1
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Ordoñez R, Zhang W, Ellis G, Zhu Y, Ashe HJ, Ribeiro-dos-Santos AM, Brosh R, Huang E, Hogan MS, Boeke JD, Maurano MT. Genomic context sensitizes regulatory elements to genetic disruption. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.02.547201. [PMID: 37781588 PMCID: PMC10541140 DOI: 10.1101/2023.07.02.547201] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Enhancer function is frequently investigated piecemeal using truncated reporter assays or single deletion analysis. Thus it remains unclear to what extent enhancer function at native loci relies on surrounding genomic context. Using the Big-IN technology for targeted integration of large DNAs, we analyzed the regulatory architecture of the murine Igf2/H19 locus, a paradigmatic model of enhancer selectivity. We assembled payloads containing a 157-kb functional Igf2/H19 locus and engineered mutations to genetically direct CTCF occupancy at the imprinting control region (ICR) that switches the target gene of the H19 enhancer cluster. Contrasting activity of payloads delivered at the endogenous Igf2/H19 locus or ectopically at Hprt revealed that the Igf2/H19 locus includes additional, previously unknown long-range regulatory elements. Exchanging components of the Igf2/H19 locus with the well-studied Sox2 locus showed that the H19 enhancer cluster functioned poorly out of context, and required its native surroundings to activate Sox2 expression. Conversely, the Sox2 locus control region (LCR) could activate both Igf2 and H19 outside its native context, but its activity was only partially modulated by CTCF occupancy at the ICR. Analysis of regulatory DNA actuation across different cell types revealed that, while the H19 enhancers are tightly coordinated within their native locus, the Sox2 LCR acts more independently. We show that these enhancer clusters typify broader classes of loci genome-wide. Our results show that unexpected dependencies may influence even the most studied functional elements, and our synthetic regulatory genomics approach permits large-scale manipulation of complete loci to investigate the relationship between locus architecture and function.
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Affiliation(s)
- Raquel Ordoñez
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- These authors contributed equally
| | - Weimin Zhang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- These authors contributed equally
| | - Gwen Ellis
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: Department of Biology, University of Vermont, Burlington, VT 05405, USA
| | - Yinan Zhu
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Hannah J. Ashe
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: School of Medicine, University of Maryland, Baltimore, MD 21201, USA
| | | | - Ran Brosh
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Emily Huang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: Highmark Health, Pittsburgh, PA 15222, USA
| | - Megan S. Hogan
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: Neochromosome Inc., Long Island City, NY 11101, USA
| | - Jef D. Boeke
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Department of Biochemistry Molecular Pharmacology, NYU School of Medicine, New York, NY 10016, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
| | - Matthew T. Maurano
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Department of Pathology, NYU School of Medicine, New York, NY 10016, USA
- Lead contact
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2
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Oh KS, Aqdas M, Sung MH. XL-DNase-Seq: Footprinting Analysis of Dynamic Transcription Factors. Methods Mol Biol 2024; 2846:243-261. [PMID: 39141240 DOI: 10.1007/978-1-0716-4071-5_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
We have developed a novel method for genomic footprinting of transcription factors (TFs) that detects potential gene regulatory relationships from DNase-seq data at the nucleotide level. We introduce an assay termed cross-link (XL)-DNase-seq, designed to capture chromatin interactions of dynamic TFs. A mild cross-linking step in XL-DNase-seq improves the detection of DNase-based footprints of dynamic TFs. The footprint strengths and detectability depend on an optimal cross-linking procedure. This method may help extract novel gene regulatory circuits involving previously undetectable TFs. The XL-DNase-seq method is illustrated here for activated mouse macrophage-like cells, which share several features with inflammatory macrophages.
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Affiliation(s)
- Kyu-Seon Oh
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Mohammad Aqdas
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Myong-Hee Sung
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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3
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Hitz BC, Lee JW, Jolanki O, Kagda MS, Graham K, Sud P, Gabdank I, Strattan JS, Sloan CA, Dreszer T, Rowe LD, Podduturi NR, Malladi VS, Chan ET, Davidson JM, Ho M, Miyasato S, Simison M, Tanaka F, Luo Y, Whaling I, Hong EL, Lee BT, Sandstrom R, Rynes E, Nelson J, Nishida A, Ingersoll A, Buckley M, Frerker M, Kim DS, Boley N, Trout D, Dobin A, Rahmanian S, Wyman D, Balderrama-Gutierrez G, Reese F, Durand NC, Dudchenko O, Weisz D, Rao SSP, Blackburn A, Gkountaroulis D, Sadr M, Olshansky M, Eliaz Y, Nguyen D, Bochkov I, Shamim MS, Mahajan R, Aiden E, Gingeras T, Heath S, Hirst M, Kent WJ, Kundaje A, Mortazavi A, Wold B, Cherry JM. The ENCODE Uniform Analysis Pipelines. RESEARCH SQUARE 2023:rs.3.rs-3111932. [PMID: 37503119 PMCID: PMC10371165 DOI: 10.21203/rs.3.rs-3111932/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses.
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Affiliation(s)
- Benjamin C Hitz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jin-Wook Lee
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Otto Jolanki
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Meenakshi S Kagda
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Keenan Graham
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Paul Sud
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Idan Gabdank
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - J Seth Strattan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Cricket A Sloan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Timothy Dreszer
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Laurence D Rowe
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Nikhil R Podduturi
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Venkat S Malladi
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Esther T Chan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jean M Davidson
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Marcus Ho
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Stuart Miyasato
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Matt Simison
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Forrest Tanaka
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yunhai Luo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ian Whaling
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Eurie L Hong
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Brian T Lee
- Genomics Institute, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Richard Sandstrom
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Eric Rynes
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Jemma Nelson
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Andrew Nishida
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Alyssa Ingersoll
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Michael Buckley
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Mark Frerker
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Daniel S Kim
- Department of Genetics, Department of Computer Science, Stanford University, 240 Pasteur Drive, Palo Alto, CA 94304, USA
| | - Nathan Boley
- Department of Genetics, Department of Computer Science, Stanford University, 240 Pasteur Drive, Palo Alto, CA 94304, USA
| | - Diane Trout
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125 USA
| | - Alex Dobin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sorena Rahmanian
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | - Dana Wyman
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | | | - Fairlie Reese
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | - Neva C Durand
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
- Department of Computer Science, Rice University, Houston, TX 77030, USA
| | - Olga Dudchenko
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - David Weisz
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Suhas S P Rao
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Alyssa Blackburn
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Dimos Gkountaroulis
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Mahdi Sadr
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Moshe Olshansky
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yossi Eliaz
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Dat Nguyen
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ivan Bochkov
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Muhammad Saad Shamim
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ragini Mahajan
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
- Department of BioSciences, Rice University, Houston, TX 77005, USA
| | - Erez Aiden
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Tom Gingeras
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Simon Heath
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain
| | - Martin Hirst
- Micheal Smith Laboratories, University of British Columbia, British Columbia, Canada
| | - W James Kent
- Genomics Institute, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Anshul Kundaje
- Department of Genetics, Department of Computer Science, Stanford University, 240 Pasteur Drive, Palo Alto, CA 94304, USA
| | - Ali Mortazavi
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | - Barbara Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125 USA
| | - J Michael Cherry
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
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4
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Hitz BC, Jin-Wook L, Jolanki O, Kagda MS, Graham K, Sud P, Gabdank I, Strattan JS, Sloan CA, Dreszer T, Rowe LD, Podduturi NR, Malladi VS, Chan ET, Davidson JM, Ho M, Miyasato S, Simison M, Tanaka F, Luo Y, Whaling I, Hong EL, Lee BT, Sandstrom R, Rynes E, Nelson J, Nishida A, Ingersoll A, Buckley M, Frerker M, Kim DS, Boley N, Trout D, Dobin A, Rahmanian S, Wyman D, Balderrama-Gutierrez G, Reese F, Durand NC, Dudchenko O, Weisz D, Rao SSP, Blackburn A, Gkountaroulis D, Sadr M, Olshansky M, Eliaz Y, Nguyen D, Bochkov I, Shamim MS, Mahajan R, Aiden E, Gingeras T, Heath S, Hirst M, Kent WJ, Kundaje A, Mortazavi A, Wold B, Cherry JM. The ENCODE Uniform Analysis Pipelines. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.04.535623. [PMID: 37066421 PMCID: PMC10104020 DOI: 10.1101/2023.04.04.535623] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses.
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Affiliation(s)
- Benjamin C Hitz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lee Jin-Wook
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Otto Jolanki
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Meenakshi S Kagda
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Keenan Graham
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Paul Sud
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Idan Gabdank
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - J Seth Strattan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Cricket A Sloan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Timothy Dreszer
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Laurence D Rowe
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Nikhil R Podduturi
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Venkat S Malladi
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Esther T Chan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jean M Davidson
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Marcus Ho
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Stuart Miyasato
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Matt Simison
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Forrest Tanaka
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yunhai Luo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ian Whaling
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Eurie L Hong
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Brian T Lee
- Genomics Institute, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Richard Sandstrom
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Eric Rynes
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Jemma Nelson
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Andrew Nishida
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Alyssa Ingersoll
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Michael Buckley
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Mark Frerker
- Altius Institute for Biomedical Sciences, 2211 Elliott Avenue, 6th Floor, Seattle, WA 98121, USA
| | - Daniel S Kim
- Dept. of Genetics, Dept. of Computer Science, Stanford University, 240 Pasteur Drive, Palo Alto, CA 94304, USA
| | - Nathan Boley
- Dept. of Genetics, Dept. of Computer Science, Stanford University, 240 Pasteur Drive, Palo Alto, CA 94304, USA
| | - Diane Trout
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125 USA
| | - Alex Dobin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sorena Rahmanian
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | - Dana Wyman
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | | | - Fairlie Reese
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | - Neva C Durand
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
- Department of Computer Science, Rice University, Houston, TX 77030, USA
| | - Olga Dudchenko
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - David Weisz
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Suhas S P Rao
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Alyssa Blackburn
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Dimos Gkountaroulis
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Mahdi Sadr
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Moshe Olshansky
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yossi Eliaz
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Dat Nguyen
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ivan Bochkov
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Muhammad Saad Shamim
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ragini Mahajan
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
- Department of BioSciences, Rice University, Houston, TX 77005, USA
| | - Erez Aiden
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Tom Gingeras
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Simon Heath
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain
| | - Martin Hirst
- Micheal Smith Laboratories, University of British Columbia, British Columbia, Canada
| | - W James Kent
- Genomics Institute, School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Anshul Kundaje
- Dept. of Genetics, Dept. of Computer Science, Stanford University, 240 Pasteur Drive, Palo Alto, CA 94304, USA
| | - Ali Mortazavi
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA
| | - Barbara Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125 USA
| | - J Michael Cherry
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
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5
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Typical Enhancers, Super-Enhancers, and Cancers. Cancers (Basel) 2022; 14:cancers14184375. [PMID: 36139535 PMCID: PMC9496678 DOI: 10.3390/cancers14184375] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/29/2022] [Accepted: 09/05/2022] [Indexed: 11/21/2022] Open
Abstract
Simple Summary The cancer genome has been exhaustively studied upon the advent of Next-Generation Sequencing technologies. Coding and non-coding sequences have been defined as hotspots of genomic variations that affect the naïve gene expression programs established in normal cells, thus working as endogenous drivers of carcinogenesis. In this review, we comprehensively summarize fundamental aspects of gene expression regulation, with emphasis on the impact of sequence and structural variations mapped across non-coding cis-acting elements of genes encoding for tumor-related transcription factors. Chromatin architecture, epigenome reprogramming, transcriptional enhancers and Super-enhancers, oncogene regulation, cutting-edge technologies, and pharmacological treatment are substantially highlighted. Abstract Non-coding segments of the human genome are enriched in cis-regulatory modules that constitute functional elements, such as transcriptional enhancers and Super-enhancers. A hallmark of cancer pathogenesis is the dramatic dysregulation of the “archetype” gene expression profiles of normal human cells. Genomic variations can promote such deficiencies when occurring across enhancers and Super-enhancers, since they affect their mechanistic principles, their functional capacity and specificity, and the epigenomic features of the chromatin microenvironment across which these regulatory elements reside. Here, we comprehensively describe: fundamental mechanisms of gene expression dysregulation in cancers that involve genomic abnormalities within enhancers’ and Super-enhancers’ (SEs) sequences, which alter the expression of oncogenic transcription factors (TFs); cutting-edge technologies applied for the analysis of variation-enriched hotspots of the cancer genome; and pharmacological approaches for the treatment of Super-enhancers’ aberrant function. Finally, we provide an intratumor meta-analysis, which highlights that genomic variations in transcription-factor-driven tumors are accompanied overexpression of genes, a portion of which encodes for additional cancer-related transcription factors.
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6
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An effector index to predict target genes at GWAS loci. Hum Genet 2022; 141:1431-1447. [PMID: 35147782 DOI: 10.1007/s00439-022-02434-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 01/15/2022] [Indexed: 11/04/2022]
Abstract
Drug development and biological discovery require effective strategies to map existing genetic associations to causal genes. To approach this problem, we selected 12 common diseases and quantitative traits for which highly powered genome-wide association studies (GWAS) were available. For each disease or trait, we systematically curated positive control gene sets from Mendelian forms of the disease and from targets of medicines used for disease treatment. We found that these positive control genes were highly enriched in proximity of GWAS-associated single-nucleotide variants (SNVs). We then performed quantitative assessment of the contribution of commonly used genomic features, including open chromatin maps, expression quantitative trait loci (eQTL), and chromatin conformation data. Using these features, we trained and validated an Effector Index (Ei), to map target genes for these 12 common diseases and traits. Ei demonstrated high predictive performance, both with cross-validation on the training set, and an independently derived set for type 2 diabetes. Key predictive features included coding or transcript-altering SNVs, distance to gene, and open chromatin-based metrics. This work outlines a simple, understandable approach to prioritize genes at GWAS loci for functional follow-up and drug development, and provides a systematic strategy for prioritization of GWAS target genes.
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7
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Loft A, Andersen MW, Madsen JGS, Mandrup S. Analysis of Enhancers and Transcriptional Networks in Thermogenic Adipocytes. Methods Mol Biol 2022; 2448:155-175. [PMID: 35167097 DOI: 10.1007/978-1-0716-2087-8_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Transcription factor (TF) networks orchestrate the regulation of gene programs in mammalian cells, including white and brown adipocytes. In this protocol, we outline how genomics and transcriptomics data can be integrated to infer causal TFs of a given cellular response or cell type using "Integrated analysis of Motif Activity and Gene Expression changes of transcription factors" (IMAGE). Here, we show how key regulatory TFs controlling white and brown adipocyte gene programs can be predicted from chromatin accessibility and RNA-seq data. Furthermore, we demonstrate how information about target sites and target genes of the predicted key regulators can be integrated to propose testable hypotheses regarding the role and mechanisms of TFs.
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Affiliation(s)
- Anne Loft
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark.
- Center for Functional Genomics and Tissue Plasticity (ATLAS), University of Southern Denmark, Odense, Denmark.
| | - Maja Worm Andersen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Jesper Grud Skat Madsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
- Center for Functional Genomics and Tissue Plasticity (ATLAS), University of Southern Denmark, Odense, Denmark
| | - Susanne Mandrup
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark.
- Center for Functional Genomics and Tissue Plasticity (ATLAS), University of Southern Denmark, Odense, Denmark.
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8
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Georgolopoulos G, Psatha N, Iwata M, Nishida A, Som T, Yiangou M, Stamatoyannopoulos JA, Vierstra J. Discrete regulatory modules instruct hematopoietic lineage commitment and differentiation. Nat Commun 2021; 12:6790. [PMID: 34815405 PMCID: PMC8611072 DOI: 10.1038/s41467-021-27159-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 10/20/2021] [Indexed: 11/08/2022] Open
Abstract
Lineage commitment and differentiation is driven by the concerted action of master transcriptional regulators at their target chromatin sites. Multiple efforts have characterized the key transcription factors (TFs) that determine the various hematopoietic lineages. However, the temporal interactions between individual TFs and their chromatin targets during differentiation and how these interactions dictate lineage commitment remains poorly understood. Here we perform dense, daily, temporal profiling of chromatin accessibility (DNase I-seq) and gene expression changes (total RNA-seq) along ex vivo human erythropoiesis to comprehensively define developmentally regulated DNase I hypersensitive sites (DHSs) and transcripts. We link both distal DHSs to their target gene promoters and individual TFs to their target DHSs, revealing that the regulatory landscape is organized in distinct sequential regulatory modules that regulate lineage restriction and maturation. Finally, direct comparison of transcriptional dynamics (bulk and single-cell) and lineage potential between erythropoiesis and megakaryopoiesis uncovers differential fate commitment dynamics between the two lineages as they exit the stem and progenitor stage. Collectively, these data provide insights into the temporally regulated synergy of the cis- and the trans-regulatory components underlying hematopoietic lineage commitment and differentiation.
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Affiliation(s)
- Grigorios Georgolopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA.
- Department of Genetics, Development & Molecular Biology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | | | - Mineo Iwata
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Andrew Nishida
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Tannishtha Som
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Minas Yiangou
- Department of Genetics, Development & Molecular Biology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - John A Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Division of Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jeff Vierstra
- Altius Institute for Biomedical Sciences, Seattle, WA, USA.
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9
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Tissue context determines the penetrance of regulatory DNA variation. Nat Commun 2021; 12:2850. [PMID: 33990600 PMCID: PMC8121920 DOI: 10.1038/s41467-021-23139-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 04/13/2021] [Indexed: 01/08/2023] Open
Abstract
Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.
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10
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Lee BH, Rhie SK. Molecular and computational approaches to map regulatory elements in 3D chromatin structure. Epigenetics Chromatin 2021; 14:14. [PMID: 33741028 PMCID: PMC7980343 DOI: 10.1186/s13072-021-00390-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 03/08/2021] [Indexed: 12/19/2022] Open
Abstract
Epigenetic marks do not change the sequence of DNA but affect gene expression in a cell-type specific manner by altering the activities of regulatory elements. Development of new molecular biology assays, sequencing technologies, and computational approaches enables us to profile the human epigenome in three-dimensional structure genome-wide. Here we describe various molecular biology techniques and bioinformatic tools that have been developed to measure the activities of regulatory elements and their chromatin interactions. Moreover, we list currently available three-dimensional epigenomic data sets that are generated in various human cell types and tissues to assist in the design and analysis of research projects.
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Affiliation(s)
- Beoung Hun Lee
- Department of Biochemistry and Molecular Medicine and the Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Suhn K Rhie
- Department of Biochemistry and Molecular Medicine and the Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA.
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11
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Mariani L, Weinand K, Gisselbrecht SS, Bulyk ML. MEDEA: analysis of transcription factor binding motifs in accessible chromatin. Genome Res 2020; 30:736-748. [PMID: 32424069 PMCID: PMC7263192 DOI: 10.1101/gr.260877.120] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 04/10/2020] [Indexed: 12/15/2022]
Abstract
Deciphering the interplay between chromatin accessibility and transcription factor (TF) binding is fundamental to understanding transcriptional regulation, control of cellular states, and the establishment of new phenotypes. Recent genome-wide chromatin accessibility profiling studies have provided catalogs of putative open regions, where TFs can recognize their motifs and regulate gene expression programs. Here, we present motif enrichment in differential elements of accessibility (MEDEA), a computational tool that analyzes high-throughput chromatin accessibility genomic data to identify cell-type-specific accessible regions and lineage-specific motifs associated with TF binding therein. To benchmark MEDEA, we used a panel of reference cell lines profiled by ENCODE and curated by the ENCODE Project Consortium for the ENCODE-DREAM Challenge. By comparing results with RNA-seq data, ChIP-seq peaks, and DNase-seq footprints, we show that MEDEA improves the detection of motifs associated with known lineage specifiers. We then applied MEDEA to 610 ENCODE DNase-seq data sets, where it revealed significant motifs even when absolute enrichment was low and where it identified novel regulators, such as NRF1 in kidney development. Finally, we show that MEDEA performs well on both bulk and single-cell ATAC-seq data. MEDEA is publicly available as part of our Glossary-GENRE suite for motif enrichment analysis.
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Affiliation(s)
- Luca Mariani
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Kathryn Weinand
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.,Bioinformatics and Integrative Genomics PhD Program, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Stephen S Gisselbrecht
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Martha L Bulyk
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.,Bioinformatics and Integrative Genomics PhD Program, Harvard University, Cambridge, Massachusetts 02138, USA.,Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
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12
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Quang D, Xie X. FactorNet: A deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data. Methods 2019; 166:40-47. [PMID: 30922998 PMCID: PMC6708499 DOI: 10.1016/j.ymeth.2019.03.020] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 03/05/2019] [Accepted: 03/20/2019] [Indexed: 01/08/2023] Open
Abstract
Due to the large numbers of transcription factors (TFs) and cell types, querying binding profiles of all valid TF/cell type pairs is not experimentally feasible. To address this issue, we developed a convolutional-recurrent neural network model, called FactorNet, to computationally impute the missing binding data. FactorNet trains on binding data from reference cell types to make predictions on testing cell types by leveraging a variety of features, including genomic sequences, genome annotations, gene expression, and signal data, such as DNase I cleavage. FactorNet implements several convenient strategies to reduce runtime and memory consumption. By visualizing the neural network models, we can interpret how the model predicts binding. We also investigate the variables that affect cross-cell type accuracy, and offer suggestions to improve upon this field. Our method ranked among the top teams in the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge, achieving first place on six of the 13 final round evaluation TF/cell type pairs, the most of any competing team. The FactorNet source code is publicly available, allowing users to reproduce our methodology from the ENCODE-DREAM Challenge.
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Affiliation(s)
- Daniel Quang
- University of California, Department of Computer Science, Irvine, CA 92697, United States.
| | - Xiaohui Xie
- University of California, Department of Computer Science, Irvine, CA 92697, United States.
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13
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Perenthaler E, Yousefi S, Niggl E, Barakat TS. Beyond the Exome: The Non-coding Genome and Enhancers in Neurodevelopmental Disorders and Malformations of Cortical Development. Front Cell Neurosci 2019; 13:352. [PMID: 31417368 PMCID: PMC6685065 DOI: 10.3389/fncel.2019.00352] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 07/16/2019] [Indexed: 12/22/2022] Open
Abstract
The development of the human cerebral cortex is a complex and dynamic process, in which neural stem cell proliferation, neuronal migration, and post-migratory neuronal organization need to occur in a well-organized fashion. Alterations at any of these crucial stages can result in malformations of cortical development (MCDs), a group of genetically heterogeneous neurodevelopmental disorders that present with developmental delay, intellectual disability and epilepsy. Recent progress in genetic technologies, such as next generation sequencing, most often focusing on all protein-coding exons (e.g., whole exome sequencing), allowed the discovery of more than a 100 genes associated with various types of MCDs. Although this has considerably increased the diagnostic yield, most MCD cases remain unexplained. As Whole Exome Sequencing investigates only a minor part of the human genome (1-2%), it is likely that patients, in which no disease-causing mutation has been identified, could harbor mutations in genomic regions beyond the exome. Even though functional annotation of non-coding regions is still lagging behind that of protein-coding genes, tremendous progress has been made in the field of gene regulation. One group of non-coding regulatory regions are enhancers, which can be distantly located upstream or downstream of genes and which can mediate temporal and tissue-specific transcriptional control via long-distance interactions with promoter regions. Although some examples exist in literature that link alterations of enhancers to genetic disorders, a widespread appreciation of the putative roles of these sequences in MCDs is still lacking. Here, we summarize the current state of knowledge on cis-regulatory regions and discuss novel technologies such as massively-parallel reporter assay systems, CRISPR-Cas9-based screens and computational approaches that help to further elucidate the emerging role of the non-coding genome in disease. Moreover, we discuss existing literature on mutations or copy number alterations of regulatory regions involved in brain development. We foresee that the future implementation of the knowledge obtained through ongoing gene regulation studies will benefit patients and will provide an explanation to part of the missing heritability of MCDs and other genetic disorders.
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Affiliation(s)
| | | | | | - Tahsin Stefan Barakat
- Department of Clinical Genetics, Erasmus MC – University Medical Center, Rotterdam, Netherlands
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14
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Sieber KB, Batorsky A, Siebenthall K, Hudkins KL, Vierstra JD, Sullivan S, Sur A, McNulty M, Sandstrom R, Reynolds A, Bates D, Diegel M, Dunn D, Nelson J, Buckley M, Kaul R, Sampson MG, Himmelfarb J, Alpers CE, Waterworth D, Akilesh S. Integrated Functional Genomic Analysis Enables Annotation of Kidney Genome-Wide Association Study Loci. J Am Soc Nephrol 2019; 30:421-441. [PMID: 30760496 PMCID: PMC6405142 DOI: 10.1681/asn.2018030309] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 12/26/2018] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Linking genetic risk loci identified by genome-wide association studies (GWAS) to their causal genes remains a major challenge. Disease-associated genetic variants are concentrated in regions containing regulatory DNA elements, such as promoters and enhancers. Although researchers have previously published DNA maps of these regulatory regions for kidney tubule cells and glomerular endothelial cells, maps for podocytes and mesangial cells have not been available. METHODS We generated regulatory DNA maps (DNase-seq) and paired gene expression profiles (RNA-seq) from primary outgrowth cultures of human glomeruli that were composed mainly of podocytes and mesangial cells. We generated similar datasets from renal cortex cultures, to compare with those of the glomerular cultures. Because regulatory DNA elements can act on target genes across large genomic distances, we also generated a chromatin conformation map from freshly isolated human glomeruli. RESULTS We identified thousands of unique regulatory DNA elements, many located close to transcription factor genes, which the glomerular and cortex samples expressed at different levels. We found that genetic variants associated with kidney diseases (GWAS) and kidney expression quantitative trait loci were enriched in regulatory DNA regions. By combining GWAS, epigenomic, and chromatin conformation data, we functionally annotated 46 kidney disease genes. CONCLUSIONS We demonstrate a powerful approach to functionally connect kidney disease-/trait-associated loci to their target genes by leveraging unique regulatory DNA maps and integrated epigenomic and genetic analysis. This process can be applied to other kidney cell types and will enhance our understanding of genome regulation and its effects on gene expression in kidney disease.
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Affiliation(s)
| | - Anna Batorsky
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | | | | | - Jeff D Vierstra
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | | | - Aakash Sur
- Phase Genomics Inc., Seattle, Washington
- Department of Biomedical and Health Informatics, and
| | - Michelle McNulty
- Division of Pediatric Nephrology, Department of Pediatrics, University of Michigan School of Medicine, Ann Arbor, Michigan; and
| | | | - Alex Reynolds
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Daniel Bates
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Morgan Diegel
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Douglass Dunn
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Jemma Nelson
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Michael Buckley
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Rajinder Kaul
- Altius Institute for Biomedical Sciences, Seattle, Washington
| | - Matthew G Sampson
- Division of Pediatric Nephrology, Department of Pediatrics, University of Michigan School of Medicine, Ann Arbor, Michigan; and
| | - Jonathan Himmelfarb
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
- Kidney Research Institute, Seattle, Washington
| | - Charles E Alpers
- Department of Anatomic Pathology
- Kidney Research Institute, Seattle, Washington
| | | | - Shreeram Akilesh
- Department of Anatomic Pathology,
- Kidney Research Institute, Seattle, Washington
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15
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Li H, Quang D, Guan Y. Anchor: trans-cell type prediction of transcription factor binding sites. Genome Res 2019; 29:281-292. [PMID: 30567711 PMCID: PMC6360811 DOI: 10.1101/gr.237156.118] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 12/13/2018] [Indexed: 12/16/2022]
Abstract
The ENCyclopedia of DNA Elements (ENCODE) consortium has generated transcription factor (TF) binding ChIP-seq data covering hundreds of TF proteins and cell types; however, due to limits on time and resources, only a small fraction of all possible TF-cell type pairs have been profiled. One solution is to build machine learning models trained on currently available epigenomic data sets that can be applied to the remaining missing pairs. A major challenge is that TF binding sites are cell-type-specific, which can be attributed to cellular contexts such as chromatin accessibility. Meanwhile, indirect TF-DNA binding and interactions between TFs complicate this regulatory process. Technical issues such as sequencing biases and batch effects render the prediction task even more challenging. Many pioneering efforts have been made to predict TF binding profiles based on DNA sequence and DNase-seq footprints, but to what extent a model can be generalized to completely untested cell conditions remains unknown. In this study, we describe our first place solution to the 2017 ENCODE-DREAM in vivo TF binding site prediction challenge. By carefully addressing multisource biases and information imbalance across cell types, we created a pipeline that significantly outperforms the current state-of-the-art methods. The proposed method is sufficiently complex enough to model nonlinear interactions between TF binding motifs and chromatin accessibility information up to 1500 bp from the genomic region of interest.
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Affiliation(s)
- Hongyang Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Daniel Quang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Yuanfang Guan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
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16
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Sullivan AM, Arsovski AA, Thompson A, Sandstrom R, Thurman RE, Neph S, Johnson AK, Sullivan ST, Sabo PJ, Neri FV, Weaver M, Diegel M, Nemhauser JL, Stamatoyannopoulos JA, Bubb KL, Queitsch C. Mapping and Dynamics of Regulatory DNA in Maturing Arabidopsis thaliana Siliques. FRONTIERS IN PLANT SCIENCE 2019; 10:1434. [PMID: 31798605 PMCID: PMC6868056 DOI: 10.3389/fpls.2019.01434] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 10/16/2019] [Indexed: 05/04/2023]
Abstract
The genome is reprogrammed during development to produce diverse cell types, largely through altered expression and activity of key transcription factors. The accessibility and critical functions of epidermal cells have made them a model for connecting transcriptional events to development in a range of model systems. In Arabidopsis thaliana and many other plants, fertilization triggers differentiation of specialized epidermal seed coat cells that have a unique morphology caused by large extracellular deposits of polysaccharides. Here, we used DNase I-seq to generate regulatory landscapes of A. thaliana seeds at two critical time points in seed coat maturation (4 and 7 DPA), enriching for seed coat cells with the INTACT method. We found over 3,000 developmentally dynamic regulatory DNA elements and explored their relationship with nearby gene expression. The dynamic regulatory elements were enriched for motifs for several transcription factors families; most notably the TCP family at the earlier time point and the MYB family at the later one. To assess the extent to which the observed regulatory sites in seeds added to previously known regulatory sites in A. thaliana, we compared our data to 11 other data sets generated with 7-day-old seedlings for diverse tissues and conditions. Surprisingly, over a quarter of the regulatory, i.e. accessible, bases observed in seeds were novel. Notably, plant regulatory landscapes from different tissues, cell types, or developmental stages were more dynamic than those generated from bulk tissue in response to environmental perturbations, highlighting the importance of extending studies of regulatory DNA to single tissues and cell types during development.
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Affiliation(s)
| | - Andrej A. Arsovski
- Department of Biology, University of Washington, Seattle, WA, United States
| | - Agnieszka Thompson
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Robert E. Thurman
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Shane Neph
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Audra K. Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Shawn T. Sullivan
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Peter J. Sabo
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Fidencio V. Neri
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Molly Weaver
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | | | | | - Kerry L. Bubb
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
- *Correspondence: Kerry L. Bubb,
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
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17
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Abstract
Programs of gene transcription are controlled by cis-acting DNA elements, including enhancers, silencers, and promoters. Local accessibility of chromatin has proven to be a highly informative structural feature for identifying such regulatory elements, which tend to be relatively open due to their interactions with proteins. Recently, ATAC-seq (assay for transposase-accessible chromatin using sequencing) has emerged as one of the most powerful approaches for genome-wide chromatin accessibility profiling. This method assesses DNA accessibility using hyperactive Tn5 transposase, which simultaneously cuts DNA and inserts sequencing adaptors, preferentially in regions of open chromatin. ATAC-seq is a relatively simple procedure which can be applied to only a few thousand cells. It is well-suited to developing embryos of sea urchins and other echinoderms, which are a prominent experimental model for understanding the genomic control of animal development. In this chapter, we present a protocol for applying ATAC-seq to embryonic cells of sea urchins.
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Affiliation(s)
- Tanvi Shashikant
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Charles A Ettensohn
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, United States.
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18
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Sijacic P, Bajic M, McKinney EC, Meagher RB, Deal RB. Changes in chromatin accessibility between Arabidopsis stem cells and mesophyll cells illuminate cell type-specific transcription factor networks. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 94. [PMID: 29513366 PMCID: PMC7219318 DOI: 10.1111/tpj.13882] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Cell differentiation is driven by changes in the activity of transcription factors (TFs) and subsequent alterations in transcription. To study this process, differences in TF binding between cell types can be deduced by probing chromatin accessibility. We used cell type-specific nuclear purification followed by the assay for transposase-accessible chromatin (ATAC-seq) to delineate differences in chromatin accessibility and TF regulatory networks between stem cells of the shoot apical meristem (SAM) and differentiated leaf mesophyll cells in Arabidopsis thaliana. Chromatin accessibility profiles of SAM stem cells and leaf mesophyll cells were very similar at a qualitative level, yet thousands of regions having quantitatively different chromatin accessibility were also identified. Analysis of the genomic regions preferentially accessible in each cell type identified hundreds of overrepresented TF-binding motifs, highlighting sets of TFs that are probably important for each cell type. Within these sets, we found evidence for extensive co-regulation of target genes by multiple TFs that are preferentially expressed in each cell type. Interestingly, the TFs within each of these cell type-enriched sets also showed evidence of extensively co-regulating each other. We further found that preferentially accessible chromatin regions in mesophyll cells tended to also be substantially accessible in the stem cells, whereas the converse was not true. This observation suggests that the generally higher accessibility of regulatory elements in stem cells might contribute to their developmental plasticity. This work demonstrates the utility of cell type-specific chromatin accessibility profiling for the rapid development of testable models of regulatory control differences between cell types.
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Affiliation(s)
- Paja Sijacic
- Department of Biology, Emory University, Atlanta, GA 30322
| | - Marko Bajic
- Department of Biology, Emory University, Atlanta, GA 30322
- Graduate Program in Genetics and Molecular Biology, Emory University, Atlanta, GA 30322
| | | | | | - Roger B. Deal
- Department of Biology, Emory University, Atlanta, GA 30322
- Correspondence to: Roger B. Deal;
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19
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Shashikant T, Khor JM, Ettensohn CA. Global analysis of primary mesenchyme cell cis-regulatory modules by chromatin accessibility profiling. BMC Genomics 2018; 19:206. [PMID: 29558892 PMCID: PMC5859501 DOI: 10.1186/s12864-018-4542-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 02/13/2018] [Indexed: 12/11/2022] Open
Abstract
Background The developmental gene regulatory network (GRN) that underlies skeletogenesis in sea urchins and other echinoderms is a paradigm of GRN structure, function, and evolution. This transcriptional network is deployed selectively in skeleton-forming primary mesenchyme cells (PMCs) of the early embryo. To advance our understanding of this model developmental GRN, we used genome-wide chromatin accessibility profiling to identify and characterize PMC cis-regulatory modules (CRMs). Results ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) analysis of purified PMCs provided a global picture of chromatin accessibility in these cells. We used both ATAC-seq and DNase-seq (DNase I hypersensitive site sequencing) to identify > 3000 sites that exhibited increased accessibility in PMCs relative to other embryonic cell lineages, and provide both computational and experimental evidence that a large fraction of these sites represent bona fide skeletogenic CRMs. Putative PMC CRMs were preferentially located near genes differentially expressed by PMCs and consensus binding sites for two key transcription factors in the PMC GRN, Alx1 and Ets1, were enriched in these CRMs. Moreover, a high proportion of candidate CRMs drove reporter gene expression specifically in PMCs in transgenic embryos. Surprisingly, we found that PMC CRMs were partially open in other embryonic lineages and exhibited hyperaccessibility as early as the 128-cell stage. Conclusions Our work provides a comprehensive picture of chromatin accessibility in an early embryonic cell lineage. By identifying thousands of candidate PMC CRMs, we significantly enhance the utility of the sea urchin skeletogenic network as a general model of GRN architecture and evolution. Our work also shows that differential chromatin accessibility, which has been used for the high-throughput identification of enhancers in differentiated cell types, is a powerful approach for the identification of CRMs in early embryonic cells. Lastly, we conclude that in the sea urchin embryo, CRMs that control the cell type-specific expression of effector genes are hyperaccessible several hours in advance of gene activation. Electronic supplementary material The online version of this article (10.1186/s12864-018-4542-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tanvi Shashikant
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Jian Ming Khor
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Charles A Ettensohn
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
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20
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Koh AS, Miller EL, Buenrostro JD, Moskowitz DM, Wang J, Greenleaf WJ, Chang HY, Crabtree GR. Rapid chromatin repression by Aire provides precise control of immune tolerance. Nat Immunol 2018; 19:162-172. [PMID: 29335648 PMCID: PMC6049828 DOI: 10.1038/s41590-017-0032-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 12/07/2017] [Indexed: 01/23/2023]
Abstract
Aire mediates the expression of tissue-specific antigens in thymic epithelial cells to promote tolerance against self-reactive T lymphocytes. However, the mechanism that allows expression of tissue-specific genes at levels that prevent harm is unknown. Here we show that Brg1 generates accessibility at tissue-specific loci to impose central tolerance. We found that Aire has an intrinsic repressive function that restricts chromatin accessibility and opposes Brg1 across the genome. Aire exerted this repressive influence within minutes after recruitment to chromatin and restrained the amplitude of active transcription. Disease-causing mutations that impair Aire-induced activation also impair the protein's repressive function, which indicates dual roles for Aire. Together, Brg1 and Aire fine-tune the expression of tissue-specific genes at levels that prevent toxicity yet promote immune tolerance.
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Affiliation(s)
- Andrew S Koh
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Erik L Miller
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jason D Buenrostro
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Society of Fellows, Harvard University, Cambridge, MA, USA
| | - David M Moskowitz
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jing Wang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - William J Greenleaf
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerburg Biohub, San Francisco, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Gerald R Crabtree
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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21
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Wolter F, Puchta H. Application of CRISPR/Cas to Understand Cis- and Trans-Regulatory Elements in Plants. Methods Mol Biol 2018; 1830:23-40. [PMID: 30043362 DOI: 10.1007/978-1-4939-8657-6_2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The recent emergence of the CRISPR/Cas system as a genome editing tool enables simple, fast, and efficient induction of DNA double-strand breaks at precise positions in the genome. This has proven extremely useful for analysis and modification of protein-coding sequences. Regulatory sequences have received much less attention, but can now be quickly and easily disrupted as well. Editing of cis-regulatory elements (CRE) offers considerable potential for crop improvement via fine-tuning of gene expression that cannot be achieved by simple KO mutations, but its widespread application is still hampered by a lack of precise knowledge about functional motifs in CRE. As demonstrated for mammalian cells, CRISPR/Cas is also extremely useful for the identification and analysis of CRE in their native environment on a large scale using tiling screens. Transcriptional complexes are another promising target for crop genome editing, as demonstrated for pathogen resistance and regulation of flowering. The development of more diverse and sophisticated CRISPR/Cas tools for genome editing will allow even more efficient and powerful approaches for editing of regulatory sequences in the future.
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Affiliation(s)
- Felix Wolter
- Botanical Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Holger Puchta
- Botanical Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany.
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22
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Chen C, Xing D, Tan L, Li H, Zhou G, Huang L, Xie XS. Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI). Science 2017; 356:189-194. [PMID: 28408603 DOI: 10.1126/science.aak9787] [Citation(s) in RCA: 243] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 02/03/2017] [Accepted: 03/17/2017] [Indexed: 12/12/2022]
Abstract
Single-cell genomics is important for biology and medicine. However, current whole-genome amplification (WGA) methods are limited by low accuracy of copy-number variation (CNV) detection and low amplification fidelity. Here we report an improved single-cell WGA method, Linear Amplification via Transposon Insertion (LIANTI), which outperforms existing methods, enabling micro-CNV detection with kilobase resolution. This allowed direct observation of stochastic firing of DNA replication origins, which differs from cell to cell. We also show that the predominant cytosine-to-thymine mutations observed in single-cell genomics often arise from the artifact of cytosine deamination upon cell lysis. However, identifying single-nucleotide variations (SNVs) can be accomplished by sequencing kindred cells. We determined the spectrum of SNVs in a single human cell after ultraviolet radiation, revealing their nonrandom genome-wide distribution.
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Affiliation(s)
- Chongyi Chen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Dong Xing
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Longzhi Tan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Heng Li
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA
| | - Guangyu Zhou
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Lei Huang
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.,Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University, Beijing 100871, China.,Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China
| | - X Sunney Xie
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA. .,Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University, Beijing 100871, China.,Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China
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23
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Vermunt MW, Creyghton MP. Transcriptional Dynamics at Brain Enhancers: from Functional Specialization to Neurodegeneration. Curr Neurol Neurosci Rep 2017; 16:94. [PMID: 27628759 PMCID: PMC5023742 DOI: 10.1007/s11910-016-0689-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Over the last decade, the noncoding part of the genome has been shown to harbour thousands of cis-regulatory elements, such as enhancers, that activate well-defined gene expression programs. Driven by the development of numerous techniques, many of these elements are now identified in multiple tissues and cell types, and their characteristics as well as importance in development and disease are becoming increasingly clear. Here, we provide an overview of the insights that were gained from the analysis of noncoding gene regulatory elements in the brain and describe their potential contribution to cell type specialization, brain function and neurodegenerative disease.
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Affiliation(s)
- Marit W Vermunt
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Uppsalalaan 8, 3584CT, Utrecht, The Netherlands
| | - Menno P Creyghton
- Hubrecht Institute-KNAW and University Medical Center Utrecht, Uppsalalaan 8, 3584CT, Utrecht, The Netherlands.
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24
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Chasman D, Roy S. Inference of cell type specific regulatory networks on mammalian lineages. ACTA ACUST UNITED AC 2017; 2:130-139. [PMID: 29082337 DOI: 10.1016/j.coisb.2017.04.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Transcriptional regulatory networks are at the core of establishing cell type specific gene expression programs. In mammalian systems, such regulatory networks are determined by multiple levels of regulation, including by transcription factors, chromatin environment, and three-dimensional organization of the genome. Recent efforts to measure diverse regulatory genomic datasets across multiple cell types and tissues offer unprecedented opportunities to examine the context-specificity and dynamics of regulatory networks at a greater resolution and scale than before. In parallel, numerous computational approaches to analyze these data have emerged that serve as important tools for understanding mammalian cell type specific regulation. In this article, we review recent computational approaches to predict the expression and sequence-based regulators of a gene's expression level and examine long-range gene regulation. We highlight promising approaches, insights gained, and open challenges that need to be overcome to build a comprehensive picture of cell type specific transcriptional regulatory networks.
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Affiliation(s)
- Deborah Chasman
- Wisconsin Institute for Discovery University of Wisconsin-Madison, Madison, WI 53715
| | - Sushmita Roy
- Wisconsin Institute for Discovery University of Wisconsin-Madison, Madison, WI 53715.,Department of Biostatistics and Medical Informatics University of Wisconsin-Madison, Madison, WI 53792
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25
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Dougherty ML, Nuttle X, Penn O, Nelson BJ, Huddleston J, Baker C, Harshman L, Duyzend MH, Ventura M, Antonacci F, Sandstrom R, Dennis MY, Eichler EE. The birth of a human-specific neural gene by incomplete duplication and gene fusion. Genome Biol 2017; 18:49. [PMID: 28279197 PMCID: PMC5345166 DOI: 10.1186/s13059-017-1163-9] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 01/27/2017] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Gene innovation by duplication is a fundamental evolutionary process but is difficult to study in humans due to the large size, high sequence identity, and mosaic nature of segmental duplication blocks. The human-specific gene hydrocephalus-inducing 2, HYDIN2, was generated by a 364 kbp duplication of 79 internal exons of the large ciliary gene HYDIN from chromosome 16q22.2 to chromosome 1q21.1. Because the HYDIN2 locus lacks the ancestral promoter and seven terminal exons of the progenitor gene, we sought to characterize transcription at this locus by coupling reverse transcription polymerase chain reaction and long-read sequencing. RESULTS 5' RACE indicates a transcription start site for HYDIN2 outside of the duplication and we observe fusion transcripts spanning both the 5' and 3' breakpoints. We observe extensive splicing diversity leading to the formation of altered open reading frames (ORFs) that appear to be under relaxed selection. We show that HYDIN2 adopted a new promoter that drives an altered pattern of expression, with highest levels in neural tissues. We estimate that the HYDIN duplication occurred ~3.2 million years ago and find that it is nearly fixed (99.9%) for diploid copy number in contemporary humans. Examination of 73 chromosome 1q21 rearrangement patients reveals that HYDIN2 is deleted or duplicated in most cases. CONCLUSIONS Together, these data support a model of rapid gene innovation by fusion of incomplete segmental duplications, altered tissue expression, and potential subfunctionalization or neofunctionalization of HYDIN2 early in the evolution of the Homo lineage.
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Affiliation(s)
- Max L Dougherty
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - Xander Nuttle
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - Osnat Penn
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - Bradley J Nelson
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - John Huddleston
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA
| | - Carl Baker
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - Lana Harshman
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - Michael H Duyzend
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
| | - Mario Ventura
- Department of Biology, University of Bari, Bari, 70121, Italy
| | | | | | - Megan Y Dennis
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, 95616, CA, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15 Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA.
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26
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Baskin E, Farouni R, Mathé EA. ALTRE: workflow for defining ALTered Regulatory Elements using chromatin accessibility data. Bioinformatics 2017; 33:740-742. [PMID: 28011773 PMCID: PMC5408819 DOI: 10.1093/bioinformatics/btw688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 10/26/2016] [Indexed: 11/13/2022] Open
Abstract
Summary Regulatory elements regulate gene transcription, and their location and accessibility is cell-type specific, particularly for enhancers. Mapping and comparing chromatin accessibility between different cell types may identify mechanisms involved in cellular development and disease progression. To streamline and simplify differential analysis of regulatory elements genome-wide using chromatin accessibility data, such as DNase-seq, ATAC-seq, we developed ALTRE ( ALT ered R egulatory E lements), an R package and associated R Shiny web app. ALTRE makes such analysis accessible to a wide range of users-from novice to practiced computational biologists. Availability and Implementation https://github.com/Mathelab/ALTRE. Contact ewy.mathe@osumc.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Elizabeth Baskin
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Rick Farouni
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Ewy A Mathé
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
- To whom correspondence should be addressed.
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27
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Tschopp P, Tabin CJ. Deep homology in the age of next-generation sequencing. Philos Trans R Soc Lond B Biol Sci 2017; 372:20150475. [PMID: 27994118 PMCID: PMC5182409 DOI: 10.1098/rstb.2015.0475] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2016] [Indexed: 12/14/2022] Open
Abstract
The principle of homology is central to conceptualizing the comparative aspects of morphological evolution. The distinctions between homologous or non-homologous structures have become blurred, however, as modern evolutionary developmental biology (evo-devo) has shown that novel features often result from modification of pre-existing developmental modules, rather than arising completely de novo. With this realization in mind, the term 'deep homology' was coined, in recognition of the remarkably conserved gene expression during the development of certain animal structures that would not be considered homologous by previous strict definitions. At its core, it can help to formulate an understanding of deeper layers of ontogenetic conservation for anatomical features that lack any clear phylogenetic continuity. Here, we review deep homology and related concepts in the context of a gene expression-based homology discussion. We then focus on how these conceptual frameworks have profited from the recent rise of high-throughput next-generation sequencing. These techniques have greatly expanded the range of organisms amenable to such studies. Moreover, they helped to elevate the traditional gene-by-gene comparison to a transcriptome-wide level. We will end with an outlook on the next challenges in the field and how technological advances might provide exciting new strategies to tackle these questions.This article is part of the themed issue 'Evo-devo in the genomics era, and the origins of morphological diversity'.
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Affiliation(s)
- Patrick Tschopp
- Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Clifford J Tabin
- Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
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28
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Hu J, Adar S. The Cartography of UV-induced DNA Damage Formation and DNA Repair. Photochem Photobiol 2017; 93:199-206. [PMID: 27861959 DOI: 10.1111/php.12668] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 09/23/2016] [Indexed: 12/29/2022]
Abstract
DNA damage presents a barrier to DNA-templated biochemical processes, including gene expression and faithful DNA replication. Compromised DNA repair leads to mutations, enhancing the risk for genetic diseases and cancer development. Conventional experimental approaches to study DNA damage required a researcher to choose between measuring bulk damage over the entire genome, with little or no resolution regarding a specific location, and obtaining data specific to a locus of interest, without a global perspective. Recent advances in high-throughput genomic tools overcame these limitations and provide high-resolution measurements simultaneously across the genome. In this review, we discuss the available methods for measuring DNA damage and their repair, focusing on genomewide assays for pyrimidine photodimers, the major types of damage induced by ultraviolet irradiation. These new genomic assays will be a powerful tool in identifying key components of genome stability and carcinogenesis.
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Affiliation(s)
- Jinchuan Hu
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Sheera Adar
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC
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29
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Qiu Z, Li R, Zhang S, Wang K, Xu M, Li J, Du Y, Yu H, Cui X. Identification of Regulatory DNA Elements Using Genome-wide Mapping of DNase I Hypersensitive Sites during Tomato Fruit Development. MOLECULAR PLANT 2016; 9:1168-1182. [PMID: 27250572 DOI: 10.1016/j.molp.2016.05.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Revised: 05/10/2016] [Accepted: 05/23/2016] [Indexed: 05/29/2023]
Abstract
Development and ripening of tomato fruit are precisely controlled by transcriptional regulation, which depends on the orchestrated accessibility of regulatory proteins to promoters and other cis-regulatory DNA elements. This accessibility and its effect on gene expression play a major role in defining the developmental process. To understand the regulatory mechanism and functional elements modulating morphological and anatomical changes during fruit development, we generated genome-wide high-resolution maps of DNase I hypersensitive sites (DHSs) from the fruit tissues of the tomato cultivar "Moneymaker" at 20 days post anthesis as well as break stage. By exploring variation of DHSs across fruit development stages, we pinpointed the most likely hypersensitive sites related to development-specific genes. By detecting binding motifs on DHSs of these development-specific genes or genes in the ascorbic acid biosynthetic pathway, we revealed the common regulatory elements contributing to coordinating gene transcription of plant ripening and specialized metabolic pathways. Our results contribute to a better understanding of the regulatory dynamics of genes involved in tomato fruit development and ripening.
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Affiliation(s)
- Zhengkun Qiu
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Ren Li
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shuaibin Zhang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Ketao Wang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Meng Xu
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jiayang Li
- State Key Laboratory of Plant Genomics and National Center for Plant Gene Research (Beijing), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongchen Du
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Hong Yu
- State Key Laboratory of Plant Genomics and National Center for Plant Gene Research (Beijing), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Xia Cui
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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30
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Deaton AM, Gómez-Rodríguez M, Mieczkowski J, Tolstorukov MY, Kundu S, Sadreyev RI, Jansen LE, Kingston RE. Enhancer regions show high histone H3.3 turnover that changes during differentiation. eLife 2016; 5. [PMID: 27304074 PMCID: PMC4965263 DOI: 10.7554/elife.15316] [Citation(s) in RCA: 69] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 06/14/2016] [Indexed: 01/09/2023] Open
Abstract
The organization of DNA into chromatin is dynamic; nucleosomes are frequently displaced to facilitate the ability of regulatory proteins to access specific DNA elements. To gain insight into nucleosome dynamics, and to follow how dynamics change during differentiation, we used a technique called time-ChIP to quantitatively assess histone H3.3 turnover genome-wide during differentiation of mouse ESCs. We found that, without prior assumptions, high turnover could be used to identify regions involved in gene regulation. High turnover was seen at enhancers, as observed previously, with particularly high turnover at super-enhancers. In contrast, regions associated with the repressive Polycomb-Group showed low turnover in ESCs. Turnover correlated with DNA accessibility. Upon differentiation, numerous changes in H3.3 turnover rates were observed, the majority of which occurred at enhancers. Thus, time-ChIP measurement of histone turnover shows that active enhancers are unusually dynamic in ESCs and changes in highly dynamic nucleosomes predominate at enhancers during differentiation.
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Affiliation(s)
- Aimee M Deaton
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States.,Department of Genetics, Harvard Medical School, Boston, United States
| | | | - Jakub Mieczkowski
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States.,Department of Genetics, Harvard Medical School, Boston, United States
| | - Michael Y Tolstorukov
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States.,Department of Medicine, Harvard Medical School, Boston, United States
| | - Sharmistha Kundu
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States.,Department of Genetics, Harvard Medical School, Boston, United States
| | - Ruslan I Sadreyev
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States.,Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, United States
| | - Lars Et Jansen
- Laboratory for Epigenetic Mechanisms, Instituto Gulbenkian de Ciencia, Oeiras, Portugal
| | - Robert E Kingston
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States.,Department of Genetics, Harvard Medical School, Boston, United States
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31
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Chaitankar V, Karakülah G, Ratnapriya R, Giuste FO, Brooks MJ, Swaroop A. Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research. Prog Retin Eye Res 2016; 55:1-31. [PMID: 27297499 DOI: 10.1016/j.preteyeres.2016.06.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 06/06/2016] [Accepted: 06/08/2016] [Indexed: 02/08/2023]
Abstract
The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.
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Affiliation(s)
- Vijender Chaitankar
- Neurobiology-Neurodegeneration & Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, Bethesda, MD, 20892-0610, USA
| | - Gökhan Karakülah
- Neurobiology-Neurodegeneration & Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, Bethesda, MD, 20892-0610, USA
| | - Rinki Ratnapriya
- Neurobiology-Neurodegeneration & Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, Bethesda, MD, 20892-0610, USA
| | - Felipe O Giuste
- Neurobiology-Neurodegeneration & Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, Bethesda, MD, 20892-0610, USA
| | - Matthew J Brooks
- Neurobiology-Neurodegeneration & Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, Bethesda, MD, 20892-0610, USA
| | - Anand Swaroop
- Neurobiology-Neurodegeneration & Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, Bethesda, MD, 20892-0610, USA.
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Engel KL, Mackiewicz M, Hardigan AA, Myers RM, Savic D. Decoding transcriptional enhancers: Evolving from annotation to functional interpretation. Semin Cell Dev Biol 2016; 57:40-50. [PMID: 27224938 DOI: 10.1016/j.semcdb.2016.05.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Revised: 05/06/2016] [Accepted: 05/18/2016] [Indexed: 12/18/2022]
Abstract
Deciphering the intricate molecular processes that orchestrate the spatial and temporal regulation of genes has become an increasingly major focus of biological research. The differential expression of genes by diverse cell types with a common genome is a hallmark of complex cellular functions, as well as the basis for multicellular life. Importantly, a more coherent understanding of gene regulation is critical for defining developmental processes, evolutionary principles and disease etiologies. Here we present our current understanding of gene regulation by focusing on the role of enhancer elements in these complex processes. Although functional genomic methods have provided considerable advances to our understanding of gene regulation, these assays, which are usually performed on a genome-wide scale, typically provide correlative observations that lack functional interpretation. Recent innovations in genome editing technologies have placed gene regulatory studies at an exciting crossroads, as systematic, functional evaluation of enhancers and other transcriptional regulatory elements can now be performed in a coordinated, high-throughput manner across the entire genome. This review provides insights on transcriptional enhancer function, their role in development and disease, and catalogues experimental tools commonly used to study these elements. Additionally, we discuss the crucial role of novel techniques in deciphering the complex gene regulatory landscape and how these studies will shape future research.
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Affiliation(s)
- Krysta L Engel
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, United States
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, United States
| | - Andrew A Hardigan
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, United States; Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, United States
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, United States
| | - Daniel Savic
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, United States.
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MNase titration reveals differences between nucleosome occupancy and chromatin accessibility. Nat Commun 2016; 7:11485. [PMID: 27151365 PMCID: PMC4859066 DOI: 10.1038/ncomms11485] [Citation(s) in RCA: 145] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Accepted: 03/31/2016] [Indexed: 01/01/2023] Open
Abstract
Chromatin accessibility plays a fundamental role in gene regulation. Nucleosome placement, usually measured by quantifying protection of DNA from enzymatic digestion, can regulate accessibility. We introduce a metric that uses micrococcal nuclease (MNase) digestion in a novel manner to measure chromatin accessibility by combining information from several digests of increasing depths. This metric, MACC (MNase accessibility), quantifies the inherent heterogeneity of nucleosome accessibility in which some nucleosomes are seen preferentially at high MNase and some at low MNase. MACC interrogates each genomic locus, measuring both nucleosome location and accessibility in the same assay. MACC can be performed either with or without a histone immunoprecipitation step, and thereby compares histone and non-histone protection. We find that changes in accessibility at enhancers, promoters and other regulatory regions do not correlate with changes in nucleosome occupancy. Moreover, high nucleosome occupancy does not necessarily preclude high accessibility, which reveals novel principles of chromatin regulation.
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Assay for transposase-accessible chromatin and circularized chromosome conformation capture, two methods to explore the regulatory landscapes of genes in zebrafish. Methods Cell Biol 2016; 135:413-30. [PMID: 27443938 DOI: 10.1016/bs.mcb.2016.02.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Accurate transcriptional control of genes is fundamental for the correct functioning of organs and developmental processes. This control depends on the interplay between the promoter of genes and other noncoding sequences, whose interaction is mediated by 3D chromatin arrangements. Thus, the detailed description of transcriptional regulatory landscapes is essential to understand the mechanisms of transcriptional regulation. However, to achieve that, two important challenges have to be faced: (1) the identification of the noncoding sequences that contribute to gene transcription and (2) the association of these sequences to the respective genes they control. In this chapter, we describe two protocols that allow overcoming these important challenges: the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and circularized chromosome conformation capture (4C-seq). ATAC-seq is a very efficient technique that, using a very low number of cells as starting material, allows the identification of active chromatin regions genome wide, whereas 4C-seq detects the subset of sequences that interact specifically with the promoter of a given gene. When combined, both techniques provide a comprehensive snapshot of the regulatory landscapes of developmental genes. The protocols we present here have been optimized for teleost fish samples, zebrafish and medaka, allowing the in-depth study of transcriptional regulation in these two emerging animal models. Given the amenability and easy genetic manipulation of these two experimental systems, we anticipate that they will be important in revealing general principles of the vertebrate regulatory genome.
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Thompson B, Varticovski L, Baek S, Hager GL. Genome-Wide Chromatin Landscape Transitions Identify Novel Pathways in Early Commitment to Osteoblast Differentiation. PLoS One 2016; 11:e0148619. [PMID: 26890492 PMCID: PMC4759368 DOI: 10.1371/journal.pone.0148619] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2015] [Accepted: 01/20/2016] [Indexed: 12/17/2022] Open
Abstract
Bone continuously undergoes remodeling by a tightly regulated process that involves osteoblast differentiation from Mesenchymal Stem Cells (MSC). However, commitment of MSC to osteoblastic lineage is a poorly understood process. Chromatin organization functions as a molecular gatekeeper of DNA functions. Detection of sites that are hypersensitive to Dnase I has been used for detailed examination of changes in response to hormones and differentiation cues. To investigate the early steps in commitment of MSC to osteoblasts, we used a model human temperature-sensitive cell line, hFOB. When shifted to non-permissive temperature, these cells undergo "spontaneous" differentiation that takes several weeks, a process that is greatly accelerated by osteogenic induction media. We performed Dnase I hypersensitivity assays combined with deep sequencing to identify genome-wide potential regulatory events in cells undergoing early steps of commitment to osteoblasts. Massive reorganization of chromatin occurred within hours of differentiation. Whereas ~30% of unique DHS sites were located in the promoters, the majority was outside of the promoters, designated as enhancers. Many of them were at novel genomic sites and need to be confirmed experimentally. We developed a novel method for identification of cellular networks based solely on DHS enhancers signature correlated to gene expression. The analysis of enhancers that were unique to differentiating cells led to identification of bone developmental program encompassing 147 genes that directly or indirectly participate in osteogenesis. Identification of these pathways provided an unprecedented view of genomic regulation during early steps of differentiation and changes related to WNT, AP-1 and other pathways may have therapeutic implications.
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Affiliation(s)
- Bethtrice Thompson
- Laboratory of Receptor Biology and Gene Expression, NCI, NIH, Bethesda, MD, United States of America
- Center for Cancer Research and Therapeutic Development, Clark Atlanta University, Atlanta, GA, United States of America
| | - Lyuba Varticovski
- Laboratory of Receptor Biology and Gene Expression, NCI, NIH, Bethesda, MD, United States of America
- * E-mail:
| | - Songjoon Baek
- Laboratory of Receptor Biology and Gene Expression, NCI, NIH, Bethesda, MD, United States of America
| | - Gordon L. Hager
- Laboratory of Receptor Biology and Gene Expression, NCI, NIH, Bethesda, MD, United States of America
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36
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Baek S, Sung MH. Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes. Methods Mol Biol 2016; 1418:225-40. [PMID: 27008018 DOI: 10.1007/978-1-4939-3578-9_12] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
High-throughput sequencing technologies have made it possible for biologists to generate genome-wide profiles of chromatin features at the nucleotide resolution. Enzymes such as nucleases or transposes have been instrumental as a chromatin-probing agent due to their ability to target accessible chromatin for cleavage or insertion. On the scale of a few hundred base pairs, preferential action of the nuclear enzymes on accessible chromatin allows mapping of cell state-specific accessibility in vivo. Such accessible regions contain functionally important regulatory sites, including promoters and enhancers, which undergo active remodeling for cells adapting in a dynamic environment. DNase-seq and the more recent ATAC-seq are two assays that are gaining popularity. Deep sequencing of DNA libraries from these assays, termed genomic footprinting, has been proposed to enable the comprehensive construction of protein occupancy profiles over the genome at the nucleotide level. Recent studies have discovered limitations of genomic footprinting which reduce the scope of detectable proteins. In addition, the identification of putative factors that bind to the observed footprints remains challenging. Despite these caveats, the methodology still presents significant advantages over alternative techniques such as ChIP-seq or FAIRE-seq. Here we describe computational approaches and tools for analysis of chromatin accessibility and genomic footprinting. Proper experimental design and assay-specific data analysis ensure the detection sensitivity and maximize retrievable information. The enzyme-based chromatin profiling approaches represent a powerful and evolving methodology which facilitates our understanding of how the genome is regulated.
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Affiliation(s)
- Songjoon Baek
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, 41 Library Drive, Bethesda, MD, 20892, USA
| | - Myong-Hee Sung
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, 41 Library Drive, Bethesda, MD, 20892, USA. .,Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD, 21224, USA.
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Domcke S, Bardet AF, Adrian Ginno P, Hartl D, Burger L, Schübeler D. Competition between DNA methylation and transcription factors determines binding of NRF1. Nature 2015; 528:575-9. [PMID: 26675734 DOI: 10.1038/nature16462] [Citation(s) in RCA: 323] [Impact Index Per Article: 35.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Accepted: 11/16/2015] [Indexed: 12/17/2022]
Abstract
Eukaryotic transcription factors (TFs) are key determinants of gene activity, yet they bind only a fraction of their corresponding DNA sequence motifs in any given cell type. Chromatin has the potential to restrict accessibility of binding sites; however, in which context chromatin states are instructive for TF binding remains mainly unknown. To explore the contribution of DNA methylation to constrained TF binding, we mapped DNase-I-hypersensitive sites in murine stem cells in the presence and absence of DNA methylation. Methylation-restricted sites are enriched for TF motifs containing CpGs, especially for those of NRF1. In fact, the TF NRF1 occupies several thousand additional sites in the unmethylated genome, resulting in increased transcription. Restoring de novo methyltransferase activity initiates remethylation at these sites and outcompetes NRF1 binding. This suggests that binding of DNA-methylation-sensitive TFs relies on additional determinants to induce local hypomethylation. In support of this model, removal of neighbouring motifs in cis or of a TF in trans causes local hypermethylation and subsequent loss of NRF1 binding. This competition between DNA methylation and TFs in vivo reveals a case of cooperativity between TFs that acts indirectly via DNA methylation. Methylation removal by methylation-insensitive factors enables occupancy of methylation-sensitive factors, a principle that rationalizes hypomethylation of regulatory regions.
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Affiliation(s)
- Silvia Domcke
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH 4058 Basel, Switzerland.,University of Basel, Faculty of Sciences, Petersplatz 1, CH 4003 Basel, Switzerland
| | - Anaïs Flore Bardet
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH 4058 Basel, Switzerland
| | - Paul Adrian Ginno
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH 4058 Basel, Switzerland
| | - Dominik Hartl
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH 4058 Basel, Switzerland.,University of Basel, Faculty of Sciences, Petersplatz 1, CH 4003 Basel, Switzerland
| | - Lukas Burger
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH 4058 Basel, Switzerland.,Swiss Institute of Bioinformatics, Maulbeerstrasse 66, CH 4058 Basel, Switzerland
| | - Dirk Schübeler
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH 4058 Basel, Switzerland.,University of Basel, Faculty of Sciences, Petersplatz 1, CH 4003 Basel, Switzerland
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Maurano MT, Haugen E, Sandstrom R, Vierstra J, Shafer A, Kaul R, Stamatoyannopoulos JA. Large-scale identification of sequence variants influencing human transcription factor occupancy in vivo. Nat Genet 2015; 47:1393-401. [PMID: 26502339 PMCID: PMC4666772 DOI: 10.1038/ng.3432] [Citation(s) in RCA: 152] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 10/02/2015] [Indexed: 12/18/2022]
Abstract
The function of human regulatory regions depends exquisitely on their local genomic environment and on cellular context, complicating experimental analysis of common disease- and trait-associated variants that localize within regulatory DNA. We use allelically resolved genomic DNase I footprinting data encompassing 166 individuals and 114 cell types to identify >60,000 common variants that directly influence transcription factor occupancy and regulatory DNA accessibility in vivo. The unprecedented scale of these data enables systematic analysis of the impact of sequence variation on transcription factor occupancy in vivo. We leverage this analysis to develop accurate models of variation affecting the recognition sites for diverse transcription factors and apply these models to discriminate nearly 500,000 common regulatory variants likely to affect transcription factor occupancy across the human genome. The approach and results provide a new foundation for the analysis and interpretation of noncoding variation in complete human genomes and for systems-level investigation of disease-associated variants.
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Affiliation(s)
- Matthew T Maurano
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Anthony Shafer
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington, USA
- Altius Institute for Biomedical Sciences, Seattle, Washington, USA
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40
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Vierstra J, Reik A, Chang KH, Stehling-Sun S, Zhou YY, Hinkley SJ, Paschon DE, Zhang L, Psatha N, Bendana YR, O'Neill CM, Song AH, Mich A, Liu PQ, Lee G, Bauer DE, Holmes MC, Orkin SH, Papayannopoulou T, Stamatoyannopoulos G, Rebar EJ, Gregory PD, Urnov FD, Stamatoyannopoulos JA. Functional footprinting of regulatory DNA. Nat Methods 2015; 12:927-30. [PMID: 26322838 PMCID: PMC5381659 DOI: 10.1038/nmeth.3554] [Citation(s) in RCA: 107] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2015] [Accepted: 07/30/2015] [Indexed: 12/19/2022]
Abstract
Regulatory regions harbor multiple transcription factor (TF) recognition sites; however, the contribution of individual sites to regulatory function remains challenging to define. We describe an approach that exploits the error-prone nature of genome editing-induced double-strand break repair to map functional elements within regulatory DNA at nucleotide resolution. We demonstrate the approach on a human erythroid enhancer, revealing single TF recognition sites that gate the majority of downstream regulatory function.
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Affiliation(s)
- Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, WA
| | | | - Kai-Hsin Chang
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA
| | | | | | | | | | - L. Zhang
- Sangamo BioSciences, Pt. Richmond, CA
| | - Nikoletta Psatha
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA
| | | | | | | | | | | | - Gary Lee
- Sangamo BioSciences, Pt. Richmond, CA
| | - Daniel E. Bauer
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA
| | | | - Stuart H. Orkin
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA
| | | | | | | | | | | | - John A. Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, WA
- Division of Oncology, Department of Medicine, University of Washington, Seattle, WA
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41
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Thompson D, Regev A, Roy S. Comparative analysis of gene regulatory networks: from network reconstruction to evolution. Annu Rev Cell Dev Biol 2015; 31:399-428. [PMID: 26355593 DOI: 10.1146/annurev-cellbio-100913-012908] [Citation(s) in RCA: 95] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights into the evolution of gene regulatory processes and their adaptive contribution. In recent years, advances in genomic and computational tools have led to a wealth of methods for such analysis at the sequence, expression, pathway, module, and entire network level. Here, we review computational methods developed to study transcriptional regulatory networks using comparative genomics, from sequence to functional data. We highlight how these methods use evolutionary conservation and divergence to reliably detect regulatory components as well as estimate the extent and rate of divergence. Finally, we discuss the promise and open challenges in linking regulatory divergence to phenotypic divergence and adaptation.
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Affiliation(s)
- Dawn Thompson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
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42
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Cardiac gene expression data and in silico analysis provide novel insights into human and mouse taste receptor gene regulation. Naunyn Schmiedebergs Arch Pharmacol 2015; 388:1009-27. [PMID: 25986534 DOI: 10.1007/s00210-015-1118-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Accepted: 03/24/2015] [Indexed: 12/21/2022]
Abstract
G protein-coupled receptors are the principal mediators of the sweet, umami, bitter, and fat taste qualities in mammals. Intriguingly, the taste receptors are also expressed outside of the oral cavity, including in the gut, airways, brain, and heart, where they have additional functions and contribute to disease. However, there is little known about the mechanisms governing the transcriptional regulation of taste receptor genes. Following our recent delineation of taste receptors in the heart, we investigated the genomic loci encoding for taste receptors to gain insight into the regulatory mechanisms that drive their expression in the heart. Gene expression analyses of healthy and diseased human and mouse hearts showed coordinated expression for a subset of chromosomally clustered taste receptors. This chromosomal clustering mirrored the cardiac expression profile, suggesting that a common gene regulatory block may control the taste receptor locus. We identified unique domains with strong regulatory potential in the vicinity of taste receptor genes. We also performed de novo motif enrichment in the proximal promoter regions and found several overrepresented DNA motifs in cardiac taste receptor gene promoters corresponding to ubiquitous and cardiac-specific transcription factor binding sites. Thus, combining cardiac gene expression data with bioinformatic analyses, this study has provided insights into the noncoding regulatory landscape for taste GPCRs. These findings also have broader relevance for the study of taste GPCRs outside of the classical gustatory system, where understanding the mechanisms controlling the expression of these receptors may have implications for future therapeutic development.
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Wilken MS, Brzezinski JA, La Torre A, Siebenthall K, Thurman R, Sabo P, Sandstrom RS, Vierstra J, Canfield TK, Hansen RS, Bender MA, Stamatoyannopoulos J, Reh TA. DNase I hypersensitivity analysis of the mouse brain and retina identifies region-specific regulatory elements. Epigenetics Chromatin 2015; 8:8. [PMID: 25972927 PMCID: PMC4429822 DOI: 10.1186/1756-8935-8-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2014] [Accepted: 01/27/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The brain, spinal cord, and neural retina comprise the central nervous system (CNS) of vertebrates. Understanding the regulatory mechanisms that underlie the enormous cell-type diversity of the CNS is a significant challenge. Whole-genome mapping of DNase I-hypersensitive sites (DHSs) has been used to identify cis-regulatory elements in many tissues. We have applied this approach to the mouse CNS, including developing and mature neural retina, whole brain, and two well-characterized brain regions, the cerebellum and the cerebral cortex. RESULTS For the various regions and developmental stages of the CNS that we analyzed, there were approximately the same number of DHSs; however, there were many DHSs unique to each CNS region and developmental stage. Many of the DHSs are likely to mark enhancers that are specific to the specific CNS region and developmental stage. We validated the DNase I mapping approach for identification of CNS enhancers using the existing VISTA Browser database and with in vivo and in vitro electroporation of the retina. Analysis of transcription factor consensus sites within the DHSs shows distinct region-specific profiles of transcriptional regulators particular to each region. Clustering developmentally dynamic DHSs in the retina revealed enrichment of developmental stage-specific transcriptional regulators. Additionally, we found reporter gene activity in the retina driven from several previously uncharacterized regulatory elements surrounding the neurodevelopmental gene Otx2. Identification of DHSs shared between mouse and human showed region-specific differences in the evolution of cis-regulatory elements. CONCLUSIONS Overall, our results demonstrate the potential of genome-wide DNase I mapping to cis-regulatory questions regarding the regional diversity within the CNS. These data represent an extensive catalogue of potential cis-regulatory elements within the CNS that display region and temporal specificity, as well as a set of DHSs common to CNS tissues. Further examination of evolutionary conservation of DHSs between CNS regions and different species may reveal important cis-regulatory elements in the evolution of the mammalian CNS.
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Affiliation(s)
- Matthew S Wilken
- Department of Biological Structure, University of Washington, 1959 NE Pacific Street, Box 357420, Seattle, WA 98195 USA ; Molecular and Cellular Biology Program, University of Washington, MCB Program Office, T-466 Health Sciences Building, Box 357275, Seattle, WA 98195 USA
| | - Joseph A Brzezinski
- Department of Biological Structure, University of Washington, 1959 NE Pacific Street, Box 357420, Seattle, WA 98195 USA ; Department of Ophthalmology, University of Colorado School of Medicine, 1675 Aurora Court, Aurora, CO 80045 USA
| | - Anna La Torre
- Department of Biological Structure, University of Washington, 1959 NE Pacific Street, Box 357420, Seattle, WA 98195 USA
| | - Kyle Siebenthall
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Robert Thurman
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Peter Sabo
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Richard S Sandstrom
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Jeff Vierstra
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Theresa K Canfield
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - R Scott Hansen
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Michael A Bender
- Department of Pediatrics, University of Washington, 1959 NE Pacific St, Health Sciences Building, Seattle, WA Box 356320, 98195 USA ; Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109 USA
| | - John Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Foege Building S-250, 3720 15th Ave NE, Box 355065, Seattle, WA 98195 USA
| | - Thomas A Reh
- Department of Biological Structure, University of Washington, 1959 NE Pacific Street, Box 357420, Seattle, WA 98195 USA
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Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller MJ, Amin V, Whitaker JW, Schultz MD, Ward LD, Sarkar A, Quon G, Sandstrom RS, Eaton ML, Wu YC, Pfenning AR, Wang X, Claussnitzer M, Liu Y, Coarfa C, Harris RA, Shoresh N, Epstein CB, Gjoneska E, Leung D, Xie W, Hawkins RD, Lister R, Hong C, Gascard P, Mungall AJ, Moore R, Chuah E, Tam A, Canfield TK, Hansen RS, Kaul R, Sabo PJ, Bansal MS, Carles A, Dixon JR, Farh KH, Feizi S, Karlic R, Kim AR, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer TR, Neph SJ, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari RC, Siebenthall KT, Sinnott-Armstrong NA, Stevens M, Thurman RE, Wu J, Zhang B, Zhou X, Beaudet AE, Boyer LA, De Jager PL, Farnham PJ, Fisher SJ, Haussler D, Jones SJM, Li W, Marra MA, McManus MT, Sunyaev S, Thomson JA, Tlsty TD, Tsai LH, Wang W, Waterland RA, Zhang MQ, Chadwick LH, Bernstein BE, Costello JF, Ecker JR, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos JA, Wang T, Kellis M. Integrative analysis of 111 reference human epigenomes. Nature 2015; 518:317-30. [PMID: 25693563 PMCID: PMC4530010 DOI: 10.1038/nature14248] [Citation(s) in RCA: 4114] [Impact Index Per Article: 457.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Accepted: 01/21/2015] [Indexed: 02/06/2023]
Abstract
The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
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Affiliation(s)
- Anshul Kundaje
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Genetics, Department of Computer Science, 300 Pasteur Dr., Lane Building, L301, Stanford, California 94305-5120, USA
| | - Wouter Meuleman
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Jason Ernst
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Biological Chemistry, University of California, Los Angeles, 615 Charles E Young Dr South, Los Angeles, California 90095, USA
| | - Misha Bilenky
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Angela Yen
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Alireza Heravi-Moussavi
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Pouya Kheradpour
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Zhizhuo Zhang
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Jianrong Wang
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Michael J Ziller
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Department of Stem Cell and Regenerative Biology, 7 Divinity Ave, Cambridge, Massachusetts 02138, USA
| | - Viren Amin
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - John W Whitaker
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Matthew D Schultz
- Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA
| | - Lucas D Ward
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Abhishek Sarkar
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Gerald Quon
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Richard S Sandstrom
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Matthew L Eaton
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Yi-Chieh Wu
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Andreas R Pfenning
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Xinchen Wang
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, Massachusetts 02142, USA
| | - Melina Claussnitzer
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Yaping Liu
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Cristian Coarfa
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - R Alan Harris
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Noam Shoresh
- The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Charles B Epstein
- The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Elizabeta Gjoneska
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, Massachusetts 02139, USA
| | - Danny Leung
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Wei Xie
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - R David Hawkins
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Ryan Lister
- Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA
| | - Chibo Hong
- Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 1450 3rd Street, San Francisco, California 94158, USA
| | - Philippe Gascard
- Department of Pathology, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143-0511, USA
| | - Andrew J Mungall
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Richard Moore
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Eric Chuah
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Angela Tam
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Theresa K Canfield
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - R Scott Hansen
- Department of Medicine, Division of Medical Genetics, University of Washington, 2211 Elliot Avenue, Seattle, Washington 98121, USA
| | - Rajinder Kaul
- Department of Medicine, Division of Medical Genetics, University of Washington, 2211 Elliot Avenue, Seattle, Washington 98121, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Mukul S Bansal
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Computer Science &Engineering, University of Connecticut, 371 Fairfield Way, Storrs, Connecticut 06269, USA
| | - Annaick Carles
- Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada
| | - Jesse R Dixon
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Kai-How Farh
- The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Soheil Feizi
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Rosa Karlic
- Bioinformatics Group, Department of Molecular Biology, Division of Biology, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia
| | - Ah-Ram Kim
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Ashwinikumar Kulkarni
- Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA
| | - Daofeng Li
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Rebecca Lowdon
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - GiNell Elliott
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Tim R Mercer
- Institute for Molecular Bioscience, University of Queensland, St Lucia, Queensland 4072, Australia
| | - Shane J Neph
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Vitor Onuchic
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Paz Polak
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA
| | - Nisha Rajagopal
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Pradipta Ray
- Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA
| | - Richard C Sallari
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Kyle T Siebenthall
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Nicholas A Sinnott-Armstrong
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Michael Stevens
- 1] Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA. [2] Department of Computer Science and Engineeering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Jie Wu
- 1] Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794-3600, USA. [2] Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Bo Zhang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Xin Zhou
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Arthur E Beaudet
- Molecular and Human Genetics Department, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Laurie A Boyer
- Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, Massachusetts 02142, USA
| | - Philip L De Jager
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. [3] Harvard Medical School, 25 Shattuck St, Boston, Massachusetts 02115, USA
| | - Peggy J Farnham
- Department of Biochemistry, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, California 90089-9601, USA
| | - Susan J Fisher
- ObGyn, Reproductive Sciences, University of California San Francisco, 35 Medical Center Way, San Francisco, California 94143, USA
| | - David Haussler
- Center for Biomolecular Sciences and Engineering, University of Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA
| | - Steven J M Jones
- 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6, Canada. [3] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, V6T 1Z4
| | - Wei Li
- Dan L. Duncan Cancer Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Marco A Marra
- 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, V6T 1Z4
| | - Michael T McManus
- Department of Microbiology and Immunology, Diabetes Center, University of California, San Francisco, 513 Parnassus Ave, San Francisco, California 94143-0534, USA
| | - Shamil Sunyaev
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. [3] Harvard Medical School, 25 Shattuck St, Boston, Massachusetts 02115, USA
| | - James A Thomson
- 1] University of Wisconsin, Madison, Wisconsin 53715, USA. [2] Morgridge Institute for Research, 330 N. Orchard Street, Madison, Wisconsin 53707, USA
| | - Thea D Tlsty
- Department of Pathology, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143-0511, USA
| | - Li-Huei Tsai
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, Massachusetts 02139, USA
| | - Wei Wang
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Robert A Waterland
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, Texas 77030, USA
| | - Michael Q Zhang
- 1] Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA. [2] Bioinformatics Division, Center for Synthetic and Systems Biology, TNLIST, Tsinghua University, Beijing 100084, China
| | - Lisa H Chadwick
- National Institute of Environmental Health Sciences, 111 T.W. Alexander Drive, Research Triangle Park, North Carolina 27709, USA
| | - Bradley E Bernstein
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Massachusetts General Hospital, 55 Fruit St, Boston, Massachusetts 02114, USA. [3] Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815-6789, USA
| | - Joseph F Costello
- Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 1450 3rd Street, San Francisco, California 94158, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA
| | - Martin Hirst
- 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada
| | - Alexander Meissner
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Department of Stem Cell and Regenerative Biology, 7 Divinity Ave, Cambridge, Massachusetts 02138, USA
| | | | - Bing Ren
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Ting Wang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Manolis Kellis
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
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Athwal RK, Walkiewicz MP, Baek S, Fu S, Bui M, Camps J, Ried T, Sung MH, Dalal Y. CENP-A nucleosomes localize to transcription factor hotspots and subtelomeric sites in human cancer cells. Epigenetics Chromatin 2015; 8:2. [PMID: 25788983 PMCID: PMC4363203 DOI: 10.1186/1756-8935-8-2] [Citation(s) in RCA: 99] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Accepted: 12/01/2014] [Indexed: 12/21/2022] Open
Abstract
Background The histone H3 variant CENP-A is normally tightly regulated to ensure only one centromere exists per chromosome. Native CENP-A is often found overexpressed in human cancer cells and a range of human tumors. Consequently, CENP-A misregulation is thought to contribute to genome instability in human cancers. However, the consequences of such overexpression have not been directly elucidated in human cancer cells. Results To investigate native CENP-A overexpression, we sought to uncover CENP-A-associated defects in human cells. We confirm that CENP-A is innately overexpressed in several colorectal cancer cell lines. In such cells, we report that a subset of structurally distinct CENP-A-containing nucleosomes associate with canonical histone H3, and with the transcription-coupled chaperones ATRX and DAXX. Furthermore, such hybrid CENP-A nucleosomes localize to DNase I hypersensitive and transcription factor binding sites, including at promoters of genes across the human genome. A distinct class of CENP-A hotspots also accumulates at subtelomeric chromosomal locations, including at the 8q24/Myc region long-associated with genomic instability. We show this 8q24 accumulation of CENP-A can also be seen in early stage primary colorectal tumors. Conclusions Our data demonstrate that excess CENP-A accumulates at noncentromeric locations in the human cancer genome. These findings suggest that ectopic CENP-A nucleosomes could alter the state of the chromatin fiber, potentially impacting gene regulation and chromosome fragility. Electronic supplementary material The online version of this article (doi:10.1186/1756-8935-8-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Rajbir K Athwal
- Chromatin Structure and Epigenetics Mechanisms Unit, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA ; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
| | - Marcin P Walkiewicz
- Chromatin Structure and Epigenetics Mechanisms Unit, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA ; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
| | - Songjoon Baek
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
| | - Song Fu
- Chromatin Structure and Epigenetics Mechanisms Unit, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA ; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
| | - Minh Bui
- Chromatin Structure and Epigenetics Mechanisms Unit, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA ; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
| | - Jordi Camps
- Genetics Branch, Center for Cancer Research, National Cancer Institute National Institutes of Health, 50 South Drive, Bethesda, MD 20892 USA
| | - Thomas Ried
- Genetics Branch, Center for Cancer Research, National Cancer Institute National Institutes of Health, 50 South Drive, Bethesda, MD 20892 USA
| | - Myong-Hee Sung
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
| | - Yamini Dalal
- Chromatin Structure and Epigenetics Mechanisms Unit, Center for Cancer Research, National Cancer Institute National Institutes of Health, 41 Center Drive, Bethesda, MD 20892 USA
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46
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Cumbie JS, Filichkin SA, Megraw M. Improved DNase-seq protocol facilitates high resolution mapping of DNase I hypersensitive sites in roots in Arabidopsis thaliana. PLANT METHODS 2015; 11:42. [PMID: 26339280 PMCID: PMC4558764 DOI: 10.1186/s13007-015-0087-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2015] [Accepted: 08/21/2015] [Indexed: 05/19/2023]
Abstract
BACKGROUND Identifying cis-regulatory elements is critical in understanding the direct and indirect regulatory mechanisms of gene expression. Current approaches include DNase-seq, a technique that combines sensitivity to the nonspecific endonuclease DNase I with high throughput sequencing to identify regions of regulatory DNA on a genome-wide scale. While this method was originally developed for human cell lines, later adaptations made the processing of plant tissues possible. Challenges still remain in processing recalcitrant tissues that have low DNA content. RESULTS By removing steps requiring the use of gel agarose plugs in DNase-seq, we were able to significantly reduce the time required to perform the protocol by at least 2 days, while also making possible the processing of difficult plant tissues. We refer to this simplified protocol as DNase I SIM (for simplified in-nucleus method). We were able to successfully create DNase-seq libraries for both leaf and root tissues in Arabidopsis using DNase I SIM. CONCLUSION This protocol simplifies and facilitates generation of DNase-seq libraries from plant tissues for high resolution mapping of DNase I hypersensitive sites.
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Affiliation(s)
- Jason S. Cumbie
- />Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331 USA
| | - Sergei A. Filichkin
- />Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331 USA
- />Center for Genome Research and Biocomputing, Oregon State University, 2082 Cordley Hall, Corvallis, OR 97331 USA
| | - Molly Megraw
- />Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331 USA
- />Department of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331 USA
- />Center for Genome Research and Biocomputing, Oregon State University, 2082 Cordley Hall, Corvallis, OR 97331 USA
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47
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Vierstra J, Rynes E, Sandstrom R, Zhang M, Canfield T, Hansen RS, Stehling-Sun S, Sabo PJ, Byron R, Humbert R, Thurman RE, Johnson AK, Vong S, Lee K, Bates D, Neri F, Diegel M, Giste E, Haugen E, Dunn D, Wilken MS, Josefowicz S, Samstein R, Chang KH, Eichler EE, De Bruijn M, Reh TA, Skoultchi A, Rudensky A, Orkin SH, Papayannopoulou T, Treuting PM, Selleri L, Kaul R, Groudine M, Bender MA, Stamatoyannopoulos JA. Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution. Science 2014; 346:1007-12. [PMID: 25411453 PMCID: PMC4337786 DOI: 10.1126/science.1246426] [Citation(s) in RCA: 186] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
To study the evolutionary dynamics of regulatory DNA, we mapped >1.3 million deoxyribonuclease I-hypersensitive sites (DHSs) in 45 mouse cell and tissue types, and systematically compared these with human DHS maps from orthologous compartments. We found that the mouse and human genomes have undergone extensive cis-regulatory rewiring that combines branch-specific evolutionary innovation and loss with widespread repurposing of conserved DHSs to alternative cell fates, and that this process is mediated by turnover of transcription factor (TF) recognition elements. Despite pervasive evolutionary remodeling of the location and content of individual cis-regulatory regions, within orthologous mouse and human cell types the global fraction of regulatory DNA bases encoding recognition sites for each TF has been strictly conserved. Our findings provide new insights into the evolutionary forces shaping mammalian regulatory DNA landscapes.
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Affiliation(s)
- Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Eric Rynes
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Miaohua Zhang
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Theresa Canfield
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - R Scott Hansen
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Sandra Stehling-Sun
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Rachel Byron
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Audra K Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Shinny Vong
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Kristen Lee
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Daniel Bates
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Fidencio Neri
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Erika Giste
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Douglas Dunn
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Matthew S Wilken
- Department of Biological Structure, University of Washington, Seattle, WA 98195, USA
| | - Steven Josefowicz
- Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Howard Hughes Medical Institute
| | - Robert Samstein
- Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Howard Hughes Medical Institute
| | - Kai-Hsin Chang
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Howard Hughes Medical Institute
| | - Marella De Bruijn
- Medical Research Council (MRC) Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, Oxford OX3 9DS, UK
| | - Thomas A Reh
- Department of Biological Structure, University of Washington, Seattle, WA 98195, USA
| | - Arthur Skoultchi
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Alexander Rudensky
- Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Howard Hughes Medical Institute
| | - Stuart H Orkin
- Howard Hughes Medical Institute. Division of Hematology/Oncology, Children's Hospital Boston and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Thalia Papayannopoulou
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Piper M Treuting
- Department of Comparative Medicine, University of Washington, Seattle, WA 98195, USA
| | - Licia Selleri
- Department of Cell and Developmental Biology, Weill Medical College of Cornell University, New York, NY 10065, USA
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Mark Groudine
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. Department of Radiation Oncology, University of Washington, Seattle, WA 98109, USA
| | - M A Bender
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. Department of Pediatrics, University of Washington, Seattle, WA 98195, USA
| | - John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Division of Oncology, Department of Medicine, University of Washington, Seattle, WA 98195, USA.
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48
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Tsompana M, Buck MJ. Chromatin accessibility: a window into the genome. Epigenetics Chromatin 2014; 7:33. [PMID: 25473421 PMCID: PMC4253006 DOI: 10.1186/1756-8935-7-33] [Citation(s) in RCA: 261] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Accepted: 11/05/2014] [Indexed: 01/09/2023] Open
Abstract
Transcriptional activation throughout the eukaryotic lineage has been tightly linked with disruption of nucleosome organization at promoters, enhancers, silencers, insulators and locus control regions due to transcription factor binding. Regulatory DNA thus coincides with open or accessible genomic sites of remodeled chromatin. Current chromatin accessibility assays are used to separate the genome by enzymatic or chemical means and isolate either the accessible or protected locations. The isolated DNA is then quantified using a next-generation sequencing platform. Wide application of these assays has recently focused on the identification of the instrumental epigenetic changes responsible for differential gene expression, cell proliferation, functional diversification and disease development. Here we discuss the limitations and advantages of current genome-wide chromatin accessibility assays with especial attention on experimental precautions and sequence data analysis. We conclude with our perspective on future improvements necessary for moving the field of chromatin profiling forward.
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Affiliation(s)
- Maria Tsompana
- New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, 701 Ellicott St, Buffalo, NY 14203 USA
| | - Michael J Buck
- New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, 701 Ellicott St, Buffalo, NY 14203 USA ; Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY USA
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49
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Yardımcı GG, Frank CL, Crawford GE, Ohler U. Explicit DNase sequence bias modeling enables high-resolution transcription factor footprint detection. Nucleic Acids Res 2014; 42:11865-78. [PMID: 25294828 PMCID: PMC4231734 DOI: 10.1093/nar/gku810] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2014] [Revised: 08/22/2014] [Accepted: 08/27/2014] [Indexed: 12/31/2022] Open
Abstract
DNaseI footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High-throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. Multiple computational approaches have been developed to identify DNase-seq footprints as predictors of TF binding. However, recent studies have pointed to a substantial cleavage bias of DNase and its negative impact on predictive performance of footprinting. To assess the potential for using DNase-seq to identify individual binding sites, we performed DNase-seq on deproteinized genomic DNA and determined sequence cleavage bias. This allowed us to build bias corrected and TF-specific footprint models. The predictive performance of these models demonstrated that predicted footprints corresponded to high-confidence TF-DNA interactions. DNase-seq footprints were absent under a fraction of ChIP-seq peaks, which we show to be indicative of weaker binding, indirect TF-DNA interactions or possible ChIP artifacts. The modeling approach was also able to detect variation in the consensus motifs that TFs bind to. Finally, cell type specific footprints were detected within DNase hypersensitive sites that are present in multiple cell types, further supporting that footprints can identify changes in TF binding that are not detectable using other strategies.
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Affiliation(s)
- Galip Gürkan Yardımcı
- Computational Biology and Bioinformatics Program, Duke University, Durham, NC 27708, USA Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA
| | - Christopher L Frank
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA Department of Molecular Genetics and Microbiology, Duke University, Durham, NC 27708, USA
| | - Gregory E Crawford
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, NC 27708, USA
| | - Uwe Ohler
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27708, USA Max Delbruck Center for Molecular Medicine, 13125 Berlin, Germany
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50
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Greenleaf WJ. Assaying the epigenome in limited numbers of cells. Methods 2014; 72:51-6. [PMID: 25461774 DOI: 10.1016/j.ymeth.2014.10.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2014] [Revised: 10/03/2014] [Accepted: 10/09/2014] [Indexed: 12/13/2022] Open
Abstract
Spectacular advances in the throughput of DNA sequencing have allowed genome-wide analysis of epigenetic features such as methylation, nucleosome position and post-translational modification, chromatin accessibility and connectivity, and transcription factor binding. However, for rare or precious biological samples, input requirements of many of these methods limit their application. In this review we discuss recent advances for low-input genome-wide analysis of chromatin immunoprecipitation, methylation, DNA accessibility, and chromatin conformation.
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Affiliation(s)
- William J Greenleaf
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, United States.
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