A draft human pangenome reference

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more tha...

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Autores: Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian, Monlong, Jean, Marco Sola, Santiago|||0000-0001-7951-3914
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/425102
Acceso en línea:https://hdl.handle.net/2117/425102
https://dx.doi.org/10.1038/s41586-023-05896-x
Access Level:acceso abierto
Palabra clave:Genome assembly algorithms
Genome informatics
Genomics
Haplotypes
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
id ES_ea6ebc362bf1b14f6a044768b4c76576
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network_name_str España
repository_id_str
dc.title.none.fl_str_mv A draft human pangenome reference
title A draft human pangenome reference
spellingShingle A draft human pangenome reference
Liao, Wen-Wei
Genome assembly algorithms
Genome informatics
Genomics
Haplotypes
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
title_short A draft human pangenome reference
title_full A draft human pangenome reference
title_fullStr A draft human pangenome reference
title_full_unstemmed A draft human pangenome reference
title_sort A draft human pangenome reference
dc.creator.none.fl_str_mv Liao, Wen-Wei
Asri, Mobin
Ebler, Jana
Doerr, Daniel
Haukness, Marina
Hickey, Glenn
Lu, Shuangjia
Lucas, Julian
Monlong, Jean
Marco Sola, Santiago|||0000-0001-7951-3914
author Liao, Wen-Wei
author_facet Liao, Wen-Wei
Asri, Mobin
Ebler, Jana
Doerr, Daniel
Haukness, Marina
Hickey, Glenn
Lu, Shuangjia
Lucas, Julian
Monlong, Jean
Marco Sola, Santiago|||0000-0001-7951-3914
author_role author
author2 Asri, Mobin
Ebler, Jana
Doerr, Daniel
Haukness, Marina
Hickey, Glenn
Lu, Shuangjia
Lucas, Julian
Monlong, Jean
Marco Sola, Santiago|||0000-0001-7951-3914
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Genome assembly algorithms
Genome informatics
Genomics
Haplotypes
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
topic Genome assembly algorithms
Genome informatics
Genomics
Haplotypes
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
description Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119¿million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90¿million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01
2025
2025-02-27
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/425102
https://dx.doi.org/10.1038/s41586-023-05896-x
url https://hdl.handle.net/2117/425102
https://dx.doi.org/10.1038/s41586-023-05896-x
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Macmillan Publishers
publisher.none.fl_str_mv Macmillan Publishers
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
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spelling A draft human pangenome referenceLiao, Wen-WeiAsri, MobinEbler, JanaDoerr, DanielHaukness, MarinaHickey, GlennLu, ShuangjiaLucas, JulianMonlong, JeanMarco Sola, Santiago|||0000-0001-7951-3914Genome assembly algorithmsGenome informaticsGenomicsHaplotypesÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::BioinformàticaHere the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119¿million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90¿million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.This work was funded in part by the National Human Genome Research Institute of the National Institutes of Health under award numbers U41HG010972, 1U01HG010973, U41HG007234, 1R01HG011274, R01HG010485, U24HG010262 U01HG010963, U24HG007497 and R01HG011649. This work was funded in part by the National Institutes of Health under award numbers U01HG010961, OT2OD033761, U24HG011853, R01-HG006677, R35-GM130151, R01HG002385, R01HG010169, U01HG01973, 5U01HG010971, R01GM123489, U24HG009081 and 1ZIAHG200398. This work was funded in part by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health. The work of F.T.-N. and V.A.S. was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health. This work was funded in part by the USDA National Institute of Food and Agriculture, grant number 2018- 67015-28199, and the National Science Foundation (NSF), grant IOS-1744309, and NSF PPoSS award number 2118709 (E.G. and P.P.). This work was funded in part by the Natural Sciences and Engineering Research Council of Canada (NSERC). G.Bourque is supported by a Canada Research Chair Tier 1 award, a FRQ-S, Distinguished Research Scholar award and by the World Premier International Research Center Initiative (WPI), MEXT, Japan. J.S. was supported by the Carlsberg Foundation. This work was funded in part by intramural funding at the National Institute of Standards and Technology. E.E.E., D.H. and E.D.J. are investigators of the Howard Hughes Medical Institute. This work was funded in part by an Oxford Nanopore Research grant (SC20130149) awarded to M. Akeson, University of California Santa Cruz. This work was funded in part by Wellcome Trust award numbers WT104947/Z/14/Z, WT222155/Z/20/Z and WT108749/ Z/15/Z. This work was funded in part by a Juan de la Cierva fellowship grant (IJC2020-045916-I) funded by MCIN/AEI/ 10.13039/501100011033 and by the European Union NextGenerationEU/ PRTR. This work was funded in part by the Novo Nordisk Foundation (NNF21OC0069089). S.H. acknowledges funding from the Central Innovation Programme (ZIM) for SMEs of the Federal Ministry for Economic Affairs and Energy of Germany. This work was supported by the BMBF- funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) (031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D and 031A538A). This work was funded in part by the German Federal Ministry of Education and Research (BMBF) (031L0184A) and the European Commission, Innovative training network (ITN) (956229). W.-W.L. was supported in part by the Government Scholarship to Study Abroad (GSSA) from the Ministry of Education of Taiwan.Peer ReviewedArticle signat per 119 autors/es: Wen-Wei Liao 1,2,3,60 , Mobin Asri 4,60 , Jana Ebler 5,6,60 , Daniel Doerr 5,6 , Marina Haukness 4 , Glenn Hickey 4 , Shuangjia Lu 1,2 , Julian K. Lucas 4 , Jean Monlong 4 , Haley J. Abel 7 , Silvia Buonaiuto 8 , Xian H. Chang 4 , Haoyu Cheng 9,10 , Justin Chu 9 , Vincenza Colonna 8,11 , Jordan M. Eizenga 4 , Xiaowen Feng 9,10 , Christian Fischer 11 , Robert S. Fulton 12,13 , Shilpa Garg 14 , Cristian Groza 15 , Andrea Guarracino 11,16 , William T. Harvey 17 , Simon Heumos 18,19 , Kerstin Howe 20 , Miten Jain 21 , Tsung-Yu Lu 22 , Charles Markello 4 , Fergal J. Martin 23 , Matthew W. Mitchell 24 , Katherine M. Munson 17 , Moses Njagi Mwaniki 25 , Adam M. Novak 4 , Hugh E. Olsen 4 , Trevor Pesout 4 , David Porubsky 17 , Pjotr Prins 11 , Jonas A. Sibbesen 26 , Jouni Sirén 4 , Chad Tomlinson 12 , Flavia Villani 11 , Mitchell R. Vollger 17,27 , Lucinda L. Antonacci-Fulton 12 , Gunjan Baid 28 , Carl A. Baker 17 , Anastasiya Belyaeva 28 , Konstantinos Billis 23 , Andrew Carroll 28 , Pi-Chuan Chang 28 , Sarah Cody 12 , Daniel E. Cook 28 , Robert M. Cook-Deegan 29 , Omar E. Cornejo 30 , Mark Diekhans 4 , Peter Ebert 5,6,31 , Susan Fairley 23 , Olivier Fedrigo 32 , Adam L. Felsenfeld 33 , Giulio Formenti 32 , Adam Frankish 23 , Yan Gao 34 , Nanibaa’ A. Garrison 35,36,37 , Carlos Garcia Giron 23 , Richard E. Green 38,39 , Leanne Haggerty 23 , Kendra Hoekzema 17 , Thibaut Hourlier 23 , Hanlee P. Ji 40 , Eimear E. Kenny 41 , Barbara A. Koenig 42 , Alexey Kolesnikov 28 , Jan O. Korbel 23,43 , Jennifer Kordosky 17 , Sergey Koren 44 , HoJoon Lee 40 , Alexandra P. Lewis 17 , Hugo Magalhães 5,6 , Santiago Marco-Sola 45,46 , Pierre Marijon 5,6 , Ann McCartney 44 , Jennifer McDaniel 47 , Jacquelyn Mountcastle 32 , Maria Nattestad 28 , Sergey Nurk 44 , Nathan D. Olson 47 , Alice B. Popejoy 48 , Daniela Puiu 49 , Mikko Rautiainen 44 , Allison A. Regier 12 , Arang Rhie 44 , Samuel Sacco 30 , Ashley D. Sanders 50 , Valerie A. Schneider 51 , Baergen I. Schultz 33 , Kishwar Shafin 28 , Michael W. Smith 33 , Heidi J. Sofia 33 , Ahmad N. Abou Tayoun 52,53 , Françoise Thibaud-Nissen 51 , Francesca Floriana Tricomi 23 , Justin Wagner 47 , Brian Walenz 44 , Jonathan M. D. Wood 20 , Aleksey V. Zimin 49,54 , Guillaume Bourque 55,56,57 , Mark J. P. Chaisson 22 , Paul Flicek 23 , Adam M. Phillippy 44 , Justin M. Zook 47 , Evan E. Eichler 17,58 , David Haussler 4,58 , Ting Wang 12,13 , Erich D. Jarvis 32,58,59 , Karen H. Miga 4 , Erik Garrison 11 ✉, Tobias Marschall 5,6 ✉, Ira M. Hall 1,2 ✉, Heng Li 9,10 ✉ & Benedict Paten 4 ✉ / 1 Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. 2 Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA. 3 Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA. 4 Genomics Institute, University of California, Santa Cruz, CA, USA. 5 Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany. 6 Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany. 7 Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA. 8 Institute of Genetics and Biophysics, National Research Council, Naples, Italy. 9 Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA. 10 Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. 11 Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA. 12 McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. 13 Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. 14 Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark. 15 Quantitative Life Sciences, McGill University, Montréal, Québec, Canada. 16 Genomics Research Centre, Human Technopole, Milan, Italy. 17 Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA. 18 Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany. 19 Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, Germany. 20 Tree of Life, Wellcome Sanger Institute, Hinxton, Cambridge, UK. 21 Northeastern University, Boston, MA, USA. 22 Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. 23 European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK. 24 Coriell Institute for Medical Research, Camden, NJ, USA. 25 Department of Computer Science, University of Pisa, Pisa, Italy. 26 Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark. 27 Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA. 28 Google, Mountain View, CA, USA. 29 Barrett and O’Connor Washington Center, Arizona State University, Washington, DC, USA. 30 Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA. 31 Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany. 32 Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA. 33 National Institutes of Health (NIH)–National Human Genome Research Institute, Bethesda, MD, USA. 34 Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA. 35 Institute for Society and Genetics, College of Letters and Science, University of California, Los Angeles, CA, USA. 36 Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. 37 Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. 38 Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA. 39 Dovetail Genomics, Scotts Valley, CA, USA. 40 Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA. 41 Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 42 Program in Bioethics and Institute for Human Genetics, University of California, San Francisco, CA, USA. 43 Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. 44 Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA. 45 Computer Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain. 46 Departament d’Arquitectura de Computadors i Sistemes Operatius, Universitat Autònoma de Barcelona, Barcelona, Spain. 47 Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. 48 Department of Public Health Sciences, University of California, Davis, CA, USA. 49 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. 50 Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany. 51 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. 52 Al Jalila Genomics Center of Excellence, Al Jalila Children’s Specialty Hospital, Dubai, UAE. 53 Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE. 54 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA. 55 Department of Human Genetics, McGill University, Montréal, Québec, Canada. 56 Canadian Center for Computational Genomics, McGill University, Montréal, Québec, Canada. 57 Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan. 58 Howard Hughes Medical Institute, Chevy Chase, MD, USA. 59 Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA.Macmillan Publishers20232023-01-0120252025-02-27journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/425102https://dx.doi.org/10.1038/s41586-023-05896-xreponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4251022026-05-27T15:37:01Z
score 15,812429

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