1
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Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J, Kawli T, Davis CA, Dobin A, Kaul R, Halow J, Van Nostrand EL, Freese P, Gorkin DU, Shen Y, He Y, Mackiewicz M, Pauli-Behn F, Williams BA, Mortazavi A, Keller CA, Zhang XO, Elhajjajy SI, Huey J, Dickel DE, Snetkova V, Wei X, Wang X, Rivera-Mulia JC, Rozowsky J, Zhang J, Chhetri SB, Zhang J, Victorsen A, White KP, Visel A, Yeo GW, Burge CB, Lécuyer E, Gilbert DM, Dekker J, Rinn J, Mendenhall EM, Ecker JR, Kellis M, Klein RJ, Noble WS, Kundaje A, Guigó R, Farnham PJ, Cherry JM, Myers RM, Ren B, Graveley BR, Gerstein MB, Pennacchio LA, Snyder MP, Bernstein BE, Wold B, Hardison RC, Gingeras TR, Stamatoyannopoulos JA, Weng Z. Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 2022; 605:E3. [PMID: 35474001 PMCID: PMC9095460 DOI: 10.1038/s41586-021-04226-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Affiliation(s)
| | - Jill E Moore
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Michael J Purcaro
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Henry E Pratt
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | | | - Noam Shoresh
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jessika Adrian
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Trupti Kawli
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Carrie A Davis
- Cold Spring Harbor Laboratory, Functional Genomics, Cold Spring Harbor, NY, USA
| | - Alexander Dobin
- Cold Spring Harbor Laboratory, Functional Genomics, Cold Spring Harbor, NY, USA
| | - Rajinder Kaul
- Altius Institute for Biomedical Sciences, Seattle, WA, USA.,Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Jessica Halow
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Eric L Van Nostrand
- Department of Cellular and Molecular Medicine, Institute for Genomic Medicine, Stem Cell Program, Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Peter Freese
- Program in Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David U Gorkin
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.,Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
| | - Yin Shen
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA.,Institute for Human Genetics, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Yupeng He
- Genomics Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - Brian A Williams
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California Irvine, Irvine, CA, USA
| | - Cheryl A Keller
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA
| | - Xiao-Ou Zhang
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Shaimae I Elhajjajy
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Jack Huey
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Diane E Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Valentina Snetkova
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Xintao Wei
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, UConn Health, Farmington, CT, USA
| | - Xiaofeng Wang
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montréal, Quebec, Canada.,Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada.,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Quebec, Canada
| | - Juan Carlos Rivera-Mulia
- Department of Biological Science, Florida State University, Tallahassee, FL, USA.,Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Medical School, Minneapolis, MN, USA
| | | | | | - Surya B Chhetri
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.,Biological Sciences, University of Alabama in Huntsville, Huntsville, AL, USA
| | - Jialing Zhang
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
| | - Alec Victorsen
- Department of Human Genetics, Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | | | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,School of Natural Sciences, University of California, Merced, Merced, CA, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, Institute for Genomic Medicine, Stem Cell Program, Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Christopher B Burge
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Lécuyer
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montréal, Quebec, Canada.,Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada.,Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Quebec, Canada
| | - David M Gilbert
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Job Dekker
- HHMI and Program in Systems Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - John Rinn
- University of Colorado Boulder, Boulder, CO, USA
| | - Eric M Mendenhall
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.,Biological Sciences, University of Alabama in Huntsville, Huntsville, AL, USA
| | - Joseph R Ecker
- Genomics Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.,Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Manolis Kellis
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - William S Noble
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Anshul Kundaje
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Roderic Guigó
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology and Universitat Pompeu Fabra, Barcelona, Spain
| | - Peggy J Farnham
- Department of Biochemistry and Molecular Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J Michael Cherry
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
| | - Bing Ren
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA. .,Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA.
| | - Brenton R Graveley
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, UConn Health, Farmington, CT, USA.
| | | | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. .,US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. .,Comparative Biochemistry Program, University of California, Berkeley, CA, USA.
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA. .,Cardiovascular Institute, Stanford School of Medicine, Stanford, CA, USA.
| | - Bradley E Bernstein
- Broad Institute and Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Barbara Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Ross C Hardison
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA.
| | - Thomas R Gingeras
- Cold Spring Harbor Laboratory, Functional Genomics, Cold Spring Harbor, NY, USA.
| | - John A Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA. .,Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA. .,Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
| | - Zhiping Weng
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA. .,Department of Thoracic Surgery, Clinical Translational Research Center, Shanghai Pulmonary Hospital, The School of Life Sciences and Technology, Tongji University, Shanghai, China. .,Bioinformatics Program, Boston University, Boston, MA, USA.
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Pratt HE, Andrews GR, Phalke N, Purcaro MJ, van der Velde A, Moore JE, Weng Z. Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites. Nucleic Acids Res 2021; 50:D141-D149. [PMID: 34755879 PMCID: PMC8728199 DOI: 10.1093/nar/gkab1039] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/12/2021] [Accepted: 10/14/2021] [Indexed: 11/13/2022] Open
Abstract
The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project. Here we present an update to Factorbook which significantly expands the breadth of cell type and TF coverage. The update includes an expanded motif catalog derived from thousands of ENCODE Phase II and III ChIP-seq experiments and HT-SELEX experiments; this motif catalog is integrated with the ENCODE registry of candidate cis-regulatory elements to annotate a comprehensive collection of genome-wide candidate TF binding sites. The database also offers novel tools for applying the motif models within machine learning frameworks and using these models for integrative analysis, including annotation of variants and disease and trait heritability. Factorbook is publicly available at www.factorbook.org; we will continue to expand the resource as ENCODE Phase IV data are released.
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Affiliation(s)
- Henry E Pratt
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Gregory R Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Nishigandha Phalke
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Michael J Purcaro
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Arjan van der Velde
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
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van der Velde A, Fan K, Tsuji J, Moore JE, Purcaro MJ, Pratt HE, Weng Z. Annotation of chromatin states in 66 complete mouse epigenomes during development. Commun Biol 2021; 4:239. [PMID: 33619351 PMCID: PMC7900196 DOI: 10.1038/s42003-021-01756-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 01/26/2021] [Indexed: 01/31/2023] Open
Abstract
The morphologically and functionally distinct cell types of a multicellular organism are maintained by their unique epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 11.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by polycomb repressive complex proteins, and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.
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Affiliation(s)
- Arjan van der Velde
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, 02215, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Junko Tsuji
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Michael J Purcaro
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA.
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4
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Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J, Kawli T, Davis CA, Dobin A, Kaul R, Halow J, Van Nostrand EL, Freese P, Gorkin DU, Shen Y, He Y, Mackiewicz M, Pauli-Behn F, Williams BA, Mortazavi A, Keller CA, Zhang XO, Elhajjajy SI, Huey J, Dickel DE, Snetkova V, Wei X, Wang X, Rivera-Mulia JC, Rozowsky J, Zhang J, Chhetri SB, Zhang J, Victorsen A, White KP, Visel A, Yeo GW, Burge CB, Lécuyer E, Gilbert DM, Dekker J, Rinn J, Mendenhall EM, Ecker JR, Kellis M, Klein RJ, Noble WS, Kundaje A, Guigó R, Farnham PJ, Cherry JM, Myers RM, Ren B, Graveley BR, Gerstein MB, Pennacchio LA, Snyder MP, Bernstein BE, Wold B, Hardison RC, Gingeras TR, Stamatoyannopoulos JA, Weng Z. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 2020; 583:699-710. [PMID: 32728249 PMCID: PMC7410828 DOI: 10.1038/s41586-020-2493-4] [Citation(s) in RCA: 879] [Impact Index Per Article: 219.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2017] [Accepted: 05/27/2020] [Indexed: 12/13/2022]
Abstract
The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.
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Affiliation(s)
- Jill E Moore
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Michael J Purcaro
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Henry E Pratt
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | | | - Noam Shoresh
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jessika Adrian
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Trupti Kawli
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Carrie A Davis
- Cold Spring Harbor Laboratory, Functional Genomics, Cold Spring Harbor, NY, USA
| | - Alexander Dobin
- Cold Spring Harbor Laboratory, Functional Genomics, Cold Spring Harbor, NY, USA
| | - Rajinder Kaul
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Jessica Halow
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Eric L Van Nostrand
- Department of Cellular and Molecular Medicine, Institute for Genomic Medicine, Stem Cell Program, Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Peter Freese
- Program in Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David U Gorkin
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
| | - Yin Shen
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
- Institute for Human Genetics, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Yupeng He
- Genomics Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - Brian A Williams
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California Irvine, Irvine, CA, USA
| | - Cheryl A Keller
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA
| | - Xiao-Ou Zhang
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Shaimae I Elhajjajy
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Jack Huey
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA
| | - Diane E Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Valentina Snetkova
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Xintao Wei
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, UConn Health, Farmington, CT, USA
| | - Xiaofeng Wang
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montréal, Quebec, Canada
- Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Quebec, Canada
| | - Juan Carlos Rivera-Mulia
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Medical School, Minneapolis, MN, USA
| | | | | | - Surya B Chhetri
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- Biological Sciences, University of Alabama in Huntsville, Huntsville, AL, USA
| | - Jialing Zhang
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
| | - Alec Victorsen
- Department of Human Genetics, Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | | | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- School of Natural Sciences, University of California, Merced, Merced, CA, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, Institute for Genomic Medicine, Stem Cell Program, Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Christopher B Burge
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Lécuyer
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montréal, Quebec, Canada
- Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Institut de Recherches Cliniques de Montréal (IRCM), Montréal, Quebec, Canada
| | - David M Gilbert
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Job Dekker
- HHMI and Program in Systems Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - John Rinn
- University of Colorado Boulder, Boulder, CO, USA
| | - Eric M Mendenhall
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- Biological Sciences, University of Alabama in Huntsville, Huntsville, AL, USA
| | - Joseph R Ecker
- Genomics Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Manolis Kellis
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - William S Noble
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Anshul Kundaje
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Roderic Guigó
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology and Universitat Pompeu Fabra, Barcelona, Spain
| | - Peggy J Farnham
- Department of Biochemistry and Molecular Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J Michael Cherry
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
| | - Bing Ren
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA.
| | - Brenton R Graveley
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, UConn Health, Farmington, CT, USA.
| | | | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Comparative Biochemistry Program, University of California, Berkeley, CA, USA.
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
- Cardiovascular Institute, Stanford School of Medicine, Stanford, CA, USA.
| | - Bradley E Bernstein
- Broad Institute and Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Barbara Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Ross C Hardison
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA.
| | - Thomas R Gingeras
- Cold Spring Harbor Laboratory, Functional Genomics, Cold Spring Harbor, NY, USA.
| | - John A Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA.
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
| | - Zhiping Weng
- University of Massachusetts Medical School, Program in Bioinformatics and Integrative Biology, Worcester, MA, USA.
- Department of Thoracic Surgery, Clinical Translational Research Center, Shanghai Pulmonary Hospital, The School of Life Sciences and Technology, Tongji University, Shanghai, China.
- Bioinformatics Program, Boston University, Boston, MA, USA.
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5
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Moore JE, Pratt HE, Purcaro MJ, Weng Z. A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods. Genome Biol 2020; 21:17. [PMID: 31969180 PMCID: PMC6977301 DOI: 10.1186/s13059-019-1924-8] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 12/23/2019] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Many genome-wide collections of candidate cis-regulatory elements (cCREs) have been defined using genomic and epigenomic data, but it remains a major challenge to connect these elements to their target genes. RESULTS To facilitate the development of computational methods for predicting target genes, we develop a Benchmark of candidate Enhancer-Gene Interactions (BENGI) by integrating the recently developed Registry of cCREs with experimentally derived genomic interactions. We use BENGI to test several published computational methods for linking enhancers with genes, including signal correlation and the TargetFinder and PEP supervised learning methods. We find that while TargetFinder is the best-performing method, it is only modestly better than a baseline distance method for most benchmark datasets when trained and tested with the same cell type and that TargetFinder often does not outperform the distance method when applied across cell types. CONCLUSIONS Our results suggest that current computational methods need to be improved and that BENGI presents a useful framework for method development and testing.
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Affiliation(s)
- Jill E Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Michael J Purcaro
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA.
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6
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Fu S, Wang Q, Moore JE, Purcaro MJ, Pratt HE, Fan K, Gu C, Jiang C, Zhu R, Kundaje A, Lu A, Weng Z. Differential analysis of chromatin accessibility and histone modifications for predicting mouse developmental enhancers. Nucleic Acids Res 2018; 46:11184-11201. [PMID: 30137428 PMCID: PMC6265487 DOI: 10.1093/nar/gky753] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 07/15/2018] [Accepted: 08/08/2018] [Indexed: 12/11/2022] Open
Abstract
Enhancers are distal cis-regulatory elements that modulate gene expression. They are depleted of nucleosomes and enriched in specific histone modifications; thus, calling DNase-seq and histone mark ChIP-seq peaks can predict enhancers. We evaluated nine peak-calling algorithms for predicting enhancers validated by transgenic mouse assays. DNase and H3K27ac peaks were consistently more predictive than H3K4me1/2/3 and H3K9ac peaks. DFilter and Hotspot2 were the best DNase peak callers, while HOMER, MUSIC, MACS2, DFilter and F-seq were the best H3K27ac peak callers. We observed that the differential DNase or H3K27ac signals between two distant tissues increased the area under the precision-recall curve (PR-AUC) of DNase peaks by 17.5-166.7% and that of H3K27ac peaks by 7.1-22.2%. We further improved this differential signal method using multiple contrast tissues. Evaluated using a blind test, the differential H3K27ac signal method substantially improved PR-AUC from 0.48 to 0.75 for predicting heart enhancers. We further validated our approach using postnatal retina and cerebral cortex enhancers identified by massively parallel reporter assays, and observed improvements for both tissues. In summary, we compared nine peak callers and devised a superior method for predicting tissue-specific mouse developmental enhancers by reranking the called peaks.
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Affiliation(s)
- Shaliu Fu
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Qin Wang
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Michael J Purcaro
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Kaili Fan
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Cuihua Gu
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Cizhong Jiang
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Ruixin Zhu
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Anshul Kundaje
- Department of Genetics, School of Medicine, Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Aiping Lu
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Zhiping Weng
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
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7
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Englot DJ, Yang L, Hamid H, Danielson N, Bai X, Marfeo A, Yu L, Gordon A, Purcaro MJ, Motelow JE, Agarwal R, Ellens DJ, Golomb JD, Shamy MCF, Zhang H, Carlson C, Doyle W, Devinsky O, Vives K, Spencer DD, Spencer SS, Schevon C, Zaveri HP, Blumenfeld H. Impaired consciousness in temporal lobe seizures: role of cortical slow activity. ACTA ACUST UNITED AC 2010; 133:3764-77. [PMID: 21081551 DOI: 10.1093/brain/awq316] [Citation(s) in RCA: 152] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Impaired consciousness requires altered cortical function. This can occur either directly from disorders that impair widespread bilateral regions of the cortex or indirectly through effects on subcortical arousal systems. It has therefore long been puzzling why focal temporal lobe seizures so often impair consciousness. Early work suggested that altered consciousness may occur with bilateral or dominant temporal lobe seizure involvement. However, other bilateral temporal lobe disorders do not impair consciousness. More recent work supports a 'network inhibition hypothesis' in which temporal lobe seizures disrupt brainstem-diencephalic arousal systems, leading indirectly to depressed cortical function and impaired consciousness. Indeed, prior studies show subcortical involvement in temporal lobe seizures and bilateral frontoparietal slow wave activity on intracranial electroencephalography. However, the relationships between frontoparietal slow waves and impaired consciousness and between cortical slowing and fast seizure activity have not been directly investigated. We analysed intracranial electroencephalography recordings during 63 partial seizures in 26 patients with surgically confirmed mesial temporal lobe epilepsy. Behavioural responsiveness was determined based on blinded review of video during seizures and classified as impaired (complex-partial seizures) or unimpaired (simple-partial seizures). We observed significantly increased delta-range 1-2 Hz slow wave activity in the bilateral frontal and parietal neocortices during complex-partial compared with simple-partial seizures. In addition, we confirmed prior work suggesting that propagation of unilateral mesial temporal fast seizure activity to the bilateral temporal lobes was significantly greater in complex-partial than in simple-partial seizures. Interestingly, we found that the signal power of frontoparietal slow wave activity was significantly correlated with the temporal lobe fast seizure activity in each hemisphere. Finally, we observed that complex-partial seizures were somewhat more common with onset in the language-dominant temporal lobe. These findings provide direct evidence for cortical dysfunction in the form of bilateral frontoparietal slow waves associated with impaired consciousness in temporal lobe seizures. We hypothesize that bilateral temporal lobe seizures may exert a powerful inhibitory effect on subcortical arousal systems. Further investigations will be needed to fully determine the role of cortical-subcortical networks in ictal neocortical dysfunction and may reveal treatments to prevent this important negative consequence of temporal lobe epilepsy.
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Affiliation(s)
- Dario J Englot
- Department of Neurosurgery, University of California, San Francisco, CA 94122, USA
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8
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Lewis KK, Bertolini MT, Hogan MJ, Laurencin C, Pettit CA, Purcaro MJ, Staub C, Williams MJ, Galvin JR. The new health-care system: results of a round table discussion. Conn Med 2010; 74:609-613. [PMID: 21189718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
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9
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Yang L, Morland TB, Schmits K, Rawson E, Narasimhan P, Motelow JE, Purcaro MJ, Peng K, Raouf S, DeSalvo MN, Oh T, Wilkerson J, Bod J, Srinivasan A, Kurashvili P, Anaya J, Manza P, Danielson N, Ransom CB, Huh L, Elrich S, Padin-Rosado J, Naidu Y, Detyniecki K, Hamid H, Fattahi P, Astur R, Xiao B, Duckrow RB, Blumenfeld H. A prospective study of loss of consciousness in epilepsy using virtual reality driving simulation and other video games. Epilepsy Behav 2010; 18:238-46. [PMID: 20537593 PMCID: PMC2914099 DOI: 10.1016/j.yebeh.2010.04.011] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2010] [Revised: 04/07/2010] [Accepted: 04/12/2010] [Indexed: 10/19/2022]
Abstract
Patients with epilepsy are at risk of traffic accidents when they have seizures while driving. However, driving is an essential part of normal daily life in many communities, and depriving patients of driving privileges can have profound consequences for their economic and social well-being. In the current study, we collected ictal performance data from a driving simulator and two other video games in patients undergoing continuous video/EEG monitoring. We captured 22 seizures in 13 patients and found that driving impairment during seizures differed in terms of both magnitude and character, depending on the seizure type. Our study documents the feasibility of a prospective study of driving and other behaviors during seizures through the use of computer-based tasks. This methodology may be applied to further describe differential driving impairment in specific types of seizures and to gain data on anatomical networks disrupted in seizures that impair consciousness and driving safety.
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Affiliation(s)
- Li Yang
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA, Department of Neurology, Xiangya Hospital, Central South University, 87 Xiang Ya Road, Changsha, Hunan, 410008, China
| | - Thomas B. Morland
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Kristen Schmits
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Elizabeth Rawson
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Poojitha Narasimhan
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Joshua E. Motelow
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Michael J. Purcaro
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Kathy Peng
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Saned Raouf
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Matthew N. DeSalvo
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Taemin Oh
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Jerome Wilkerson
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Jessica Bod
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Aditya Srinivasan
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Pimen Kurashvili
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Joseph Anaya
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Peter Manza
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Nathan Danielson
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Christopher B. Ransom
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Linda Huh
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Susan Elrich
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Jose Padin-Rosado
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Yamini Naidu
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Kamil Detyniecki
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Hamada Hamid
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Pooia Fattahi
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Robert Astur
- Department of Psychiatry, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA, Olin Neuropsychiatry Research Center, Institute of Living, 200 Retreat Avenue, Whitehall Building, Hartford, CT 06106
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiang Ya Road, Changsha, Hunan, 410008, China
| | - Robert B. Duckrow
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
| | - Hal Blumenfeld
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA, Department of Neurobiology, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA, Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA
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10
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DeSalvo MN, Schridde U, Mishra AM, Motelow JE, Purcaro MJ, Danielson N, Bai X, Hyder F, Blumenfeld H. Focal BOLD fMRI changes in bicuculline-induced tonic-clonic seizures in the rat. Neuroimage 2010; 50:902-9. [PMID: 20079442 DOI: 10.1016/j.neuroimage.2010.01.006] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2009] [Revised: 11/15/2009] [Accepted: 01/05/2010] [Indexed: 10/20/2022] Open
Abstract
Generalized tonic-clonic seizures cause widespread physiological changes throughout the cerebral cortex and subcortical structures in the brain. Using combined blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) at 9.4 T and electroencephalography (EEG), these changes can be characterized with high spatiotemporal resolution. We studied BOLD changes in anesthetized Wistar rats during bicuculline-induced tonic-clonic seizures. Bicuculline, a GABA(A) receptor antagonist, was injected systemically and seizure activity was observed on EEG as high-amplitude, high-frequency polyspike discharges followed by clonic paroxysmal activity of lower frequency, with mean electrographic seizure duration of 349 s. Our aim was to characterize the spatial localization, direction, and timing of BOLD signal changes during the pre-ictal, ictal and post-ictal periods. Group analysis was performed across seizures using paired t-maps of BOLD signal superimposed on high-resolution anatomical images. Regional analysis was then performed using volumes of interest to quantify BOLD timecourses. In the pre-ictal period we found focal BOLD increases in specific areas of somatosensory cortex (S1, S2) and thalamus several seconds before seizure onset. During seizures we observed BOLD increases in cortex, brainstem and thalamus and BOLD decreases in the hippocampus. The largest ictal BOLD increases remained in the focal regions of somatosensory cortex showing pre-ictal increases. During the post-ictal period we observed widespread BOLD decreases. These findings support a model in which "generalized" tonic-clonic seizures begin with focal changes before electrographic seizure onset, which progress to non-uniform changes during seizures, possibly shedding light on the etiology and pathophysiology of similar seizures in humans.
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Affiliation(s)
- Matthew N DeSalvo
- Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA
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11
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Lewis KK, Vassar-Pettit CA, Williams MJ, Purcaro MJ, Genao I. Primary-care in Connecticut: results of a roundtable discussion. Conn Med 2009; 73:421-425. [PMID: 19708323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
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12
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Blumenfeld H, Varghese GI, Purcaro MJ, Motelow JE, Enev M, McNally KA, Levin AR, Hirsch LJ, Tikofsky R, Zubal IG, Paige AL, Spencer SS. Cortical and subcortical networks in human secondarily generalized tonic-clonic seizures. ACTA ACUST UNITED AC 2009; 132:999-1012. [PMID: 19339252 DOI: 10.1093/brain/awp028] [Citation(s) in RCA: 229] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Generalized tonic-clonic seizures are among the most dramatic physiological events in the nervous system. The brain regions involved during partial seizures with secondary generalization have not been thoroughly investigated in humans. We used single photon emission computed tomography (SPECT) to image cerebral blood flow (CBF) changes in 59 secondarily generalized seizures from 53 patients. Images were analysed using statistical parametric mapping to detect cortical and subcortical regions most commonly affected in three different time periods: (i) during the partial seizure phase prior to generalization; (ii) during the generalization period; and (iii) post-ictally. We found that in the pre-generalization period, there were focal CBF increases in the temporal lobe on group analysis, reflecting the most common region of partial seizure onset. During generalization, individual patients had focal CBF increases in variable regions of the cerebral cortex. Group analysis during generalization revealed that the most consistent increase occurred in the superior medial cerebellum, thalamus and basal ganglia. Post-ictally, there was a marked progressive CBF increase in the cerebellum which spread to involve the bilateral lateral cerebellar hemispheres, as well as CBF increases in the midbrain and basal ganglia. CBF decreases were seen in the fronto-parietal association cortex, precuneus and cingulate gyrus during and following seizures, similar to the 'default mode' regions reported previously to show decreased activity in seizures and in normal behavioural tasks. Analysis of patient behaviour during and following seizures showed impaired consciousness at the time of SPECT tracer injections. Correlation analysis across patients demonstrated that cerebellar CBF increases were related to increases in the upper brainstem and thalamus, and to decreases in the fronto-parietal association cortex. These results reveal a network of cortical and subcortical structures that are most consistently involved in secondarily generalized tonic-clonic seizures. Abnormal increased activity in subcortical structures (cerebellum, basal ganglia, brainstem and thalamus), along with decreased activity in the association cortex may be crucial for motor manifestations and for impaired consciousness in tonic-clonic seizures. Understanding the networks involved in generalized tonic-clonic seizures can provide insights into mechanisms of behavioural changes, and may elucidate targets for improved therapies.
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Affiliation(s)
- H Blumenfeld
- Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8018, USA.
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13
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Varghese GI, Purcaro MJ, Motelow JE, Enev M, McNally KA, Levin AR, Hirsch LJ, Tikofsky R, Paige AL, Zubal IG, Spencer SS, Blumenfeld H. Clinical use of ictal SPECT in secondarily generalized tonic-clonic seizures. ACTA ACUST UNITED AC 2009; 132:2102-13. [PMID: 19339251 DOI: 10.1093/brain/awp027] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Partial seizures produce increased cerebral blood flow in the region of seizure onset. These regional cerebral blood flow increases can be detected by single photon emission computed tomography (ictal SPECT), providing a useful clinical tool for seizure localization. However, when partial seizures secondarily generalize, there are often questions of interpretation since propagation of seizures could produce ambiguous results. Ictal SPECT from secondarily generalized seizures has not been thoroughly investigated. We analysed ictal SPECT from 59 secondarily generalized tonic-clonic seizures obtained during epilepsy surgery evaluation in 53 patients. Ictal versus baseline interictal SPECT difference analysis was performed using ISAS (http://spect.yale.edu). SPECT injection times were classified based on video/EEG review as either pre-generalization, during generalization or in the immediate post-ictal period. We found that in the pre-generalization and generalization phases, ictal SPECT showed significantly more regions of cerebral blood flow increases than in partial seizures without secondary generalization. This made identification of a single unambiguous region of seizure onset impossible 50% of the time with ictal SPECT in secondarily generalized seizures. However, cerebral blood flow increases on ictal SPECT correctly identified the hemisphere (left versus right) of seizure onset in 84% of cases. In addition, when a single unambiguous region of cerebral blood flow increase was seen on ictal SPECT, this was the correct localization 80% of the time. In agreement with findings from partial seizures without secondary generalization, cerebral blood flow increases in the post-ictal period and cerebral blood flow decreases during or following seizures were not useful for localizing seizure onset. Interestingly, however, cerebral blood flow hypoperfusion during the generalization phase (but not pre-generalization) was greater on the side opposite to seizure onset in 90% of patients. These findings suggest that, with appropriate cautious interpretation, ictal SPECT in secondarily generalized seizures can help localize the region of seizure onset.
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Affiliation(s)
- G I Varghese
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut 06520-8018, USA
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