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Griffith EC, West AE, Greenberg ME. Neuronal enhancers fine-tune adaptive circuit plasticity. Neuron 2024; 112:3043-3057. [PMID: 39208805 PMCID: PMC11550865 DOI: 10.1016/j.neuron.2024.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/22/2024] [Accepted: 08/06/2024] [Indexed: 09/04/2024]
Abstract
Neuronal activity-regulated gene expression plays a crucial role in sculpting neural circuits that underpin adaptive brain function. Transcriptional enhancers are now recognized as key components of gene regulation that orchestrate spatiotemporally precise patterns of gene transcription. We propose that the dynamics of enhancer activation uniquely position these genomic elements to finely tune activity-dependent cellular plasticity. Enhancer specificity and modularity can be exploited to gain selective genetic access to specific cell states, and the precise modulation of target gene expression within restricted cellular contexts enabled by targeted enhancer manipulation allows for fine-grained evaluation of gene function. Mounting evidence also suggests that enduring stimulus-induced changes in enhancer states can modify target gene activation upon restimulation, thereby contributing to a form of cell-wide metaplasticity. We advocate for focused exploration of activity-dependent enhancer function to gain new insight into the mechanisms underlying brain plasticity and cognitive dysfunction.
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Affiliation(s)
- Eric C Griffith
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Anne E West
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.
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2
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Koesterich J, Liu J, Williams SE, Yang N, Kreimer A. Network Analysis of Enhancer-Promoter Interactions Highlights Cell-Type-Specific Mechanisms of Transcriptional Regulation Variation. Int J Mol Sci 2024; 25:9840. [PMID: 39337329 PMCID: PMC11432627 DOI: 10.3390/ijms25189840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 09/08/2024] [Accepted: 09/10/2024] [Indexed: 09/30/2024] Open
Abstract
Gene expression is orchestrated by a complex array of gene regulatory elements that govern transcription in a cell-type-specific manner. Though previously studied, the ability to utilize regulatory elements to identify disrupting variants remains largely elusive. To identify important factors within these regions, we generated enhancer-promoter interaction (EPI) networks and investigated the presence of disease-associated variants that fall within these regions. Our study analyzed six neuronal cell types across neural differentiation, allowing us to examine closely related cell types and across differentiation stages. Our results expand upon previous findings of cell-type specificity of enhancer, promoter, and transcription factor binding sites. Notably, we find that regulatory regions within EPI networks can identify the enrichment of variants associated with neuropsychiatric disorders within specific cell types and network sub-structures. This enrichment within sub-structures can allow for a better understanding of potential mechanisms by which variants may disrupt transcription. Together, our findings suggest that EPIs can be leveraged to better understand cell-type-specific regulatory architecture and used as a selection method for disease-associated variants to be tested in future functional assays. Combined with these future functional characterization assays, EPIs can be used to better identify and characterize regulatory variants' effects on such networks and model their mechanisms of gene regulation disruption across different disorders. Such findings can be applied in practical settings, such as diagnostic tools and drug development.
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Affiliation(s)
- Justin Koesterich
- Graduate Programs in Molecular Biosciences, Rutgers The State University of New Jersey, 604 Allison Rd., Piscataway, NJ 08854, USA
- Department of Biochemistry and Molecular Biology, Rutgers The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA
- Center for Advanced Biotechnology and Medicine, Rutgers The State University of New Jersey, 679 Hoes Lane West, Piscataway, NJ 08854, USA
| | - Jiayi Liu
- Graduate Programs in Molecular Biosciences, Rutgers The State University of New Jersey, 604 Allison Rd., Piscataway, NJ 08854, USA
- Department of Biochemistry and Molecular Biology, Rutgers The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA
- Center for Advanced Biotechnology and Medicine, Rutgers The State University of New Jersey, 679 Hoes Lane West, Piscataway, NJ 08854, USA
| | - Sarah E Williams
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Institute of Regenerative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Alper Center for Neurodevelopment and Regeneration, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nan Yang
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Institute of Regenerative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Alper Center for Neurodevelopment and Regeneration, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Anat Kreimer
- Graduate Programs in Molecular Biosciences, Rutgers The State University of New Jersey, 604 Allison Rd., Piscataway, NJ 08854, USA
- Department of Biochemistry and Molecular Biology, Rutgers The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA
- Center for Advanced Biotechnology and Medicine, Rutgers The State University of New Jersey, 679 Hoes Lane West, Piscataway, NJ 08854, USA
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3
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Di Nardo M, Musio A. Cohesin - bridging the gap among gene transcription, genome stability, and human diseases. FEBS Lett 2024. [PMID: 38852996 DOI: 10.1002/1873-3468.14949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/15/2024] [Accepted: 05/08/2024] [Indexed: 06/11/2024]
Abstract
The intricate landscape of cellular processes governing gene transcription, chromatin organization, and genome stability is a fascinating field of study. A key player in maintaining this delicate equilibrium is the cohesin complex, a molecular machine with multifaceted roles. This review presents an in-depth exploration of these intricate connections and their significant impact on various human diseases.
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Affiliation(s)
- Maddalena Di Nardo
- Institute for Biomedical Technologies (ITB), National Research Council (CNR), Pisa, Italy
| | - Antonio Musio
- Institute for Biomedical Technologies (ITB), National Research Council (CNR), Pisa, Italy
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4
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Ye W, Yu Y, Zhu X, Wan W, Liu Y, Zou H, Zhu Z. A Common Functional Variant at the Enhancer of the Rheumatoid Arthritis Risk Gene ORMDL3 Regulates its Expression Through Allele-Specific JunD Binding. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:485-495. [PMID: 37881318 PMCID: PMC10593690 DOI: 10.1007/s43657-023-00107-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 10/27/2023]
Abstract
Genome-wide association studies (GWASs) have identified over 100 loci associated with rheumatoid arthritis (RA); however, the functionally affected genes and the underlying molecular mechanisms contributing to these associations are often unknown. In this study, we conducted an integrative genomic analysis incorporating multiple "omics" data and identified a functional regulatory DNA variant, rs56199421, and a plausible mechanism by which it regulates the expression of a putative RA risk gene, ORMDL Sphingolipid Biosynthesis Regulator 3 (ORMDL3). The T allele of rs56199421, located in the enhancer region of ORMDL3, exhibited stronger direct binding ability than the other C allele of rs56199421 did in vitro with the transcription factor JunD and demonstrated higher transcriptional activity. Moreover, the T allele of rs56199421 is associated with elevated RA risk, and ORMDL3 expression is increased in RA patients. Thus, these findings suggest that the T allele of rs56199421 enhances JunD transcription factor binding, increases enhancer activity, and elevates the expression of the RA risk gene ORMDL3. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-023-00107-z.
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Affiliation(s)
- Wenjing Ye
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Institute of Rheumatology, Immunology and Allergy, Fudan University, Shanghai, 200040 China
| | - Yiyun Yu
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Institute of Rheumatology, Immunology and Allergy, Fudan University, Shanghai, 200040 China
| | - Xiaoxia Zhu
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Institute of Rheumatology, Immunology and Allergy, Fudan University, Shanghai, 200040 China
| | - Weiguo Wan
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Institute of Rheumatology, Immunology and Allergy, Fudan University, Shanghai, 200040 China
| | - Yun Liu
- The Ministry of Education Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032 China
| | - Hejian Zou
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Institute of Rheumatology, Immunology and Allergy, Fudan University, Shanghai, 200040 China
| | - Zaihua Zhu
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Institute of Rheumatology, Immunology and Allergy, Fudan University, Shanghai, 200040 China
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5
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Luo R, Yan J, Oh JW, Xi W, Shigaki D, Wong W, Cho HS, Murphy D, Cutler R, Rosen BP, Pulecio J, Yang D, Glenn RA, Chen T, Li QV, Vierbuchen T, Sidoli S, Apostolou E, Huangfu D, Beer MA. Dynamic network-guided CRISPRi screen identifies CTCF-loop-constrained nonlinear enhancer gene regulatory activity during cell state transitions. Nat Genet 2023; 55:1336-1346. [PMID: 37488417 PMCID: PMC11012226 DOI: 10.1038/s41588-023-01450-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 06/20/2023] [Indexed: 07/26/2023]
Abstract
Comprehensive enhancer discovery is challenging because most enhancers, especially those contributing to complex diseases, have weak effects on gene expression. Our gene regulatory network modeling identified that nonlinear enhancer gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Using human embryonic stem cell definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. We discovered a comprehensive set of enhancers for each of the core endoderm-specifying transcription factors. Many enhancers had strong effects mid-transition but weak effects post-transition, consistent with the nonlinear temporal responses to enhancer perturbation predicted by the modeling. Integrating three-dimensional genomic information, we were able to develop a CTCF-loop-constrained Interaction Activity model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and systematic enhancer discovery in both normal and pathological cell state transitions.
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Affiliation(s)
- Renhe Luo
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Jielin Yan
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Jin Woo Oh
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Wang Xi
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Dustin Shigaki
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Wilfred Wong
- Computational & Systems Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Hyein S Cho
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Dylan Murphy
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
- Department of Medicine, Weill Cornell Medicine, New York City, NY, USA
| | - Ronald Cutler
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Bess P Rosen
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Julian Pulecio
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Dapeng Yang
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Rachel A Glenn
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Tingxu Chen
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Qing V Li
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Thomas Vierbuchen
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA
| | - Simone Sidoli
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Effie Apostolou
- Department of Medicine, Weill Cornell Medicine, New York City, NY, USA
| | - Danwei Huangfu
- Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA.
| | - Michael A Beer
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
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6
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Luo R, Yan J, Oh JW, Xi W, Shigaki D, Wong W, Cho H, Murphy D, Cutler R, Rosen BP, Pulecio J, Yang D, Glenn R, Chen T, Li QV, Vierbuchen T, Sidoli S, Apostolou E, Huangfu D, Beer MA. Dynamic network-guided CRISPRi screen reveals CTCF loop-constrained nonlinear enhancer-gene regulatory activity in cell state transitions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531569. [PMID: 36945628 PMCID: PMC10028945 DOI: 10.1101/2023.03.07.531569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Comprehensive enhancer discovery is challenging because most enhancers, especially those affected in complex diseases, have weak effects on gene expression. Our network modeling revealed that nonlinear enhancer-gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Utilizing hESC definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. The screen discovered a comprehensive set of enhancers (4 to 9 per locus) for each of the core endoderm lineage-specifying transcription factors, and many enhancers had strong effects mid-transition but weak effects post-transition. Through integrating enhancer activity measurements and three-dimensional enhancer-promoter interaction information, we were able to develop a CTCF loop-constrained Interaction Activity (CIA) model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and more comprehensive enhancer discovery in both normal and pathological cell state transitions.
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7
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Bene K, Halasz L, Nagy L. Transcriptional repression shapes the identity and function of tissue macrophages. FEBS Open Bio 2021; 11:3218-3229. [PMID: 34358410 PMCID: PMC8634859 DOI: 10.1002/2211-5463.13269] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 07/16/2021] [Accepted: 08/05/2021] [Indexed: 12/22/2022] Open
Abstract
The changing extra‐ and intracellular microenvironment calls for rapid cell fate decisions that are precisely and primarily regulated at the transcriptional level. The cellular components of the immune system are excellent examples of how cells respond and adapt to different environmental stimuli. Innate immune cells such as macrophages are able to modulate their transcriptional programs and epigenetic regulatory networks through activation and repression of particular genes, allowing them to quickly respond to a rapidly changing environment. Tissue macrophages are essential components of different immune‐ and nonimmune cell‐mediated physiological mechanisms in mammals and are widely used models for investigating transcriptional regulatory mechanisms. Therefore, it is critical to unravel the distinct sets of transcription activators, repressors, and coregulators that play roles in determining tissue macrophage identity and functions during homeostasis, as well as in diseases affecting large human populations, such as metabolic syndromes, immune‐deficiencies, and tumor development. In this review, we will focus on transcriptional repressors that play roles in tissue macrophage development and function under physiological conditions.
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Affiliation(s)
- Krisztian Bene
- Department of Biochemistry and Molecular Biology, Nuclear Receptor Research Laboratory, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Laszlo Halasz
- Departments of Medicine and Biological Chemistry, Johns Hopkins University School of Medicine, Institute for Fundamental Biomedical Research, Johns Hopkins All Children's Hospital, St. Petersburg, FL, USA
| | - Laszlo Nagy
- Department of Biochemistry and Molecular Biology, Nuclear Receptor Research Laboratory, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.,Departments of Medicine and Biological Chemistry, Johns Hopkins University School of Medicine, Institute for Fundamental Biomedical Research, Johns Hopkins All Children's Hospital, St. Petersburg, FL, USA
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8
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Liou SH, Singh SK, Singer RH, Coleman RA, Liu WL. Structure of the p53/RNA polymerase II assembly. Commun Biol 2021; 4:397. [PMID: 33767390 PMCID: PMC7994806 DOI: 10.1038/s42003-021-01934-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Accepted: 03/02/2021] [Indexed: 02/07/2023] Open
Abstract
The tumor suppressor p53 protein activates expression of a vast gene network in response to stress stimuli for cellular integrity. The molecular mechanism underlying how p53 targets RNA polymerase II (Pol II) to regulate transcription remains unclear. To elucidate the p53/Pol II interaction, we have determined a 4.6 Å resolution structure of the human p53/Pol II assembly via single particle cryo-electron microscopy. Our structure reveals that p53's DNA binding domain targets the upstream DNA binding site within Pol II. This association introduces conformational changes of the Pol II clamp into a further-closed state. A cavity was identified between p53 and Pol II that could possibly host DNA. The transactivation domain of p53 binds the surface of Pol II's jaw that contacts downstream DNA. These findings suggest that p53's functional domains directly regulate DNA binding activity of Pol II to mediate transcription, thereby providing insights into p53-regulated gene expression.
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Affiliation(s)
- Shu-Hao Liou
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Sameer K Singh
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Robert H Singer
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY, USA
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Robert A Coleman
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY, USA.
| | - Wei-Li Liu
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY, USA.
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9
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Brown CY, Sadlon T, Hope CM, Wong YY, Wong S, Liu N, Withers H, Brown K, Bandara V, Gundsambuu B, Pederson S, Breen J, Robertson SA, Forrest A, Beyer M, Barry SC. Molecular Insights Into Regulatory T-Cell Adaptation to Self, Environment, and Host Tissues: Plasticity or Loss of Function in Autoimmune Disease. Front Immunol 2020; 11:1269. [PMID: 33072063 PMCID: PMC7533603 DOI: 10.3389/fimmu.2020.01269] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 05/19/2020] [Indexed: 12/19/2022] Open
Abstract
There has been much interest in the ability of regulatory T cells (Treg) to switch function in vivo, either as a result of genetic risk of disease or in response to environmental and metabolic cues. The relationship between levels of FOXP3 and functional fitness plays a significant part in this plasticity. There is an emerging role for Treg in tissue repair that may be less dependent on FOXP3, and the molecular mechanisms underpinning this are not fully understood. As a result of detailed, high-resolution functional genomics, the gene regulatory networks and key functional mediators of Treg phenotype downstream of FOXP3 have been mapped, enabling a mechanistic insight into Treg function. This transcription factor-driven programming of T-cell function to generate Treg requires the switching on and off of key genes that form part of the Treg gene regulatory network and raises the possibility that this is reversible. It is plausible that subtle shifts in expression levels of specific genes, including transcription factors and non-coding RNAs, change the regulation of the Treg gene network. The subtle skewing of gene expression initiates changes in function, with the potential to promote chronic disease and/or to license appropriate inflammatory responses. In the case of autoimmunity, there is an underlying genetic risk, and the interplay of genetic and environmental cues is complex and impacts gene regulation networks frequently involving promoters and enhancers, the regulatory elements that control gene expression levels and responsiveness. These promoter–enhancer interactions can operate over long distances and are highly cell type specific. In autoimmunity, the genetic risk can result in changes in these enhancer/promoter interactions, and this mainly impacts genes which are expressed in T cells and hence impacts Treg/conventional T-cell (Tconv) function. Genetic risk may cause the subtle alterations to the responsiveness of gene regulatory networks which are controlled by or control FOXP3 and its target genes, and the application of assays of the 3D organization of chromatin, enabling the connection of non-coding regulatory regions to the genes they control, is revealing the direct impact of environmental/metabolic/genetic risk on T-cell function and is providing mechanistic insight into susceptibility to inflammatory and autoimmune conditions.
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Affiliation(s)
- Cheryl Y Brown
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Timothy Sadlon
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia.,Women's and Children's Health Network, North Adelaide, SA, Australia
| | | | - Ying Y Wong
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Soon Wong
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Ning Liu
- Bioinformatics Hub, University of Adelaide, Adelaide, SA, Australia
| | - Holly Withers
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Katherine Brown
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Veronika Bandara
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Batjargal Gundsambuu
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Stephen Pederson
- Bioinformatics Hub, University of Adelaide, Adelaide, SA, Australia
| | - James Breen
- Bioinformatics Hub, University of Adelaide, Adelaide, SA, Australia
| | - Sarah Anne Robertson
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
| | - Alistair Forrest
- QEII Medical Centre and Centre for Medical Research, Harry Perkins Institute of Medical Research, Murdoch, WA, Australia
| | - Marc Beyer
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Simon Charles Barry
- Molecular Immunology, Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia.,Women's and Children's Health Network, North Adelaide, SA, Australia
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10
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Abstract
Spatiotemporal control of gene expression during development requires orchestrated activities of numerous enhancers, which are cis-regulatory DNA sequences that, when bound by transcription factors, support selective activation or repression of associated genes. Proper activation of enhancers is critical during embryonic development, adult tissue homeostasis, and regeneration, and inappropriate enhancer activity is often associated with pathological conditions such as cancer. Multiple consortia [e.g., the Encyclopedia of DNA Elements (ENCODE) Consortium and National Institutes of Health Roadmap Epigenomics Mapping Consortium] and independent investigators have mapped putative regulatory regions in a large number of cell types and tissues, but the sequence determinants of cell-specific enhancers are not yet fully understood. Machine learning approaches trained on large sets of these regulatory regions can identify core transcription factor binding sites and generate quantitative predictions of enhancer activity and the impact of sequence variants on activity. Here, we review these computational methods in the context of enhancer prediction and gene regulatory network models specifying cell fate.
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Affiliation(s)
- Michael A Beer
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205, USA;
| | - Dustin Shigaki
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205, USA;
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11
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Supervised enhancer prediction with epigenetic pattern recognition and targeted validation. Nat Methods 2020; 17:807-814. [PMID: 32737473 PMCID: PMC8073243 DOI: 10.1038/s41592-020-0907-8] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 06/18/2020] [Indexed: 12/20/2022]
Abstract
Enhancers are important noncoding elements, but they have been traditionally hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mouse and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription-factor binding patterns at predicted enhancers versus promoters. We demonstrated that these patterns enable the construction of a secondary model effectively discriminating between enhancers and promoters.
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12
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Novel Approaches for Identifying the Molecular Background of Schizophrenia. Cells 2020; 9:cells9010246. [PMID: 31963710 PMCID: PMC7017322 DOI: 10.3390/cells9010246] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/06/2020] [Accepted: 01/16/2020] [Indexed: 12/20/2022] Open
Abstract
Recent advances in psychiatric genetics have led to the discovery of dozens of genomic loci associated with schizophrenia. However, a gap exists between the detection of genetic associations and understanding the underlying molecular mechanisms. This review describes the basic approaches used in the so-called post-GWAS studies to generate biological interpretation of the existing population genetic data, including both molecular (creation and analysis of knockout animals, exploration of the transcriptional effects of common variants in human brain cells) and computational (fine-mapping of causal variability, gene set enrichment analysis, partitioned heritability analysis) methods. The results of the crucial studies, in which these approaches were used to uncover the molecular and neurobiological basis of the disease, are also reported.
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13
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Korkmaz G, Manber Z, Lopes R, Prekovic S, Schuurman K, Kim Y, Teunissen H, Flach K, Wit ED, Galli GG, Zwart W, Elkon R, Agami R. A CRISPR-Cas9 screen identifies essential CTCF anchor sites for estrogen receptor-driven breast cancer cell proliferation. Nucleic Acids Res 2019; 47:9557-9572. [PMID: 31372638 PMCID: PMC6765117 DOI: 10.1093/nar/gkz675] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 07/11/2019] [Accepted: 07/24/2019] [Indexed: 01/07/2023] Open
Abstract
Estrogen receptor α (ERα) is an enhancer activating transcription factor, a key driver of breast cancer and a main target for cancer therapy. ERα-mediated gene regulation requires proper chromatin-conformation to facilitate interactions between ERα-bound enhancers and their target promoters. A major determinant of chromatin structure is the CCCTC-binding factor (CTCF), that dimerizes and together with cohesin stabilizes chromatin loops and forms the boundaries of topologically associated domains. However, whether CTCF-binding elements (CBEs) are essential for ERα-driven cell proliferation is unknown. To address this question in a global manner, we implemented a CRISPR-based functional genetic screen targeting CBEs located in the vicinity of ERα-bound enhancers. We identified four functional CBEs and demonstrated the role of one of them in inducing chromatin conformation changes in favor of activation of PREX1, a key ERα target gene in breast cancer. Indeed, high PREX1 expression is a bona-fide marker of ERα-dependency in cell lines, and is associated with good outcome after anti-hormonal treatment. Altogether, our data show that distinct CTCF-mediated chromatin structures are required for ERα- driven breast cancer cell proliferation.
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Affiliation(s)
- Gozde Korkmaz
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Zohar Manber
- Department of Human Genetics, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Rui Lopes
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Stefan Prekovic
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Karianne Schuurman
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Yongsoo Kim
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Hans Teunissen
- Division of Gene Regulation, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Koen Flach
- Division of Gene Regulation, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Elzo de Wit
- Division of Gene Regulation, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Giorgio G Galli
- Disease area Oncology, Novartis Institute for Biomedical Research, CH-4002 Basel, Switzerland
| | - Wilbert Zwart
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.,Laboratory of Chemical Biology and Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, PO Box 513, 5600MB, Eindhoven, The Netherlands
| | - Ran Elkon
- Department of Human Genetics, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Reuven Agami
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.,Erasmus MC, Rotterdam University, Doctor Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
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14
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Rezazadeh S, Yang D, Tombline G, Simon M, Regan SP, Seluanov A, Gorbunova V. SIRT6 promotes transcription of a subset of NRF2 targets by mono-ADP-ribosylating BAF170. Nucleic Acids Res 2019; 47:7914-7928. [PMID: 31216030 DOI: 10.1093/nar/gkz528] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 05/22/2019] [Accepted: 06/12/2019] [Indexed: 12/22/2022] Open
Abstract
SIRT6 is critical for activating transcription of Nuclear factor (erythroid-derived 2)-like 2 (NRF2) responsive genes during oxidative stress. However, while the mechanism of SIRT6-mediated silencing is well understood, the mechanism of SIRT6-mediated transcriptional activation is unknown. Here, we employed SIRT6 separation of function mutants to reveal that SIRT6 mono-ADP-ribosylation activity is required for transcriptional activation. We demonstrate that SIRT6 mono-ADP-ribosylation of BAF170, a subunit of BAF chromatin remodeling complex, is critical for activation of a subset of NRF2 responsive genes upon oxidative stress. We show that SIRT6 recruits BAF170 to enhancer region of the Heme oxygenase-1 locus and promotes recruitment of RNA polymerase II. Furthermore, SIRT6 mediates the formation of the active chromatin 10-kb loop at the HO-1 locus, which is absent in SIRT6 deficient tissue. These results provide a novel mechanism for SIRT6-mediated transcriptional activation, where SIRT6 mono-ADP-ribosylates and recruits chromatin remodeling proteins to mediate the formation of active chromatin loop.
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Affiliation(s)
| | - David Yang
- University of Rochester, Rochester, NY 14627, USA
| | | | | | - Sean P Regan
- University of Rochester, Rochester, NY 14627, USA
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15
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Xia JH, Wei GH. Enhancer Dysfunction in 3D Genome and Disease. Cells 2019; 8:cells8101281. [PMID: 31635067 PMCID: PMC6830074 DOI: 10.3390/cells8101281] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 10/10/2019] [Accepted: 10/14/2019] [Indexed: 12/13/2022] Open
Abstract
Spatiotemporal patterns of gene expression depend on enhancer elements and other factors during individual development and disease progression. The rapid progress of high-throughput techniques has led to well-defined enhancer chromatin properties. Various genome-wide methods have revealed a large number of enhancers and the discovery of three-dimensional (3D) genome architecture showing the distant interacting mechanisms of enhancers that loop to target gene promoters. Whole genome sequencing projects directed at cancer have led to the discovery of substantial enhancer dysfunction in misregulating gene expression and in tumor initiation and progression. Results from genome-wide association studies (GWAS) combined with functional genomics analyses have elucidated the functional impacts of many cancer risk-associated variants that are enriched within the enhancer regions of chromatin. Risk variants dysregulate the expression of enhancer variant-associated genes via 3D genomic interactions. Moreover, these enhancer variants often alter the chromatin binding affinity for cancer-relevant transcription factors, which in turn leads to aberrant expression of the genes associated with cancer susceptibility. In this review, we investigate the extent to which these genetic regulatory circuits affect cancer predisposition and how the recent development of genome-editing methods have enabled the determination of the impacts of genomic variation and alteration on cancer phenotype, which will eventually lead to better management plans and treatment responses to human cancer in the clinic.
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Affiliation(s)
- Ji-Han Xia
- Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90014 Oulu, Finland.
| | - Gong-Hong Wei
- Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90014 Oulu, Finland.
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16
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Rowe EM, Xing V, Biggar KK. Lysine methylation: Implications in neurodegenerative disease. Brain Res 2019; 1707:164-171. [DOI: 10.1016/j.brainres.2018.11.024] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 11/13/2018] [Accepted: 11/18/2018] [Indexed: 12/14/2022]
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17
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Genome-wide identification of enhancer elements in the placenta. Placenta 2018; 79:72-77. [PMID: 30268337 DOI: 10.1016/j.placenta.2018.09.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 09/03/2018] [Accepted: 09/10/2018] [Indexed: 12/25/2022]
Abstract
Normal placental development is essential for a healthy pregnancy, and is contingent upon tight spatiotemporal regulation of gene expression. One level of transcriptional control is via enhancer elements in the genome. Enhancers are distal cis-regulatory elements that can impact gene expression regardless of their position or orientation. The study of enhancers in the placenta is usually focused on one or two at a time, and the simultaneous identification of all enhancers has been limited. However, such a holistic approach is necessary if we are to gain a systems-level understanding of gene expression regulation in the placenta. Here, we review current methods for genome-scale enhancer identification, as well as studies that have applied those techniques in the placenta, with the aim of guiding future research.
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18
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Swinstead EE, Paakinaho V, Hager GL. Chromatin reprogramming in breast cancer. Endocr Relat Cancer 2018; 25:R385-R404. [PMID: 29692347 PMCID: PMC6029727 DOI: 10.1530/erc-18-0033] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 04/24/2018] [Indexed: 02/06/2023]
Abstract
Reprogramming of the chromatin landscape is a critical component to the transcriptional response in breast cancer. Effects of sex hormones such as estrogens and progesterone have been well described to have a critical impact on breast cancer proliferation. However, the complex network of the chromatin landscape, enhancer regions and mode of function of steroid receptors (SRs) and other transcription factors (TFs), is an intricate web of signaling and functional processes that is still largely misunderstood at the mechanistic level. In this review, we describe what is currently known about the dynamic interplay between TFs with chromatin and the reprogramming of enhancer elements. Emphasis has been placed on characterizing the different modes of action of TFs in regulating enhancer activity, specifically, how different SRs target enhancer regions to reprogram chromatin in breast cancer cells. In addition, we discuss current techniques employed to study enhancer function at a genome-wide level. Further, we have noted recent advances in live cell imaging technology. These single-cell approaches enable the coupling of population-based assays with real-time studies to address many unsolved questions about SRs and chromatin dynamics in breast cancer.
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Affiliation(s)
- Erin E Swinstead
- Laboratory of Receptor Biology and Gene ExpressionNational Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Ville Paakinaho
- Laboratory of Receptor Biology and Gene ExpressionNational Cancer Institute, NIH, Bethesda, Maryland, USA
- Institute of BiomedicineUniversity of Eastern Finland, Kuopio, Finland
| | - Gordon L Hager
- Laboratory of Receptor Biology and Gene ExpressionNational Cancer Institute, NIH, Bethesda, Maryland, USA
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19
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Sadlon T, Brown CY, Bandara V, Hope CM, Schjenken JE, Pederson SM, Breen J, Forrest A, Beyer M, Robertson S, Barry SC. Unravelling the molecular basis for regulatory T-cell plasticity and loss of function in disease. Clin Transl Immunology 2018; 7:e1011. [PMID: 29497530 PMCID: PMC5827651 DOI: 10.1002/cti2.1011] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 01/28/2018] [Accepted: 01/29/2018] [Indexed: 12/14/2022] Open
Abstract
Regulatory T cells (Treg) are critical for preventing autoimmunity and curtailing responses of conventional effector T cells (Tconv). The reprogramming of T‐cell fate and function to generate Treg requires switching on and off of key gene regulatory networks, which may be initiated by a subtle shift in expression levels of specific genes. This can be achieved by intermediary regulatory processes that include microRNA and long noncoding RNA‐based regulation of gene expression. There are well‐documented microRNA profiles in Treg and Tconv, and these can operate to either reinforce or reduce expression of a specific set of target genes, including FOXP3 itself. This type of feedforward/feedback regulatory loop is normally stable in the steady state, but can alter in response to local cues or genetic risk. This may go some way to explaining T‐cell plasticity. In addition, in chronic inflammation or autoimmunity, altered Treg/Tconv function may be influenced by changes in enhancer–promoter interactions, which are highly cell type‐specific. These interactions are impacted by genetic risk based on genome‐wide association studies and may cause subtle alterations to the gene regulatory networks controlled by or controlling FOXP3 and its target genes. Recent insights into the 3D organisation of chromatin and the mapping of noncoding regulatory regions to the genes they control are shedding new light on the direct impact of genetic risk on T‐cell function and susceptibility to inflammatory and autoimmune conditions.
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Affiliation(s)
- Timothy Sadlon
- Women's and Children's Health Network North Adelaide SA Australia.,Molecular immunology Robinson Research Institute University of Adelaide Adelaide SA Australia
| | - Cheryl Y Brown
- Molecular immunology Robinson Research Institute University of Adelaide Adelaide SA Australia
| | - Veronika Bandara
- Molecular immunology Robinson Research Institute University of Adelaide Adelaide SA Australia
| | | | - John E Schjenken
- Reproductive Immunology Robinson Research Institute University of Adelaide Adelaide SA Australia
| | - Stephen M Pederson
- Molecular immunology Robinson Research Institute University of Adelaide Adelaide SA Australia.,University of Adelaide Bioinformatics Hub University of Adelaide Adelaide SA Australia
| | - James Breen
- Molecular immunology Robinson Research Institute University of Adelaide Adelaide SA Australia.,University of Adelaide Bioinformatics Hub University of Adelaide Adelaide SA Australia
| | - Alistair Forrest
- Harry Perkins Institute of Medical Research University of Western Australia Perth, WA Australia
| | - Marc Beyer
- Deutsches Zentrum fur Neurodegenerative Erkrankungen Bonn Germany
| | - Sarah Robertson
- Reproductive Immunology Robinson Research Institute University of Adelaide Adelaide SA Australia
| | - Simon C Barry
- Molecular immunology Robinson Research Institute University of Adelaide Adelaide SA Australia
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20
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Catarino RR, Stark A. Assessing sufficiency and necessity of enhancer activities for gene expression and the mechanisms of transcription activation. Genes Dev 2018; 32:202-223. [PMID: 29491135 PMCID: PMC5859963 DOI: 10.1101/gad.310367.117] [Citation(s) in RCA: 124] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Enhancers are important genomic regulatory elements directing cell type-specific transcription. They assume a key role during development and disease, and their identification and functional characterization have long been the focus of scientific interest. The advent of next-generation sequencing and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9-based genome editing has revolutionized the means by which we study enhancer biology. In this review, we cover recent developments in the prediction of enhancers based on chromatin characteristics and their identification by functional reporter assays and endogenous DNA perturbations. We discuss that the two latter approaches provide different and complementary insights, especially in assessing enhancer sufficiency and necessity for transcription activation. Furthermore, we discuss recent insights into mechanistic aspects of enhancer function, including findings about cofactor requirements and the role of post-translational histone modifications such as monomethylation of histone H3 Lys4 (H3K4me1). Finally, we survey how these approaches advance our understanding of transcription regulation with respect to promoter specificity and transcriptional bursting and provide an outlook covering open questions and promising developments.
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Affiliation(s)
- Rui R Catarino
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), 1030 Vienna, Austria
| | - Alexander Stark
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), 1030 Vienna, Austria
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21
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Nizovtseva EV, Todolli S, Olson WK, Studitsky VM. Towards quantitative analysis of gene regulation by enhancers. Epigenomics 2017; 9:1219-1231. [PMID: 28799793 DOI: 10.2217/epi-2017-0061] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Enhancers are regulatory DNA sequences that can activate transcription over large distances. Recent studies have revealed the widespread role of distant activation in eukaryotic gene regulation and in the development of various human diseases, including cancer. Here we review recent progress in the field, focusing on new experimental and computational approaches that quantify the role of chromatin structure and dynamics during enhancer-promoter interactions in vitro and in vivo.
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Affiliation(s)
- Ekaterina V Nizovtseva
- Cancer Epigenetics Program, Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 19422, USA
| | - Stefjord Todolli
- Department of Chemistry & Chemical Biology, Center for Quantitative Biology, Rutgers, the State University of New Jersey, 610 Taylor Rd., Piscataway, NJ 08854, USA
| | - Wilma K Olson
- Department of Chemistry & Chemical Biology, Center for Quantitative Biology, Rutgers, the State University of New Jersey, 610 Taylor Rd., Piscataway, NJ 08854, USA
| | - Vasily M Studitsky
- Cancer Epigenetics Program, Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 19422, USA.,Biology Faculty, Moscow State University, Moscow 119991, Russia.,Laboratory of Epigenetics, Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russia
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22
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Li P, Shi ML, Shen WL, Zhang Z, Xie DJ, Zhang XY, He C, Zhang Y, Zhao ZH. Coordinated regulation of IFITM1, 2 and 3 genes by an IFN-responsive enhancer through long-range chromatin interactions. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2017; 1860:885-893. [PMID: 28511927 PMCID: PMC7102783 DOI: 10.1016/j.bbagrm.2017.05.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Revised: 04/21/2017] [Accepted: 05/08/2017] [Indexed: 11/26/2022]
Abstract
Interferon-induced transmembrane protein (IFITM) 1, 2 and 3 genes encode a family of interferon (IFN)-induced transmembrane proteins that block entry of a broad spectrum of pathogens. However, the transcriptional regulation of these genes, especially whether there exist any enhancers and their roles during the IFN induction process remain elusive. Here, through public data mining, episomal luciferase reporter assay and in vivo CRISPR-Cas9 genome editing, we identified an IFN-responsive enhancer located 35kb upstream of IFITM3 gene promoter upregulating the IFN-induced expression of IFITM1, 2 and 3 genes. Chromatin immunoprecipitation (ChIP), electrophoretic mobility shift assay (EMSA) and luciferase reporter assay demonstrated that signal transducers and activators of transcription (STAT) 1 bound to the enhancer with the treatment of IFN and was indispensable for the enhancer activity. Furthermore, using chromosome conformation capture technique, we revealed that the IFITM1, 2 and 3 genes physically clustered together and constitutively looped to the distal enhancer through long-range interactions in both HEK293 and A549 cells, providing structural basis for coordinated regulation of IFITM1, 2 and 3 by the enhancer. Finally, we showed that in vivo truncation of the enhancer impaired IFN-induced resistance to influenza A virus (IAV) infection. These findings expand our understanding of the mechanisms underlying the transcriptional regulation of IFITM1, 2 and 3 expression and its ability to mediate IFN signaling.
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Affiliation(s)
- Ping Li
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - Ming-Lei Shi
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - Wen-Long Shen
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - Zhang Zhang
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - De-Jian Xie
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - Xiang-Yuan Zhang
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - Chao He
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China
| | - Yan Zhang
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China.
| | - Zhi-Hu Zhao
- Beijing Institute of Biotechnology, No. 20, Dongdajie Street, Fengtai District, Beijing 100071, China.
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23
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Casas-Tintó S, Arnés M, Ferrús A. Drosophila enhancer-Gal4 lines show ectopic expression during development. ROYAL SOCIETY OPEN SCIENCE 2017; 4:170039. [PMID: 28405401 PMCID: PMC5383858 DOI: 10.1098/rsos.170039] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 02/27/2017] [Indexed: 06/07/2023]
Abstract
In Drosophila melanogaster the most widely used technique to drive gene expression is the binary UAS/Gal4 system. We show here that a set of nervous system specific enhancers (elav, D42/Toll-6, OK6/RapGAP1) display ectopic activity in epithelial tissues during development, which is seldom considered in experimental studies. This ectopic activity is variable, unstable and influenced by the primary sequence of the enhancer and the insertion site in the chromosome. In addition, the ectopic activity is independent of the protein expressed, Gal4, as it is reproduced also with the expression of Gal80. Another enhancer, LN2 from the sex lethal (Sxl) gene, shows sex-dependent features in its ectopic expression. Feminization of LN2 expressing males does not alter the male specific pattern indicating that the sexual dimorphism of LN2 expression is an intrinsic feature of this enhancer. Other X chromosome enhancers corresponding to genes not related to sex determination do not show sexual dimorphism in their ectopic expressions. Although variable and unstable, the ectopic activation of enhancer-Gal4 lines seems to be regulated in terms of tissue and intensity. To characterize the full domain of expression of enhancer-Gal4 constructs is relevant for the design of transgenic animal models and biotechnology tools, as well as for the correct interpretation of developmental and behavioural studies in which Gal4 lines are used.
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24
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Singh SK, Qiao Z, Song L, Jani V, Rice W, Eng E, Coleman RA, Liu WL. Structural visualization of the p53/RNA polymerase II assembly. Genes Dev 2016; 30:2527-2537. [PMID: 27920087 PMCID: PMC5159667 DOI: 10.1101/gad.285692.116] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 10/18/2016] [Indexed: 01/03/2023]
Abstract
Singh et al. dissected the human p53/Pol II interaction via single-particle cryo-electron microscopy, structural docking, and biochemical analyses. These findings indicate that p53 may structurally regulate DNA-binding functions of Pol II via the clamp domain, thereby providing insights into p53-regulated Pol II transcription. The master tumor suppressor p53 activates transcription in response to various cellular stresses in part by facilitating recruitment of the transcription machinery to DNA. Recent studies have documented a direct yet poorly characterized interaction between p53 and RNA polymerase II (Pol II). Therefore, we dissected the human p53/Pol II interaction via single-particle cryo-electron microscopy, structural docking, and biochemical analyses. This study reveals that p53 binds Pol II via the Rpb1 and Rpb2 subunits, bridging the DNA-binding cleft of Pol II proximal to the upstream DNA entry site. In addition, the key DNA-binding surface of p53, frequently disrupted in various cancers, remains exposed within the assembly. Furthermore, the p53/Pol II cocomplex displays a closed conformation as defined by the position of the Pol II clamp domain. Notably, the interaction of p53 and Pol II leads to increased Pol II elongation activity. These findings indicate that p53 may structurally regulate DNA-binding functions of Pol II via the clamp domain, thereby providing insights into p53-regulated Pol II transcription.
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Affiliation(s)
- Sameer K Singh
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Zhen Qiao
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Lihua Song
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Vijay Jani
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - William Rice
- New York Structural Biology Center, Manhattan, New York 10027, USA
| | - Edward Eng
- New York Structural Biology Center, Manhattan, New York 10027, USA
| | - Robert A Coleman
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Wei-Li Liu
- Gruss-Lipper Biophotonics Center, Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
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25
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Gokoolparsadh A, Sutton GJ, Charamko A, Green NFO, Pardy CJ, Voineagu I. Searching for convergent pathways in autism spectrum disorders: insights from human brain transcriptome studies. Cell Mol Life Sci 2016; 73:4517-4530. [PMID: 27405608 PMCID: PMC11108267 DOI: 10.1007/s00018-016-2304-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Revised: 06/16/2016] [Accepted: 07/05/2016] [Indexed: 01/07/2023]
Abstract
Autism spectrum disorder (ASD) is one of the most heritable neuropsychiatric conditions. The complex genetic landscape of the disorder includes both common and rare variants at hundreds of genetic loci. This marked heterogeneity has thus far hampered efforts to develop genetic diagnostic panels and targeted pharmacological therapies. Here, we give an overview of the current literature on the genetic basis of ASD, and review recent human brain transcriptome studies and their role in identifying convergent pathways downstream of the heterogeneous genetic variants. We also discuss emerging evidence on the involvement of non-coding genomic regions and non-coding RNAs in ASD.
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Affiliation(s)
- Akira Gokoolparsadh
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia
| | - Gavin J Sutton
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia
| | - Alexiy Charamko
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia
| | - Nicole F Oldham Green
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia
| | - Christopher J Pardy
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia
| | - Irina Voineagu
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia.
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26
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Awazu A. Prediction of nucleosome positioning by the incorporation of frequencies and distributions of three different nucleotide segment lengths into a general pseudo k-tuple nucleotide composition. Bioinformatics 2016; 33:42-48. [PMID: 27563027 PMCID: PMC5860184 DOI: 10.1093/bioinformatics/btw562] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Revised: 08/02/2016] [Accepted: 08/19/2016] [Indexed: 11/13/2022] Open
Abstract
Motivation Nucleosome positioning plays important roles in many eukaryotic intranuclear processes, such as transcriptional regulation and chromatin structure formation. The investigations of nucleosome positioning rules provide a deeper understanding of these intracellular processes. Results Nucleosome positioning prediction was performed using a model consisting of three types of variables characterizing a DNA sequence—the number of five-nucleotide sequences, the number of three-nucleotide combinations in one period of a helix, and mono- and di-nucleotide distributions in DNA fragments. Using recently proposed stringent benchmark datasets with low biases for Saccharomyces cerevisiae, Homo sapiens, Caenorhabditis elegans and Drosophila melanogaster, the present model was shown to have a better prediction performance than the recently proposed predictors. This model was able to display the common and organism-dependent factors that affect nucleosome forming and inhibiting sequences as well. Therefore, the predictors developed here can accurately predict nucleosome positioning and help determine the key factors influencing this process. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Akinori Awazu
- Department of Mathematical and Life Sciences.,Research Center for Mathematics on Chromatin Live Dynamics, Hiroshima University, Kagami-yama 1-3-1, Higashi-Hiroshima, 739-8526, Japan
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27
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Le JV, Luo Y, Darcy MA, Lucas CR, Goodwin MF, Poirier MG, Castro CE. Probing Nucleosome Stability with a DNA Origami Nanocaliper. ACS NANO 2016; 10:7073-84. [PMID: 27362329 PMCID: PMC5460529 DOI: 10.1021/acsnano.6b03218] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
The organization of eukaryotic DNA into nucleosomes and chromatin undergoes dynamic structural changes to regulate genome processing, including transcription and DNA repair. Critical chromatin rearrangements occur over a wide range of distances, including the mesoscopic length scale of tens of nanometers. However, there is a lack of methodologies that probe changes over this mesoscopic length scale within chromatin. We have designed, constructed, and implemented a DNA-based nanocaliper that probes this mesoscopic length scale. We developed an approach of integrating nucleosomes into our nanocaliper at two attachment points with over 50% efficiency. Here, we focused on attaching the two DNA ends of the nucleosome to the ends of the two nanocaliper arms, so the hinge angle is a readout of the nucleosome end-to-end distance. We demonstrate that nucleosomes integrated with 6, 26, and 51 bp linker DNA are partially unwrapped by the nanocaliper by an amount consistent with previously observed structural transitions. In contrast, the nucleosomes integrated with the longer 75 bp linker DNA remain fully wrapped. We found that the nanocaliper angle is a sensitive measure of nucleosome disassembly and can read out transcription factor (TF) binding to its target site within the nucleosome. Interestingly, the nanocaliper not only detects TF binding but also significantly increases the probability of TF occupancy at its site by partially unwrapping the nucleosome. These studies demonstrate the feasibility of using DNA nanotechnology to both detect and manipulate nucleosome structure, which provides a foundation of future mesoscale studies of nucleosome and chromatin structural dynamics.
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Affiliation(s)
- Jenny V. Le
- Biophysics Graduate Program, The Ohio State University, Columbus OH 43214
| | - Yi Luo
- Biophysics Graduate Program, The Ohio State University, Columbus OH 43214
| | - Michael A. Darcy
- Department of Physics, The Ohio State University, Columbus OH 43214
| | | | | | - Michael G. Poirier
- Biophysics Graduate Program, The Ohio State University, Columbus OH 43214
- Department of Physics, The Ohio State University, Columbus OH 43214
- Corresponding authors: ,
| | - Carlos E. Castro
- Biophysics Graduate Program, The Ohio State University, Columbus OH 43214
- Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus OH 43214
- Corresponding authors: ,
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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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29
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Multiplex enhancer-reporter assays uncover unsophisticated TP53 enhancer logic. Genome Res 2016; 26:882-95. [PMID: 27197205 PMCID: PMC4937571 DOI: 10.1101/gr.204149.116] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 05/17/2016] [Indexed: 12/11/2022]
Abstract
Transcription factors regulate their target genes by binding to regulatory regions in the genome. Although the binding preferences of TP53 are known, it remains unclear what distinguishes functional enhancers from nonfunctional binding. In addition, the genome is scattered with recognition sequences that remain unoccupied. Using two complementary techniques of multiplex enhancer-reporter assays, we discovered that functional enhancers could be discriminated from nonfunctional binding events by the occurrence of a single TP53 canonical motif. By combining machine learning with a meta-analysis of TP53 ChIP-seq data sets, we identified a core set of more than 1000 responsive enhancers in the human genome. This TP53 cistrome is invariably used between cell types and experimental conditions, whereas differences among experiments can be attributed to indirect nonfunctional binding events. Our data suggest that TP53 enhancers represent a class of unsophisticated cell-autonomous enhancers containing a single TP53 binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors.
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30
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Rastegar S, Strähle U. The Zebrafish as Model for Deciphering the Regulatory Architecture of Vertebrate Genomes. GENETICS, GENOMICS AND FISH PHENOMICS 2016; 95:195-216. [DOI: 10.1016/bs.adgen.2016.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Mannini L, C Lamaze F, Cucco F, Amato C, Quarantotti V, Rizzo IM, Krantz ID, Bilodeau S, Musio A. Mutant cohesin affects RNA polymerase II regulation in Cornelia de Lange syndrome. Sci Rep 2015; 5:16803. [PMID: 26581180 PMCID: PMC4652179 DOI: 10.1038/srep16803] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 10/20/2015] [Indexed: 01/10/2023] Open
Abstract
In addition to its role in sister chromatid cohesion, genome stability and integrity, the cohesin complex is involved in gene transcription. Mutations in core cohesin subunits SMC1A, SMC3 and RAD21, or their regulators NIPBL and HDAC8, cause Cornelia de Lange syndrome (CdLS). Recent evidence reveals that gene expression dysregulation could be the underlying mechanism for CdLS. These findings raise intriguing questions regarding the potential role of cohesin-mediated transcriptional control and pathogenesis. Here, we identified numerous dysregulated genes occupied by cohesin by combining the transcriptome of CdLS cell lines carrying mutations in SMC1A gene and ChIP-Seq data. Genome-wide analyses show that genes changing in expression are enriched for cohesin-binding. In addition, our results indicate that mutant cohesin impairs both RNA polymerase II (Pol II) transcription initiation at promoters and elongation in the gene body. These findings highlight the pivotal role of cohesin in transcriptional regulation and provide an explanation for the typical gene dysregulation observed in CdLS patients.
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Affiliation(s)
- Linda Mannini
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Fabien C Lamaze
- Centre de recherche sur le cancer de l'Université Laval, Québec, Canada.,Centre de recherche du CHU de Québec (Hôtel-Dieu de Québec), Québec, Canada
| | - Francesco Cucco
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Clelia Amato
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Valentina Quarantotti
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Ilaria M Rizzo
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Ian D Krantz
- Division of Human Genetics, The Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Steve Bilodeau
- Centre de recherche sur le cancer de l'Université Laval, Québec, Canada.,Centre de recherche du CHU de Québec (Hôtel-Dieu de Québec), Québec, Canada.,Département de biologie moléculaire, biochimie médicale et pathologie, Faculté de Médecine, Université Laval, Québec, Canada
| | - Antonio Musio
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Pisa, Italy
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Pacheco MP, John E, Kaoma T, Heinäniemi M, Nicot N, Vallar L, Bueb JL, Sinkkonen L, Sauter T. Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network. BMC Genomics 2015; 16:809. [PMID: 26480823 PMCID: PMC4617894 DOI: 10.1186/s12864-015-1984-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 10/06/2015] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND The reconstruction of context-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important in research and medicine. Current reconstruction methods suffer from high computational effort and arbitrary threshold setting. Moreover, understanding the underlying epigenetic regulation might allow the identification of putative intervention points within metabolic networks. Genes under high regulatory load from multiple enhancers or super-enhancers are known key genes for disease and cell identity. However, their role in regulation of metabolism and their placement within the metabolic networks has not been studied. METHODS Here we present FASTCORMICS, a fast and robust workflow for the creation of high-quality metabolic models from transcriptomics data. FASTCORMICS is devoid of arbitrary parameter settings and due to its low computational demand allows cross-validation assays. Applying FASTCORMICS, we have generated models for 63 primary human cell types from microarray data, revealing significant differences in their metabolic networks. RESULTS To understand the cell type-specific regulation of the alternative metabolic pathways we built multiple models during differentiation of primary human monocytes to macrophages and performed ChIP-Seq experiments for histone H3 K27 acetylation (H3K27ac) to map the active enhancers in macrophages. Focusing on the metabolic genes under high regulatory load from multiple enhancers or super-enhancers, we found these genes to show the most cell type-restricted and abundant expression profiles within their respective pathways. Importantly, the high regulatory load genes are associated to reactions enriched for transport reactions and other pathway entry points, suggesting that they are critical regulatory control points for cell type-specific metabolism. CONCLUSIONS By integrating metabolic modelling and epigenomic analysis we have identified high regulatory load as a common feature of metabolic genes at pathway entry points such as transporters within the macrophage metabolic network. Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming.
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Affiliation(s)
- Maria Pires Pacheco
- Life Sciences Research Unit, University of Luxembourg, 162a, Avenue de la Faïencerie, L-1511, Luxembourg, Luxembourg.
| | - Elisabeth John
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg.
| | - Tony Kaoma
- Genomics Research Unit, Luxembourg Institute of Health, L-1526, Luxembourg, Luxembourg.
| | - Merja Heinäniemi
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, 70211, Kuopio, Finland.
| | - Nathalie Nicot
- Genomics Research Unit, Luxembourg Institute of Health, L-1526, Luxembourg, Luxembourg.
| | - Laurent Vallar
- Genomics Research Unit, Luxembourg Institute of Health, L-1526, Luxembourg, Luxembourg.
| | - Jean-Luc Bueb
- Life Sciences Research Unit, University of Luxembourg, 162a, Avenue de la Faïencerie, L-1511, Luxembourg, Luxembourg.
| | - Lasse Sinkkonen
- Life Sciences Research Unit, University of Luxembourg, 162a, Avenue de la Faïencerie, L-1511, Luxembourg, Luxembourg.
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg.
| | - Thomas Sauter
- Life Sciences Research Unit, University of Luxembourg, 162a, Avenue de la Faïencerie, L-1511, Luxembourg, Luxembourg.
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Patrushev LI, Kovalenko TF. Functions of noncoding sequences in mammalian genomes. BIOCHEMISTRY (MOSCOW) 2015; 79:1442-69. [PMID: 25749159 DOI: 10.1134/s0006297914130021] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Most of the mammalian genome consists of nucleotide sequences not coding for proteins. Exons of genes make up only 3% of the human genome, while the significance of most other sequences remains unknown. Recent genome studies with high-throughput methods demonstrate that the so-called noncoding part of the genome may perform important functions. This hypothesis is supported by three groups of experimental data: 1) approximately 10% of the sequences, most of which are located in noncoding parts of the genome, is evolutionarily conserved and thus can be of functional importance; 2) up to 99% of the mammalian genome is being transcribed forming short and long noncoding RNAs in addition to common mRNA; and 3) mutations in noncoding parts of the genome can be accompanied by progression of pathological states of the organism. In the light of these data, in the review we consider the functional role of numerous known sequences of noncoding parts of the genome including introns, DNA methylation regions, enhancers and locus control regions, insulators, S/MAR sequences, pseudogenes, and genes of noncoding RNAs, as well as transposons and simple repeats of centromeric and telomeric regions of chromosomes. The assumption is made that the intergenic noncoding sequences without definite/clear functions can be involved in spatial organization of genetic loci in interphase nuclei.
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Affiliation(s)
- L I Patrushev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, 117997, Russia.
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35
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Long-Range Transcriptional Control of the Il2 Gene by an Intergenic Enhancer. Mol Cell Biol 2015; 35:3880-91. [PMID: 26351138 DOI: 10.1128/mcb.00592-15] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 08/28/2015] [Indexed: 02/08/2023] Open
Abstract
Interleukin-2 (IL-2) is a potent cytokine with roles in both immunity and tolerance. Genetic studies in humans and mice demonstrate a role for Il2 in autoimmune disease susceptibility, and for decades the proximal Il2 upstream regulatory region has served as a paradigm of tissue-specific, inducible gene regulation. In this study, we have identified a novel long-range enhancer of the Il2 gene located 83 kb upstream of the transcription start site. This element can potently enhance Il2 transcription in recombinant reporter assays in vitro, and the native region undergoes chromatin remodeling, transcribes a bidirectional enhancer RNA, and loops to physically interact with the Il2 gene in vivo in a CD28-dependent manner in CD4(+) T cells. This cis regulatory element is evolutionarily conserved and is situated near a human single-nucleotide polymorphism (SNP) associated with multiple autoimmune disorders. These results indicate that the regulatory architecture of the Il2 locus is more complex than previously appreciated and suggest a novel molecular basis for the genetic association of Il2 polymorphism with autoimmune disease.
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36
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González-Vallinas J, Pagès A, Singh B, Eyras E. A semi-supervised approach uncovers thousands of intragenic enhancers differentially activated in human cells. BMC Genomics 2015; 16:523. [PMID: 26169177 PMCID: PMC4501197 DOI: 10.1186/s12864-015-1704-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Accepted: 06/15/2015] [Indexed: 02/06/2023] Open
Abstract
Background Transcriptional enhancers are generally known to regulate gene transcription from afar. Their activation involves a series of changes in chromatin marks and recruitment of protein factors. These enhancers may also occur inside genes, but how many may be active in human cells and their effects on the regulation of the host gene remains unclear. Results We describe a novel semi-supervised method based on the relative enrichment of chromatin signals between 2 conditions to predict active enhancers. We applied this method to the tumoral K562 and the normal GM12878 cell lines to predict enhancers that are differentially active in one cell type. These predictions show enhancer-like properties according to positional distribution, correlation with gene expression and production of enhancer RNAs. Using this model, we predict 10,365 and 9777 intragenic active enhancers in K562 and GM12878, respectively, and relate the differential activation of these enhancers to expression and splicing differences of the host genes. Conclusions We propose that the activation or silencing of intragenic transcriptional enhancers modulate the regulation of the host gene by means of a local change of the chromatin and the recruitment of enhancer-related factors that may interact with the RNA directly or through the interaction with RNA binding proteins. Predicted enhancers are available at http://regulatorygenomics.upf.edu/Projects/enhancers.html. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1704-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Amadís Pagès
- Universitat Pompeu Fabra, Dr Aiguader 88, E08003, Barcelona, Spain.
| | - Babita Singh
- Universitat Pompeu Fabra, Dr Aiguader 88, E08003, Barcelona, Spain.
| | - Eduardo Eyras
- Universitat Pompeu Fabra, Dr Aiguader 88, E08003, Barcelona, Spain. .,Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, E08010, Barcelona, Spain.
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37
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Yao P, Lin P, Gokoolparsadh A, Assareh A, Thang MWC, Voineagu I. Coexpression networks identify brain region-specific enhancer RNAs in the human brain. Nat Neurosci 2015; 18:1168-74. [PMID: 26167905 DOI: 10.1038/nn.4063] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Accepted: 06/18/2015] [Indexed: 12/17/2022]
Abstract
Despite major progress in identifying enhancer regions on a genome-wide scale, the majority of available data are limited to model organisms and human transformed cell lines. We have identified a robust set of enhancer RNAs (eRNAs) expressed in the human brain and constructed networks assessing eRNA-gene coexpression interactions across human fetal brain and multiple adult brain regions. Our data identify brain region-specific eRNAs and show that enhancer regions expressing eRNAs are enriched for genetic variants associated with autism spectrum disorders.
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Affiliation(s)
- Pu Yao
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Peijie Lin
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Akira Gokoolparsadh
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Amelia Assareh
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Mike W C Thang
- QFAB Bioinformatics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Queensland, Australia
| | - Irina Voineagu
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
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38
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Lochmann TL, Thomas RR, Bennett JP, Taylor SM. Epigenetic Modifications of the PGC-1α Promoter during Exercise Induced Expression in Mice. PLoS One 2015; 10:e0129647. [PMID: 26053857 PMCID: PMC4460005 DOI: 10.1371/journal.pone.0129647] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Accepted: 05/12/2015] [Indexed: 11/18/2022] Open
Abstract
The transcriptional coactivator, PGC-1α, is known for its role in mitochondrial biogenesis. Although originally thought to exist as a single protein isoform, recent studies have identified additional promoters which produce multiple mRNA transcripts. One of these promoters (promoter B), approximately 13.7kb upstream of the canonical PGC-1α promoter (promoter A), yields alternative transcripts present at levels much lower than the canonical PGC-1α mRNA transcript. In skeletal muscle, exercise resulted in a substantial, rapid increase of mRNA of these alternative PGC-1α transcripts. Although the β2-adrenergic receptor was identified as a signaling pathway that activates transcription from PGC-1α promoter B, it is not yet known what molecular changes occur to facilitate PGC-1α promoter B activation following exercise. We sought to determine whether epigenetic modifications were involved in this exercise response in mouse skeletal muscle. We found that DNA hydroxymethylation correlated to increased basal mRNA levels from PGC-1α promoter A, but that DNA methylation appeared to play no role in the exercise-induced activation of PGC-1α promoter B. The level of the activating histone mark H3K4me3 increased with exercise 2–4 fold across PGC-1α promoter B, but remained unaltered past the canonical PGC-1α transcriptional start site. Together, these data show that epigenetic modifications partially explain exercise-induced changes in the skeletal muscle mRNA levels of PGC-1α isoforms.
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Affiliation(s)
- Timothy L. Lochmann
- Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Microbiology and Immunology, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Ravindar R. Thomas
- Parkinson’s Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - James P. Bennett
- Parkinson’s Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Neurology, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Physiology and Biophysics, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Shirley M. Taylor
- Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Microbiology and Immunology, Virginia Commonwealth University, Richmond, Virginia, United States of America
- * E-mail:
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Bhatia S, Gordon CT, Foster RG, Melin L, Abadie V, Baujat G, Vazquez MP, Amiel J, Lyonnet S, van Heyningen V, Kleinjan DA. Functional assessment of disease-associated regulatory variants in vivo using a versatile dual colour transgenesis strategy in zebrafish. PLoS Genet 2015; 11:e1005193. [PMID: 26030420 PMCID: PMC4452300 DOI: 10.1371/journal.pgen.1005193] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Accepted: 04/02/2015] [Indexed: 11/26/2022] Open
Abstract
Disruption of gene regulation by sequence variation in non-coding regions of the genome is now recognised as a significant cause of human disease and disease susceptibility. Sequence variants in cis-regulatory elements (CREs), the primary determinants of spatio-temporal gene regulation, can alter transcription factor binding sites. While technological advances have led to easy identification of disease-associated CRE variants, robust methods for discerning functional CRE variants from background variation are lacking. Here we describe an efficient dual-colour reporter transgenesis approach in zebrafish, simultaneously allowing detailed in vivo comparison of spatio-temporal differences in regulatory activity between putative CRE variants and assessment of altered transcription factor binding potential of the variant. We validate the method on known disease-associated elements regulating SHH, PAX6 and IRF6 and subsequently characterise novel, ultra-long-range SOX9 enhancers implicated in the craniofacial abnormality Pierre Robin Sequence. The method provides a highly cost-effective, fast and robust approach for simultaneously unravelling in a single assay whether, where and when in embryonic development a disease-associated CRE-variant is affecting its regulatory function. Cis-regulatory elements (CREs) play a vital role in gene regulation by providing spatial and temporal specificity to the expression of their target genes. Understanding how these regions of the genome work is of vital importance for human health as it has been demonstrated that genetic changes in these regions can result in incorrect gene expression, leading to a variety of human diseases. Functional characterization of putative CREs and the effects of mutations on their activity is currently a major bottleneck in many studies towards understanding the causes and mechanisms of disease and disease susceptibility. We describe a robust in-vivo approach using dual-colour reporter transgenesis in zebrafish for unambiguous assessment of the effects of disease-associated CRE mutations on CRE activity during the entire time-course of embryonic development. The highly efficient, cost-effective and modular design of the assay allows rapid analysis of several CRE-variants in parallel. We illustrate the robustness of our approach using examples of CRE-variants associated with a broad spectrum of genetic diseases including brain, limb, eye and jaw disorders. In a single assay the method can address where and when in development the CRE variant affects its activity, what potential target genes are misregulated by the change and what upstream trans-acting factors are likely to mediate this effect.
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Affiliation(s)
- Shipra Bhatia
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail: (SB); (VvH); (DAK)
| | - Christopher T. Gordon
- INSERM U781, Hôpital Necker-Enfants Malades and Université Paris Descartes-Sorbonne Paris Cité, Institute Imagine, Paris, France
| | - Robert G. Foster
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Lucie Melin
- INSERM U781, Hôpital Necker-Enfants Malades and Université Paris Descartes-Sorbonne Paris Cité, Institute Imagine, Paris, France
| | - Véronique Abadie
- Service de Pédiatrie Générale, Université Paris Descartes, Hôpital Necker-Enfants Malades, Paris, France
| | - Geneviève Baujat
- Departement de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris France
| | - Marie-Paule Vazquez
- Service de Chirurgie Maxillo-Faciale et Plastique, CRMR des Malformations de la Face et de la Cavité Buccale, Hôpital Necker-Enfants Malades, Paris, France
| | - Jeanne Amiel
- INSERM U781, Hôpital Necker-Enfants Malades and Université Paris Descartes-Sorbonne Paris Cité, Institute Imagine, Paris, France
- Departement de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris France
| | - Stanislas Lyonnet
- INSERM U781, Hôpital Necker-Enfants Malades and Université Paris Descartes-Sorbonne Paris Cité, Institute Imagine, Paris, France
- Departement de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris France
| | - Veronica van Heyningen
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail: (SB); (VvH); (DAK)
| | - Dirk A. Kleinjan
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail: (SB); (VvH); (DAK)
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40
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Shen E, Shulha H, Weng Z, Akbarian S. Regulation of histone H3K4 methylation in brain development and disease. Philos Trans R Soc Lond B Biol Sci 2015; 369:rstb.2013.0514. [PMID: 25135975 DOI: 10.1098/rstb.2013.0514] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The growing list of mutations implicated in monogenic disorders of the developing brain includes at least seven genes (ARX, CUL4B, KDM5A, KDM5C, KMT2A, KMT2C, KMT2D) with loss-of-function mutations affecting proper regulation of histone H3 lysine 4 methylation, a chromatin mark which on a genome-wide scale is broadly associated with active gene expression, with its mono-, di- and trimethylated forms differentially enriched at promoter and enhancer and other regulatory sequences. In addition to these rare genetic syndromes, dysregulated H3K4 methylation could also play a role in the pathophysiology of some cases diagnosed with autism or schizophrenia, two conditions which on a genome-wide scale are associated with H3K4 methylation changes at hundreds of loci in a subject-specific manner. Importantly, the reported alterations for some of the diseased brain specimens included a widespread broadening of H3K4 methylation profiles at gene promoters, a process that could be regulated by the UpSET(KMT2E/MLL5)-histone deacetylase complex. Furthermore, preclinical studies identified maternal immune activation, parental care and monoaminergic drugs as environmental determinants for brain-specific H3K4 methylation. These novel insights into the epigenetic risk architectures of neurodevelopmental disease will be highly relevant for efforts aimed at improved prevention and treatment of autism and psychosis spectrum disorders.
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Affiliation(s)
- Erica Shen
- Department of Psychiatry, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hennady Shulha
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01604, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01604, USA
| | - Schahram Akbarian
- Department of Psychiatry, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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41
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Melnikova LS, Kostyuchenko MV, Georgiev PG. Functional organization of the white gene enhancer in Drosophila melanogaster. DOKL BIOCHEM BIOPHYS 2015; 461:89-93. [PMID: 25937222 DOI: 10.1134/s1607672915020076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Indexed: 11/23/2022]
Affiliation(s)
- L S Melnikova
- Institute of Gene Biology, Russian Academy of Sciences, ul. Vavilova 34/5, Moscow, 119334, Russia,
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42
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Ceballos-Chávez M, Subtil-Rodríguez A, Giannopoulou EG, Soronellas D, Vázquez-Chávez E, Vicent GP, Elemento O, Beato M, Reyes JC. The chromatin Remodeler CHD8 is required for activation of progesterone receptor-dependent enhancers. PLoS Genet 2015; 11:e1005174. [PMID: 25894978 PMCID: PMC4403880 DOI: 10.1371/journal.pgen.1005174] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2014] [Accepted: 03/25/2015] [Indexed: 01/01/2023] Open
Abstract
While the importance of gene enhancers in transcriptional regulation is well established, the mechanisms and the protein factors that determine enhancers activity have only recently begun to be unravelled. Recent studies have shown that progesterone receptor (PR) binds regions that display typical features of gene enhancers. Here, we show by ChIP-seq experiments that the chromatin remodeler CHD8 mostly binds promoters under proliferation conditions. However, upon progestin stimulation, CHD8 re-localizes to PR enhancers also enriched in p300 and H3K4me1. Consistently, CHD8 depletion severely impairs progestin-dependent gene regulation. CHD8 binding is PR-dependent but independent of the pioneering factor FOXA1. The SWI/SNF chromatin-remodelling complex is required for PR-dependent gene activation. Interestingly, we show that CHD8 interacts with the SWI/SNF complex and that depletion of BRG1 and BRM, the ATPases of SWI/SNF complex, impairs CHD8 recruitment. We also show that CHD8 is not required for H3K27 acetylation, but contributes to increase accessibility of the enhancer to DNaseI. Furthermore, CHD8 was required for RNAPII recruiting to the enhancers and for transcription of enhancer-derived RNAs (eRNAs). Taken together our data demonstrate that CHD8 is involved in late stages of PR enhancers activation. A lot of research has been devoted during the last decades to understand the mechanisms that control gene promoters activity, however, much less is known about enhancers. Only recently, the use of genome-wide chromatin immunoprecipitation techniques has revealed the existence of more than 400,000 enhancers in the human genome. We are starting to understand the importance of these regulatory elements and how they are activated or repressed. In this work we discover that the chromatin remodeler CHD8 is recruited to Progesteron Receptor-dependent enhancers upon hormone treatment. CHD8 is required for late steps in the activation of these enhancers, including transcription of the enhancers and synthesis of eRNA (long noncoding RNAs derived form the enhancers).
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Affiliation(s)
- María Ceballos-Chávez
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
| | - Alicia Subtil-Rodríguez
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
- * E-mail: (ASR); (JCR)
| | - Eugenia G. Giannopoulou
- Biological Sciences Department, New York City College of Technology, City University of New York, Brooklyn, New York, New York, United States of America
- Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, New York, United States of America
| | - Daniel Soronellas
- Centre for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Elena Vázquez-Chávez
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
| | - Guillermo P. Vicent
- Centre for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Olivier Elemento
- HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, Cornell University, New York, New York, United States of America
| | - Miguel Beato
- Centre for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - José C. Reyes
- Molecular Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
- * E-mail: (ASR); (JCR)
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43
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Younger ST, Kenzelmann-Broz D, Jung H, Attardi LD, Rinn JL. Integrative genomic analysis reveals widespread enhancer regulation by p53 in response to DNA damage. Nucleic Acids Res 2015; 43:4447-62. [PMID: 25883152 PMCID: PMC4482066 DOI: 10.1093/nar/gkv284] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Accepted: 03/23/2015] [Indexed: 02/04/2023] Open
Abstract
The tumor suppressor p53 has been studied extensively as a direct transcriptional activator of protein-coding genes. Recent studies, however, have shed light on novel regulatory functions of p53 within noncoding regions of the genome. Here, we use a systematic approach that integrates transcriptome-wide expression analysis, genome-wide p53 binding profiles and chromatin state maps to characterize the global regulatory roles of p53 in response to DNA damage. Notably, our approach identified conserved features of the p53 network in both human and mouse primary fibroblast models. In addition to known p53 targets, we identify many previously unappreciated mRNAs and long noncoding RNAs that are regulated by p53. Moreover, we find that p53 binding occurs predominantly within enhancers in both human and mouse model systems. The ability to modulate enhancer activity offers an additional layer of complexity to the p53 network and greatly expands the diversity of genomic elements directly regulated by p53.
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Affiliation(s)
- Scott T Younger
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Daniela Kenzelmann-Broz
- Division of Radiation and Cancer Biology, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Heiyoun Jung
- Division of Radiation and Cancer Biology, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Laura D Attardi
- Division of Radiation and Cancer Biology, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - John L Rinn
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
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44
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Blatti C, Kazemian M, Wolfe S, Brodsky M, Sinha S. Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism. Nucleic Acids Res 2015; 43:3998-4012. [PMID: 25791631 PMCID: PMC4417154 DOI: 10.1093/nar/gkv195] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Accepted: 02/24/2015] [Indexed: 11/17/2022] Open
Abstract
Characterization of cell type specific regulatory networks and elements is a major challenge in genomics, and emerging strategies frequently employ high-throughput genome-wide assays of transcription factor (TF) to DNA binding, histone modifications or chromatin state. However, these experiments remain too difficult/expensive for many laboratories to apply comprehensively to their system of interest. Here, we explore the potential of elucidating regulatory systems in varied cell types using computational techniques that rely on only data of gene expression, low-resolution chromatin accessibility, and TF–DNA binding specificities (‘motifs’). We show that static computational motif scans overlaid with chromatin accessibility data reasonably approximate experimentally measured TF–DNA binding. We demonstrate that predicted binding profiles and expression patterns of hundreds of TFs are sufficient to identify major regulators of ∼200 spatiotemporal expression domains in the Drosophila embryo. We are then able to learn reliable statistical models of enhancer activity for over 70 expression domains and apply those models to annotate domain specific enhancers genome-wide. Throughout this work, we apply our motif and accessibility based approach to comprehensively characterize the regulatory network of fruitfly embryonic development and show that the accuracy of our computational method compares favorably to approaches that rely on data from many experimental assays.
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Affiliation(s)
- Charles Blatti
- Department of Computer Science, University of Illinois, Urbana, IL 61801, USA
| | - Majid Kazemian
- National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Scot Wolfe
- Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01655, USA Department of Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Michael Brodsky
- Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01655, USA Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Saurabh Sinha
- Department of Computer Science, University of Illinois, Urbana, IL 61801, USA Institute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA
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45
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Pazin MJ. Using the ENCODE Resource for Functional Annotation of Genetic Variants. Cold Spring Harb Protoc 2015; 2015:522-36. [PMID: 25762420 DOI: 10.1101/pdb.top084988] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This article illustrates the use of the Encyclopedia of DNA Elements (ENCODE) resource to generate or refine hypotheses from genomic data on disease and other phenotypic traits. First, the goals and history of ENCODE and related epigenomics projects are reviewed. Second, the rationale for ENCODE and the major data types used by ENCODE are briefly described, as are some standard heuristics for their interpretation. Third, the use of the ENCODE resource is examined. Standard use cases for ENCODE, accessing the ENCODE resource, and accessing data from related projects are discussed. Although the focus of this article is the use of ENCODE data, some of the same approaches can be used with data from other projects.
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Affiliation(s)
- Michael J Pazin
- Division of Genome Sciences, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892
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46
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Chromatin proteomic profiling reveals novel proteins associated with histone-marked genomic regions. Proc Natl Acad Sci U S A 2015; 112:3841-6. [PMID: 25755260 DOI: 10.1073/pnas.1502971112] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
More than a thousand proteins are thought to contribute to mammalian chromatin and its regulation, but our understanding of the genomic occupancy and function of most of these proteins is limited. Here we describe an approach, which we call "chromatin proteomic profiling," to identify proteins associated with genomic regions marked by specifically modified histones. We used ChIP-MS to identify proteins associated with genomic regions marked by histones modified at specific lysine residues, including H3K27ac, H3K4me3, H3K79me2, H3K36me3, H3K9me3, and H4K20me3, in ES cells. We identified 332 known and 114 novel proteins associated with these histone-marked genomic segments. Many of the novel candidates have been implicated in various diseases, and their chromatin association may provide clues to disease mechanisms. More than 100 histone modifications have been described, so similar chromatin proteomic profiling studies should prove to be valuable for identifying many additional chromatin-associated proteins in a broad spectrum of cell types.
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47
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Suryamohan K, Halfon MS. Identifying transcriptional cis-regulatory modules in animal genomes. WILEY INTERDISCIPLINARY REVIEWS. DEVELOPMENTAL BIOLOGY 2015; 4:59-84. [PMID: 25704908 PMCID: PMC4339228 DOI: 10.1002/wdev.168] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Revised: 11/04/2014] [Accepted: 11/16/2014] [Indexed: 11/08/2022]
Abstract
UNLABELLED Gene expression is regulated through the activity of transcription factors (TFs) and chromatin-modifying proteins acting on specific DNA sequences, referred to as cis-regulatory elements. These include promoters, located at the transcription initiation sites of genes, and a variety of distal cis-regulatory modules (CRMs), the most common of which are transcriptional enhancers. Because regulated gene expression is fundamental to cell differentiation and acquisition of new cell fates, identifying, characterizing, and understanding the mechanisms of action of CRMs is critical for understanding development. CRM discovery has historically been challenging, as CRMs can be located far from the genes they regulate, have few readily identifiable sequence characteristics, and for many years were not amenable to high-throughput discovery methods. However, the recent availability of complete genome sequences and the development of next-generation sequencing methods have led to an explosion of both computational and empirical methods for CRM discovery in model and nonmodel organisms alike. Experimentally, CRMs can be identified through chromatin immunoprecipitation directed against TFs or histone post-translational modifications, identification of nucleosome-depleted 'open' chromatin regions, or sequencing-based high-throughput functional screening. Computational methods include comparative genomics, clustering of known or predicted TF-binding sites, and supervised machine-learning approaches trained on known CRMs. All of these methods have proven effective for CRM discovery, but each has its own considerations and limitations, and each is subject to a greater or lesser number of false-positive identifications. Experimental confirmation of predictions is essential, although shortcomings in current methods suggest that additional means of validation need to be developed. For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST The authors have declared no conflicts of interest for this article.
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Affiliation(s)
- Kushal Suryamohan
- Department of Biochemistry, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- NY State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, NY 14203, USA
| | - Marc S. Halfon
- Department of Biochemistry, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- Department of Biological Sciences, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- Department of Biomedical Informatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- NY State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, NY 14203, USA
- Molecular and Cellular Biology Department and Program in Cancer Genetics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
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48
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Yue F, Cheng Y, Breschi A, Vierstra J, Wu W, Ryba T, Sandstrom R, Ma Z, Davis C, Pope BD, Shen Y, Pervouchine DD, Djebali S, Thurman RE, Kaul R, Rynes E, Kirilusha A, Marinov GK, Williams BA, Trout D, Amrhein H, Fisher-Aylor K, Antoshechkin I, DeSalvo G, See LH, Fastuca M, Drenkow J, Zaleski C, Dobin A, Prieto P, Lagarde J, Bussotti G, Tanzer A, Denas O, Li K, Bender MA, Zhang M, Byron R, Groudine MT, McCleary D, Pham L, Ye Z, Kuan S, Edsall L, Wu YC, Rasmussen MD, Bansal MS, Kellis M, Keller CA, Morrissey CS, Mishra T, Jain D, Dogan N, Harris RS, Cayting P, Kawli T, Boyle AP, Euskirchen G, Kundaje A, Lin S, Lin Y, Jansen C, Malladi VS, Cline MS, Erickson DT, Kirkup VM, Learned K, Sloan CA, Rosenbloom KR, Lacerda de Sousa B, Beal K, Pignatelli M, Flicek P, Lian J, Kahveci T, Lee D, Kent WJ, Ramalho Santos M, Herrero J, Notredame C, Johnson A, Vong S, Lee K, Bates D, Neri F, Diegel M, Canfield T, Sabo PJ, Wilken MS, Reh TA, Giste E, Shafer A, Kutyavin T, Haugen E, Dunn D, Reynolds AP, Neph S, Humbert R, Hansen RS, De Bruijn M, Selleri L, Rudensky A, Josefowicz S, Samstein R, Eichler EE, Orkin SH, Levasseur D, Papayannopoulou T, Chang KH, Skoultchi A, Gosh S, Disteche C, Treuting P, Wang Y, Weiss MJ, Blobel GA, Cao X, Zhong S, Wang T, Good PJ, Lowdon RF, Adams LB, Zhou XQ, Pazin MJ, Feingold EA, Wold B, Taylor J, Mortazavi A, Weissman SM, Stamatoyannopoulos JA, Snyder MP, Guigo R, Gingeras TR, Gilbert DM, Hardison RC, Beer MA, Ren B. A comparative encyclopedia of DNA elements in the mouse genome. Nature 2015; 515:355-64. [PMID: 25409824 PMCID: PMC4266106 DOI: 10.1038/nature13992] [Citation(s) in RCA: 1190] [Impact Index Per Article: 132.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 10/24/2014] [Indexed: 12/11/2022]
Abstract
The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.
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Affiliation(s)
- Feng Yue
- 1] Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Department of Biochemistry and Molecular Biology, College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania 17033, USA
| | - Yong Cheng
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Alessandra Breschi
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Weisheng Wu
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Tyrone Ryba
- Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, Florida 32306-4295, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Zhihai Ma
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Carrie Davis
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Benjamin D Pope
- Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, Florida 32306-4295, USA
| | - Yin Shen
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Dmitri D Pervouchine
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Sarah Djebali
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Eric Rynes
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Anthony Kirilusha
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Georgi K Marinov
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Brian A Williams
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Diane Trout
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Henry Amrhein
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Katherine Fisher-Aylor
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Igor Antoshechkin
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Gilberto DeSalvo
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Lei-Hoon See
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Meagan Fastuca
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Jorg Drenkow
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Chris Zaleski
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Alex Dobin
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Pablo Prieto
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Julien Lagarde
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Giovanni Bussotti
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Andrea Tanzer
- 1] Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain. [2] Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Waehringerstrasse 17/3/303, A-1090 Vienna, Austria
| | - Olgert Denas
- Departments of Biology and Mathematics and Computer Science, Emory University, O. Wayne Rollins Research Center, 1510 Clifton Road NE, Atlanta, Georgia 30322, USA
| | - Kanwei Li
- Departments of Biology and Mathematics and Computer Science, Emory University, O. Wayne Rollins Research Center, 1510 Clifton Road NE, Atlanta, Georgia 30322, USA
| | - M A Bender
- 1] Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA. [2] Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Miaohua Zhang
- Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Rachel Byron
- Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Mark T Groudine
- 1] Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. [2] Department of Radiation Oncology, University of Washington, Seattle, Washington 98195, USA
| | - David McCleary
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Long Pham
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Zhen Ye
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Samantha Kuan
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Lee Edsall
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Yi-Chieh Wu
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - Matthew D Rasmussen
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - Mukul S Bansal
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - Manolis Kellis
- 1] Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA. [2] Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Cheryl A Keller
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Christapher S Morrissey
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Tejaswini Mishra
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Deepti Jain
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Nergiz Dogan
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Robert S Harris
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Philip Cayting
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Trupti Kawli
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Alan P Boyle
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Ghia Euskirchen
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Shin Lin
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Yiing Lin
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Camden Jansen
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, California 92697, USA
| | - Venkat S Malladi
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Melissa S Cline
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Drew T Erickson
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Vanessa M Kirkup
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Katrina Learned
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Cricket A Sloan
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Kate R Rosenbloom
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Beatriz Lacerda de Sousa
- Departments of Obstetrics/Gynecology and Pathology, and Center for Reproductive Sciences, University of California San Francisco, San Francisco, California 94143, USA
| | - Kathryn Beal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Miguel Pignatelli
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jin Lian
- Yale University, Department of Genetics, PO Box 208005, 333 Cedar Street, New Haven, Connecticut 06520-8005, USA
| | - Tamer Kahveci
- Computer &Information Sciences &Engineering, University of Florida, Gainesville, Florida 32611, USA
| | - Dongwon Lee
- McKusick-Nathans Institute of Genetic Medicine and Department of Biomedical Engineering, Johns Hopkins University, 733 N. Broadway, BRB 573 Baltimore, Maryland 21205, USA
| | - W James Kent
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Miguel Ramalho Santos
- Departments of Obstetrics/Gynecology and Pathology, and Center for Reproductive Sciences, University of California San Francisco, San Francisco, California 94143, USA
| | - Javier Herrero
- 1] European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. [2] Bill Lyons Informatics Centre, UCL Cancer Institute, University College London, London WC1E 6DD, UK
| | - Cedric Notredame
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Audra Johnson
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Shinny Vong
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Kristen Lee
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Daniel Bates
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Fidencio Neri
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Theresa Canfield
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Matthew S Wilken
- Department of Biological Structure, University of Washington, HSB I-516, 1959 NE Pacific Street, Seattle, Washington 98195, USA
| | - Thomas A Reh
- Department of Biological Structure, University of Washington, HSB I-516, 1959 NE Pacific Street, Seattle, Washington 98195, USA
| | - Erika Giste
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Anthony Shafer
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Tanya Kutyavin
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Douglas Dunn
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Alex P Reynolds
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Shane Neph
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - R Scott Hansen
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Marella De Bruijn
- MRC Molecular Haemotology Unit, University of Oxford, Oxford OX3 9DS, UK
| | - Licia Selleri
- Department of Cell and Developmental Biology, Weill Cornell Medical College, New York, New York 10065, USA
| | - Alexander Rudensky
- HHMI and Ludwig Center at Memorial Sloan Kettering Cancer Center, Immunology Program, Memorial Sloan Kettering Cancer Canter, New York, New York 10065, USA
| | - Steven Josefowicz
- HHMI and Ludwig Center at Memorial Sloan Kettering Cancer Center, Immunology Program, Memorial Sloan Kettering Cancer Canter, New York, New York 10065, USA
| | - Robert Samstein
- HHMI and Ludwig Center at Memorial Sloan Kettering Cancer Center, Immunology Program, Memorial Sloan Kettering Cancer Canter, New York, New York 10065, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Stuart H Orkin
- Dana Farber Cancer Institute, Harvard Medical School, Cambridge, Massachusetts 02138, USA
| | - Dana Levasseur
- University of Iowa Carver College of Medicine, Department of Internal Medicine, Iowa City, Iowa 52242, USA
| | - Thalia Papayannopoulou
- Division of Hematology, Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Kai-Hsin Chang
- University of Iowa Carver College of Medicine, Department of Internal Medicine, Iowa City, Iowa 52242, USA
| | - Arthur Skoultchi
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Srikanta Gosh
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Christine Disteche
- Department of Pathology, University of Washington, Seattle, Washington 98195, USA
| | - Piper Treuting
- Department of Comparative Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Yanli Wang
- Bioinformatics and Genomics program, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Mitchell J Weiss
- Department of Hematology, St Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Gerd A Blobel
- 1] Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, USA. [2] Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Xiaoyi Cao
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Sheng Zhong
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Ting Wang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Peter J Good
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Rebecca F Lowdon
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Leslie B Adams
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Xiao-Qiao Zhou
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Michael J Pazin
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Elise A Feingold
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Barbara Wold
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - James Taylor
- Departments of Biology and Mathematics and Computer Science, Emory University, O. Wayne Rollins Research Center, 1510 Clifton Road NE, Atlanta, Georgia 30322, USA
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, California 92697, USA
| | - Sherman M Weissman
- Yale University, Department of Genetics, PO Box 208005, 333 Cedar Street, New Haven, Connecticut 06520-8005, USA
| | | | - Michael P Snyder
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Roderic Guigo
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Thomas R Gingeras
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - David M Gilbert
- Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, Florida 32306-4295, USA
| | - Ross C Hardison
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Michael A Beer
- McKusick-Nathans Institute of Genetic Medicine and Department of Biomedical Engineering, Johns Hopkins University, 733 N. Broadway, BRB 573 Baltimore, Maryland 21205, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
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Rad R, Rad L, Wang W, Strong A, Ponstingl H, Bronner IF, Mayho M, Steiger K, Weber J, Hieber M, Veltkamp C, Eser S, Geumann U, Öllinger R, Zukowska M, Barenboim M, Maresch R, Cadiñanos J, Friedrich M, Varela I, Constantino-Casas F, Sarver A, Ten Hoeve J, Prosser H, Seidler B, Bauer J, Heikenwälder M, Metzakopian E, Krug A, Ehmer U, Schneider G, Knösel T, Rümmele P, Aust D, Grützmann R, Pilarsky C, Ning Z, Wessels L, Schmid RM, Quail MA, Vassiliou G, Esposito I, Liu P, Saur D, Bradley A. A conditional piggyBac transposition system for genetic screening in mice identifies oncogenic networks in pancreatic cancer. Nat Genet 2014; 47:47-56. [PMID: 25485836 DOI: 10.1038/ng.3164] [Citation(s) in RCA: 64] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 11/12/2014] [Indexed: 01/02/2023]
Abstract
Here we describe a conditional piggyBac transposition system in mice and report the discovery of large sets of new cancer genes through a pancreatic insertional mutagenesis screen. We identify Foxp1 as an oncogenic transcription factor that drives pancreatic cancer invasion and spread in a mouse model and correlates with lymph node metastasis in human patients with pancreatic cancer. The propensity of piggyBac for open chromatin also enabled genome-wide screening for cancer-relevant noncoding DNA, which pinpointed a Cdkn2a cis-regulatory region. Histologically, we observed different tumor subentities and discovered associated genetic events, including Fign insertions in hepatoid pancreatic cancer. Our studies demonstrate the power of genetic screening to discover cancer drivers that are difficult to identify by other approaches to cancer genome analysis, such as downstream targets of commonly mutated human cancer genes. These piggyBac resources are universally applicable in any tissue context and provide unique experimental access to the genetic complexity of cancer.
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Affiliation(s)
- Roland Rad
- 1] Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany. [2] German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany. [3] The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Lena Rad
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Wei Wang
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Alexander Strong
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Hannes Ponstingl
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Iraad F Bronner
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Matthew Mayho
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Katja Steiger
- Department of Pathology, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Julia Weber
- 1] Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany. [2] German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Maren Hieber
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Christian Veltkamp
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Stefan Eser
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Ulf Geumann
- 1] Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany. [2] German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rupert Öllinger
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Magdalena Zukowska
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Maxim Barenboim
- 1] Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany. [2] German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Roman Maresch
- 1] Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany. [2] German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Juan Cadiñanos
- Instituto de Medicina Oncológica y Molecular de Asturias (IMOMA), Oviedo, Spain
| | - Mathias Friedrich
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Ignacio Varela
- Instituto de Biomedicina y Biotecnología de Cantabria (UC-CSIC-SODERCAN), Santander, Spain
| | | | - Aaron Sarver
- Biostatistics and Bioinformatics Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jelle Ten Hoeve
- Bioinformatics and Statistics, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Haydn Prosser
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Barbara Seidler
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Judith Bauer
- Institute of Virology, Technische Universität München, Munich, Germany
| | | | | | - Anne Krug
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Ursula Ehmer
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Günter Schneider
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Thomas Knösel
- Institute of Pathology, Ludwig Maximilians Universität München, München, Germany
| | - Petra Rümmele
- Institute of Pathology, Universität Regensburg, Regensburg, Germany
| | - Daniela Aust
- Institute of Pathology, Technische Universität Dresden, Dresden, Germany
| | - Robert Grützmann
- Department of Surgery, Technische Universität Dresden, Dresden, Germany
| | | | - Zemin Ning
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Lodewyk Wessels
- Bioinformatics and Statistics, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Roland M Schmid
- Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany
| | - Michael A Quail
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - George Vassiliou
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Irene Esposito
- Institute of Pathology, Medizinische Universität Insbruck, Insbruck, Austria
| | - Pentao Liu
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
| | - Dieter Saur
- 1] Department of Medicine II, Klinikum Rechts der Isar, Technische Universität München, München, Germany. [2] German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Allan Bradley
- The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, UK
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