre for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Elena Vázquez-Chávez
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
| | - Guillermo P. Vicent
- Centre for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Olivier Elemento
- HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, Cornell University, New York, New York, United States of America
| | - Miguel Beato
- Centre for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - José C. Reyes
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
- * E-mail: (ASR); (JCR)
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35
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Epigenomic evolution in diffuse large B-cell lymphomas. Nat Commun 2015; 6:6921. [PMID: 25891015 PMCID: PMC4411286 DOI: 10.1038/ncomms7921] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2014] [Accepted: 03/16/2015] [Indexed: 12/24/2022] Open
Abstract
The contribution of epigenomic alterations to tumour progression and relapse is not well characterized. Here we characterize an association between disease progression and DNA methylation in diffuse large B-cell lymphoma (DLBCL). By profiling genome-wide DNA methylation at single-base pair resolution in thirteen DLBCL diagnosis–relapse sample pairs, we show that DLBCL patients exhibit heterogeneous evolution of tumour methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse-associated methylation signature converging on key pathways such as transforming growth factor-β (TGF-β) receptor activity. We also observe decreased intra-tumour methylation heterogeneity from diagnosis to relapsed tumour samples. Relapse-free patients display lower intra-tumour methylation heterogeneity at diagnosis compared with relapsed patients in an independent validation cohort. Furthermore, intra-tumour methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse. The contribution of epigenomic alterations to tumour progression and relapse is not well characterized. Here the authors characterize epigenetic evolution in aggressive B-cell lymphoma and find that epigenomic heterogeneity may not only support and drive the relapse phenotype but also be used to predict lymphoma relapse.
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36
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Hatzi K, Nance JP, Kroenke MA, Bothwell M, Haddad EK, Melnick A, Crotty S. BCL6 orchestrates Tfh cell differentiation via multiple distinct mechanisms. ACTA ACUST UNITED AC 2015; 212:539-53. [PMID: 25824819 PMCID: PMC4387288 DOI: 10.1084/jem.20141380] [Citation(s) in RCA: 190] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2014] [Accepted: 03/12/2015] [Indexed: 12/31/2022]
Abstract
Follicular helper T cells (Tfh cells) are required for T cell help to B cells, and BCL6 is the defining transcription factor of Tfh cells. However, the functions of BCL6 in Tfh cells have largely remained unclear. Here we defined the BCL6 cistrome in primary human germinal center Tfh cells to assess mechanisms of BCL6 regulation of CD4 T cells, comparing and contrasting BCL6 function in T and B cells. BCL6 primarily acts as a repressor in Tfh cells, and BCL6 binding was associated with control of Tfh cell migration and repression of alternative cell fates. Interestingly, although some BCL6-bound genes possessed BCL6 DNA-binding motifs, many BCL6-bound loci were instead characterized by the presence of DNA motifs for AP1 or STAT. AP1 complexes are key positive downstream mediators of TCR signaling and external stimuli. We show that BCL6 can directly bind AP1, and BCL6 depends on AP1 for recruitment to BCL6-binding sites with AP1 motifs, suggesting that BCL6 subverts AP1 activity. These findings reveal that BCL6 has broad and multifaceted effects on Tfh biology and provide insight into how this master regulator mediates distinct cell context-dependent phenotypes.
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Affiliation(s)
- Katerina Hatzi
- Division of Hematology and Medical Oncology, Weill Cornell Medical College, Cornell University, New York, NY 10065
| | - J Philip Nance
- Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037
| | - Mark A Kroenke
- Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037
| | - Marcella Bothwell
- University of California, San Diego Department of Surgery and Division of Pediatric Otolaryngology, Rady Children's Hospital-San Diego, San Diego, CA 92123 University of California, San Diego Department of Surgery and Division of Pediatric Otolaryngology, Rady Children's Hospital-San Diego, San Diego, CA 92123
| | - Elias K Haddad
- Vaccine and Gene Therapy Institute of Florida, Port St. Lucie, FL 34987
| | - Ari Melnick
- Division of Hematology and Medical Oncology, Weill Cornell Medical College, Cornell University, New York, NY 10065
| | - Shane Crotty
- Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037
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37
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Alarcón CR, Lee H, Goodarzi H, Halberg N, Tavazoie SF. N6-methyladenosine marks primary microRNAs for processing. Nature 2015; 519:482-5. [PMID: 25799998 DOI: 10.1038/nature14281] [Citation(s) in RCA: 964] [Impact Index Per Article: 107.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2014] [Accepted: 02/02/2015] [Indexed: 12/21/2022]
Abstract
The first step in the biogenesis of microRNAs is the processing of primary microRNAs (pri-miRNAs) by the microprocessor complex, composed of the RNA-binding protein DGCR8 and the type III RNase DROSHA. This initial event requires recognition of the junction between the stem and the flanking single-stranded RNA of the pri-miRNA hairpin by DGCR8 followed by recruitment of DROSHA, which cleaves the RNA duplex to yield the pre-miRNA product. While the mechanisms underlying pri-miRNA processing have been determined, the mechanism by which DGCR8 recognizes and binds pri-miRNAs, as opposed to other secondary structures present in transcripts, is not understood. Here we find in mammalian cells that methyltransferase-like 3 (METTL3) methylates pri-miRNAs, marking them for recognition and processing by DGCR8. Consistent with this, METTL3 depletion reduced the binding of DGCR8 to pri-miRNAs and resulted in the global reduction of mature miRNAs and concomitant accumulation of unprocessed pri-miRNAs. In vitro processing reactions confirmed the sufficiency of the N(6)-methyladenosine (m(6)A) mark in promoting pri-miRNA processing. Finally, gain-of-function experiments revealed that METTL3 is sufficient to enhance miRNA maturation in a global and non-cell-type-specific manner. Our findings reveal that the m(6)A mark acts as a key post-transcriptional modification that promotes the initiation of miRNA biogenesis.
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Affiliation(s)
- Claudio R Alarcón
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Hyeseung Lee
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Hani Goodarzi
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Nils Halberg
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Sohail F Tavazoie
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
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38
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RNA-Seq and ChIP-Seq reveal SQSTM1/p62 as a key mediator of JunB suppression of NF-κB-dependent inflammation. J Invest Dermatol 2014; 135:1016-1024. [PMID: 25501661 PMCID: PMC4366298 DOI: 10.1038/jid.2014.519] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2014] [Revised: 11/26/2014] [Accepted: 12/04/2014] [Indexed: 11/08/2022]
Abstract
Mice with epidermal deletion of JunB transcription factor displayed a psoriasis-like inflammation. The relevance of these findings to humans and the mechanisms mediating JunB function are not fully understood. Here we demonstrate that impaired JunB function via gene silencing or overexpression of a dominant negative mutant increased human keratinocyte cell proliferation but decreased cell barrier function. RNA-seq revealed over 500 genes affected by JunB loss of function, which included the upregulation of an array of proinflammatory molecules relevant to psoriasis. Among these were tumor necrosis factor α (TNFα), CCL2, CXCL10, IL6R, and SQSTM1, an adaptor protein involved in nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation. Chromatin immunoprecipitation (ChIP)-Seq and gene reporter analyses showed that JunB directly suppressed SQSTM1 by binding to a consensus AP-1 cis element located around 2 kb upstream of SQSTM1-transcription start site. Similar to JunB loss of function, SQSTM1-overexpression induced TNFα, CCL2, and CXCL10. Conversely, NF-κB inhibition genetically with a mutant IκBα or pharmacologically with pyrrolidine dithiocarbamate (PDTC) prevented cytokine, but not IL6R, induction by JunB deficiency. Taken together, our findings indicate that JunB controls epidermal growth, barrier formation, and proinflammatory responses through direct and indirect mechanisms, pinpointing SQSTM1 as a key mediator of JunB suppression of NF-κB-dependent inflammation.
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DNA hydroxymethylation profiling reveals that WT1 mutations result in loss of TET2 function in acute myeloid leukemia. Cell Rep 2014; 9:1841-1855. [PMID: 25482556 DOI: 10.1016/j.celrep.2014.11.004] [Citation(s) in RCA: 207] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Revised: 10/04/2014] [Accepted: 11/04/2014] [Indexed: 12/21/2022] Open
Abstract
Somatic mutations in IDH1/IDH2 and TET2 result in impaired TET2-mediated conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC). The observation that WT1 inactivating mutations anticorrelate with TET2/IDH1/IDH2 mutations in acute myeloid leukemia (AML) led us to hypothesize that WT1 mutations may impact TET2 function. WT1 mutant AML patients have reduced 5hmC levels similar to TET2/IDH1/IDH2 mutant AML. These mutations are characterized by convergent, site-specific alterations in DNA hydroxymethylation, which drive differential gene expression more than alterations in DNA promoter methylation. WT1 overexpression increases global levels of 5hmC, and WT1 silencing reduced 5hmC levels. WT1 physically interacts with TET2 and TET3, and WT1 loss of function results in a similar hematopoietic differentiation phenotype as observed with TET2 deficiency. These data provide a role for WT1 in regulating DNA hydroxymethylation and suggest that TET2 IDH1/IDH2 and WT1 mutations define an AML subtype defined by dysregulated DNA hydroxymethylation.
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40
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Chakravarty D, Sboner A, Nair SS, Giannopoulou E, Li R, Hennig S, Mosquera JM, Pauwels J, Park K, Kossai M, MacDonald TY, Fontugne J, Erho N, Vergara IA, Ghadessi M, Davicioni E, Jenkins RB, Palanisamy N, Chen Z, Nakagawa S, Hirose T, Bander NH, Beltran H, Fox AH, Elemento O, Rubin MA. The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer. Nat Commun 2014; 5:5383. [PMID: 25415230 PMCID: PMC4241506 DOI: 10.1038/ncomms6383] [Citation(s) in RCA: 463] [Impact Index Per Article: 46.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2013] [Accepted: 09/26/2014] [Indexed: 02/08/2023] Open
Abstract
The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription.
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Affiliation(s)
- Dimple Chakravarty
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA
| | - Andrea Sboner
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA [3] Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, New York 10021, USA
| | - Sujit S Nair
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, George Washington University, Washington DC 20037, USA
| | - Eugenia Giannopoulou
- 1] Biological Sciences Department, New York City College of Technology, City University of New York, Brooklyn, New York 11201, USA [2] Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, New York 10021, USA
| | - Ruohan Li
- School of Biomedical, Biomolecular and Chemical Sciences, University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Sven Hennig
- Chemical Genomics Centre, 44227 Dortmund, Germany
| | - Juan Miguel Mosquera
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA
| | - Jonathan Pauwels
- Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA
| | - Kyung Park
- Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA
| | - Myriam Kossai
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA
| | - Theresa Y MacDonald
- Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA
| | - Jacqueline Fontugne
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA
| | - Nicholas Erho
- Research and Development, GenomeDx Biosciences, Vancouver, British Columbia, Canada V6B 1B8
| | - Ismael A Vergara
- Research and Development, GenomeDx Biosciences, Vancouver, British Columbia, Canada V6B 1B8
| | - Mercedeh Ghadessi
- Research and Development, GenomeDx Biosciences, Vancouver, British Columbia, Canada V6B 1B8
| | - Elai Davicioni
- Research and Development, GenomeDx Biosciences, Vancouver, British Columbia, Canada V6B 1B8
| | - Robert B Jenkins
- Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Nallasivam Palanisamy
- 1] Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, Michigan 48105, USA [2] Henry Ford Health System, Medical Group Urology - Prostate Cancer Research, 1 Ford Place, Room 2D26, Detroit, Michigan 48202, USA
| | - Zhengming Chen
- Division of Biostatistics and Epidemiology, Department of Public Health, Weill Cornell Medical College, New York, New York 10021, USA
| | - Shinichi Nakagawa
- RNA Biology Laboratory, RIKEN Advanced Research Institute, Hirosawa 2-1, Wako 351-0198, Japan
| | - Tetsuro Hirose
- Institute for Genetic Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 060-0815, Japan
| | - Neil H Bander
- Department of Urology, Weill Cornell Medical College of Cornell University, New York, New York 10021, USA
| | - Himisha Beltran
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA
| | - Archa H Fox
- School of Biomedical, Biomolecular and Chemical Sciences, University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Olivier Elemento
- 1] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA [2] Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, New York 10021, USA
| | - Mark A Rubin
- 1] Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 413 East 69th Street, Room 1402, New York, New York 10021, USA [2] Institute for Precision Medicine, Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York 10021, USA
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Chojnowski K, Goryca K, Rubel T, Mikula M. jChIP: a graphical environment for exploratory ChIP-Seq data analysis. BMC Res Notes 2014; 7:676. [PMID: 25260876 PMCID: PMC4189168 DOI: 10.1186/1756-0500-7-676] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2014] [Accepted: 09/23/2014] [Indexed: 12/18/2022] Open
Abstract
Background Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-Seq) provides a powerful tool for discovering protein-DNA interactions. Still, the computational analysis of the great amount of ChIP-Seq data generated, involving mapping of raw data to reference genome, has been a bottle neck for most of researchers in the transcriptional and epigenetic fields. Thus, user-friendly ChIP-Seq processing method sare much needed to enable greater community of computational and bench biologists to exploit the power of ChIP-Seq technology . Findings jChIP is a graphical tool that was developed to analyze and display ChIP-Seq data. It matches reads to the corresponding loci downloaded from Ensembl Genes or Ensembl Regulation databases. jChIP provides a friendly interface for exploratory analysis of mapped reads as well as peak calling data. The built-in functions for graphical display of reads distribution allows to evaluate the quality and meaning of ChIP-Seq data. Conclusion jChIP is a user-friendly GUI-based software for the analysis of ChIP-Seq data within context of known genomic features. Further, jChIP provides tools for discovering new and refining known genome-wide protein binding patterns.
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Affiliation(s)
- Krzysztof Chojnowski
- Department of Genetics, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw 02-781, Poland.
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42
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Popovic R, Martinez-Garcia E, Giannopoulou EG, Zhang Q, Zhang Q, Ezponda T, Shah MY, Zheng Y, Will CM, Small EC, Hua Y, Bulic M, Jiang Y, Carrara M, Calogero RA, Kath WL, Kelleher NL, Wang JP, Elemento O, Licht JD. Histone methyltransferase MMSET/NSD2 alters EZH2 binding and reprograms the myeloma epigenome through global and focal changes in H3K36 and H3K27 methylation. PLoS Genet 2014; 10:e1004566. [PMID: 25188243 PMCID: PMC4154646 DOI: 10.1371/journal.pgen.1004566] [Citation(s) in RCA: 170] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2013] [Accepted: 06/30/2014] [Indexed: 02/06/2023] Open
Abstract
Overexpression of the histone methyltransferase MMSET in t(4;14)+ multiple myeloma patients is believed to be the driving factor in the pathogenesis of this subtype of myeloma. MMSET catalyzes dimethylation of lysine 36 on histone H3 (H3K36me2), and its overexpression causes a global increase in H3K36me2, redistributing this mark in a broad, elevated level across the genome. Here, we demonstrate that an increased level of MMSET also induces a global reduction of lysine 27 trimethylation on histone H3 (H3K27me3). Despite the net decrease in H3K27 methylation, specific genomic loci exhibit enhanced recruitment of the EZH2 histone methyltransferase and become hypermethylated on this residue. These effects likely contribute to the myeloma phenotype since MMSET-overexpressing cells displayed increased sensitivity to EZH2 inhibition. Furthermore, we demonstrate that such MMSET-mediated epigenetic changes require a number of functional domains within the protein, including PHD domains that mediate MMSET recruitment to chromatin. In vivo, targeting of MMSET by an inducible shRNA reversed histone methylation changes and led to regression of established tumors in athymic mice. Together, our work elucidates previously unrecognized interplay between MMSET and EZH2 in myeloma oncogenesis and identifies domains to be considered when designing inhibitors of MMSET function.
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Affiliation(s)
- Relja Popovic
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Eva Martinez-Garcia
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Eugenia G. Giannopoulou
- Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, New York, United States of America
- Biological Sciences Department, New York City College of Technology, City University of New York, Brooklyn, New York, New York, United States of America
| | - Quanwei Zhang
- Department of Statistics, Northwestern University, Evanston, Illinois, United States of America
| | - Qingyang Zhang
- Department of Statistics, Northwestern University, Evanston, Illinois, United States of America
| | - Teresa Ezponda
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Mrinal Y. Shah
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Yupeng Zheng
- Department of Chemistry and Molecular Biosciences, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, United States of America
| | - Christine M. Will
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Eliza C. Small
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Youjia Hua
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Marinka Bulic
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Yanwen Jiang
- HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
| | - Matteo Carrara
- Molecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Raffaele A. Calogero
- Molecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - William L. Kath
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, Illinois, United States of America
| | - Neil L. Kelleher
- Department of Chemistry and Molecular Biosciences, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, United States of America
| | - Ji-Ping Wang
- Department of Statistics, Northwestern University, Evanston, Illinois, United States of America
| | - Olivier Elemento
- HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
| | - Jonathan D. Licht
- Division of Hematology/Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
- * E-mail:
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43
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Palmer CJ, Galan-Caridad JM, Weisberg SP, Lei L, Esquilin JM, Croft GF, Wainwright B, Canoll P, Owens DM, Reizis B. Zfx facilitates tumorigenesis caused by activation of the Hedgehog pathway. Cancer Res 2014; 74:5914-24. [PMID: 25164012 DOI: 10.1158/0008-5472.can-14-0834] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The Hedgehog (Hh) signaling pathway regulates normal development and cell proliferation in metazoan organisms, but its aberrant activation can promote tumorigenesis. Hh-induced tumors arise from various tissues and they may be indolent or aggressive, as is the case with skin basal cell carcinoma (BCC) or cerebellar medulloblastoma, respectively. Little is known about common cell-intrinsic factors that control the development of such diverse Hh-dependent tumors. Transcription factor Zfx is required for the self-renewal of hematopoietic and embryonic stem cells, as well as for the propagation of acute myeloid and T-lymphoblastic leukemias. We report here that Zfx facilitates the development of experimental BCC and medulloblastoma in mice initiated by deletion of the Hh inhibitory receptor Ptch1. Simultaneous deletion of Zfx along with Ptch1 prevented BCC formation and delayed medulloblastoma development. In contrast, Zfx was dispensable for tumorigenesis in a mouse model of glioblastoma. We used genome-wide expression and chromatin-binding analysis in a human medulloblastoma cell line to characterize direct, evolutionarily conserved targets of Zfx, identifying Dis3L and Ube2j1 as two targets required for the growth of the human medulloblastoma cells. Our results establish Zfx as a common cell-intrinsic regulator of diverse Hh-induced tumors, with implications for the definition of new therapeutic targets in these malignancies.
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Affiliation(s)
- Colin J Palmer
- Department of Microbiology and Immunology, Columbia University Medical Center, New York, New York
| | - Jose M Galan-Caridad
- Department of Microbiology and Immunology, Columbia University Medical Center, New York, New York
| | - Stuart P Weisberg
- Department of Microbiology and Immunology, Columbia University Medical Center, New York, New York
| | - Liang Lei
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, New York
| | - Jose M Esquilin
- Division of Pediatric Hematology, Columbia University Medical Center, New York, New York
| | - Gist F Croft
- Departments of Pathology, Neurology and Neuroscience, and Project A.L.S./Laboratory for Stem Cell Research, Columbia University Medical Center, New York, New York
| | - Brandon Wainwright
- Institute for Molecular Bioscience, University of Queensland, St. Lucia, Queensland, Australia
| | - Peter Canoll
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, New York
| | - David M Owens
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, New York. Department of Dermatology, Columbia University Medical Center, New York, New York
| | - Boris Reizis
- Department of Microbiology and Immunology, Columbia University Medical Center, New York, New York.
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44
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Goodarzi H, Zhang S, Buss CG, Fish L, Tavazoie S, Tavazoie SF. Metastasis-suppressor transcript destabilization through TARBP2 binding of mRNA hairpins. Nature 2014; 513:256-60. [PMID: 25043050 DOI: 10.1038/nature13466] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2013] [Accepted: 05/12/2014] [Indexed: 01/30/2023]
Abstract
Aberrant regulation of RNA stability has an important role in many disease states. Deregulated post-transcriptional modulation, such as that governed by microRNAs targeting linear sequence elements in messenger RNAs, has been implicated in the progression of many cancer types. A defining feature of RNA is its ability to fold into structures. However, the roles of structural mRNA elements in cancer progression remain unexplored. Here we performed an unbiased search for post-transcriptional modulators of mRNA stability in breast cancer by conducting whole-genome transcript stability measurements in poorly and highly metastatic isogenic human breast cancer lines. Using a computational framework that searches RNA sequence and structure space, we discovered a family of GC-rich structural cis-regulatory RNA elements, termed sRSEs for structural RNA stability elements, which are significantly overrepresented in transcripts displaying reduced stability in highly metastatic cells. By integrating computational and biochemical approaches, we identified TARBP2, a double-stranded RNA-binding protein implicated in microRNA processing, as the trans factor that binds the sRSE family and similar structural elements--collectively termed TARBP2-binding structural elements (TBSEs)--in transcripts. TARBP2 is overexpressed in metastatic cells and metastatic human breast tumours and destabilizes transcripts containing TBSEs. Endogenous TARBP2 promotes metastatic cell invasion and colonization by destabilizing amyloid precursor protein (APP) and ZNF395 transcripts, two genes previously associated with Alzheimer's and Huntington's disease, respectively. We reveal these genes to be novel metastasis suppressor genes in breast cancer. The cleavage product of APP, extracellular amyloid-α peptide, directly suppresses invasion while ZNF395 transcriptionally represses a pro-metastatic gene expression program. The expression levels of TARBP2, APP and ZNF395 in human breast carcinomas support their experimentally uncovered roles in metastasis. Our findings establish a non-canonical and direct role for TARBP2 in mammalian gene expression regulation and reveal that regulated RNA destabilization through protein-mediated binding of mRNA structural elements can govern cancer progression.
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Affiliation(s)
- Hani Goodarzi
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Steven Zhang
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Colin G Buss
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Lisa Fish
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Saeed Tavazoie
- Department of Biochemistry and Molecular Biophysics, and Department of Systems Biology, Columbia University, New York, New York 10032, USA
| | - Sohail F Tavazoie
- Laboratory of Systems Cancer Biology, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
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45
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Nair NU, Kumar S, Moret BME, Bucher P. Probabilistic partitioning methods to find significant patterns in ChIP-Seq data. Bioinformatics 2014; 30:2406-13. [PMID: 24812341 DOI: 10.1093/bioinformatics/btu318] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION We have witnessed an enormous increase in ChIP-Seq data for histone modifications in the past few years. Discovering significant patterns in these data is an important problem for understanding biological mechanisms. RESULTS We propose probabilistic partitioning methods to discover significant patterns in ChIP-Seq data. Our methods take into account signal magnitude, shape, strand orientation and shifts. We compare our methods with some current methods and demonstrate significant improvements, especially with sparse data. Besides pattern discovery and classification, probabilistic partitioning can serve other purposes in ChIP-Seq data analysis. Specifically, we exemplify its merits in the context of peak finding and partitioning of nucleosome positioning patterns in human promoters. AVAILABILITY AND IMPLEMENTATION The software and code are available in the supplementary material. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Nishanth Ulhas Nair
- Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland
| | - Sunil Kumar
- Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland
| | - Bernard M E Moret
- Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland
| | - Philipp Bucher
- Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland
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46
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Kuo PY, Leshchenko VV, Fazzari MJ, Perumal D, Gellen T, He T, Iqbal J, Baumgartner-Wennerholm S, Nygren L, Zhang F, Zhang W, Suh KS, Goy A, Yang DT, Chan WC, Kahl BS, Verma AK, Gascoyne RD, Kimby E, Sander B, Ye BH, Melnick AM, Parekh S. High-resolution chromatin immunoprecipitation (ChIP) sequencing reveals novel binding targets and prognostic role for SOX11 in mantle cell lymphoma. Oncogene 2014; 34:1231-40. [PMID: 24681958 DOI: 10.1038/onc.2014.44] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2013] [Revised: 01/07/2014] [Accepted: 01/19/2014] [Indexed: 12/18/2022]
Abstract
Sex determining region Y-box 11 (SOX11) expression is specific for mantle cell lymphoma (MCL) as compared with other non-Hodgkin's lymphomas. However, the function and direct-binding targets of SOX11 in MCL are largely unknown. We used high-resolution chromatin immunoprecipitation sequencing to identify the direct target genes of SOX11 in a genome-wide, unbiased manner and elucidate its functional significance. Pathway analysis identified WNT, PKA and TGF-beta signaling pathways as significantly enriched by SOX11-target genes. Quantitative chromatin immunoprecipitation sequencing and promoter reporter assays confirmed that SOX11 directly binds to individual genes and modulates their transcription activities in these pathways in MCL. Functional studies using RNA interference demonstrate that SOX11 directly regulates WNT in MCL. We analyzed SOX11 expression in three independent well-annotated tissue microarrays from the University of Wisconsin (UW), Karolinska Institute and British Columbia Cancer Agency. Our findings suggest that high SOX11 expression is associated with improved survival in a subset of MCL patients, particularly those treated with intensive chemotherapy. Transcriptional regulation of WNT and other biological pathways affected by SOX11-target genes may help explain the impact of SOX11 expression on patient outcomes.
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Affiliation(s)
- P-Y Kuo
- Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - V V Leshchenko
- Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - M J Fazzari
- 1] Department of Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA [2] Department of Genetics, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA
| | - D Perumal
- Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - T Gellen
- Albert Einstein Cancer Center, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA
| | - T He
- Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - J Iqbal
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - S Baumgartner-Wennerholm
- Department of Medicine, Center for Haematology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - L Nygren
- Department of Laboratory Medicine, Division of Pathology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - F Zhang
- Bioinformatics Laboratory, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - W Zhang
- Bioinformatics Laboratory, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - K S Suh
- Genomics and Biomarkers Program, John Theurer Cancer Center, Hackensack University Medical Center, Hackensack, NJ, USA
| | - A Goy
- Genomics and Biomarkers Program, John Theurer Cancer Center, Hackensack University Medical Center, Hackensack, NJ, USA
| | - D T Yang
- Department of Pathology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - W-C Chan
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - B S Kahl
- Department of Medicine, School of Medicine and Public Health, and The UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA
| | - A K Verma
- Albert Einstein Cancer Center, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA
| | - R D Gascoyne
- Department of Pathology and Experimental Therapeutics, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - E Kimby
- Department of Medicine, Center for Haematology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - B Sander
- Department of Laboratory Medicine, Division of Pathology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - B H Ye
- Department of Cell Biology, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA
| | - A M Melnick
- 1] Hematology and Oncology Division, Weill Cornell Medical College, New York, NY, USA [2] Department of Pharmacology, Weill Cornell Medical College, New York, NY, USA
| | - S Parekh
- Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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47
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The transcriptional modulator BCL6 as a molecular target for breast cancer therapy. Oncogene 2014; 34:1073-82. [PMID: 24662818 PMCID: PMC4175367 DOI: 10.1038/onc.2014.61] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Revised: 01/16/2014] [Accepted: 01/19/2014] [Indexed: 12/13/2022]
Abstract
Inappropriate expression or activation of transcription factors can drive patterns of gene expression, leading to the malignant behavior of breast cancer cells. We have found that the transcriptional repressor BCL6 is highly expressed in breast cancer cell lines, and its locus is amplified in about half of primary breast cancers. To understand how BCL6 regulates gene expression in breast cancer cells, we used chromatin immunoprecipitation followed by deep sequencing to identify the BCL6 binding sites on a genomic scale. This revealed that BCL6 regulates a unique cohort of genes in breast cancer cell lines compared with B-cell lymphomas. Furthermore, BCL6 expression promotes the survival of breast cancer cells, and targeting BCL6 with a peptidomimetic inhibitor leads to apoptosis of these cells. Finally, combining a BCL6 inhibitor and a signal transducer and activator of transcription3 inhibitor provided enhanced cell killing in triple-negative breast cancer cell lines, suggesting that combination therapy may be particularly useful. Thus, targeting BCL6 alone or in conjunction with other signaling pathways may be a useful therapeutic strategy for treating breast cancer.
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48
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Cornwell EW, Mirbod A, Wu CL, Kandarian SC, Jackman RW. C26 cancer-induced muscle wasting is IKKβ-dependent and NF-kappaB-independent. PLoS One 2014; 9:e87776. [PMID: 24489962 PMCID: PMC3906224 DOI: 10.1371/journal.pone.0087776] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Accepted: 12/30/2013] [Indexed: 12/24/2022] Open
Abstract
Existing data suggest that NF-kappaB signaling is a key regulator of cancer-induced skeletal muscle wasting. However, identification of the components of this signaling pathway and of the NF-κB transcription factors that regulate wasting is far from complete. In muscles of C26 tumor bearing mice, overexpression of dominant negative (d.n.) IKKβ blocked muscle wasting by 69% and the IκBα-super repressor blocked wasting by 41%. In contrast, overexpression of d.n. IKKα or d.n. NIK did not block C26-induced wasting. Surprisingly, overexpression of d.n. p65 or d.n. c-Rel did not significantly affect muscle wasting. Genome-wide mRNA expression arrays showed upregulation of many genes previously implicated in muscle atrophy. To test if these upregulated genes were direct targets of NF-κB transcription factors, we compared genome-wide p65 binding to DNA in control and cachectic muscle using ChIP-sequencing. Bioinformatic analysis of ChIP-sequencing data from control and C26 muscles showed very little p65 binding to genes in cachexia and little to suggest that upregulated p65 binding influences the gene expression associated with muscle based cachexia. The p65 ChIP-seq data are consistent with our finding of no significant change in protein binding to an NF-κB oligonucleotide in a gel shift assay, no activation of a NF-κB-dependent reporter, and no effect of d.n.p65 overexpression in muscles of tumor bearing mice. Taken together, these data support the idea that although inhibition of IκBα, and particularly IKKβ, blocks cancer-induced wasting, the alternative NF-κB signaling pathway is not required. In addition, the downstream NF-κB transcription factors, p65 and c-Rel do not appear to regulate the transcriptional changes induced by the C26 tumor. These data are consistent with the growing body of literature showing that there are NF-κB-independent substrates of IKKβ and IκBα that regulate physiological processes.
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Affiliation(s)
- Evangeline W. Cornwell
- Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Azadeh Mirbod
- Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Chia-Ling Wu
- Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Susan C. Kandarian
- Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Robert W. Jackman
- Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America
- * E-mail:
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Strbenac D, Armstrong NJ, Yang JYH. Detection and classification of peaks in 5' cap RNA sequencing data. BMC Genomics 2013; 14 Suppl 5:S9. [PMID: 24564843 PMCID: PMC3852351 DOI: 10.1186/1471-2164-14-s5-s9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND The large-scale sequencing of 5' cap enriched cDNA promises to reveal the diversity of transcription initiation across entire genomes. The process of transcription is noisy, and there is often no single, exact start site. This creates the need for a fast and simple method of identifying transcription start peaks based on this type of data. Due to both biological and technical noise, many of the peaks seen are not real transcription initiation events. Classification of the observed peaks is an essential filtering step in the discovery of genuine initiation locations. RESULTS We develop a two-stage approach consisting of a fast and simple algorithm based on a sliding window with Poisson null distribution for detecting the genomic locations of peaks, followed by a linear support vector machine classifier to distinguish between peaks which represent the initiation of transcription and peaks that do not. Comparison of classification performance to the best existing method based on whole genome segmentation showed comparable precision and improved recall. Internal features, which are intrinsic to the data and require no further experiments, had high precision and recall rates. Addition of pooled external data or matched RNA sequencing data resulted in gains of recall with equivalent precision. CONCLUSIONS The Poisson sliding window model is an effective and fast way of taking the peak neighbourhood into account, and finding statistically significant peaks over a range of transcript expression values. It is orders of magnitude faster than doing whole genome segmentation. The support vector classification scheme has better precision and recall than existing methods. Integrating additional datasets is shown to provide minor gains in recall, in comparison to using only the cap-sequencing data.
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Krystkowiak I, Lenart J, Debski K, Kuterba P, Petas M, Kaminska B, Dabrowski M. Nencki Genomics Database--Ensembl funcgen enhanced with intersections, user data and genome-wide TFBS motifs. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2013; 2013:bat069. [PMID: 24089456 PMCID: PMC3788330 DOI: 10.1093/database/bat069] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
We present the Nencki Genomics Database, which extends the functionality of Ensembl Regulatory Build (funcgen) for the three species: human, mouse and rat. The key enhancements over Ensembl funcgen include the following: (i) a user can add private data, analyze them alongside the public data and manage access rights; (ii) inside the database, we provide efficient procedures for computing intersections between regulatory features and for mapping them to the genes. To Ensembl funcgen-derived data, which include data from ENCODE, we add information on conserved non-coding (putative regulatory) sequences, and on genome-wide occurrence of transcription factor binding site motifs from the current versions of two major motif libraries, namely, Jaspar and Transfac. The intersections and mapping to the genes are pre-computed for the public data, and the result of any procedure run on the data added by the users is stored back into the database, thus incrementally increasing the body of pre-computed data. As the Ensembl funcgen schema for the rat is currently not populated, our database is the first database of regulatory features for this frequently used laboratory animal. The database is accessible without registration using the mysql client: mysql –h database.nencki-genomics.org –u public. Registration is required only to add or access private data. A WSDL webservice provides access to the database from any SOAP client, including the Taverna Workbench with a graphical user interface. Database URL:http://www.nencki-genomics.org.
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Affiliation(s)
- Izabella Krystkowiak
- Laboratory of Molecular Neurobiology, Neurobiology Center, Nencki Institute of Experimental Biology, Warsaw, Poland
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