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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: 1135] [Impact Index Per Article: 126.1] [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: 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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2
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Vierstra J, Rynes E, Sandstrom R, Zhang M, Canfield T, Hansen RS, Stehling-Sun S, Sabo PJ, Byron R, Humbert R, Thurman RE, Johnson AK, Vong S, Lee K, Bates D, Neri F, Diegel M, Giste E, Haugen E, Dunn D, Wilken MS, Josefowicz S, Samstein R, Chang KH, Eichler EE, De Bruijn M, Reh TA, Skoultchi A, Rudensky A, Orkin SH, Papayannopoulou T, Treuting PM, Selleri L, Kaul R, Groudine M, Bender MA, Stamatoyannopoulos JA. Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution. Science 2014; 346:1007-12. [PMID: 25411453 PMCID: PMC4337786 DOI: 10.1126/science.1246426] [Citation(s) in RCA: 186] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
To study the evolutionary dynamics of regulatory DNA, we mapped >1.3 million deoxyribonuclease I-hypersensitive sites (DHSs) in 45 mouse cell and tissue types, and systematically compared these with human DHS maps from orthologous compartments. We found that the mouse and human genomes have undergone extensive cis-regulatory rewiring that combines branch-specific evolutionary innovation and loss with widespread repurposing of conserved DHSs to alternative cell fates, and that this process is mediated by turnover of transcription factor (TF) recognition elements. Despite pervasive evolutionary remodeling of the location and content of individual cis-regulatory regions, within orthologous mouse and human cell types the global fraction of regulatory DNA bases encoding recognition sites for each TF has been strictly conserved. Our findings provide new insights into the evolutionary forces shaping mammalian regulatory DNA landscapes.
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Affiliation(s)
- Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Eric Rynes
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Miaohua Zhang
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Theresa Canfield
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - R Scott Hansen
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Sandra Stehling-Sun
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Rachel Byron
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Audra K Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Shinny Vong
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Kristen Lee
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Daniel Bates
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Fidencio Neri
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Erika Giste
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Douglas Dunn
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Matthew S Wilken
- Department of Biological Structure, University of Washington, Seattle, WA 98195, USA
| | - Steven Josefowicz
- Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Howard Hughes Medical Institute
| | - Robert Samstein
- Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Howard Hughes Medical Institute
| | - Kai-Hsin Chang
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Howard Hughes Medical Institute
| | - Marella De Bruijn
- Medical Research Council (MRC) Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, Oxford OX3 9DS, UK
| | - Thomas A Reh
- Department of Biological Structure, University of Washington, Seattle, WA 98195, USA
| | - Arthur Skoultchi
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Alexander Rudensky
- Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Howard Hughes Medical Institute
| | - Stuart H Orkin
- Howard Hughes Medical Institute. Division of Hematology/Oncology, Children's Hospital Boston and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Thalia Papayannopoulou
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Piper M Treuting
- Department of Comparative Medicine, University of Washington, Seattle, WA 98195, USA
| | - Licia Selleri
- Department of Cell and Developmental Biology, Weill Medical College of Cornell University, New York, NY 10065, USA
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Mark Groudine
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. Department of Radiation Oncology, University of Washington, Seattle, WA 98109, USA
| | - M A Bender
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. Department of Pediatrics, University of Washington, Seattle, WA 98195, USA
| | - John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Division of Oncology, Department of Medicine, University of Washington, Seattle, WA 98195, USA.
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3
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Stergachis AB, Neph S, Reynolds A, Humbert R, Miller B, Paige SL, Vernot B, Cheng JB, Thurman RE, Sandstrom R, Haugen E, Heimfeld S, Murry CE, Akey JM, Stamatoyannopoulos JA. Developmental fate and cellular maturity encoded in human regulatory DNA landscapes. Cell 2013; 154:888-903. [PMID: 23953118 DOI: 10.1016/j.cell.2013.07.020] [Citation(s) in RCA: 222] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2013] [Revised: 04/16/2013] [Accepted: 07/12/2013] [Indexed: 10/26/2022]
Abstract
Cellular-state information between generations of developing cells may be propagated via regulatory regions. We report consistent patterns of gain and loss of DNase I-hypersensitive sites (DHSs) as cells progress from embryonic stem cells (ESCs) to terminal fates. DHS patterns alone convey rich information about cell fate and lineage relationships distinct from information conveyed by gene expression. Developing cells share a proportion of their DHS landscapes with ESCs; that proportion decreases continuously in each cell type as differentiation progresses, providing a quantitative benchmark of developmental maturity. Developmentally stable DHSs densely encode binding sites for transcription factors involved in autoregulatory feedback circuits. In contrast to normal cells, cancer cells extensively reactivate silenced ESC DHSs and those from developmental programs external to the cell lineage from which the malignancy derives. Our results point to changes in regulatory DNA landscapes as quantitative indicators of cell-fate transitions, lineage relationships, and dysfunction.
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Affiliation(s)
- Andrew B Stergachis
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Shane Neph
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Alex Reynolds
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Brady Miller
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.,Department of Medicine, Division of Hematology University of Washington, Seattle, WA 98195, USA
| | - Sharon L Paige
- Department of Pathology, University of Washington, Seattle, WA 98109, USA.,Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA
| | - Benjamin Vernot
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Jeffrey B Cheng
- Department of Dermatology, University of California, San Francisco, CA 94143, USA
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - Shelly Heimfeld
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Charles E Murry
- Department of Pathology, University of Washington, Seattle, WA 98109, USA.,Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA.,Department of Bioengineering, University of Washington, Seattle, WA 98109, USA.,Department of Medicine, Division of Cardiology University of Washington, Seattle, WA 98195, USA
| | - Joshua M Akey
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA
| | - John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.,Department of Medicine, Division of Oncology University of Washington, Seattle, WA 98195, USA
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4
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Thurman RE, Rynes E, Humbert R, Vierstra J, Maurano MT, Haugen E, Sheffield NC, Stergachis AB, Wang H, Vernot B, Garg K, Sandstrom R, Bates D, Canfield TK, Diegel M, Dunn D, Ebersol AK, Frum T, Giste E, Harding L, Johnson AK, Johnson EM, Kutyavin T, Lajoie B, Lee BK, Lee K, London D, Lotakis D, Neph S, Neri F, Nguyen ED, Reynolds AP, Roach V, Safi A, Sanchez ME, Sanyal A, Shafer A, Simon JM, Song L, Vong S, Weaver M, Zhang Z, Zhang Z, Lenhard B, Tewari M, Dorschner MO, Hansen RS, Navas PA, Stamatoyannopoulos G, Iyer VR, Lieb JD, Sunyaev SR, Akey JM, Sabo PJ, Kaul R, Furey TS, Dekker J, Crawford GE, Stamatoyannopoulos JA. The accessible chromatin landscape of the human genome. Nature 2012; 489:75-82. [PMID: 22955617 PMCID: PMC3721348 DOI: 10.1038/nature11232] [Citation(s) in RCA: 1898] [Impact Index Per Article: 158.2] [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: 12/15/2011] [Accepted: 05/15/2012] [Indexed: 02/07/2023]
Abstract
DNase I hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ∼2.9 million DHSs that encompass virtually all known experimentally validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns. We connect ∼580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is organized with dozens to hundreds of co-activated elements, and the transcellular DNase I sensitivity pattern at a given region can predict cell-type-specific functional behaviours. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation.
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Affiliation(s)
- Robert E. Thurman
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Eric Rynes
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, WA
| | | | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, WA
| | | | | | - Hao Wang
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Benjamin Vernot
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Kavita Garg
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Daniel Bates
- Department of Genome Sciences, University of Washington, Seattle, WA
| | | | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Douglas Dunn
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Abigail K. Ebersol
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Tristan Frum
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Erika Giste
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Lisa Harding
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Audra K. Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Ericka M. Johnson
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Tanya Kutyavin
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Bryan Lajoie
- Program in Gene Function, University of Massachusetts Medical School, Worcester, MA
| | - Bum-Kyu Lee
- Institute for Cellular and Molecular Biology, University of Texas, Austin, TX
| | - Kristen Lee
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Darin London
- Institute for Genome Sciences and Policy, Duke University, Durham, NC
| | - Dimitra Lotakis
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Shane Neph
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Fidencio Neri
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Eric D. Nguyen
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Alex P. Reynolds
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Vaughn Roach
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Alexias Safi
- Institute for Genome Sciences and Policy, Duke University, Durham, NC
| | - Minerva E. Sanchez
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Amartya Sanyal
- Program in Gene Function, University of Massachusetts Medical School, Worcester, MA
| | - Anthony Shafer
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Jeremy M. Simon
- Department of Biology, University of North Carolina, Chapel Hill, NC
| | - Lingyun Song
- Institute for Genome Sciences and Policy, Duke University, Durham, NC
| | - Shinny Vong
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Molly Weaver
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Zhancheng Zhang
- Department of Biology, University of North Carolina, Chapel Hill, NC
| | - Zhuzhu Zhang
- Department of Biology, University of North Carolina, Chapel Hill, NC
| | - Boris Lenhard
- Bergen Center for Computational Science, University of Bergen, Bergen, Norway
| | - Muneesh Tewari
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Michael O. Dorschner
- Dept. of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA
| | - R. Scott Hansen
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Patrick A. Navas
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | | | - Vishwanath R. Iyer
- Institute for Cellular and Molecular Biology, University of Texas, Austin, TX
| | - Jason D. Lieb
- Department of Biology, University of North Carolina, Chapel Hill, NC
| | - Shamil R. Sunyaev
- Dept. of Medicine, Division of Genetics, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA
| | - Joshua M. Akey
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Peter J. Sabo
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Rajinder Kaul
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA
| | - Terrence S. Furey
- Department of Biology, University of North Carolina, Chapel Hill, NC
| | - Job Dekker
- Program in Gene Function, University of Massachusetts Medical School, Worcester, MA
| | | | - John A. Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, WA
- Department of Medicine, Division of Oncology, University of Washington, Seattle, WA
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5
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Neph S, Vierstra J, Stergachis AB, Reynolds AP, Haugen E, Vernot B, Thurman RE, Sandstrom R, Johnson AK, Maurano MT, Humbert R, Rynes E, Wang H, Vong S, Lee K, Bates D, Diegel M, Roach V, Dunn D, Neri J, Schafer A, Hansen RS, Kutyavin T, Giste E, Weaver M, Canfield T, Sabo P, Zhang M, Balasundaram G, Byron R, MacCoss MJ, Akey JM, Bender M, Groudine M, Kaul R, Stamatoyannopoulos JA. An expansive human regulatory lexicon encoded in transcription factor footprints. Nature 2012; 489:83-90. [PMID: 22955618 PMCID: PMC3736582 DOI: 10.1038/nature11212] [Citation(s) in RCA: 566] [Impact Index Per Article: 47.2] [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: 12/11/2011] [Accepted: 05/10/2012] [Indexed: 01/04/2023]
Abstract
Regulatory factor binding to genomic DNA protects the underlying sequence from cleavage by DNase I, leaving nucleotide-resolution footprints. Using genomic DNase I footprinting across 41 diverse cell and tissue types, we detected 45 million transcription factor occupancy events within regulatory regions, representing differential binding to 8.4 million distinct short sequence elements. Here we show that this small genomic sequence compartment, roughly twice the size of the exome, encodes an expansive repertoire of conserved recognition sequences for DNA-binding proteins that nearly doubles the size of the human cis-regulatory lexicon. We find that genetic variants affecting allelic chromatin states are concentrated in footprints, and that these elements are preferentially sheltered from DNA methylation. High-resolution DNase I cleavage patterns mirror nucleotide-level evolutionary conservation and track the crystallographic topography of protein-DNA interfaces, indicating that transcription factor structure has been evolutionarily imprinted on the human genome sequence. We identify a stereotyped 50-base-pair footprint that precisely defines the site of transcript origination within thousands of human promoters. Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely parallel major regulators of development, differentiation and pluripotency.
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Affiliation(s)
- Shane Neph
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | | | - Alex P. Reynolds
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Benjamin Vernot
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Robert E. Thurman
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Audra K. Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Matthew T. Maurano
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Eric Rynes
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Hao Wang
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Shinny Vong
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Kristen Lee
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Daniel Bates
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Vaughn Roach
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Douglas Dunn
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Jun Neri
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Anthony Schafer
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - R. Scott Hansen
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195
| | - Tanya Kutyavin
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Erika Giste
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Molly Weaver
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Theresa Canfield
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Peter Sabo
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Miaohua Zhang
- Basic Sciences Division, Fred Hutchison Cancer Research Center, Seattle, WA 98109
| | | | - Rachel Byron
- Basic Sciences Division, Fred Hutchison Cancer Research Center, Seattle, WA 98109
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Joshua M. Akey
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Michael Bender
- Basic Sciences Division, Fred Hutchison Cancer Research Center, Seattle, WA 98109
| | - Mark Groudine
- Basic Sciences Division, Fred Hutchison Cancer Research Center, Seattle, WA 98109
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195
| | - John A. Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
- Division of Oncology, Deparment of Medicine, University of Washington, Seattle, WA 98195
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6
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Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, Reynolds AP, Sandstrom R, Qu H, Brody J, Shafer A, Neri F, Lee K, Kutyavin T, Stehling-Sun S, Johnson AK, Canfield TK, Giste E, Diegel M, Bates D, Hansen RS, Neph S, Sabo PJ, Heimfeld S, Raubitschek A, Ziegler S, Cotsapas C, Sotoodehnia N, Glass I, Sunyaev SR, Kaul R, Stamatoyannopoulos JA. Systematic localization of common disease-associated variation in regulatory DNA. Science 2012; 337:1190-5. [PMID: 22955828 DOI: 10.1126/science.1222794] [Citation(s) in RCA: 2409] [Impact Index Per Article: 200.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure-related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn's disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.
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Affiliation(s)
- Matthew T Maurano
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
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7
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Neph S, Kuehn MS, Reynolds AP, Haugen E, Thurman RE, Johnson AK, Rynes E, Maurano MT, Vierstra J, Thomas S, Sandstrom R, Humbert R, Stamatoyannopoulos JA. BEDOPS: high-performance genomic feature operations. ACTA ACUST UNITED AC 2012; 28:1919-20. [PMID: 22576172 DOI: 10.1093/bioinformatics/bts277] [Citation(s) in RCA: 567] [Impact Index Per Article: 47.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
UNLABELLED The large and growing number of genome-wide datasets highlights the need for high-performance feature analysis and data comparison methods, in addition to efficient data storage and retrieval techniques. We introduce BEDOPS, a software suite for common genomic analysis tasks which offers improved flexibility, scalability and execution time characteristics over previously published packages. The suite includes a utility to compress large inputs into a lossless format that can provide greater space savings and faster data extractions than alternatives. AVAILABILITY http://code.google.com/p/bedops/ includes binaries, source and documentation.
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Affiliation(s)
- Shane Neph
- Department of Genome Sciences and Department of Medicine, University of Washington, Seattle, Washington, DC 98195, USA.
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8
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Liu M, Li CL, Stamatoyannopoulos G, Dorschner MO, Humbert R, Stamatoyannopoulos JA, Emery DW. Gammaretroviral vector integration occurs overwhelmingly within and near DNase hypersensitive sites. Hum Gene Ther 2011; 23:231-7. [PMID: 21981728 DOI: 10.1089/hum.2010.177] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Concerns surrounding the oncogenic potential of recombinant gammaretroviral vectors has spurred a great deal of interest in vector integration site (VIS) preferences. Although gammaretroviral vectors exhibit a modest preference for integration near transcription start sites (TSS) of active genes, such associations only account for about a third of all VIS. Previous studies suggested a correlation between gammaretroviral VIS and DNase hypersensitive sites (DHS), which mark chromatin regions associated with cis-regulatory elements. In order to study this issue directly, we assessed the correlation between 167 validated gammaretroviral VIS and a deep genome-wide map of DHS, both determined in the same cell line (the human fibrosarcoma HT1080). The DHS map was developed by sequencing individual DNase I cleavage sites using massively parallel sequencing technologies. These studies revealed an overwhelming preference for integrations associated with DHS, with a median distance of only 238 bp between individual VIS and the nearest DHS for the experimental dataset, compared to 3 kb for a random dataset and 577 to 1457 bp for two unrelated cell lines (p<0.001). Indeed, nearly 84% of all VIS were found to be located within 1 kb of a DHS (p=10(-43)). Further, this correlation was statistically independent from the association with TSS. The preference for DHS far exceeds that seen for other hallmarks of gammaretroviral VIS, including TSS, and may help explain several aspects of gammaretroviral vector biology, including the mechanism of VIS selection, as well as the relative frequency and underlying biology of gammaretroviral vector-mediated genotoxicity.
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Affiliation(s)
- Mingdong Liu
- Department of Medicine, Division of Medical Genetics, University of Washington , Seattle, WA 98195, USA
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9
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Abstract
AbstractProteins, due to their complex structures, possess infinite possibilities for assembling themselves as well as other biological and nonbiological materials into complex, multicomponent structures. Many examples from nature demonstrate the high degree of flexibility, strength and “intelligence” offered by protein-organized, self-assembling systems. However, several problems must be overcome before self-assembling protein-based products can become commercially feasible. One problem is the high cost of protein production. A second problem involves the question of producing nonidentical protein subunits in the proper stoichiometry for self-assembly. A third problem involves the stability of the protein components of larger structures.We have been developing protein-producing bioreactors to address the problems associated with the commercial production of proteins, both as individual products as well as components of self assembling systems. The approach that we have taken is to clone the gene or cDNA that encodes the desired protein(s) and tailor the expression of the protein so that it can be produced at high levels under conditions where cell division is blocked. This assures that supplied nutrients go into product and not biomass, and at the same time provides conditions where cells can be immobilized without fracturing the support matrix during division. The blocking of cell growth also allows for the adjustment of protein stoichiometry by setting the ratios of cells that produce different subunits of complex structures.To simplify downstream processing and purification, we have designed a system where nearly pure protein is secreted directly into the medium. This approach allows for automated downstream processing and separation of product from cells before it is degraded. The model system that we are using for the development of the protein-producing bioreactors utilizes genetically modified strains ofEscherichia colithat secrete proteins which are usually found in the periplasmic space directly into the medium. The phosphatebinding protein serves as an ideal model protein for bioreactor development, since the regulatory elements that control its production are turned on by phosphate limitation, which also arrests cell division. We are presently determining if these regulatory and secretory elements can be used to direct the synthesis and secretion of heterologous proteins.
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10
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Abstract
We developed a primer design method, Pythia, in which state of the art DNA binding affinity computations are directly integrated into the primer design process. We use chemical reaction equilibrium analysis to integrate multiple binding energy calculations into a conservative measure of polymerase chain reaction (PCR) efficiency, and a precomputed index on genomic sequences to evaluate primer specificity. We show that Pythia can design primers with success rates comparable with those of current methods, but yields much higher coverage in difficult genomic regions. For example, in RepeatMasked sequences in the human genome, Pythia achieved a median coverage of 89% as compared with a median coverage of 51% for Primer3. For parameter settings yielding sensitivities of 81%, our method has a recall of 97%, compared with the Primer3 recall of 48%. Because our primer design approach is based on the chemistry of DNA interactions, it has fewer and more physically meaningful parameters than current methods, and is therefore easier to adjust to specific experimental requirements. Our software is freely available at http://pythia.sourceforge.net.
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Affiliation(s)
- Tobias Mann
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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11
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Attanasio C, Reymond A, Humbert R, Lyle R, Kuehn MS, Neph S, Sabo PJ, Goldy J, Weaver M, Haydock A, Lee K, Dorschner M, Dermitzakis ET, Antonarakis SE, Stamatoyannopoulos JA. Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells. Genome Biol 2008; 9:R168. [PMID: 19055709 PMCID: PMC2646272 DOI: 10.1186/gb-2008-9-12-r168] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [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: 06/09/2008] [Revised: 09/24/2008] [Accepted: 12/02/2008] [Indexed: 01/26/2023] Open
Abstract
The fraction of experimentally active conserved non-coding sequences within any given cell type is low, so classical assays are unlikely to expose their potential. Background Conserved non-coding sequences in the human genome are approximately tenfold more abundant than known genes, and have been hypothesized to mark the locations of cis-regulatory elements. However, the global contribution of conserved non-coding sequences to the transcriptional regulation of human genes is currently unknown. Deeply conserved elements shared between humans and teleost fish predominantly flank genes active during morphogenesis and are enriched for positive transcriptional regulatory elements. However, such deeply conserved elements account for <1% of the conserved non-coding sequences in the human genome, which are predominantly mammalian. Results We explored the regulatory potential of a large sample of these 'common' conserved non-coding sequences using a variety of classic assays, including chromatin remodeling, and enhancer/repressor and promoter activity. When tested across diverse human model cell types, we find that the fraction of experimentally active conserved non-coding sequences within any given cell type is low (approximately 5%), and that this proportion increases only modestly when considered collectively across cell types. Conclusions The results suggest that classic assays of cis-regulatory potential are unlikely to expose the functional potential of the substantial majority of mammalian conserved non-coding sequences in the human genome.
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Affiliation(s)
- Catia Attanasio
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1 rue Michel Servet, 1211, Geneva 4, Switzerland.
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Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, Thurman RE, Kuehn MS, Taylor CM, Neph S, Koch CM, Asthana S, Malhotra A, Adzhubei I, Greenbaum JA, Andrews RM, Flicek P, Boyle PJ, Cao H, Carter NP, Clelland GK, Davis S, Day N, Dhami P, Dillon SC, Dorschner MO, Fiegler H, Giresi PG, Goldy J, Hawrylycz M, Haydock A, Humbert R, James KD, Johnson BE, Johnson EM, Frum TT, Rosenzweig ER, Karnani N, Lee K, Lefebvre GC, Navas PA, Neri F, Parker SCJ, Sabo PJ, Sandstrom R, Shafer A, Vetrie D, Weaver M, Wilcox S, Yu M, Collins FS, Dekker J, Lieb JD, Tullius TD, Crawford GE, Sunyaev S, Noble WS, Dunham I, Denoeud F, Reymond A, Kapranov P, Rozowsky J, Zheng D, Castelo R, Frankish A, Harrow J, Ghosh S, Sandelin A, Hofacker IL, Baertsch R, Keefe D, Dike S, Cheng J, Hirsch HA, Sekinger EA, Lagarde J, Abril JF, Shahab A, Flamm C, Fried C, Hackermüller J, Hertel J, Lindemeyer M, Missal K, Tanzer A, Washietl S, Korbel J, Emanuelsson O, Pedersen JS, Holroyd N, Taylor R, Swarbreck D, Matthews N, Dickson MC, Thomas DJ, Weirauch MT, Gilbert J, Drenkow J, Bell I, Zhao X, Srinivasan KG, Sung WK, Ooi HS, Chiu KP, Foissac S, Alioto T, Brent M, Pachter L, Tress ML, Valencia A, Choo SW, Choo CY, Ucla C, Manzano C, Wyss C, Cheung E, Clark TG, Brown JB, Ganesh M, Patel S, Tammana H, Chrast J, Henrichsen CN, Kai C, Kawai J, Nagalakshmi U, Wu J, Lian Z, Lian J, Newburger P, Zhang X, Bickel P, Mattick JS, Carninci P, Hayashizaki Y, Weissman S, Hubbard T, Myers RM, Rogers J, Stadler PF, Lowe TM, Wei CL, Ruan Y, Struhl K, Gerstein M, Antonarakis SE, Fu Y, Green ED, Karaöz U, Siepel A, Taylor J, Liefer LA, Wetterstrand KA, Good PJ, Feingold EA, Guyer MS, Cooper GM, Asimenos G, Dewey CN, Hou M, Nikolaev S, Montoya-Burgos JI, Löytynoja A, Whelan S, Pardi F, Massingham T, Huang H, Zhang NR, Holmes I, Mullikin JC, Ureta-Vidal A, Paten B, Seringhaus M, Church D, Rosenbloom K, Kent WJ, Stone EA, Batzoglou S, Goldman N, Hardison RC, Haussler D, Miller W, Sidow A, Trinklein ND, Zhang ZD, Barrera L, Stuart R, King DC, Ameur A, Enroth S, Bieda MC, Kim J, Bhinge AA, Jiang N, Liu J, Yao F, Vega VB, Lee CWH, Ng P, Shahab A, Yang A, Moqtaderi Z, Zhu Z, Xu X, Squazzo S, Oberley MJ, Inman D, Singer MA, Richmond TA, Munn KJ, Rada-Iglesias A, Wallerman O, Komorowski J, Fowler JC, Couttet P, Bruce AW, Dovey OM, Ellis PD, Langford CF, Nix DA, Euskirchen G, Hartman S, Urban AE, Kraus P, Van Calcar S, Heintzman N, Kim TH, Wang K, Qu C, Hon G, Luna R, Glass CK, Rosenfeld MG, Aldred SF, Cooper SJ, Halees A, Lin JM, Shulha HP, Zhang X, Xu M, Haidar JNS, Yu Y, Ruan Y, Iyer VR, Green RD, Wadelius C, Farnham PJ, Ren B, Harte RA, Hinrichs AS, Trumbower H, Clawson H, Hillman-Jackson J, Zweig AS, Smith K, Thakkapallayil A, Barber G, Kuhn RM, Karolchik D, Armengol L, Bird CP, de Bakker PIW, Kern AD, Lopez-Bigas N, Martin JD, Stranger BE, Woodroffe A, Davydov E, Dimas A, Eyras E, Hallgrímsdóttir IB, Huppert J, Zody MC, Abecasis GR, Estivill X, Bouffard GG, Guan X, Hansen NF, Idol JR, Maduro VVB, Maskeri B, McDowell JC, Park M, Thomas PJ, Young AC, Blakesley RW, Muzny DM, Sodergren E, Wheeler DA, Worley KC, Jiang H, Weinstock GM, Gibbs RA, Graves T, Fulton R, Mardis ER, Wilson RK, Clamp M, Cuff J, Gnerre S, Jaffe DB, Chang JL, Lindblad-Toh K, Lander ES, Koriabine M, Nefedov M, Osoegawa K, Yoshinaga Y, Zhu B, de Jong PJ. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 2007; 447:799-816. [PMID: 17571346 PMCID: PMC2212820 DOI: 10.1038/nature05874] [Citation(s) in RCA: 3782] [Impact Index Per Article: 222.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
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Sabo PJ, Kuehn MS, Thurman R, Johnson BE, Johnson EM, Cao H, Yu M, Rosenzweig E, Goldy J, Haydock A, Weaver M, Shafer A, Lee K, Neri F, Humbert R, Singer MA, Richmond TA, Dorschner MO, McArthur M, Hawrylycz M, Green RD, Navas PA, Noble WS, Stamatoyannopoulos JA. Genome-scale mapping of DNase I sensitivity in vivo using tiling DNA microarrays. Nat Methods 2006; 3:511-8. [PMID: 16791208 DOI: 10.1038/nmeth890] [Citation(s) in RCA: 273] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2006] [Accepted: 05/22/2006] [Indexed: 11/09/2022]
Abstract
Localized accessibility of critical DNA sequences to the regulatory machinery is a key requirement for regulation of human genes. Here we describe a high-resolution, genome-scale approach for quantifying chromatin accessibility by measuring DNase I sensitivity as a continuous function of genome position using tiling DNA microarrays (DNase-array). We demonstrate this approach across 1% ( approximately 30 Mb) of the human genome, wherein we localized 2,690 classical DNase I hypersensitive sites with high sensitivity and specificity, and also mapped larger-scale patterns of chromatin architecture. DNase I hypersensitive sites exhibit marked aggregation around transcriptional start sites (TSSs), though the majority mark nonpromoter functional elements. We also developed a computational approach for visualizing higher-order features of chromatin structure. This revealed that human chromatin organization is dominated by large (100-500 kb) 'superclusters' of DNase I hypersensitive sites, which encompass both gene-rich and gene-poor regions. DNase-array is a powerful and straightforward approach for systematic exposition of the cis-regulatory architecture of complex genomes.
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Affiliation(s)
- Peter J Sabo
- Department of Genome Sciences, University of Washington, 1705 NE Pacific St., Box 357730, Seattle, Washington 98195, USA
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Mann TP, Humbert R, Stamatoyannopolous JA, Noble WS. AUTOMATED VALIDATION OF POLYMERASE CHAIN REACTION AMPLICON MELTING CURVES. J Bioinform Comput Biol 2006; 4:299-315. [PMID: 16819785 DOI: 10.1142/s0219720006001989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2005] [Revised: 12/01/2005] [Accepted: 01/31/2006] [Indexed: 11/18/2022]
Abstract
The polymerase chain reaction (PCR) is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for determination of DNA copy numbers, quantitating transcription, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses is the current requirement for manual validation of individual PCRs to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation ("melting") curves of individual PCRs — a time-consuming and costly process. Here we describe a robust computational solution to this fundamental problem. Using a training set of 10 080 reactions comprising multiple quantitative PCRs from each of 1728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCRs with better than 99% accuracy. This approach has broad utility, and eliminates a major bottleneck to widespread application of PCR for high-throughput genomic applications.
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Affiliation(s)
- Tobias P Mann
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
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15
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Danchin N, Kadri Z, Cambou JP, Hanania G, Humbert R, Clerson P, Vaur L, Guéret P, Blanchard D, Genès N, Lablanche JM. [Management of patients admitted for acute myocardial infarction in France from 1995 to 2000: time to admission dependent improvement in outcome]. Arch Mal Coeur Vaiss 2005; 98:1149-54. [PMID: 16379113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
The in-hospital management and short- and long-term outcomes was assessed in 2 registries of consecutive patients admitted for acute myocardial infarction, 5 years apart, in France. The 2000 cohort was younger and with a less frequent history of cardiac diseases, but was more often diabetic and with anterior infarcts. Time to admission was actually longer in 2000 than in 1995 (median 5.25 hours vs 4.00 hours). Overall, reperfusion therapy was used in 43% of the patients in both registries. However, the use of reperfusion therapy increased from 1995 to 2000 in patients admitted within 6 hours of symptom onset (64 vs 58%), with an increasing use of primary angioplasty (from 12 to 30%). Five-day mortality significantly improved from 7.7 to 6.1% (p < 0.03) and one-year survival was also less in the most recent period (85 vs 81%, p < 0.01). Multivariate analyses showed that the period of inclusion (2000 vs 1995) was an independent predictor of both short- and long-term mortality in patients admitted within 6 hours of symptom onset. Thus, in the real world setting, a continued decline in one-year mortality was observed in patients admitted to intensive care units for recent acute myocardial infarction, especially for patients admitted early. This goes along with a shift in reperfusion therapy towards a broader use of primary angioplasty, and with an increased use of the early prescription of recognised secondary prevention medications.
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Affiliation(s)
- N Danchin
- Cardiologie, Hôpital européen Georges Pompidou , Leblanc, Paris.
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16
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Mann TP, Humbert R, Stamatoyannopolous JA, Noble WS. Automated validation of polymerase chain reactions using amplicon melting curves. Proc IEEE Comput Syst Bioinform Conf 2005:377-85. [PMID: 16447995 DOI: 10.1109/csb.2005.17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
PCR, the polymerase chain reaction, is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for determination of DNA copy numbers, quantitating transcription, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses is the current requirement for manual validation of individual PCR reactions to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation ("melting") curves of individual PCR reactions - a time-consuming and costly process. Here we describe a robust computational solution to this fundamental problem. Using a training set of 10,080 reactions comprising multiple quantitative PCR reactions from each of 1,728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCR reactions with better than 99% accuracy. This approach has broad utility, and eliminates a major bottleneck to widespread application of PCR for high-throughput genomic applications.
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Affiliation(s)
- Tobias P Mann
- Department of Genome Science, University of Washington, Seattle, WA, USA
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17
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Hanania G, Cambou JP, Guéret P, Vaur L, Blanchard D, Lablanche JM, Boutalbi Y, Humbert R, Clerson P, Genès N, Danchin N. Management and in-hospital outcome of patients with acute myocardial infarction admitted to intensive care units at the turn of the century: results from the French nationwide USIC 2000 registry. Heart 2004; 90:1404-10. [PMID: 15547013 PMCID: PMC1768566 DOI: 10.1136/hrt.2003.025460] [Citation(s) in RCA: 89] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/18/2003] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVE To assess actual practices and in-hospital outcome of patients with acute myocardial infarction on a nationwide scale. METHODS Of 443 intensive care units in France, 369 (83%) prospectively collected data on all cases of infarction (within < 48 hours of symptom onset) in November 2000. RESULTS 2320 patients (median age 68 years, 73% men) were included, of whom 83% had ST segment elevation infarction (STEMI). Patients without STEMI were older and had a more frequent history of cardiovascular disease. Median time to admission was 5.0 hours for patients with and 6.5 hours for those without STEMI. Reperfusion therapy was used for 53% of patients with STEMI (thrombolysis 28%, primary angioplasty 25%). In-hospital mortality was 8.7% (5.5% of patients without and 9.3% of those with STEMI). Multivariate analysis found that age, Killip class, lower blood pressure, higher heart rate on admission, anterior location of infarct, STEMI, diabetes mellitus, previous stroke, and no current smoking independently predicted in-hospital mortality. At hospital discharge, 95% received antiplatelet agents, 75% received beta blockers, and over 60% received statins. Angiotensin converting enzyme inhibitors were prescribed for 40% of the patients without and 52% of those with ST elevation. CONCLUSIONS This nationwide registry, including all types of centres irrespective of their size and experience, shows continued improvement in patient care and outcomes. Time from symptom onset to admission, however, has not improved in recent years and reperfusion therapy is used for just over 50% of patients with STEMI, with an increasing use of primary angioplasty.
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Dorschner MO, Hawrylycz M, Humbert R, Wallace JC, Shafer A, Kawamoto J, Mack J, Hall R, Goldy J, Sabo PJ, Kohli A, Li Q, McArthur M, Stamatoyannopoulos JA. High-throughput localization of functional elements by quantitative chromatin profiling. Nat Methods 2004; 1:219-25. [PMID: 15782197 DOI: 10.1038/nmeth721] [Citation(s) in RCA: 109] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2004] [Accepted: 10/19/2004] [Indexed: 11/08/2022]
Abstract
Identification of functional, noncoding elements that regulate transcription in the context of complex genomes is a major goal of modern biology. Localization of functionality to specific sequences is a requirement for genetic and computational studies. Here, we describe a generic approach, quantitative chromatin profiling, that uses quantitative analysis of in vivo chromatin structure over entire gene loci to rapidly and precisely localize cis-regulatory sequences and other functional modalities encoded by DNase I hypersensitive sites. To demonstrate the accuracy of this approach, we analyzed approximately 300 kilobases of human genome sequence from diverse gene loci and cleanly delineated functional elements corresponding to a spectrum of classical cis-regulatory activities including enhancers, promoters, locus control regions and insulators as well as novel elements. Systematic, high-throughput identification of functional elements coinciding with DNase I hypersensitive sites will substantially expand our knowledge of transcriptional regulation and should simplify the search for noncoding genetic variation with phenotypic consequences.
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Affiliation(s)
- Michael O Dorschner
- Department of Molecular Biology, Regulome, 2211 Elliott Avenue, Suite 600, Seattle, Washington 98121, USA
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Sabo PJ, Hawrylycz M, Wallace JC, Humbert R, Yu M, Shafer A, Kawamoto J, Hall R, Mack J, Dorschner MO, McArthur M, Stamatoyannopoulos JA. Discovery of functional noncoding elements by digital analysis of chromatin structure. Proc Natl Acad Sci U S A 2004; 101:16837-42. [PMID: 15550541 PMCID: PMC534745 DOI: 10.1073/pnas.0407387101] [Citation(s) in RCA: 116] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
We developed a quantitative methodology, digital analysis of chromatin structure (DACS), for high-throughput, automated mapping of DNase I-hypersensitive sites and associated cis-regulatory sequences in the human and other complex genomes. We used 19/20-bp genomic DNA tags to localize individual DNase I cutting events in nuclear chromatin and produced approximately 257,000 tags from erythroid cells. Tags were mapped to the human genome, and a quantitative algorithm was applied to discriminate statistically significant clusters of independent DNase I cutting events. We show that such clusters identify both known regulatory sequences and previously unrecognized functional elements across the genome. We used in silico simulation to demonstrate that DACS is capable of efficient and accurate localization of the majority of DNase I-hypersensitive sites in the human genome without requiring an independent validation step. A unique feature of DACS is that it permits unbiased evaluation of the chromatin state of regulatory sequences from widely separated genomic loci. We found surprisingly large differences in the accessibility of distant regulatory sequences, suggesting the existence of a hierarchy of nuclear organization that escapes detection by conventional chromatin assays.
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Affiliation(s)
- Peter J Sabo
- Department of Molecular Biology, Regulome, 2211 Elliott Avenue, Suite 600, Seattle, WA 98121, USA
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20
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Sabo PJ, Humbert R, Hawrylycz M, Wallace JC, Dorschner MO, McArthur M, Stamatoyannopoulos JA. Genome-wide identification of DNaseI hypersensitive sites using active chromatin sequence libraries. Proc Natl Acad Sci U S A 2004; 101:4537-42. [PMID: 15070753 PMCID: PMC384782 DOI: 10.1073/pnas.0400678101] [Citation(s) in RCA: 112] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Comprehensive identification of sequences that regulate transcription is one of the major goals of genome biology. Focal alteration in chromatin structure in vivo, detectable through hypersensitivity to DNaseI and other nucleases, is the sine qua non of a diverse cast of transcriptional regulatory elements including enhancers, promoters, insulators, and locus control regions. We developed an approach for genome-scale identification of DNaseI hypersensitive sites (HSs) via isolation and cloning of in vivo DNaseI cleavage sites to create libraries of active chromatin sequences (ACSs). Here, we describe analysis of >61,000 ACSs derived from erythroid cells. We observed peaks in the density of ACSs at the transcriptional start sites of known genes at non-gene-associated CpG islands, and, to a lesser degree, at evolutionarily conserved noncoding sequences. Peaks in ACS density paralleled the distribution of DNaseI HSs. ACSs and DNaseI HSs were distributed between both expressed and nonexpressed genes, suggesting that a large proportion of genes reside within open chromatin domains. The results permit a quantitative approximation of the distribution of HSs and classical cis-regulatory sequences in the human genome.
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Affiliation(s)
- Peter J Sabo
- Department of Molecular Biology, Regulome, Canal View Building, 551 North 34th Street, Seattle, WA 98103, USA
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Cambou JP, Danchin N, Boutalbi Y, Hanania G, Humbert R, Clerson P, Vaur L, Guéret P, Blanchard D, Genès N, Lablanche JM. Évolution de la prise en charge et du pronostic de l'infarctus du myocarde en France entre 1995 et 2000 : résultats des études USIK 1995 et USIC 2000Evolution of the management and outcomes of patients admitted for acute myocardial infarction in France from 1995 to 2000: data from the USIK 1995 and USIC 2000 nationwide registries. Ann Cardiol Angeiol (Paris) 2004; 53:12-7. [PMID: 15038522 DOI: 10.1016/s0003-3928(03)00201-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
We assessed the in-hospital management and short- and long-term outcomes of two series of patients admitted for acute myocardial infarction, 5 years apart, in France. The most recent cohort was younger and with a less frequent history of cardiac diseases, but was more often diabetic and with anterior infarcts. Five-day mortality significantly improved from 7.7% to 6.1% (P < 0.03) and 1-year survival was also less in the most recent period (15% versus 19%, P < 0.01). Multivariate analyses showed that the period of inclusion (2000 versus 1995) was an independent predictor of both short- and long-term mortality. In analyses restricted to the patients who were alive by day 5, initial treatment with statins was associated with a 38% decrease in the risk of death at 1 year. Likewise, in patients with left ventricular ejection fraction < or = 35%, the early prescription of ACE inhibitors was associated with a 41% reduction in the risk of 1-year mortality. Thus, in the real world setting, a continued decline in 1-year mortality is observed in patients admitted to intensive care units for recent acute myocardial infarction. This goes along with a shift in reperfusion therapy towards a broader use of coronary angioplasty and with an increased use of the early prescription of recognised secondary prevention medications.
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Affiliation(s)
- J P Cambou
- Service de cardiologie, hôpital européen Georges-Pompidou, 20, rue Leblanc, 75015 Paris, France
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22
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Ziégler M, de Broucker T, Damier P, Humbert R, Clerson P, Richard-Berthe C. [Handipark: a simple test of the impact of Parkinson's disease on activities of daily living]. Rev Neurol (Paris) 2003; 159:767-74. [PMID: 13679719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/23/2023]
Abstract
Handipark, a new score for measuring the impact of Parkinson's disease on daily life activities is presented. The global score ranging from 1 to 10 (without half points) is easy to determine. For a given patient, the score takes into account 5 items describing the global impact of the disease;Inter- and intra-observer reproducibility were determined. The reliability of the score was tested during two sessions separated by a 3-week interval. Five qualified neurologists scored 30 Parkinson's patients presented randomly for scoring using a semi-structured video-recorded interview. Intra-observer reproducibility was good (concordance coefficient; k=0.74, Spearman's correlation coefficient; r=0.88). Inter-observer reproducibility was also good: r=0.96 (first session), r=0.87 (second session); the agreement coefficient between the 5 observers was k=0.85 (first session), k=0.82 (second session). Distribution curves of the Hanipark score was described in 150 Parkinson's disease patients to study the correlation with items of other scales specific for Parkinson's disease (UPDRS, Hoehn & Yahr). A number significant correlations were found. Handipark is a reliable tool easy to use in clinical practice by a large panel of physicians caring for Parkinson's disease patients to assess the impact of Parkinson's disease. Further studies are needed to assess its usefulness for the follow-up of patients and assess the therapeutic impact.
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Affiliation(s)
- M Ziégler
- Service de Neurologie, Hôpital Léopold Bellan, Paris
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23
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Daniel F, Dreno B, Poli F, Auffret N, Beylot C, Bodokh I, Chivot M, Humbert P, Meynadier J, Clerson P, Humbert R, Berrou JP, Dropsy R. [Descriptive epidemiological study of acne on scholar pupils in France during autumn 1996]. Ann Dermatol Venereol 2000; 127:273-8. [PMID: 10804300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
BACKGROUND Acne is the most common symptom prompting patients to consult a dermatologist. No previous study has been conducted in France to determine the prevalence of acne and describe the main epidemiological features. SUBJECTS AND METHODS A cross sectional study was conducted in November 1996 and included 913 school children aged 11 to 18 years. This sample was statistically representative of the entire secondary school population in France during the 1996-1997 school year. The subjects were stratified by 5 criteria: age, sex, rural or urban residence, sun exposure, type of school. RESULTS Taking the clinical diagnosis made by the dermatologist investigator as the main criteria, the overall prevalence of acne was 72 p. 100. It was 76.1 p. 100 using the new ECLA grading system previously described. The prevalence of acne was sex and age dependent: highest scores were found for girls aged 14-16 years and for boys aged 16-17 years. Genetic factors were very important for the outcome of acne. Finally, 41 p. 100 of the acneic subjects were following a treatment, prescribed by a dermatologist in two-third of the cases. DISCUSSION These results are in agreement with those previously published in the literature although some differences were disclosed. It would appear important to distinguish between minimal acne with a few retentional pimples occuring during adolescence and severe acne (more than 20 pimples on the face) requiring early medical care to avoid scarring.
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Affiliation(s)
- F Daniel
- Groupe de Recherche et d'Etude sur l'Acné (GREA), Hôpital St-Joseph, 185, rue Raymond Losserand, 75014 Paris
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Goffinet F, Humbert R, Clerson P, Philippe HJ, Bréart G, Cabrol D. [National survey on the use of induced labor by obstetricians. Study Group on Induced Labor]. J Gynecol Obstet Biol Reprod (Paris) 1999; 28:319-29. [PMID: 10480062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
INTRODUCTION A strong rise in the use of induced labor has been observed in France. The aim of this work was to analyze the different methods used for achieving induction of labor and their implications. METHODS One out of four French obstetricians were randomly selected to answer a questionnaire on their practice for achieving induction of labor. Four hundred of the 997 obstetricians answered the questionnaire. Univariate and multivariate analysis was applied. RESULTS A high rate of induced labor was correlated with some areas of the country and with private practice. Certain methods were used in spite of opposing advice by experts in the field: elective induction of labor with unfavorable cervix, use of prostaglandins in elective induction of labor, induction of labor in cases of scarred uterus or breech presentation, use of misoprostol. Some methods were still used in spite of their poor efficacy: intravenous oxytocin used with unfavorable cervix, use of intravensou PGE2. CONCLUSION This study would show that theory and practice are often distinctly different. Induction of labor is currently used on a far wider scale than ever before. We obviously need studies for careful assessment of the circumstances in which induction of labor is used in order to improve methods and indications of such a clinical practice.
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Nevin DN, Zambon A, Furlong CE, Richter RJ, Humbert R, Hokanson JE, Brunzell JD. Paraoxonase genotypes, lipoprotein lipase activity, and HDL. Arterioscler Thromb Vasc Biol 1996; 16:1243-9. [PMID: 8857920 DOI: 10.1161/01.atv.16.10.1243] [Citation(s) in RCA: 63] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Paraxonase, an enzyme associated with the high density lipoprotein (HDL) particle, hydrolyzes paraoxon, the active metabolite of the insecticide parathion. Several studies have shown that paraxonase levels in humans have a distribution characteristic of two alleles, one with low activity and the other with high activity. Paraoxonase also has arylesterase activity, which does not exhibit activity polymorphism and can therefore serve as an estimate of enzyme protein. Although the ability of paraoxon to irreversibly inhibit lipoprotein lipase (LPL) has been exploited experimentally for many years, the role of plasma paraoxonase in lipoprotein metabolism is unknown. Seventy-two normal individuals were examined for paraoxonase genotypes, plasma paraoxonase and arylesterase activities, postheparin LPL and hepatic lipase (HL) activities, and lipoprotein levels to determine whether (1) paraoxonase activity or genotype determines lipoprotein levels via an effect on LPL or HL activity or (2) variation in LPL and HL activities determines HDL levels and indirectly affects paraoxonase activity and protein levels in plasma. In the entire group, paraoxonase activity was related to arylesterase activity and genotype. Whereas arylesterase activity was correlated with HDL cholesterol (HDL-C) and apolipoproteinA-I (apoA-I) levels, neither arylesterase nor paraoxonase was correlated with LPL or HL activity. Furthermore, LPL activity was positively correlated and HL inversely correlated with HDL cholesterol and apoA-I levels, whereas LPL was inversely correlated with triglyceride levels. The paraoxonase genotypes of the study group were 30 individuals homozygous for the low-activity allele, 38 heterozygotes, and 4 individuals homozygous for the high-activity allele. Paraoxonase genotype accounted for approximately .75 of the variation in paraoxonase activity. Paraoxonase activity was linearly related to arylesterase activity within each subgroup. No difference in either LPL or HL activity was seen as a function of paraoxonase genotype, nor were differences seen in plasma triglyceride or HDL-C by genotype by ANOVA. The relation between LPL and HL and components of HDL in the paraoxonase genotypic subgroups in general reflected the associations seen in the group as a whole. Multivariate analysis showed that LPL, HL, and arylesterase, a measure of paraoxonase mass, were independent predictors of HDL cholesterol, while paraoxonase genotype or activity was not. Thus, variation in LPL and HL appears to be significantly related to HDL cholesterol and apoA-I levels. The levels of HDL are a major correlate of paraoxonase protein levels, while paraoxonase genotype is the major predictor of plasma paraoxonase activity.
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Affiliation(s)
- D N Nevin
- Division of Metabolism, School of Public Health and Community Medicine, University of Washington 98195-6426, USA
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Abstract
Serum paraoxonase/arylesterase (PON) is an "A" esterase found in the HDL2 fraction of mammalian sera closely associated with apolipoproteins A1 and J. This enzyme hydrolyzes the active metabolites (oxons) of several organophosphate (OP) insecticides as well as the P-F bond of the nerve agents soman and sarin. PON also destroys biologically active, multioxygenated phospholipids. Two factors result in large individual variations in PON serum levels, a substrate-dependent activity polymorphism and large individual differences in PON protein levels that are stable over time. Animal model studies indicate that PON activity levels are likely to play a major role in determining sensitivity to OPs. The arg192 PON isoform appears to be a risk factor in coronary artery disease. We report here the characterization of a 28-kb contig encompassing 300 bp of 5' sequence, the entire coding region, and 2 kb of 3'-flanking sequence of the PON gene. The structural portion of the paraoxonase protein is encoded by nine exons that form the primary transcript through the use of typical splice donor and acceptor sites. DNA sequences of the regions surrounding all the coding exons have been determined. A polymorphic CA repeat is located in intron 4.
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Affiliation(s)
- J B Clendenning
- Department of Genetics, University of Washington, Seattle 98195, USA
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Elkohen M, Clerson P, Mounier-Véhier C, Gressin V, Humbert R, Carré A. [Effects of bisoprolol and ramipril on short-term variability of systolic blood pressure during mental stress test: spectrum analysis]. Arch Mal Coeur Vaiss 1995; 88:1075-80. [PMID: 8572849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
UNLABELLED The mid frequency component (MFC = 66-128 mHz) of blood pressure is an index of sympathetic vascular control. To investigate the effect of bisoprolol (B) and ramipril (R) treatment (TT) on the short-term variability of systolic blood pressure (SBP) diastolic blood pressure (DPB) and heart rate (HR) reactivity during mental stress, we studied 54 mild essential untreated hypertensive patients (24 men, 45 +/- 9.6 years, BP > 160/90 mmHg after a 15-days placebo run-in period) who were randomly assigned to double blind treatment (B: 10 mg/day: n = 28 and R: 5 mg/day: n = 26). A Stroop Word Color Conflict Test (SWCCT) was performed before and after 2 months of treatment. Hemodynamic parameters (BP and HR) were measured by a non invasive device (Finapres 2300E, Ohmeda-Maurepas) and underwent spectral analysis (SBP: mmHg.Hz-1/2, HR: beats/min.Hz-1/2, Anapres 1.2, Notocord-Orgametrie Systems, Igny-Lille) at rest and during SWCCT. The sympathetic vascular activity was assessed by calculating the area of the mid-frequency component (MFC = 66-128 Hz). RESULTS [table: see text] CONCLUSION The absolute variations in sympathetic activity during SWCCT as demonstrated by analysis of MFC of SBP and HR is not affected by chronic ramipril treatment, whereas bisoprolol attenuates sympathetic reactivity during SWCCT.
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Affiliation(s)
- M Elkohen
- Service de médecine interne et HTA, Hôpital cardiologique, CHRU de Lille
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Elkohen M, Clerson P, Mounier-Véhier CL, Humbert R, Prost PL, Poncelet P, Carré A. [Blood pressure variability and stimulation tests: value of the Stroop word color conflict test]. Arch Mal Coeur Vaiss 1994; 87:1073-1077. [PMID: 7755462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
OBJECTIVES To study the modifications of the BP and its short-term variability in hypertensives patients submitted at to a psychological stress test. DESIGN AND METHODS Fourty nine hypertensive subjects (27 women and 22 men, aged 46 +/- 9, SBP 164 +/- 10, DBP 97 +/- 6 mmHg after a 15 days placebo run-in period) were studied. We used the original version of Stroop Word Color Conflict Test (SWCCT) to induce mental stress. Haemodynamic parameters (SBP, DBP, MPB and HR) were measured continuously by a non invasive method (Finapres) with data acquisition every 0.5 second allowing spectral analysis of SBP variability at rest, during and after SWCCT (FFT algorithm on 256 point time series Anapres 1.2). RESULTS All haemodynamic parameters increased during stress test (p = 0.001). The mean value and the variability (V) of SBP standard deviation (SD) increased during SWCCT (p = 0.001 and p = 0.003 respectively). Two minutes after the test, SPB returned to the rest level, while the overall variability of SPB remained elevated (p = 0.007). Spectral analysis: the total area under the curve and the mid frequency component (MFC) (66-128 mHz) increased during and after SWCCT (p = 0.001). [table: see text] CONCLUSION Short-term variability of SBP is increased in hypertensives when submitted to a SWCCT appears to induce sustained orthosympathetic stimulation as suggested by the increase of mid frequency component (Mayer waves).
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Affiliation(s)
- M Elkohen
- Service de médecine-interne et HTA, Hôpital cardiologique, Lille
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Clerson P, Elkohen M, Mounier-Véhier C, Humbert R, Jouvent R, Prost PL, Carré A. [Stress, blood pressure reactivity and arterial hypertension: not an unambiguous relation]. Arch Mal Coeur Vaiss 1994; 87:1097-101. [PMID: 7755467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
UNLABELLED In order to determine the different ways the hypertensives' blood pressure would react during mental stress, 49 patients, 27 women and 22 men, were submitted at the Stroop Word Colour Conflict Test. Their haemodynamic parameters were recorded by finger photoplethysmography (Finapres device), with equidistant sampling (2 Hz). Temporal and spectral analysis showed evidence of: a quick and short elevation of BP and HR and a greater variability of SBP, as shown by the increase of the MF (66-128 mHZ) module. Patients can be divided into 3 clusters according to the reactivity of SBP. Group I (N, mean +/- sigma) 13, + 32.7 +/- 8 mmHg; group II 24, + 10.3 +/- 6; group III 12, -10.2 +/- 7. They were comparable on anxiety level and on any demographic and clinical feature. In group III, the higher NA at rest, the bigger the fall of SBP when stressed. The cognitive efficiency of these patients is increased by stress. Spectral analysis: Mid frequency (66-128 mHz) components are markedly higher in group III, before, during and after SWCCT showing a higher sympathetic tonus. CONCLUSION The reactivity of BP is not homogeneous. One fourth of our patients showed a decrease of SBP during the cognitive treatment stage of the test without showing a decrease of sympathetic tone. Anxiety level is not predictive of BP's response.
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Akers R, Alexander G, Allison J, Anderson KJ, Arcelli S, Asai S, Astbury A, Axen D, Azuelos G, Ball AH, Barlow RJ, Barnett S, Bartoldus R, Batley JR, Beaudoin G, Beck A, Beck GA, Becker J, Beeston C, Behnke T, Bell KW, Bella G, Bentkowski P, Berlich P, Bethke S, Biebel O, Bloodworth IJ, Bock P, Boden B, Bosch HM, Boutemeur M, Bright-Thomas P, Brown RM, Buijs A, Burckhart HJ, Burgard C, Capiluppi P, Carnegie RK, Carter AA, Carter JR, Chang CY, Charlesworth C, Charlton DG, Chu SL, Clarke PEL, Clayton JC, Cohen I, Conboy JE, Cooper M, Coupland M, Cuffiani M, Dado S, Dallapiccola C, Dallavalle GM, Darling C, Jong S, Pozo LA, Deng H, Dittmar M, Dixit MS, Couto e Silva E, Duboscq JE, Duchovni E, Duckeck G, Duerdoth IP, Dumas DJP, Elcombe PA, Estabrooks PG, Etzion E, Evans HG, Fabbri F, Fabbro B, Fierro M, Fincke-Keeler M, Fischer HM, Folman R, Fong DG, Foucher M, Fukui H, F�rtjes A, Gaidot A, Gary JW, Gascon J, Geddes NI, Geich-Gimbel C, Gensler SW, Gentit FX, Geralis T, Giacomelli G, Giacomelli P, Giacomelli R, Gibson V, Gibson WR, Gillies JD, Goldberg J, Gingrich DM, Goodrick MJ, Gorn W, Grandi C, Grant FC, Hagemann J, Hanson GG, Hansroul M, Hargrove CK, narrison PF, Hart J, Hart PA, Hattersley PM, Hauschild M, Hawkes CM, Heflin E, Hemingway RJ, Herten G, Heuer RD, Hill JC, Hillier SJ, Hilse T, Hinshaw DA, Hobson PR, Hochman D, Homer RJ, Honma AK, Hughes-Jones RE, Humbert R, Igo-Kemenes P, Ihssen H, Imrie DC, Jawahery A, Jeffreys PW, Jeremie H, Jimack M, Jones M, Jones RWL, Jovanovic P, Jui C, Karlen D, Kawagoe K, Kawamoto T, Keeler RK, Kellogg RG, Kennedy BW, King J, Kluth S, Kobayashi T, Kobel M, Koetke DS, Kokott TP, Komamiya S, Kowalewski R, Howard R, Krogh J, Kroll J, Kyberd P, Lafferty GD, Lafoux H, Lahmann R, Lauber J, Layter JG, Leblanc P, Du P, Lee AM, Lefebvre E, Lehto MH, Lellouch D, Leroy C, Letts J, Levinson L, Li Z, Lloyd SL, Loebinger FK, Long GD, Lorazo B, Losty MJ, Lou XC, Ludwig J, Luig A, Mannelli M, Marcellini S, Markus C, Martin AJ, Martin JP, Mashimo T, M�ttig P, Maur U, McKenna J, McMahon TJ, McNutt JR, Meijers F, Merritt FS, Mes H, Michelini A, Middleton RP, Mikenberg G, Mildenberger J, Miller DJ, Mir R, Mohr W, Moisan C, Montanari A, Mori T, Morii M, M�ller U, Nellen B, Nguyen HH, O'Neale SW, Oakham FG, Odorici F, Ogren HO, Oram CJ, Oreglia MJ, Orito S, Pansart JP, Paschievici P, Patrick GN, Pearce MJ, Pfister P, Pilcher JE, Pinfold J, Pitman D, Plane DE, Poffenberger P, Poli B, Pritchard TW, Przysiezniak H, Quast G, Redmond MW, Rees DL, Richards GE, Rison M, Robins SA, Robinson D, Rollnik A, Roney JM, Ros E, Rossberg S, Rossi AM, Rosvick M, Routenburg P, Runge K, Runolfsson O, Rust DR, Sasaki M, Sbarra C, Schaile AD, Schaile O, Scharf F, Scharff-Hansen P, Schenk P, Schmitt B, Schmitt H, Schr�der M, Schultz-Coulon HC, Sch�tz P, Schulz M, Schwick C, Schwiening J, Scott WG, Settles M, Shears TG, Shen BC, Shepherd-Themistocleous CH, Sherwood P, Siroli GP, Skillman A, Skuja A, Smith AM, Smith TJ, Snow GA, Sobie R, Springer RW, Sproston M, Stahl A, Stegmann C, Stephens K, Steuerer J, Str�hmer R, Strom D, Takeda H, Tarem S, Tecchio M, Teixeira-Dias P, Tesch N, Thomson MA, Torrente-Lujan E, Towers S, Tresilian NJ, Tsukamoto T, Turner MF, plas D, Kooten R, VanDalen GJ, Vasseur G, Vincter M, Wagner A, Wagner DL, Wahl C, Ward CP, Ward DR, Ward JJ, Watkins PM, Watson AT, Watson NK, Weber P, Wells PS, Wermes N, Wilkens B, Wilson GW, Wilson JA, Winterer VH, Wlodek T, Wolf G, Wotton S, Wyatt TR, Yaari R, Yeaman A, Yekutieli G, Yurko M, Zeuner W, Zorn GT. QCD studies using a cone-based jet finding algorithm fore + e ? collisons at LEP. ACTA ACUST UNITED AC 1994. [DOI: 10.1007/bf01411011] [Citation(s) in RCA: 63] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Kim US, Fujimoto BS, Furlong CE, Sundstrom JA, Humbert R, Teller DC, Schurr JM. Dynamics and structures of DNA: long-range effects of a 16 base-pair (CG)8 sequence on secondary structure. Biopolymers 1993; 33:1725-45. [PMID: 8241430 DOI: 10.1002/bip.360331110] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The effects of inserting 16 base pair (bp) of alternating CG [(CG)8] near the middle of a much longer restriction fragment (1097 bp) are investigated by measuring various properties that are sensitive to secondary and tertiary structure. Results for this fragment are compared with those for a control fragment (1089 bp) with the identical sequence except at the insert. Another fragment (1382 bp), which contains a 296-bp extension at the 5'-end of the 1089-bp control fragment, is also used as a secondary control in some experiments. When the 1097-bp (CG)8 insert fragment is compared with the control fragments in 0.1 M NaCl buffer, the (CG)8 insert is found to induce disproportionately large relative changes in the molar ellipticity at 273 nm ([theta]273), the torsion constant (alpha) measured by fluorescence polarization anisotropy, the optical melting profile, and the susceptibility to S1 nuclease. Estimates of the minimum distance over which the (CG)8 insert alters the secondary structure range from 330 to 550 bp. With increasing NaCl concentration, the 1097-bp insert fragment undergoes a structural transition between 2.0 and 2.5 M that is manifested in the apparent diffusion coefficient (Dplat) from dynamic light scattering at large scattering vector. This transition, which is not exhibited by the control DNAs, is presumed to involve formation of Z-helix at the insert. However, the observed decrease in (Dplat) is attributed to an increase in bending rigidity, which perforce must be globally distributed far beyond the (CG)8 insert per se. In 4.25 M NaCl (but not in 0.1 M NaCl), the addition of 1 ethidium dye per 300 bp induces an extensive structural transition in the 1097 bp (CG)8 insert fragment. This transition, which also is not exhibited by the control DNAs, significantly decreases the bending rigidity, doubles [theta]273, and takes place on a time scale of a few days. Removal of ethidium and salt by dialysis vs 0.1 M NaCl buffer restores the original properties of the 1097-bp (CG)8 insert fragment. The present results are consistent with a (fluctuating, long-range) description of the secondary structure in which a given short sequence transiently fluctuates among two or more distinct secondary structures that extend over much larger domains of variable position and size, and whose relative stabilities depend on distant as well as close-lying base pairs.
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Affiliation(s)
- U S Kim
- Department of Chemistry, University of Washington, Seattle 98195
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Abstract
The organophosphate cholinesterase inhibitor paraoxon is hydrolysed by serum paraoxonase/arylesterase. A genetic polymorphism of paraoxonase (PON) activity which determines high versus low paraoxon hydrolysis in human populations, may determine sensitivity to parathion poisoning. We demonstrate that arginine at position 192 specifies high activity PON whereas a glutamine specifies the low activity variant. Allele-specific probes or restriction enzyme analysis of amplified DNA allow for the genotyping of individuals. PON maps to chromosome 7q21-22, proximal to the cystic fibrosis gene, in agreement with previous genetic linkage studies.
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Affiliation(s)
- R Humbert
- Department of Genetics, University of Washington, Seattle 98195
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Hassett C, Richter RJ, Humbert R, Chapline C, Crabb JW, Omiecinski CJ, Furlong CE. Characterization of cDNA clones encoding rabbit and human serum paraoxonase: the mature protein retains its signal sequence. Biochemistry 1991; 30:10141-9. [PMID: 1657140 DOI: 10.1021/bi00106a010] [Citation(s) in RCA: 188] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Serum paraoxonase hydrolyzes the toxic metabolites of a variety of organophosphorus insecticides. High serum paraoxonase levels appear to protect against the neurotoxic effects of organophosphorus substrates of this enzyme [Costa et al. (1990) Toxicol. Appl. Pharmacol. 103, 66-76]. The amino acid sequence accounting for 42% of rabbit paraoxonase was determined by (1) gas-phase sequencing of the intact protein and (2) peptide fragments from lysine and arginine digests. From these data, two oligonucleotide probes were synthesized and used to screen a rabbit liver cDNA library. A clone was isolated and sequenced, and contained a 1294-bp insert encoding an open reading frame of 359 amino acids. Northern blot hybridization with RNA isolated from various rabbit tissues indicated that paraoxonase mRNA is synthesized predominately, if not exclusively, in the liver. Southern blot experiments suggested that rabbit paraoxonase is coded by a single gene and is not a family member of closely related genes. Human paraoxonase clones were isolated from a liver cDNA library by using the rabbit cDNA as a hybridization probe. Inserts from three of the longest clones were sequenced, and one full-length clone contained an open reading frame encoding 355 amino acids, four less than the rabbit paraoxonase protein. Each of the human clones appeared to be polyadenylated at a different site, consistent with the absence of the canonical polyadenylation signal sequence. Of potential significance with respect to the paraoxonase polymorphism, the derived amino acid sequence from one of the partial human cDNA clones differed at two positions from the full-length clone. Amino-terminal sequences derived from purified rabbit and human paraoxonase proteins suggested that the signal sequence is retained, with the exception of the initiator methionine residue [Furlong et al. (1991) Biochemistry (preceding paper in this issue)]. Characterization of the rabbit and human paraoxonase cDNA clones confirms that the signal sequences are not processed, except for the N-terminal methionine residue. The rabbit and human cDNA clones demonstrate striking nucleotide and deduced amino acid similarities (greater than 85%), suggesting an important metabolic role and constraints on the evolution of this protein.
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Affiliation(s)
- C Hassett
- Department of Environmental Health, School of Public Health and Community Medicine, University of Washington, Seattle 98195
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Akrawy MZ, Alexander G, Allison J, Allport PP, Anderson KJ, Armitage JC, Arnison GTJ, Ashton P, Azuelos G, Baines JTM, Ball AH, Banks J, Barker GJ, Barlow RJ, Batley JR, Beck A, Becker J, Behnke T, Bell KW, Bella G, Bethke S, Biebel O, Binder U, Bloodworth IJ, Bock P, Breuker H, Brown RM, Brun R, Buijs A, Burckhart HJ, Capiluppi P, Carnegie RK, Carter AA, Carter JR, Chang CY, Charlton DG, Chrin JTM, Clarke PEL, Cohen I, Collins WJ, Conboy JE, Couch M, Coupland M, Cuffiani M, Dado S, Dallavalle GM, Debu P, Deninno MM, Dieckmann A, Dittmar M, Dixit MS, Duchovni E, Duerdoth IP, Dumas DJP, Elcombe PA, Estabrooks PG, Etzion E, Fabbri F, Farthouat P, Fischer HM, Fong DG, French MT, Fukunaga C, Gaidot A, Ganel O, Gary JW, Gascon J, Geddes NI, Gee CNP, Geich-Gimbel C, Gensler SW, Gentit FX, Giacomelli G, Gibson V, Gibson WR, Gillies JD, Goldberg J, Goodrick MJ, Gorn W, Granite D, Gross E, Grunhaus J, Hagedorn H, Hagemann J, Hansroul M, Hargrove CK, Harrus I, Hart J, Hattersley PM, Hauschild M, Hawkes CM, Heflin E, Hemingway RJ, Heuer RD, Hill JC, Hillier SJ, Ho C, Hobbs JD, Hobson PR, Hochman D, Holl B, Homer RJ, Hou SR, Howarth CP, Hughes-Jones RE, Humbert R, Igo-Kemenes P, Ihssen H, Imrie DC, Janissen L, Jawahery A, Jeffreys PW, Jeremie H, Jimack M, Jobes M, Jones RWL, Jovanovic P, Karlen D, Kawagoe K, Kawamoto T, Kellogg RG, Kennedy BW, Kleinwort C, Klem DE, Knop G, Kobayashi T, Kokott TP, K�pke L, Kowalewski R, Kreutzmann H, Kroll J, Kuwano M, Kyberd P, Lafferty GD, Lamarche F, Larson WJ, Layter JG, Du P, Leblanc P, Lee AM, Lehto MH, Lellouch D, Lennert P, Lessard L, Levinson L, Lloyd SL, Loebinger FK, Lorah JM, Lorazo B, Losty MJ, Ludwig J, Ma J, Macbeth AA, Mannelli M, Marcellini S, Maringer G, Martin AJ, Martin JP, Mashimo T, M�ttig P, Maur U, McMahon TJ, McNutt JR, Meijers F, Menszner D, Merritt FS, Mes H, Michelini A, Middleton RP, Mikenberg G, Mildenberger J, Miller DJ, Milstene C, Minowa M, Mohr W, Montanari A, Mori T, Moss MW, Murphy PG, Murray WJ, Nellen B, Nguyen HH, Nozaki M, O'Dowd AJP, O'Neale SW, O'Neill BP, Oakham FG, Odorici F, Ogg M, Oh H, Oreglia MJ, Orito S, Pansart JP, Patrick GN, Pawley SJ, Pfister P, Pilcher JE, Pinfold JL, Plane DE, Poli B, Pouladdej A, Prebys E, Pritchard TW, Quast G, Raab J, Redmond MW, Rees DL, Regimbald M, Riles K, Roach CM, Robins SA, Rollnik A, Roney JM, Rossberg S, Rossi AM, Routenburg P, Runge K, Runolfsson O, Sanghera S, Sansum RA, Sasaki M, Saunders BJ, Schaile AD, Schaile O, Schappert W, Scharff-Hansen P, Schreiber S, Schwarz J, Shapira A, Shen BC, Sherwood P, Simon A, Singh P, Siroli GP, Skuja A, Smith AM, Smith TJ, Snow GA, Springer RW, Sproston M, Stephens K, Stier HE, Stroehmer R, Strom D, Takeda H, Takeshita T, Taras P, Thackray NJ, Tsukamoto T, Turner MF, Tysarczyk-Niemeyer G, plas D, VanDalen GJ, Vasseur G, Virtue CJ, Schmitt H, Krogh J, Wagner A, Wahl C, Walker JP, Ward CP, Ward DR, Watkins PM, Watson AT, Watson NK, Weber M, Weisz S, Wells PS, Wermes N, Weymann M, Wilson GW, Wilson JA, Wingerter I, Winterer VH, Wood NC, Wotton S, Wuensch B, Wyatt TR, Yaari R, Yang Y, Yekutieli G, Yoshida T, Zeuner W, Zorn GT. A study of the recombination scheme dependence of jet production rates and of ? s ( $$M_{Z^0 } $$ ) in hadronicZ 0 decays. ACTA ACUST UNITED AC 1991. [DOI: 10.1007/bf01549689] [Citation(s) in RCA: 65] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Alexander G, Allison J, Allport PP, Anderson KJ, Arcelli S, Armitage JC, Ashton P, Astbury A, Axen D, Azuelos G, Bahan GA, Baines JTM, Ball AH, Banks J, Barker GJ, Barlow RJ, Batley JR, Beaudoin G, Beck A, Becker J, Behnke T, Bell KW, Bella G, Bethke S, Biebel O, Binder U, Bloodworth IJ, Bock P, Bosch HM, Bougerolle S, Brabson BB, Breuker H, Brown RM, Brun R, Buijs A, Burckhart HJ, Capiluppi P, Carnegie RK, Carter AA, Carter JR, Chang CY, Charlton DG, Chrin JTM, Clarke PEL, Cohen I, Collins WJ, Conboy JE, Cooper M, Couch M, Coupland M, Cuffiani M, Dado S, Dallavalle GM, Jong S, Debu P, Deninno MM, Dieckmann A, Dittmar M, Dixit MS, Duchovni E, Duckeck G, Duerdoth IP, Dumas DJP, Eckerlin G, Elcombe PA, Estabrooks PG, Etzion E, Fabbri F, Fincke-Keeler M, Fischer HM, Fong DG, Fukunaga C, Gaidot A, Ganel O, Gary JW, Gascon J, McGowan RF, Geddes NI, Geich-Gimbel C, Gensler SW, Gentit FX, Giacomelli G, Gibson V, Gibson WR, Gillies JD, Goldberg J, Goodrick MJ, Gorn W, Grandi C, Gross E, Hagemann J, Hanson GG, Hansroul M, Hargrove CK, Harrison PF, Hart J, Hattersley PM, Hauschild M, Hawkes CM, Heflin E, Hemingway RJ, Heuer RD, Hill JC, Hillier SJ, Hinshaw DA, Ho C, Hobbs JD, Hobson PR, Hochman D, Holl B, Homer RJ, Hou SR, Howarth CP, Hughes-Jones RE, Humbert R, Igo-Kemenes P, Ihssen H, Imrie DC, Janissen L, Jawahery A, Jeffreys PW, Jeremie H, Jimack M, Jobes M, Jones RWL, Jovanovic P, Karlen D, Kawagoe K, Kawamoto T, Keeler RK, Kellogg RG, Kennedy BW, Kleinwort C, Klem DE, Kobayashi T, Kokott TP, Komamiya S, Köpke L, Kowalewski R, Kreutzmann H, Krogh J, Kroll J, Kuwano M, Kyberd P, Lafferty GD, Lamarche F, Larson WJ, Layter JG, Du P, Leblanc P, Lee AM, Lehto MH, Lellouch D, Lennert P, Leroy C, Lessard L, Levegrün S, Levinson L, Lloyd SL, Loebinger FK, Lorah JM, Lorazo B, Losty MJ, Lou XC, Ludwig J, Mannelli M, Marcellini S, Maringer G, Martin AJ, Martin JP, Mashimo T, Mättig P, Maur U, McMahon TJ, McNutt JR, Meijers F, Menszner D, Merritt FS, Mes H, Michelini A, Middleton RP, Mikenberg G, Mildenberger J, Miller DJ, Milstene C, Mir R, Mohr W, Moisan C, Montanari A, Mori T, Moss MW, Mouthuy T, Murphy PG, Nellen B, Nguyen HH, Nozaki M, O'Neale SW, O'Neill BP, Oakham FG, Odorici F, Ogg M, Ogren HO, Oh H, Oram CJ, Oreglia MJ, Orito S, Pansart JP, Panzer-Steindel B, Paschievici P, Patrick GN, Pawley SJ, Pfister P, Pilcher JE, Pinfold JL, Plane DE, Poffenberger P, Poli B, Pouladdej A, Prebys E, Pritchard TW, Przysiezniak H, Quast G, Redmond MW, Rees DL, Riles K, Robins SA, Robinson D, Rollnik A, Roney JM, Rossberg S, Rossi AM, Routenburg P, Runge K, Runolfsson O, Rust DR, Sanghera S, Sasaki M, Schaile AD, Schaile O, Schappert W, Scharff-Hansen P, Schenk P, Schmitt H, Schreiber S, Schwarz J, Scott WG, Settles M, Shen BC, Sherwood P, Shypit R, Simon A, Singh P, Siroli GP, Skuja A, Smith AM, Smith TJ, Snow GA, Sobie R, Springer RW, Sproston M, Stephens K, Stier HE, Strom D, Takeda H, Takeshita T, Taras P, Tarem S, Teixeira-Dias P, Thackray NJ, Tsukamoto T, Turner MF, Tysarczyk-Niemeyer G, plas D, Kooten R, Dalen GJ, Vasseur G, Virtue CJ, Wagner A, Wahl C, Walker JP, Ward CP, Ward DR, Watkins PM, Watson AT, Watson NK, Weber M, Weisz S, Wells PS, Wermes N, Weymann M, Whalley MA, Wilson GW, Wilson JA, Wingerter I, Winterer VH, Wood NC, Wotton S, Wyatt TR, Yaari R, Yangh Y, Yekutieli G, Zacharov I, Zeuner W, Zorn GT. Measurement of theZ 0 line shape parameters and the electroweak couplings of charged leptons. ACTA ACUST UNITED AC 1991. [DOI: 10.1007/bf01560437] [Citation(s) in RCA: 26] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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O'Regan JK, Humbert R. Estimating psychometric functions in forced-choice situations: significant biases found in threshold and slope estimations when small samples are used. Percept Psychophys 1989; 46:434-42. [PMID: 2813028 DOI: 10.3758/bf03210858] [Citation(s) in RCA: 33] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
When a theoretical psychometric function is fitted to experimental data (as in the obtaining of a psychophysical threshold), maximum-likelihood or probit methods are generally used. In the present paper, the behavior of these curve-fitting methods is studied for the special case of forced-choice experiments, in which the probability of a subject's making a correct response by chance is not zero. A mathematical investigation of the variance of the threshold and slope estimators shows that, in this case, the accuracy of the methods is much worse, and their sensitivity to the way data are sampled is greater, than in the case in which chance level is zero. Further, Monte Carlo simulations show that, in practical situations in which only a finite number of observations are made, the mean threshold and slope estimates are significantly biased. The amount of bias depends on the curve-fitting method and on the range of intensity values, but it is always greater in forced-choice situations than when chance level is zero.
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Abstract
A strain of Escherichia coli which was derived from a gentamicin-resistant clinical isolate was found to be cross-resistant to neomycin and streptomycin. The molecular nature of the genetic defect was found to be an insertion of two GC base pairs in the uncG gene of the mutant. The insertion led to the production of a truncated gamma subunit of 247 amino acids in length instead of the 286 amino acids that are present in the normal gamma subunit. A plasmid which carried the ATP synthase genes from the mutant produced resistance to aminoglycoside antibiotics when it was introduced into a strain with a chromosomal deletion of the ATP synthase genes. Removal of the genes coding for the beta and epsilon subunits abolished antibiotic resistance coded by the mutant plasmid. The relationship between antibiotic resistance and the gamma subunit was investigated by testing the antibiotic resistance of plasmids carrying various combinations of unc genes. The presence of genes for the F0 portion of the ATP synthase in the presence or absence of genes for the gamma subunit was not sufficient to cause antibiotic resistance. alpha, beta, and truncated gamma subunits were detected on washed membranes of the mutant by immunoblotting. The first 247 amino acid residues of the gamma subunit may be sufficient to allow its association with other F1 subunits in such a way that the proton gate of F0 is held open by the mutant F1.
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Affiliation(s)
- R Humbert
- Department of Biological Sciences, Stanford University, California 94305-5020
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Abstract
The purpose of this study was to determine whether plasma oxytocin (OT) levels change during human sexual responses and, if so, to demonstrate the temporal pattern of change. Plasma OT levels were measured by RIA before, during, and after private self-stimulation to orgasm in normal men (n = 9) and women (n = 13). Blood samples were collected continuously through indwelling venous catheters. The subjects pressed a signal to indicate the start and finish of orgasm/ejaculation. Objective assessment of sexual arousal and orgasm was obtained by measuring blood-pulse amplitude and electromyographic activity, recorded continuously throughout testing from an anal device containing a photoplethysmograph and electromyograph electrodes connected to a polygraph located in an adjacent room. These measures allowed collection of data from men and women of changes in blood flow and muscle activity in the lower pelvic/pubic area. Plasma OT levels increased during sexual arousal in both women and men and were significantly higher during orgasm/ejaculation than during prior baseline testing. We suggest that the temporal pattern of secretion could be related to smooth muscle contractions of the reproductive system during orgasm.
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Abstract
Plasmids carrying cloned segments of the unc operon of Escherichia coli have been used in genetic complementation analyses to identify three independent mutants defective in the uncH gene, which codes for the delta subunit of the ATP synthetase. Mutations in other unc genes have also been mapped by this technique. ATPase activity was present in extracts of the uncH mutants, but the enzyme was not as tightly bound to the membrane as it was in the parental strain. ATP-dependent membrane energization was absent in membranes isolated from the uncH mutants and could not be restored by adding normal F1 ATPase from the wild-type strain. F1 ATPase prepared from uncH mutants could not restore ATP-dependent membrane energization when added to wild-type membranes depleted of F1. Membranes of the uncH mutants were not rendered proton permeable as a result of washing with low-ionic-strength buffer.
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Abstract
By injection into mice we assessed the potential for full development and oviposition of young schistosomules, juveniles, and paired adults of Schistosoma mansoni, all grown in vitro from cercariae. Schistosomules 2-hr or 13-days-old were injected into mice via the tail vein; older worms were implanted surgically into the ileocolic vein. Also implanted were previously ovigerous adult pairs that had been perfused from mice and maintained in culture up to 53 days. Eventually, all were capable of producing viable eggs except the worm-pairs that had been grown to the adult stage in vitro; these failed to grow or develop further when implanted into mice. We concluded that pairs once mature in vivo could regain the capacity for oviposition even after prolonged maintenance in vitro, but worms grown entirely in vitro to pairing may have missed some required stimulus which cannot be furnished later, even by an adequate animal host.
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Abstract
Genetic experiments have indicated that asparagine auxotrophs of Escherichias coli K-12 can be made asparagine prototrophs at either of two sites on the chromosome and that wild-type strains require both sites to be mutated to produce asparagine auxotrophy. The former asn locus is now called asnA, and the new gene is designated asnB. The asnB gene is located near gal.AsnA+ asnB and asnA asnB+ strains were constructed, and the asparagine synthetic reaction was characterized in extracts. These studies revealed that the asnA gene codes for the enzyme previously described (H. Cedar and J.H. Schwartz, J. Biol. Chem. 244: 4112-4121, 1969), whereas the asnB gene is involved in the production of an enzyme which differs from the one previously described in its specific activity in extracts, its stability at low and high temperatures, and its apparent ability to use either glutamine or ammonia as amide nitrogen donor. Physiological studies showed that either enzyme alone is sufficient to allow a maximal growth rate under conditions of asparagine limitation.
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Humbert R. Beitrag zur Frage der biologischen Heilungsmöglichkeit experimenteller Tuberkulose durch langdauernde INH-Therapie. Lung 1955. [DOI: 10.1007/bf02180112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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