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English AC, Dolzhenko E, Ziaei Jam H, McKenzie SK, Olson ND, De Coster W, Park J, Gu B, Wagner J, Eberle MA, Gymrek M, Chaisson MJP, Zook JM, Sedlazeck FJ. Analysis and benchmarking of small and large genomic variants across tandem repeats. Nat Biotechnol 2024:10.1038/s41587-024-02225-z. [PMID: 38671154 DOI: 10.1038/s41587-024-02225-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 03/28/2024] [Indexed: 04/28/2024]
Abstract
Tandem repeats (TRs) are highly polymorphic in the human genome, have thousands of associated molecular traits and are linked to over 60 disease phenotypes. However, they are often excluded from at-scale studies because of challenges with variant calling and representation, as well as a lack of a genome-wide standard. Here, to promote the development of TR methods, we created a catalog of TR regions and explored TR properties across 86 haplotype-resolved long-read human assemblies. We curated variants from the Genome in a Bottle (GIAB) HG002 individual to create a TR dataset to benchmark existing and future TR analysis methods. We also present an improved variant comparison method that handles variants greater than 4 bp in length and varying allelic representation. The 8.1% of the genome covered by the TR catalog holds ~24.9% of variants per individual, including 124,728 small and 17,988 large variants for the GIAB HG002 'truth-set' TR benchmark. We demonstrate the utility of this pipeline across short-read and long-read technologies.
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Affiliation(s)
- Adam C English
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
| | | | - Helyaneh Ziaei Jam
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | | | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Applied and Translational Neurogenomics Group, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jonghun Park
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Bida Gu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, Houston, TX, USA.
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2
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Hickey G, Monlong J, Ebler J, Novak AM, Eizenga JM, Gao Y, Marschall T, Li H, Paten B, Abel HJ, Antonacci-Fulton LL, Asri M, Baid G, Baker CA, Belyaeva A, Billis K, Bourque G, Buonaiuto S, Carroll A, Chaisson MJP, Chang PC, Chang XH, Cheng H, Chu J, Cody S, Colonna V, Cook DE, Cook-Deegan RM, Cornejo OE, Diekhans M, Doerr D, Ebert P, Ebler J, Eichler EE, Eizenga JM, Fairley S, Fedrigo O, Felsenfeld AL, Feng X, Fischer C, Flicek P, Formenti G, Frankish A, Fulton RS, Gao Y, Garg S, Garrison E, Garrison NA, Giron CG, Green RE, Groza C, Guarracino A, Haggerty L, Hall IM, Harvey WT, Haukness M, Haussler D, Heumos S, Hickey G, Hoekzema K, Hourlier T, Howe K, Jain M, Jarvis ED, Ji HP, Kenny EE, Koenig BA, Kolesnikov A, Korbel JO, Kordosky J, Koren S, Lee H, Lewis AP, Li H, Liao WW, Lu S, Lu TY, Lucas JK, Magalhães H, Marco-Sola S, Marijon P, Markello C, Marschall T, Martin FJ, McCartney A, McDaniel J, Miga KH, Mitchell MW, Monlong J, Mountcastle J, Munson KM, Mwaniki MN, Nattestad M, Novak AM, Nurk S, Olsen HE, Olson ND, Paten B, Pesout T, Phillippy AM, Popejoy AB, Porubsky D, Prins P, Puiu D, Rautiainen M, Regier AA, Rhie A, Sacco S, Sanders AD, Schneider VA, Schultz BI, Shafin K, Sibbesen JA, Sirén J, Smith MW, Sofia HJ, Tayoun ANA, Thibaud-Nissen F, Tomlinson C, Tricomi FF, Villani F, Vollger MR, Wagner J, Walenz B, Wang T, Wood JMD, Zimin AV, Zook JM. Pangenome graph construction from genome alignments with Minigraph-Cactus. Nat Biotechnol 2024; 42:663-673. [PMID: 37165083 PMCID: PMC10638906 DOI: 10.1038/s41587-023-01793-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [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: 10/06/2022] [Accepted: 04/18/2023] [Indexed: 05/12/2023]
Abstract
Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome.
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Affiliation(s)
- Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- These authors contributed equally: Glenn Hickey, Jean Monlong
| | - Jean Monlong
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- These authors contributed equally: Glenn Hickey, Jean Monlong
| | - Jana Ebler
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Adam M. Novak
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Jordan M. Eizenga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Yan Gao
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Haley J. Abel
- Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Carl A. Baker
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Canadian Center for Computational Genomics, McGill University, Montreal, QC, Canada
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Silvia Buonaiuto
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
| | | | - Mark J. P. Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | | | - Xian H. Chang
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Justin Chu
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sarah Cody
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Vincenza Colonna
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - Robert M. Cook-Deegan
- Arizona State University, Barrett and O’Connor Washington Center, Washington, DC, USA
| | - Omar E. Cornejo
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Daniel Doerr
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Peter Ebert
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jana Ebler
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Jordan M. Eizenga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Susan Fairley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Olivier Fedrigo
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Adam L. Felsenfeld
- National Institutes of Health (NIH)–National Human Genome Research Institute, Bethesda, MD, USA
| | - Xiaowen Feng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Christian Fischer
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Robert S. Fulton
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Yan Gao
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Shilpa Garg
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Nanibaa’ A. Garrison
- Institute for Society and Genetics, College of Letters and Science, University of California, Los Angeles, Los Angeles, CA, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Carlos Garcia Giron
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Richard E. Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA
- Dovetail Genomics, Scotts Valley, CA, USA
| | - Cristian Groza
- Quantitative Life Sciences, McGill University, Montreal, QC, Canada
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - Leanne Haggerty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Ira M. Hall
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - David Haussler
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Simon Heumos
- Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- These authors contributed equally: Glenn Hickey, Jean Monlong
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Kerstin Howe
- Tree of Life, Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Miten Jain
- Northeastern University, Boston, MA, USA
| | - Erich D. Jarvis
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
| | - Hanlee P. Ji
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eimear E. Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Barbara A. Koenig
- Program in Bioethics and Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | | | - Jan O. Korbel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - HoJoon Lee
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Wen-Wei Liao
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Shuangjia Lu
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Tsung-Yu Lu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Julian K. Lucas
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Hugo Magalhães
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Santiago Marco-Sola
- Computer Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain
- Departament d’Arquitectura de Computadors i Sistemes Operatius, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Pierre Marijon
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Charles Markello
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Tobias Marschall
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Fergal J. Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Ann McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Jean Monlong
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- These authors contributed equally: Glenn Hickey, Jean Monlong
| | | | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Adam M. Novak
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hugh E. Olsen
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Trevor Pesout
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alice B. Popejoy
- Department of Public Health Sciences, University of California, Davis, Davis, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Daniela Puiu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Allison A. Regier
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Samuel Sacco
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Ashley D. Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Baergen I. Schultz
- National Institutes of Health (NIH)–National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Jonas A. Sibbesen
- Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark
| | - Jouni Sirén
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Michael W. Smith
- National Institutes of Health (NIH)–National Human Genome Research Institute, Bethesda, MD, USA
| | - Heidi J. Sofia
- National Institutes of Health (NIH)–National Human Genome Research Institute, Bethesda, MD, USA
| | - Ahmad N. Abou Tayoun
- Al Jalila Genomics Center of Excellence, Al Jalila Children’s Specialty Hospital, Dubai, UAE
- Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Chad Tomlinson
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Francesca Floriana Tricomi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Brian Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ting Wang
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Aleksey V. Zimin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
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3
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Gustafson JA, Gibson SB, Damaraju N, Zalusky MPG, Hoekzema K, Twesigomwe D, Yang L, Snead AA, Richmond PA, De Coster W, Olson ND, Guarracino A, Li Q, Miller AL, Goffena J, Anderson Z, Storz SHR, Ward SA, Sinha M, Gonzaga-Jauregui C, Clarke WE, Basile AO, Corvelo A, Reeves C, Helland A, Musunuri RL, Revsine M, Patterson KE, Paschal CR, Zakarian C, Goodwin S, Jensen TD, Robb E, McCombie WR, Sedlazeck FJ, Zook JM, Montgomery SB, Garrison E, Kolmogorov M, Schatz MC, McLaughlin RN, Dashnow H, Zody MC, Loose M, Jain M, Eichler EE, Miller DE. Nanopore sequencing of 1000 Genomes Project samples to build a comprehensive catalog of human genetic variation. medRxiv 2024:2024.03.05.24303792. [PMID: 38496498 PMCID: PMC10942501 DOI: 10.1101/2024.03.05.24303792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Less than half of individuals with a suspected Mendelian condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control datasets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project ONT Sequencing Consortium aims to generate LRS data from at least 800 of the 1000 Genomes Project samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37x and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.
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Affiliation(s)
- Jonas A. Gustafson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Sophia B. Gibson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Nikhita Damaraju
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Miranda PG Zalusky
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Lei Yang
- Pacific Northwest Research Institute, Seattle, WA, USA
| | | | | | - Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Human Technopole, Milan, Italy
| | - Qiuhui Li
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Angela L. Miller
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Joy Goffena
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Zachery Anderson
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Sophie HR Storz
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Sydney A. Ward
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Maisha Sinha
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Claudia Gonzaga-Jauregui
- International Laboratory for Human Genome Research, Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México
| | - Wayne E. Clarke
- New York Genome Center, New York, NY, USA
- Outlier Informatics Inc., Saskatoon, SK, Canada
| | | | | | | | | | | | - Mahler Revsine
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | | | - Cate R. Paschal
- Department of Laboratories, Seattle Children’s Hospital, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Christina Zakarian
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Sara Goodwin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Esther Robb
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | | | | | | | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Mikhail Kolmogorov
- Cancer Data Science Laboratory, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Richard N. McLaughlin
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
- Pacific Northwest Research Institute, Seattle, WA, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
| | | | - Matt Loose
- Deep Seq, School of Life Sciences, University of Nottingham, Nottingham, England
| | - Miten Jain
- Department of Bioengineering, Department of Physics, Khoury College of Computer Sciences, Northeastern University, Boston, MA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Danny E. Miller
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
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Jain S, Bakolitsa C, Brenner SE, Radivojac P, Moult J, Repo S, Hoskins RA, Andreoletti G, Barsky D, Chellapan A, Chu H, Dabbiru N, Kollipara NK, Ly M, Neumann AJ, Pal LR, Odell E, Pandey G, Peters-Petrulewicz RC, Srinivasan R, Yee SF, Yeleswarapu SJ, Zuhl M, Adebali O, Patra A, Beer MA, Hosur R, Peng J, Bernard BM, Berry M, Dong S, Boyle AP, Adhikari A, Chen J, Hu Z, Wang R, Wang Y, Miller M, Wang Y, Bromberg Y, Turina P, Capriotti E, Han JJ, Ozturk K, Carter H, Babbi G, Bovo S, Di Lena P, Martelli PL, Savojardo C, Casadio R, Cline MS, De Baets G, Bonache S, Díez O, Gutiérrez-Enríquez S, Fernández A, Montalban G, Ootes L, Özkan S, Padilla N, Riera C, De la Cruz X, Diekhans M, Huwe PJ, Wei Q, Xu Q, Dunbrack RL, Gotea V, Elnitski L, Margolin G, Fariselli P, Kulakovskiy IV, Makeev VJ, Penzar DD, Vorontsov IE, Favorov AV, Forman JR, Hasenahuer M, Fornasari MS, Parisi G, Avsec Z, Çelik MH, Nguyen TYD, Gagneur J, Shi FY, Edwards MD, Guo Y, Tian K, Zeng H, Gifford DK, Göke J, Zaucha J, Gough J, Ritchie GRS, Frankish A, Mudge JM, Harrow J, Young EL, Yu Y, Huff CD, Murakami K, Nagai Y, Imanishi T, Mungall CJ, Jacobsen JOB, Kim D, Jeong CS, Jones DT, Li MJ, Guthrie VB, Bhattacharya R, Chen YC, Douville C, Fan J, Kim D, Masica D, Niknafs N, Sengupta S, Tokheim C, Turner TN, Yeo HTG, Karchin R, Shin S, Welch R, Keles S, Li Y, Kellis M, Corbi-Verge C, Strokach AV, Kim PM, Klein TE, Mohan R, Sinnott-Armstrong NA, Wainberg M, Kundaje A, Gonzaludo N, Mak ACY, Chhibber A, Lam HYK, Dahary D, Fishilevich S, Lancet D, Lee I, Bachman B, Katsonis P, Lua RC, Wilson SJ, Lichtarge O, Bhat RR, Sundaram L, Viswanath V, Bellazzi R, Nicora G, Rizzo E, Limongelli I, Mezlini AM, Chang R, Kim S, Lai C, O’Connor R, Topper S, van den Akker J, Zhou AY, Zimmer AD, Mishne G, Bergquist TR, Breese MR, Guerrero RF, Jiang Y, Kiga N, Li B, Mort M, Pagel KA, Pejaver V, Stamboulian MH, Thusberg J, Mooney SD, Teerakulkittipong N, Cao C, Kundu K, Yin Y, Yu CH, Kleyman M, Lin CF, Stackpole M, Mount SM, Eraslan G, Mueller NS, Naito T, Rao AR, Azaria JR, Brodie A, Ofran Y, Garg A, Pal D, Hawkins-Hooker A, Kenlay H, Reid J, Mucaki EJ, Rogan PK, Schwarz JM, Searls DB, Lee GR, Seok C, Krämer A, Shah S, Huang CV, Kirsch JF, Shatsky M, Cao Y, Chen H, Karimi M, Moronfoye O, Sun Y, Shen Y, Shigeta R, Ford CT, Nodzak C, Uppal A, Shi X, Joseph T, Kotte S, Rana S, Rao A, Saipradeep VG, Sivadasan N, Sunderam U, Stanke M, Su A, Adzhubey I, Jordan DM, Sunyaev S, Rousseau F, Schymkowitz J, Van Durme J, Tavtigian SV, Carraro M, Giollo M, Tosatto SCE, Adato O, Carmel L, Cohen NE, Fenesh T, Holtzer T, Juven-Gershon T, Unger R, Niroula A, Olatubosun A, Väliaho J, Yang Y, Vihinen M, Wahl ME, Chang B, Chong KC, Hu I, Sun R, Wu WKK, Xia X, Zee BC, Wang MH, Wang M, Wu C, Lu Y, Chen K, Yang Y, Yates CM, Kreimer A, Yan Z, Yosef N, Zhao H, Wei Z, Yao Z, Zhou F, Folkman L, Zhou Y, Daneshjou R, Altman RB, Inoue F, Ahituv N, Arkin AP, Lovisa F, Bonvini P, Bowdin S, Gianni S, Mantuano E, Minicozzi V, Novak L, Pasquo A, Pastore A, Petrosino M, Puglisi R, Toto A, Veneziano L, Chiaraluce R, Ball MP, Bobe JR, Church GM, Consalvi V, Cooper DN, Buckley BA, Sheridan MB, Cutting GR, Scaini MC, Cygan KJ, Fredericks AM, Glidden DT, Neil C, Rhine CL, Fairbrother WG, Alontaga AY, Fenton AW, Matreyek KA, Starita LM, Fowler DM, Löscher BS, Franke A, Adamson SI, Graveley BR, Gray JW, Malloy MJ, Kane JP, Kousi M, Katsanis N, Schubach M, Kircher M, Mak ACY, Tang PLF, Kwok PY, Lathrop RH, Clark WT, Yu GK, LeBowitz JH, Benedicenti F, Bettella E, Bigoni S, Cesca F, Mammi I, Marino-Buslje C, Milani D, Peron A, Polli R, Sartori S, Stanzial F, Toldo I, Turolla L, Aspromonte MC, Bellini M, Leonardi E, Liu X, Marshall C, McCombie WR, Elefanti L, Menin C, Meyn MS, Murgia A, Nadeau KCY, Neuhausen SL, Nussbaum RL, Pirooznia M, Potash JB, Dimster-Denk DF, Rine JD, Sanford JR, Snyder M, Cote AG, Sun S, Verby MW, Weile J, Roth FP, Tewhey R, Sabeti PC, Campagna J, Refaat MM, Wojciak J, Grubb S, Schmitt N, Shendure J, Spurdle AB, Stavropoulos DJ, Walton NA, Zandi PP, Ziv E, Burke W, Chen F, Carr LR, Martinez S, Paik J, Harris-Wai J, Yarborough M, Fullerton SM, Koenig BA, McInnes G, Shigaki D, Chandonia JM, Furutsuki M, Kasak L, Yu C, Chen R, Friedberg I, Getz GA, Cong Q, Kinch LN, Zhang J, Grishin NV, Voskanian A, Kann MG, Tran E, Ioannidis NM, Hunter JM, Udani R, Cai B, Morgan AA, Sokolov A, Stuart JM, Minervini G, Monzon AM, Batzoglou S, Butte AJ, Greenblatt MS, Hart RK, Hernandez R, Hubbard TJP, Kahn S, O’Donnell-Luria A, Ng PC, Shon J, Veltman J, Zook JM. CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods. Genome Biol 2024; 25:53. [PMID: 38389099 PMCID: PMC10882881 DOI: 10.1186/s13059-023-03113-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 11/17/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors. RESULTS Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic. CONCLUSIONS Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.
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Jam HZ, Zook JM, Javadzadeh S, Park J, Sehgal A, Gymrek M. Genome-wide profiling of genetic variation at tandem repeat from long reads. bioRxiv 2024:2024.01.20.576266. [PMID: 38328152 PMCID: PMC10849534 DOI: 10.1101/2024.01.20.576266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Tandem repeats are frequent across the human genome, and variation in repeat length has been linked to a variety of traits. Recent improvements in long read sequencing technologies have the potential to greatly improve TR analysis, especially for long or complex repeats. Here we introduce LongTR, which accurately genotypes tandem repeats from high fidelity long reads available from both PacBio and Oxford Nanopore Technologies. LongTR is freely available at https://github.com/gymrek-lab/longtr.
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Affiliation(s)
- Helyaneh Ziaei Jam
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA
| | - Sara Javadzadeh
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jonghun Park
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Aarushi Sehgal
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
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6
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English A, Dolzhenko E, Jam HZ, Mckenzie S, Olson ND, De Coster W, Park J, Gu B, Wagner J, Eberle MA, Gymrek M, Chaisson MJP, Zook JM, Sedlazeck FJ. Benchmarking of small and large variants across tandem repeats. bioRxiv 2023:2023.10.29.564632. [PMID: 37961319 PMCID: PMC10634962 DOI: 10.1101/2023.10.29.564632] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Tandem repeats (TRs) are highly polymorphic in the human genome, have thousands of associated molecular traits, and are linked to over 60 disease phenotypes. However, their complexity often excludes them from at-scale studies due to challenges with variant calling, representation, and lack of a genome-wide standard. To promote TR methods development, we create a comprehensive catalog of TR regions and explore its properties across 86 samples. We then curate variants from the GIAB HG002 individual to create a tandem repeat benchmark. We also present a variant comparison method that handles small and large alleles and varying allelic representation. The 8.1% of the genome covered by the TR catalog holds ∼24.9% of variants per individual, including 124,728 small and 17,988 large variants for the GIAB HG002 TR benchmark. We work with the GIAB community to demonstrate the utility of this benchmark across short and long read technologies.
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7
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Rhie A, Nurk S, Cechova M, Hoyt SJ, Taylor DJ, Altemose N, Hook PW, Koren S, Rautiainen M, Alexandrov IA, Allen J, Asri M, Bzikadze AV, Chen NC, Chin CS, Diekhans M, Flicek P, Formenti G, Fungtammasan A, Garcia Giron C, Garrison E, Gershman A, Gerton JL, Grady PGS, Guarracino A, Haggerty L, Halabian R, Hansen NF, Harris R, Hartley GA, Harvey WT, Haukness M, Heinz J, Hourlier T, Hubley RM, Hunt SE, Hwang S, Jain M, Kesharwani RK, Lewis AP, Li H, Logsdon GA, Lucas JK, Makalowski W, Markovic C, Martin FJ, Mc Cartney AM, McCoy RC, McDaniel J, McNulty BM, Medvedev P, Mikheenko A, Munson KM, Murphy TD, Olsen HE, Olson ND, Paulin LF, Porubsky D, Potapova T, Ryabov F, Salzberg SL, Sauria MEG, Sedlazeck FJ, Shafin K, Shepelev VA, Shumate A, Storer JM, Surapaneni L, Taravella Oill AM, Thibaud-Nissen F, Timp W, Tomaszkiewicz M, Vollger MR, Walenz BP, Watwood AC, Weissensteiner MH, Wenger AM, Wilson MA, Zarate S, Zhu Y, Zook JM, Eichler EE, O'Neill RJ, Schatz MC, Miga KH, Makova KD, Phillippy AM. The complete sequence of a human Y chromosome. Nature 2023; 621:344-354. [PMID: 37612512 PMCID: PMC10752217 DOI: 10.1038/s41586-023-06457-y] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [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: 12/02/2022] [Accepted: 07/19/2023] [Indexed: 08/25/2023]
Abstract
The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure that includes long palindromes, tandem repeats and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4,5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029-base-pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, showing the complete ampliconic structures of gene families TSPY, DAZ and RBMY; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a previous assembly of the CHM13 genome4 and mapped available population variation, clinical variants and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.
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Affiliation(s)
- Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Oxford Nanopore Technologies Inc., Oxford, UK
| | - Monika Cechova
- Faculty of Informatics, Masaryk University, Brno, Czech Republic
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Savannah J Hoyt
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Dylan J Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Nicolas Altemose
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Paul W Hook
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ivan A Alexandrov
- Federal Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
- Center for Algorithmic Biotechnology, Saint Petersburg State University, St Petersburg, Russia
- Department of Anatomy and Anthropology and Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Jamie Allen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Andrey V Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego, CA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Chen-Shan Chin
- GeneDX Holdings Corp, Stamford, CT, USA
- Foundation of Biological Data Science, Belmont, CA, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Department of Genetics, University of Cambridge, Cambridge, UK
| | | | | | - Carlos Garcia Giron
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Ariel Gershman
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jennifer L Gerton
- Stowers Institute for Medical Research, Kansas City, MO, USA
- University of Kansas Medical Center, Kansas City, MO, USA
| | - Patrick G S Grady
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - Leanne Haggerty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Reza Halabian
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, Münster, Germany
| | - Nancy F Hansen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert Harris
- Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Gabrielle A Hartley
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Jakob Heinz
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Sarah E Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Stephen Hwang
- XDBio Program, Johns Hopkins University, Baltimore, MD, USA
| | - Miten Jain
- Department of Bioengineering, Department of Physics, Northeastern University, Boston, MA, USA
| | - Rupesh K Kesharwani
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Julian K Lucas
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Wojciech Makalowski
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, Münster, Germany
| | - Christopher Markovic
- Genome Technology Access Center at the McDonnell Genome Institute, Washington University, St. Louis, MO, USA
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Ann M Mc Cartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Jennifer McDaniel
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Brandy M McNulty
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Paul Medvedev
- Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA, USA
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA
- Center for Computational Biology and Bioinformatics, Pennsylvania State University, University Park, PA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Saint Petersburg State University, St Petersburg, Russia
- UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Terence D Murphy
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Hugh E Olsen
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Nathan D Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Luis F Paulin
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Fedor Ryabov
- Masters Program in National Research University Higher School of Economics, Moscow, Russia
| | - Steven L Salzberg
- Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | | | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | | | | | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | - Likhitha Surapaneni
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Angela M Taravella Oill
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Marta Tomaszkiewicz
- Department of Biology, Pennsylvania State University, University Park, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, State College, PA, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Brian P Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Allison C Watwood
- Department of Biology, Pennsylvania State University, University Park, PA, USA
| | | | | | - Melissa A Wilson
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Yiming Zhu
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA
| | - Justin M Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Investigator, Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Rachel J O'Neill
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
| | - Michael C Schatz
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Karen H Miga
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Kateryna D Makova
- Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
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8
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Chin CS, Behera S, Khalak A, Sedlazeck FJ, Sudmant PH, Wagner J, Zook JM. Multiscale analysis of pangenomes enables improved representation of genomic diversity for repetitive and clinically relevant genes. Nat Methods 2023; 20:1213-1221. [PMID: 37365340 PMCID: PMC10406601 DOI: 10.1038/s41592-023-01914-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 05/17/2023] [Indexed: 06/28/2023]
Abstract
Advancements in sequencing technologies and assembly methods enable the regular production of high-quality genome assemblies characterizing complex regions. However, challenges remain in efficiently interpreting variation at various scales, from smaller tandem repeats to megabase rearrangements, across many human genomes. We present a PanGenome Research Tool Kit (PGR-TK) enabling analyses of complex pangenome structural and haplotype variation at multiple scales. We apply the graph decomposition methods in PGR-TK to the class II major histocompatibility complex demonstrating the importance of the human pangenome for analyzing complicated regions. Moreover, we investigate the Y-chromosome genes, DAZ1/DAZ2/DAZ3/DAZ4, of which structural variants have been linked to male infertility, and X-chromosome genes OPN1LW and OPN1MW linked to eye disorders. We further showcase PGR-TK across 395 complex repetitive medically important genes. This highlights the power of PGR-TK to resolve complex variation in regions of the genome that were previously too complex to analyze.
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Affiliation(s)
- Chen-Shan Chin
- GeneDX, Stamford, CT, USA.
- Foundation of Biological Data Science, Belmont, CA, USA.
| | - Sairam Behera
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Asif Khalak
- Foundation of Biological Data Science, Belmont, CA, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
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9
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Liao WW, Asri M, Ebler J, Doerr D, Haukness M, Hickey G, Lu S, Lucas JK, Monlong J, Abel HJ, Buonaiuto S, Chang XH, Cheng H, Chu J, Colonna V, Eizenga JM, Feng X, Fischer C, Fulton RS, Garg S, Groza C, Guarracino A, Harvey WT, Heumos S, Howe K, Jain M, Lu TY, Markello C, Martin FJ, Mitchell MW, Munson KM, Mwaniki MN, Novak AM, Olsen HE, Pesout T, Porubsky D, Prins P, Sibbesen JA, Sirén J, Tomlinson C, Villani F, Vollger MR, Antonacci-Fulton LL, Baid G, Baker CA, Belyaeva A, Billis K, Carroll A, Chang PC, Cody S, Cook DE, Cook-Deegan RM, Cornejo OE, Diekhans M, Ebert P, Fairley S, Fedrigo O, Felsenfeld AL, Formenti G, Frankish A, Gao Y, Garrison NA, Giron CG, Green RE, Haggerty L, Hoekzema K, Hourlier T, Ji HP, Kenny EE, Koenig BA, Kolesnikov A, Korbel JO, Kordosky J, Koren S, Lee H, Lewis AP, Magalhães H, Marco-Sola S, Marijon P, McCartney A, McDaniel J, Mountcastle J, Nattestad M, Nurk S, Olson ND, Popejoy AB, Puiu D, Rautiainen M, Regier AA, Rhie A, Sacco S, Sanders AD, Schneider VA, Schultz BI, Shafin K, Smith MW, Sofia HJ, Abou Tayoun AN, Thibaud-Nissen F, Tricomi FF, Wagner J, Walenz B, Wood JMD, Zimin AV, Bourque G, Chaisson MJP, Flicek P, Phillippy AM, Zook JM, Eichler EE, Haussler D, Wang T, Jarvis ED, Miga KH, Garrison E, Marschall T, Hall IM, Li H, Paten B. A draft human pangenome reference. Nature 2023; 617:312-324. [PMID: 37165242 PMCID: PMC10172123 DOI: 10.1038/s41586-023-05896-x] [Citation(s) in RCA: 170] [Impact Index Per Article: 170.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 02/28/2023] [Indexed: 05/12/2023]
Abstract
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.
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Affiliation(s)
- Wen-Wei Liao
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Mobin Asri
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Jana Ebler
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Daniel Doerr
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Marina Haukness
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Glenn Hickey
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Shuangjia Lu
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA
| | - Julian K Lucas
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Jean Monlong
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Haley J Abel
- Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Silvia Buonaiuto
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
| | - Xian H Chang
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Justin Chu
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Vincenza Colonna
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jordan M Eizenga
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Xiaowen Feng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Christian Fischer
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Robert S Fulton
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Shilpa Garg
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Cristian Groza
- Quantitative Life Sciences, McGill University, Montréal, Québec, Canada
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Simon Heumos
- Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Kerstin Howe
- Tree of Life, Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Miten Jain
- Northeastern University, Boston, MA, USA
| | - Tsung-Yu Lu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Charles Markello
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Adam M Novak
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Hugh E Olsen
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Trevor Pesout
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jonas A Sibbesen
- Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark
| | - Jouni Sirén
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Chad Tomlinson
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Carl A Baker
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | | | - Sarah Cody
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Robert M Cook-Deegan
- Barrett and O'Connor Washington Center, Arizona State University, Washington, DC, USA
| | - Omar E Cornejo
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA
| | - Mark Diekhans
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
- Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Susan Fairley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Olivier Fedrigo
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Adam L Felsenfeld
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yan Gao
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nanibaa' A Garrison
- Institute for Society and Genetics, College of Letters and Science, University of California, Los Angeles, CA, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Carlos Garcia Giron
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Richard E Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA
- Dovetail Genomics, Scotts Valley, CA, USA
| | - Leanne Haggerty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Hanlee P Ji
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Barbara A Koenig
- Program in Bioethics and Institute for Human Genetics, University of California, San Francisco, CA, USA
| | | | - Jan O Korbel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - HoJoon Lee
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hugo Magalhães
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Santiago Marco-Sola
- Computer Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain
- Departament d'Arquitectura de Computadors i Sistemes Operatius, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Pierre Marijon
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Ann McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | | | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Alice B Popejoy
- Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Daniela Puiu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Allison A Regier
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Samuel Sacco
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Valerie A Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Baergen I Schultz
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Michael W Smith
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | - Heidi J Sofia
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | - Ahmad N Abou Tayoun
- Al Jalila Genomics Center of Excellence, Al Jalila Children's Specialty Hospital, Dubai, UAE
- Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Francesca Floriana Tricomi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Brian Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Aleksey V Zimin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- Canadian Center for Computational Genomics, McGill University, Montréal, Québec, Canada
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - David Haussler
- Genomics Institute, University of California, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Ting Wang
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Erich D Jarvis
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
| | - Karen H Miga
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany.
| | - Ira M Hall
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA.
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, CA, USA.
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10
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Olson ND, Wagner J, Dwarshuis N, Miga KH, Sedlazeck FJ, Salit M, Zook JM. Variant calling and benchmarking in an era of complete human genome sequences. Nat Rev Genet 2023:10.1038/s41576-023-00590-0. [PMID: 37059810 DOI: 10.1038/s41576-023-00590-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2023] [Indexed: 04/16/2023]
Abstract
Genetic variant calling from DNA sequencing has enabled understanding of germline variation in hundreds of thousands of humans. Sequencing technologies and variant-calling methods have advanced rapidly, routinely providing reliable variant calls in most of the human genome. We describe how advances in long reads, deep learning, de novo assembly and pangenomes have expanded access to variant calls in increasingly challenging, repetitive genomic regions, including medically relevant regions, and how new benchmark sets and benchmarking methods illuminate their strengths and limitations. Finally, we explore the possible future of more complete characterization of human genome variation in light of the recent completion of a telomere-to-telomere human genome reference assembly and human pangenomes, and we consider the innovations needed to benchmark their newly accessible repetitive regions and complex variants.
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Affiliation(s)
- Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan Dwarshuis
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Fritz J Sedlazeck
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | | | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
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11
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Behera S, LeFaive J, Orchard P, Mahmoud M, Paulin LF, Farek J, Soto DC, Parker SCJ, Smith AV, Dennis MY, Zook JM, Sedlazeck FJ. FixItFelix: improving genomic analysis by fixing reference errors. Genome Biol 2023; 24:31. [PMID: 36810122 PMCID: PMC9942314 DOI: 10.1186/s13059-023-02863-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 01/20/2023] [Indexed: 02/23/2023] Open
Abstract
The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.
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Affiliation(s)
- Sairam Behera
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jonathon LeFaive
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Luis F Paulin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Daniela C Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Albert V Smith
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Megan Y Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, Houston, TX, USA.
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12
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Duncavage EJ, Coleman JF, de Baca ME, Kadri S, Leon A, Routbort M, Roy S, Suarez CJ, Vanderbilt C, Zook JM. Recommendations for the Use of in Silico Approaches for Next-Generation Sequencing Bioinformatic Pipeline Validation: A Joint Report of the Association for Molecular Pathology, Association for Pathology Informatics, and College of American Pathologists. J Mol Diagn 2023; 25:3-16. [PMID: 36244574 DOI: 10.1016/j.jmoldx.2022.09.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 09/14/2022] [Accepted: 09/28/2022] [Indexed: 11/21/2022] Open
Abstract
In silico approaches for next-generation sequencing (NGS) data modeling have utility in the clinical laboratory as a tool for clinical assay validation. In silico NGS data can take a variety of forms, including pure simulated data or manipulated data files in which variants are inserted into existing data files. In silico data enable simulation of a range of variants that may be difficult to obtain from a single physical sample. Such data allow laboratories to more accurately test the performance of clinical bioinformatics pipelines without sequencing additional cases. For example, clinical laboratories may use in silico data to simulate low variant allele fraction variants to test the analytical sensitivity of variant calling software or simulate a range of insertion/deletion sizes to determine the performance of insertion/deletion calling software. In this article, the Working Group reviews the different types of in silico data with their strengths and limitations, methods to generate in silico data, and how data can be used in the clinical molecular diagnostic laboratory. Survey data indicate how in silico NGS data are currently being used. Finally, potential applications for which in silico data may become useful in the future are presented.
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Affiliation(s)
- Eric J Duncavage
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri.
| | - Joshua F Coleman
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, University of Utah, Salt Lake City, Utah
| | - Monica E de Baca
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Pacific Pathology Partners, Seattle, Washington
| | - Sabah Kadri
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, Anne and Robert H Lurie Children's Hospital of Chicago, Chicago, Illinois
| | - Annette Leon
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Color Health, Burlingame, California
| | - Mark Routbort
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Hematopathology, MD Anderson Cancer Center, Houston, Texas
| | - Somak Roy
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology and Laboratory Medicine, Cincinnati Children's Hospital, Cincinnati, Ohio
| | - Carlos J Suarez
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, Stanford University, Palo Alto, California
| | - Chad Vanderbilt
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Justin M Zook
- In Silico Pipeline Validation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Biomarker and Genomic Sciences Group, National Institute of Standards and Technology, Gaithersburg, Maryland
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13
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Jarvis ED, Formenti G, Rhie A, Guarracino A, Yang C, Wood J, Tracey A, Thibaud-Nissen F, Vollger MR, Porubsky D, Cheng H, Asri M, Logsdon GA, Carnevali P, Chaisson MJP, Chin CS, Cody S, Collins J, Ebert P, Escalona M, Fedrigo O, Fulton RS, Fulton LL, Garg S, Gerton JL, Ghurye J, Granat A, Green RE, Harvey W, Hasenfeld P, Hastie A, Haukness M, Jaeger EB, Jain M, Kirsche M, Kolmogorov M, Korbel JO, Koren S, Korlach J, Lee J, Li D, Lindsay T, Lucas J, Luo F, Marschall T, Mitchell MW, McDaniel J, Nie F, Olsen HE, Olson ND, Pesout T, Potapova T, Puiu D, Regier A, Ruan J, Salzberg SL, Sanders AD, Schatz MC, Schmitt A, Schneider VA, Selvaraj S, Shafin K, Shumate A, Stitziel NO, Stober C, Torrance J, Wagner J, Wang J, Wenger A, Xiao C, Zimin AV, Zhang G, Wang T, Li H, Garrison E, Haussler D, Hall I, Zook JM, Eichler EE, Phillippy AM, Paten B, Howe K, Miga KH. Semi-automated assembly of high-quality diploid human reference genomes. Nature 2022; 611:519-531. [PMID: 36261518 PMCID: PMC9668749 DOI: 10.1038/s41586-022-05325-5] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 09/06/2022] [Indexed: 01/01/2023]
Abstract
The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.
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Affiliation(s)
- Erich D. Jarvis
- grid.134907.80000 0001 2166 1519Vertebrate Genome Laboratory, The Rockefeller University, New York, NY USA ,grid.413575.10000 0001 2167 1581Howard Hughes Medical Institute, Chevy Chase, MD USA
| | - Giulio Formenti
- grid.134907.80000 0001 2166 1519Vertebrate Genome Laboratory, The Rockefeller University, New York, NY USA
| | - Arang Rhie
- grid.94365.3d0000 0001 2297 5165Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Andrea Guarracino
- grid.510779.d0000 0004 9414 6915Genomics Research Centre, Human Technopole, Viale Rita Levi-Montalcini, Milan, Italy
| | - Chentao Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | - Jonathan Wood
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Alan Tracey
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Francoise Thibaud-Nissen
- grid.94365.3d0000 0001 2297 5165National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD USA
| | - Mitchell R. Vollger
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - David Porubsky
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Haoyu Cheng
- grid.65499.370000 0001 2106 9910Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Mobin Asri
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Glennis A. Logsdon
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Paolo Carnevali
- grid.507326.50000 0004 6090 4941Chan Zuckerberg Initiative, Redwood City, CA USA
| | - Mark J. P. Chaisson
- grid.42505.360000 0001 2156 6853Quantitative and Computational Biology, University of Southern California, Los Angeles, CA USA
| | | | - Sarah Cody
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Joanna Collins
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Peter Ebert
- grid.411327.20000 0001 2176 9917Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Merly Escalona
- grid.205975.c0000 0001 0740 6917Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA USA
| | - Olivier Fedrigo
- grid.134907.80000 0001 2166 1519Vertebrate Genome Laboratory, The Rockefeller University, New York, NY USA
| | - Robert S. Fulton
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Lucinda L. Fulton
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Shilpa Garg
- grid.5254.60000 0001 0674 042XDepartment of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer L. Gerton
- grid.250820.d0000 0000 9420 1591Stowers Institute for Medical Research, Kansas City, MO USA
| | - Jay Ghurye
- grid.504403.6Dovetail Genomics, Scotts Valley, CA USA
| | | | - Richard E. Green
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - William Harvey
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Patrick Hasenfeld
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Alex Hastie
- grid.470262.50000 0004 0473 1353Bionano Genomics, San Diego, CA USA
| | - Marina Haukness
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Erich B. Jaeger
- grid.185669.50000 0004 0507 3954Illumina, Inc., San Diego, CA USA
| | - Miten Jain
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Melanie Kirsche
- grid.21107.350000 0001 2171 9311Department of Computer Science, Johns Hopkins University, Baltimore, MD USA
| | - Mikhail Kolmogorov
- grid.266100.30000 0001 2107 4242Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA USA
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Sergey Koren
- grid.94365.3d0000 0001 2297 5165Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Jonas Korlach
- grid.423340.20000 0004 0640 9878Pacific Biosciences, Menlo Park, CA USA
| | - Joyce Lee
- grid.470262.50000 0004 0473 1353Bionano Genomics, San Diego, CA USA
| | - Daofeng Li
- grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO USA
| | - Tina Lindsay
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Julian Lucas
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Feng Luo
- grid.26090.3d0000 0001 0665 0280School of Computing, Clemson University, Clemson, SC USA
| | - Tobias Marschall
- grid.411327.20000 0001 2176 9917Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Matthew W. Mitchell
- grid.282012.b0000 0004 0627 5048Coriell Institute for Medical Research, Camden, NJ USA
| | - Jennifer McDaniel
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Fan Nie
- grid.216417.70000 0001 0379 7164Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Hugh E. Olsen
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Nathan D. Olson
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Trevor Pesout
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Tamara Potapova
- grid.250820.d0000 0000 9420 1591Stowers Institute for Medical Research, Kansas City, MO USA
| | - Daniela Puiu
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Allison Regier
- grid.511991.40000 0004 4910 5831DNAnexus, Mountain View, CA USA
| | - Jue Ruan
- grid.410727.70000 0001 0526 1937Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Steven L. Salzberg
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Ashley D. Sanders
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Michael C. Schatz
- grid.21107.350000 0001 2171 9311Department of Computer Science, Johns Hopkins University, Baltimore, MD USA
| | | | - Valerie A. Schneider
- grid.94365.3d0000 0001 2297 5165National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD USA
| | | | - Kishwar Shafin
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Alaina Shumate
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Nathan O. Stitziel
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Cardiovascular Division, John T. Milliken Department of Internal Medicine, Washington University School of Medicine, St. Louis, USA
| | - Catherine Stober
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - James Torrance
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Justin Wagner
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Jianxin Wang
- grid.216417.70000 0001 0379 7164Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Aaron Wenger
- grid.423340.20000 0004 0640 9878Pacific Biosciences, Menlo Park, CA USA
| | - Chuanle Xiao
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Aleksey V. Zimin
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Guojie Zhang
- grid.13402.340000 0004 1759 700XCenter for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, China
| | - Ting Wang
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO USA
| | - Heng Li
- grid.65499.370000 0001 2106 9910Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA USA
| | - Erik Garrison
- grid.267301.10000 0004 0386 9246Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN USA
| | - David Haussler
- grid.413575.10000 0001 2167 1581Howard Hughes Medical Institute, Chevy Chase, MD USA ,grid.205975.c0000 0001 0740 6917Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA USA
| | - Ira Hall
- grid.47100.320000000419368710Yale School of Medicine, New Haven, CT USA
| | - Justin M. Zook
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Evan E. Eichler
- grid.413575.10000 0001 2167 1581Howard Hughes Medical Institute, Chevy Chase, MD USA ,grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Adam M. Phillippy
- grid.94365.3d0000 0001 2297 5165Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Benedict Paten
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Kerstin Howe
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Karen H. Miga
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
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14
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Mc Cartney AM, Shafin K, Alonge M, Bzikadze AV, Formenti G, Fungtammasan A, Howe K, Jain C, Koren S, Logsdon GA, Miga KH, Mikheenko A, Paten B, Shumate A, Soto DC, Sović I, Wood JMD, Zook JM, Phillippy AM, Rhie A. Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies. Nat Methods 2022; 19:687-695. [PMID: 35361931 PMCID: PMC9812399 DOI: 10.1038/s41592-022-01440-3] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 03/04/2022] [Indexed: 01/07/2023]
Abstract
Advances in long-read sequencing technologies and genome assembly methods have enabled the recent completion of the first telomere-to-telomere human genome assembly, which resolves complex segmental duplications and large tandem repeats, including centromeric satellite arrays in a complete hydatidiform mole (CHM13). Although derived from highly accurate sequences, evaluation revealed evidence of small errors and structural misassemblies in the initial draft assembly. To correct these errors, we designed a new repeat-aware polishing strategy that made accurate assembly corrections in large repeats without overcorrection, ultimately fixing 51% of the existing errors and improving the assembly quality value from 70.2 to 73.9 measured from PacBio high-fidelity and Illumina k-mers. By comparing our results to standard automated polishing tools, we outline common polishing errors and offer practical suggestions for genome projects with limited resources. We also show how sequencing biases in both high-fidelity and Oxford Nanopore Technologies reads cause signature assembly errors that can be corrected with a diverse panel of sequencing technologies.
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Affiliation(s)
- Ann M. Mc Cartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, NHGRI, NIH
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Michael Alonge
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA, USA
| | - Giulio Formenti
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University, New York, NY, USA
| | | | | | - Chirag Jain
- Genome Informatics Section, Computational and Statistical Genomics Branch, NHGRI, NIH,Department of Computational and Data Sciences, Indian Institute of Science, Bangalore KA, India
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, NHGRI, NIH
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Daniela C. Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis, CA, USA
| | - Ivan Sović
- Pacific Biosciences, Menlo Park, CA, USA,Digital BioLogic d.o.o., Ivanić-Grad, Croatia
| | | | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, NHGRI, NIH,Correspondence: ,
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, NHGRI, NIH,Correspondence: ,
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15
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Olson ND, Wagner J, McDaniel J, Stephens SH, Westreich ST, Prasanna AG, Johanson E, Boja E, Maier EJ, Serang O, Jáspez D, Lorenzo-Salazar JM, Muñoz-Barrera A, Rubio-Rodríguez LA, Flores C, Kyriakidis K, Malousi A, Shafin K, Pesout T, Jain M, Paten B, Chang PC, Kolesnikov A, Nattestad M, Baid G, Goel S, Yang H, Carroll A, Eveleigh R, Bourgey M, Bourque G, Li G, Ma C, Tang L, Du Y, Zhang S, Morata J, Tonda R, Parra G, Trotta JR, Brueffer C, Demirkaya-Budak S, Kabakci-Zorlu D, Turgut D, Kalay Ö, Budak G, Narcı K, Arslan E, Brown R, Johnson IJ, Dolgoborodov A, Semenyuk V, Jain A, Tetikol HS, Jain V, Ruehle M, Lajoie B, Roddey C, Catreux S, Mehio R, Ahsan MU, Liu Q, Wang K, Ebrahim Sahraeian SM, Fang LT, Mohiyuddin M, Hung C, Jain C, Feng H, Li Z, Chen L, Sedlazeck FJ, Zook JM. PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions. Cell Genom 2022; 2:S2666-979X(22)00058-1. [PMID: 35720974 PMCID: PMC9205427 DOI: 10.1016/j.xgen.2022.100129] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 11/01/2021] [Accepted: 04/08/2022] [Indexed: 11/19/2022]
Abstract
The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications. Challenge submissions included numerous innovative methods, with graph-based and machine learning methods scoring best for short-read and long-read datasets, respectively. With machine learning approaches, combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.
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Affiliation(s)
- Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | | | | | | | - Elaine Johanson
- Office of Health Informatics, Office of the Chief Scientist, Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, USA
| | - Emily Boja
- Office of Health Informatics, Office of the Chief Scientist, Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, USA
| | - Ezekiel J. Maier
- Booz Allen Hamilton, 8283 Greensboro Drive, Mclean, VA 22102, USA
| | - Omar Serang
- DNAnexus, Inc., 1975 W El Camino Real #204, Mountain View, CA 94040, USA
| | - David Jáspez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - José M. Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Adrián Muñoz-Barrera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Luis A. Rubio-Rodríguez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Carlos Flores
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario N.S. de Candelaria, Santa Cruz de Tenerife, Spain
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, 38200 San Cristóbal de La Laguna, Spain
| | - Konstantinos Kyriakidis
- School of Pharmacy, Aristotle University of Thessaloniki (AUTH), 541 24 Thessaloniki, Greece
- Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation, 570 01 Thessaloniki, Greece
| | - Andigoni Malousi
- Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation, 570 01 Thessaloniki, Greece
- Laboratory of Biological Chemistry, School of Medicine, Aristotle University of Thessaloniki (AUTH), 541 24 Thessaloniki, Greece
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, USA
| | - Trevor Pesout
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, USA
| | - Miten Jain
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, USA
| | - Pi-Chuan Chang
- Google Inc, 1600 Amphitheater Pkwy, Mountain View, CA 94040, USA
| | | | - Maria Nattestad
- Google Inc, 1600 Amphitheater Pkwy, Mountain View, CA 94040, USA
| | - Gunjan Baid
- Google Inc, 1600 Amphitheater Pkwy, Mountain View, CA 94040, USA
| | - Sidharth Goel
- Google Inc, 1600 Amphitheater Pkwy, Mountain View, CA 94040, USA
| | - Howard Yang
- Google Inc, 1600 Amphitheater Pkwy, Mountain View, CA 94040, USA
| | - Andrew Carroll
- Google Inc, 1600 Amphitheater Pkwy, Mountain View, CA 94040, USA
| | - Robert Eveleigh
- The Canadian Center for Computational Genomics (C3G), Montréal, QC, Canada
| | - Mathieu Bourgey
- The Canadian Center for Computational Genomics (C3G), Montréal, QC, Canada
| | - Guillaume Bourque
- The Canadian Center for Computational Genomics (C3G), Montréal, QC, Canada
| | - Gen Li
- HuXinDao, QingZhuHu TaiYangShan Road, KaiFu, ChangSha, HuNan, China
| | - ChouXian Ma
- HuXinDao, QingZhuHu TaiYangShan Road, KaiFu, ChangSha, HuNan, China
| | - LinQi Tang
- HuXinDao, QingZhuHu TaiYangShan Road, KaiFu, ChangSha, HuNan, China
| | - YuanPing Du
- HuXinDao, QingZhuHu TaiYangShan Road, KaiFu, ChangSha, HuNan, China
| | - ShaoWei Zhang
- HuXinDao, QingZhuHu TaiYangShan Road, KaiFu, ChangSha, HuNan, China
| | - Jordi Morata
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Raúl Tonda
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Genís Parra
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Jean-Rémi Trotta
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Christian Brueffer
- Division of Oncology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | | | | | - Deniz Turgut
- Seven Bridges Genomics, Inc, Charlestown, MA, USA
| | - Özem Kalay
- Seven Bridges Genomics, Inc, Charlestown, MA, USA
| | - Gungor Budak
- Seven Bridges Genomics, Inc, Charlestown, MA, USA
| | - Kübra Narcı
- Seven Bridges Genomics, Inc, Charlestown, MA, USA
| | - Elif Arslan
- Seven Bridges Genomics, Inc, Charlestown, MA, USA
| | | | | | | | | | - Amit Jain
- Seven Bridges Genomics, Inc, Charlestown, MA, USA
| | | | | | | | | | | | | | | | - Mian Umair Ahsan
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Qian Liu
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | - Li Tai Fang
- Roche Sequencing Solutions, Santa Clara, CA 95050, USA
| | | | | | - Chirag Jain
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | | | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
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16
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Wagner J, Olson ND, Harris L, Khan Z, Farek J, Mahmoud M, Stankovic A, Kovacevic V, Yoo B, Miller N, Rosenfeld JA, Ni B, Zarate S, Kirsche M, Aganezov S, Schatz MC, Narzisi G, Byrska-Bishop M, Clarke W, Evani US, Markello C, Shafin K, Zhou X, Sidow A, Bansal V, Ebert P, Marschall T, Lansdorp P, Hanlon V, Mattsson CA, Barrio AM, Fiddes IT, Xiao C, Fungtammasan A, Chin CS, Wenger AM, Rowell WJ, Sedlazeck FJ, Carroll A, Salit M, Zook JM. Benchmarking challenging small variants with linked and long reads. Cell Genom 2022; 2:100128. [PMID: 36452119 PMCID: PMC9706577 DOI: 10.1016/j.xgen.2022.100128] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.
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Affiliation(s)
- Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
- Corresponding author
| | - Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Lindsay Harris
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Ziad Khan
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Ana Stankovic
- Seven Bridges, Omladinskih brigada 90g, 11070 Belgrade, Republic of Serbia
| | - Vladimir Kovacevic
- Seven Bridges, Omladinskih brigada 90g, 11070 Belgrade, Republic of Serbia
| | - Byunggil Yoo
- Children’s Mercy Kansas City, Kansas City, MO, USA
| | - Neil Miller
- Children’s Mercy Kansas City, Kansas City, MO, USA
| | | | - Bohan Ni
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Giuseppe Narzisi
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | | | - Wayne Clarke
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | - Uday S. Evani
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | - Charles Markello
- University of California at Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA, USA
| | - Kishwar Shafin
- University of California at Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA, USA
| | - Xin Zhou
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Arend Sidow
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Vikas Bansal
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Peter Ebert
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Tobias Marschall
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Peter Lansdorp
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Vincent Hanlon
- Terry Fox Laboratory, BC Cancer Research Institute and Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Carl-Adam Mattsson
- Terry Fox Laboratory, BC Cancer Research Institute and Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | | | | | | | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Andrew Carroll
- Google Inc., 1600 Amphitheatre Pkwy., Mountain View, CA 94040, USA
| | - Marc Salit
- Joint Initiative for Metrology in Biology, SLAC National Laboratory, Stanford, CA, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
- Corresponding author
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17
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Wagner J, Olson ND, Harris L, McDaniel J, Cheng H, Fungtammasan A, Hwang YC, Gupta R, Wenger AM, Rowell WJ, Khan ZM, Farek J, Zhu Y, Pisupati A, Mahmoud M, Xiao C, Yoo B, Sahraeian SME, Miller DE, Jáspez D, Lorenzo-Salazar JM, Muñoz-Barrera A, Rubio-Rodríguez LA, Flores C, Narzisi G, Evani US, Clarke WE, Lee J, Mason CE, Lincoln SE, Miga KH, Ebbert MTW, Shumate A, Li H, Chin CS, Zook JM, Sedlazeck FJ. Curated variation benchmarks for challenging medically relevant autosomal genes. Nat Biotechnol 2022; 40:672-680. [PMID: 35132260 PMCID: PMC9117392 DOI: 10.1038/s41587-021-01158-1] [Citation(s) in RCA: 71] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 11/10/2021] [Indexed: 11/09/2022]
Abstract
The repetitive nature and complexity of some medically relevant genes poses a challenge for their accurate analysis in a clinical setting. The Genome in a Bottle Consortium has provided variant benchmark sets, but these exclude nearly 400 medically relevant genes due to their repetitiveness or polymorphic complexity. Here, we characterize 273 of these 395 challenging autosomal genes using a haplotype-resolved whole-genome assembly. This curated benchmark reports over 17,000 single-nucleotide variations, 3,600 insertions and deletions and 200 structural variations each for human genome reference GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically relevant genes, including CBS, CRYAA and KCNE1. When masking these false duplications, variant recall can improve from 8% to 100%. Forming benchmarks from a haplotype-resolved whole-genome assembly may become a prototype for future benchmarks covering the whole genome.
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Affiliation(s)
- Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Lindsay Harris
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Haoyu Cheng
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | | | | | | | | | - Ziad M Khan
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Yiming Zhu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Aishwarya Pisupati
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Byunggil Yoo
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | | | - Danny E Miller
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David Jáspez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - José M Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Adrián Muñoz-Barrera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Luis A Rubio-Rodríguez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Carlos Flores
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario N.S. de Candelaria, Santa Cruz de Tenerife, Spain
| | | | | | | | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | | | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mark T W Ebbert
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
- Department of Internal Medicine, Division of Biomedical Informatics, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
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18
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Altemose N, Glennis A, Bzikadze AV, Sidhwani P, Langley SA, Caldas GV, Hoyt SJ, Uralsky L, Ryabov FD, Shew CJ, Sauria MEG, Borchers M, Gershman A, Mikheenko A, Shepelev VA, Dvorkina T, Kunyavskaya O, Vollger MR, Rhie A, McCartney AM, Asri M, Lorig-Roach R, Shafin K, Aganezov S, Olson D, de Lima LG, Potapova T, Hartley GA, Haukness M, Kerpedjiev P, Gusev F, Tigyi K, Brooks S, Young A, Nurk S, Koren S, Salama SR, Paten B, Rogaev EI, Streets A, Karpen GH, Dernburg AF, Sullivan BA, Straight AF, Wheeler TJ, Gerton JL, Eichler EE, Phillippy AM, Timp W, Dennis MY, O'Neill RJ, Zook JM, Schatz MC, Pevzner PA, Diekhans M, Langley CH, Alexandrov IA, Miga KH. Complete genomic and epigenetic maps of human centromeres. Science 2022; 376:eabl4178. [PMID: 35357911 PMCID: PMC9233505 DOI: 10.1126/science.abl4178] [Citation(s) in RCA: 157] [Impact Index Per Article: 78.5] [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] [Indexed: 12/20/2022]
Abstract
Existing human genome assemblies have almost entirely excluded repetitive sequences within and near centromeres, limiting our understanding of their organization, evolution, and functions, which include facilitating proper chromosome segregation. Now, a complete, telomere-to-telomere human genome assembly (T2T-CHM13) has enabled us to comprehensively characterize pericentromeric and centromeric repeats, which constitute 6.2% of the genome (189.9 megabases). Detailed maps of these regions revealed multimegabase structural rearrangements, including in active centromeric repeat arrays. Analysis of centromere-associated sequences uncovered a strong relationship between the position of the centromere and the evolution of the surrounding DNA through layered repeat expansions. Furthermore, comparisons of chromosome X centromeres across a diverse panel of individuals illuminated high degrees of structural, epigenetic, and sequence variation in these complex and rapidly evolving regions.
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Affiliation(s)
- Nicolas Altemose
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - A. Glennis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA, USA
| | - Pragya Sidhwani
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Sasha A. Langley
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Lev Uralsky
- Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
| | | | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | | | | | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | | | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Olga Kunyavskaya
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Ryan Lorig-Roach
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Daniel Olson
- Department of Computer Science, University of Montana, Missoula, MT. USA
| | | | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | | | - Fedor Gusev
- Vavilov Institute of General Genetics, Moscow, Russia
| | - Kristof Tigyi
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Shelise Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alice Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sofie R. Salama
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Gary H. Karpen
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- BioEngineering and BioMedical Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Abby F. Dernburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Travis J. Wheeler
- Department of Computer Science, University of Montana, Missoula, MT. USA
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research, Kansas City, MO, USA
- University of Kansas Medical School, Department of Biochemistry and Molecular Biology and Cancer Center, University of Kansas, Kansas City, KS, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | - Rachel J. O'Neill
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California at San Diego, San Diego, CA, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Charles H. Langley
- Department of Evolution and Ecology, University of California Davis, Davis, CA, USA
| | - Ivan A. Alexandrov
- Vavilov Institute of General Genetics, Moscow, Russia
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
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19
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Aganezov S, Yan SM, Soto DC, Kirsche M, Zarate S, Avdeyev P, Taylor DJ, Shafin K, Shumate A, Xiao C, Wagner J, McDaniel J, Olson ND, Sauria MEG, Vollger MR, Rhie A, Meredith M, Martin S, Lee J, Koren S, Rosenfeld JA, Paten B, Layer R, Chin CS, Sedlazeck FJ, Hansen NF, Miller DE, Phillippy AM, Miga KH, McCoy RC, Dennis MY, Zook JM, Schatz MC. A complete reference genome improves analysis of human genetic variation. Science 2022; 376:eabl3533. [PMID: 35357935 DOI: 10.1126/science.abl3533] [Citation(s) in RCA: 94] [Impact Index Per Article: 47.0] [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
Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.
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Affiliation(s)
- Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie M Yan
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Daniela C Soto
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel Avdeyev
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Dylan J Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, USA
| | - Justin Wagner
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jennifer McDaniel
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Melissa Meredith
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Skylar Martin
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | - Sergey Koren
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Ryan Layer
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | | | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nancy F Hansen
- Comparative Genomics Analysis Unit, National Human Genome Research Institute, Rockville, MD, USA
| | - Danny E Miller
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA, USA
| | - Adam M Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y Dennis
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.,Department of Biology, Johns Hopkins University, Baltimore, MD, USA.,Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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20
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Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, Alonge M, Antonarakis SE, Borchers M, Bouffard GG, Brooks SY, Caldas GV, Chen NC, Cheng H, Chin CS, Chow W, de Lima LG, Dishuck PC, Durbin R, Dvorkina T, Fiddes IT, Formenti G, Fulton RS, Fungtammasan A, Garrison E, Grady PG, Graves-Lindsay TA, Hall IM, Hansen NF, Hartley GA, Haukness M, Howe K, Hunkapiller MW, Jain C, Jain M, Jarvis ED, Kerpedjiev P, Kirsche M, Kolmogorov M, Korlach J, Kremitzki M, Li H, Maduro VV, Marschall T, McCartney AM, McDaniel J, Miller DE, Mullikin JC, Myers EW, Olson ND, Paten B, Peluso P, Pevzner PA, Porubsky D, Potapova T, Rogaev EI, Rosenfeld JA, Salzberg SL, Schneider VA, Sedlazeck FJ, Shafin K, Shew CJ, Shumate A, Sims Y, Smit AFA, Soto DC, Sović I, Storer JM, Streets A, Sullivan BA, Thibaud-Nissen F, Torrance J, Wagner J, Walenz BP, Wenger A, Wood JMD, Xiao C, Yan SM, Young AC, Zarate S, Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O’Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM. The complete sequence of a human genome. Science 2022; 376:44-53. [PMID: 35357919 PMCID: PMC9186530 DOI: 10.1126/science.abj6987] [Citation(s) in RCA: 894] [Impact Index Per Article: 447.0] [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] [Indexed: 12/11/2022]
Abstract
Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.
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Affiliation(s)
- Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego; La Jolla, CA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Nicolas Altemose
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
| | - Lev Uralsky
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Michael Alonge
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | | | | | - Gerard G. Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Shelise Y. Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | | | | | | | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Richard Durbin
- Wellcome Sanger Institute; Cambridge, UK
- Department of Genetics, University of Cambridge; Cambridge, UK
| | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | | | - Giulio Formenti
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Robert S. Fulton
- Department of Genetics, Washington University School of Medicine; St. Louis, MO, USA
| | | | - Erik Garrison
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- University of Tennessee Health Science Center; Memphis, TN, USA
| | - Patrick G.S. Grady
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | | | - Ira M. Hall
- Department of Genetics, Yale University School of Medicine; New Haven, CT, USA
| | - Nancy F. Hansen
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | | | - Chirag Jain
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
- Department of Computational and Data Sciences, Indian Institute of Science; Bangalore KA, India
| | - Miten Jain
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Erich D. Jarvis
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | | | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | | | - Milinn Kremitzki
- McDonnell Genome Institute, Washington University in St. Louis; St. Louis, MO, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | - Valerie V. Maduro
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Tobias Marschall
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics; Düsseldorf, Germany
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Jennifer McDaniel
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Danny E. Miller
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital; Seattle, WA, USA
| | - James C. Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Eugene W. Myers
- Max-Planck Institute of Molecular Cell Biology and Genetics; Dresden, Germany
| | - Nathan D. Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research; Kansas City, MO, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School; Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University; Moscow, Russia
| | | | - Steven L. Salzberg
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine; Houston TX, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Ying Sims
- Wellcome Sanger Institute; Cambridge, UK
| | | | - Daniela C. Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan Sović
- Pacific Biosciences; Menlo Park, CA, USA
- Digital BioLogic d.o.o.; Ivanić-Grad, Croatia
| | | | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
- Chan Zuckerberg Biohub; San Francisco, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine; Durham, NC, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | | | - Justin Wagner
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Brian P. Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Stephanie M. Yan
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Alice C. Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Urvashi Surti
- Department of Pathology, University of Pittsburgh; Pittsburgh, PA, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan A. Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences; Moscow, Russia
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research; Kansas City, MO, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical School; Kansas City, MO, USA
| | - Rachel J. O’Neill
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
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21
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Pan B, Ren L, Onuchic V, Guan M, Kusko R, Bruinsma S, Trigg L, Scherer A, Ning B, Zhang C, Glidewell-Kenney C, Xiao C, Donaldson E, Sedlazeck FJ, Schroth G, Yavas G, Grunenwald H, Chen H, Meinholz H, Meehan J, Wang J, Yang J, Foox J, Shang J, Miclaus K, Dong L, Shi L, Mohiyuddin M, Pirooznia M, Gong P, Golshani R, Wolfinger R, Lababidi S, Sahraeian SME, Sherry S, Han T, Chen T, Shi T, Hou W, Ge W, Zou W, Guo W, Bao W, Xiao W, Fan X, Gondo Y, Yu Y, Zhao Y, Su Z, Liu Z, Tong W, Xiao W, Zook JM, Zheng Y, Hong H. Assessing reproducibility of inherited variants detected with short-read whole genome sequencing. Genome Biol 2022; 23:2. [PMID: 34980216 PMCID: PMC8722114 DOI: 10.1186/s13059-021-02569-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. RESULTS To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. CONCLUSIONS Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.
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Affiliation(s)
- Bohu Pan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Luyao Ren
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | | | | | | | - Len Trigg
- Real Time Genomics, Hamilton, New Zealand
| | - Andreas Scherer
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, the Netherlands
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Chaoyang Zhang
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
| | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Eric Donaldson
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Gokhan Yavas
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | | | | | - Joe Meehan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Jing Wang
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100013, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Jun Shang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | - Lianhua Dong
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100013, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ping Gong
- Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS, 39180, USA
| | | | | | - Samir Lababidi
- Office of Health Informatics, Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | | | - Steve Sherry
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Tao Han
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tao Chen
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tieliu Shi
- The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Weigong Ge
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wen Zou
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenjing Guo
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenjun Bao
- SAS Institute Inc., Cary, NC, 27513, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, 94305, USA
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yoichi Gondo
- Department of Molecular Life Sciences, Tokai University School of Medicine, 143 Shimokasuya, Isehara, 259-1193, Japan
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Yongmei Zhao
- CCR-SF Bioinformatics Group, Advanced Biomedical and Computational Sciences, Biomedical Informatics and Data Science, Frederick National Laboratory for Cancer Research, Frederick, MD, 21701, USA
| | - Zhenqiang Su
- Takeda Pharmaceuticals, Cambridge, MA, 02139, USA
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenming Xiao
- Division of Molecular Genetics and Pathology, Center for Device and Radiological Health, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 200438, China.
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
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22
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Foox J, Tighe SW, Nicolet CM, Zook JM, Byrska-Bishop M, Clarke WE, Khayat MM, Mahmoud M, Laaguiby PK, Herbert ZT, Warner D, Grills GS, Jen J, Levy S, Xiang J, Alonso A, Zhao X, Zhang W, Teng F, Zhao Y, Lu H, Schroth GP, Narzisi G, Farmerie W, Sedlazeck FJ, Baldwin DA, Mason CE. Author Correction: Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study. Nat Biotechnol 2021; 39:1466. [PMID: 34635840 DOI: 10.1038/s41587-021-01122-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Scott W Tighe
- University of Vermont Cancer Center, Vermont Integrative Genomics Resource, University of Vermont, Burlington, VT, USA
| | - Charles M Nicolet
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Justin M Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | | | - Michael M Khayat
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Phoebe K Laaguiby
- University of Vermont Cancer Center, Vermont Integrative Genomics Resource, University of Vermont, Burlington, VT, USA
| | - Zachary T Herbert
- Molecular Biology Core Facilities, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Derek Warner
- DNA Sequencing Core, University of Utah, Salt Lake City, UT, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA
| | - Jin Jen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Shawn Levy
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Jenny Xiang
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Alicia Alonso
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Xia Zhao
- BGI-Shenzhen, Shenzhen, China.,MGI, BGI-Shenzhen, Shenzhen, China
| | | | | | - Yonggang Zhao
- BGI-Shenzhen, Shenzhen, China.,Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Haorong Lu
- BGI-Shenzhen, Shenzhen, China.,Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, China
| | | | | | - William Farmerie
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA. .,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
| | - Don A Baldwin
- Department of Pathology, Fox Chase Cancer Center, Philadelphia, PA, USA.
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA. .,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. .,The Feil Family Brain and Mind Research Institute, New York, NY, USA. .,The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.
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23
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Foox J, Tighe SW, Nicolet CM, Zook JM, Byrska-Bishop M, Clarke WE, Khayat MM, Mahmoud M, Laaguiby PK, Herbert ZT, Warner D, Grills GS, Jen J, Levy S, Xiang J, Alonso A, Zhao X, Zhang W, Teng F, Zhao Y, Lu H, Schroth GP, Narzisi G, Farmerie W, Sedlazeck FJ, Baldwin DA, Mason CE. Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study. Nat Biotechnol 2021; 39:1129-1140. [PMID: 34504351 PMCID: PMC8985210 DOI: 10.1038/s41587-021-01049-5] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 08/05/2021] [Indexed: 02/08/2023]
Abstract
Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.
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Affiliation(s)
- Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Scott W. Tighe
- University of Vermont Cancer Center, Vermont Integrative Genomics Resource, University of Vermont, Burlington, VT, USA
| | - Charles M. Nicolet
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | | | - Michael M. Khayat
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Phoebe K. Laaguiby
- University of Vermont Cancer Center, Vermont Integrative Genomics Resource, University of Vermont, Burlington, VT, USA
| | - Zachary T. Herbert
- Molecular Biology Core Facilities, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Derek Warner
- DNA Sequencing Core, University of Utah, Salt Lake City, UT, USA
| | - George S. Grills
- Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA
| | - Jin Jen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Shawn Levy
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Jenny Xiang
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Alicia Alonso
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Xia Zhao
- BGI-Shenzhen, Shenzhen, China.,MGI, BGI-Shenzhen, Shenzhen, China
| | | | | | - Yonggang Zhao
- BGI-Shenzhen, Shenzhen, China.,Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Haorong Lu
- BGI-Shenzhen, Shenzhen, China.,Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, China
| | | | | | - William Farmerie
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Correspondence and requests for materials should be addressed to Fritz J. Sedlazeck, Don A. Baldwin or Christopher E. Mason. ; ;
| | - Don A. Baldwin
- Department of Pathology, Fox Chase Cancer Center, Philadelphia, PA, USA.,Correspondence and requests for materials should be addressed to Fritz J. Sedlazeck, Don A. Baldwin or Christopher E. Mason. ; ;
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.,The Feil Family Brain and Mind Research Institute, New York, NY, USA.,The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.,Correspondence and requests for materials should be addressed to Fritz J. Sedlazeck, Don A. Baldwin or Christopher E. Mason. ; ;
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24
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Affiliation(s)
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD 20899
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25
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Garg S, Fungtammasan A, Carroll A, Chou M, Schmitt A, Zhou X, Mac S, Peluso P, Hatas E, Ghurye J, Maguire J, Mahmoud M, Cheng H, Heller D, Zook JM, Moemke T, Marschall T, Sedlazeck FJ, Aach J, Chin CS, Church GM, Li H. Chromosome-scale, haplotype-resolved assembly of human genomes. Nat Biotechnol 2020; 39:309-312. [PMID: 33288905 PMCID: PMC7954703 DOI: 10.1038/s41587-020-0711-0] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [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: 10/21/2019] [Revised: 09/09/2020] [Accepted: 09/17/2020] [Indexed: 12/14/2022]
Abstract
Haplotype-resolved or phased genome assembly provides a complete picture of genomes and their complex genetic variations. However, current algorithms for phased assembly either do not generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method named diploid assembly (DipAsm) that uses long, accurate reads and long-range conformation data for single individuals to generate a chromosome-scale phased assembly within 1 day. Applied to four public human genomes, PGP1, HG002, NA12878 and HG00733, DipAsm produced haplotype-resolved assemblies with minimum contig length needed to cover 50% of the known genome (NG50) up to 25 Mb and phased ~99.5% of heterozygous sites at 98–99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies for the discovery of structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as the human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) regions. DipAsm will facilitate high-quality precision medicine and studies of individual haplotype variation and population diversity. Assembly of phased human genomes is achieved by combining long reads and long-range conformational data.
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Affiliation(s)
- Shilpa Garg
- Department of Genetics, Harvard Medical School, Boston, MA, USA. .,Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA. .,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | | | | | - Mike Chou
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | | | | | | | | | | | - Jay Ghurye
- Dovetail Genomics, Scotts Valley, CA, USA
| | | | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - David Heller
- Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Tobias Marschall
- Saarland University, Saarbrücken, Germany.,Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - John Aach
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | | | - George M Church
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA. .,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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26
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Chin CS, Wagner J, Zeng Q, Garrison E, Garg S, Fungtammasan A, Rautiainen M, Aganezov S, Kirsche M, Zarate S, Schatz MC, Xiao C, Rowell WJ, Markello C, Farek J, Sedlazeck FJ, Bansal V, Yoo B, Miller N, Zhou X, Carroll A, Barrio AM, Salit M, Marschall T, Dilthey AT, Zook JM. A diploid assembly-based benchmark for variants in the major histocompatibility complex. Nat Commun 2020; 11:4794. [PMID: 32963235 PMCID: PMC7508831 DOI: 10.1038/s41467-020-18564-9] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 08/27/2020] [Indexed: 01/20/2023] Open
Abstract
Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks.
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Affiliation(s)
- Chen-Shan Chin
- DNAnexus, Inc, 1975 W El Camino Real, Suite 204, Mountain View, CA, 94040, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD, 20899, USA
| | - Qiandong Zeng
- Laboratory Corporation of America Holdings, 3400 Computer Drive, Westborough, MA, 01581, USA
| | - Erik Garrison
- University of California, Santa Cruz, 1156 High St, Santa Cruz, CA, 95064, USA
| | - Shilpa Garg
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | | | - Mikko Rautiainen
- Center for Bioinformatics, Saarland University, Saarland Informatics Campus E2.1, 66123, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, 66123, Saarbrücken, Germany
- Saarland Graduate School for Computer Science, Saarland Informatics Campus E1.3, 66123, Saarbrücken, Germany
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, NY, 11724, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA
| | | | - Charles Markello
- University of California, Santa Cruz, 1156 High St, Santa Cruz, CA, 95064, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Vikas Bansal
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Byunggil Yoo
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Neil Miller
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Xin Zhou
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
| | - Andrew Carroll
- Google Inc, 1600 Amphitheatre Pkwy, Mountain View, CA, 94043, USA
| | | | - Marc Salit
- Joint Initiative for Metrology in Biology, Stanford, CA, 94305, USA
| | - Tobias Marschall
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Alexander T Dilthey
- Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD, 20899, USA.
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27
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Shafin K, Pesout T, Lorig-Roach R, Haukness M, Olsen HE, Bosworth C, Armstrong J, Tigyi K, Maurer N, Koren S, Sedlazeck FJ, Marschall T, Mayes S, Costa V, Zook JM, Liu KJ, Kilburn D, Sorensen M, Munson KM, Vollger MR, Monlong J, Garrison E, Eichler EE, Salama S, Haussler D, Green RE, Akeson M, Phillippy A, Miga KH, Carnevali P, Jain M, Paten B. Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes. Nat Biotechnol 2020; 38:1044-1053. [PMID: 32686750 PMCID: PMC7483855 DOI: 10.1038/s41587-020-0503-6] [Citation(s) in RCA: 209] [Impact Index Per Article: 52.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Accepted: 03/26/2020] [Indexed: 01/05/2023]
Abstract
De novo assembly of a human genome using nanopore long-read sequences has been reported, but it used more than 150,000 CPU hours and weeks of wall-clock time. To enable rapid human genome assembly, we present Shasta, a de novo long-read assembler, and polishing algorithms named MarginPolish and HELEN. Using a single PromethION nanopore sequencer and our toolkit, we assembled 11 highly contiguous human genomes de novo in 9 d. We achieved roughly 63× coverage, 42-kb read N50 values and 6.5× coverage in reads >100 kb using three flow cells per sample. Shasta produced a complete haploid human genome assembly in under 6 h on a single commercial compute node. MarginPolish and HELEN polished haploid assemblies to more than 99.9% identity (Phred quality score QV = 30) with nanopore reads alone. Addition of proximity-ligation sequencing enabled near chromosome-level scaffolds for all 11 genomes. We compare our assembly performance to existing methods for diploid, haploid and trio-binned human samples and report superior accuracy and speed.
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Affiliation(s)
| | - Trevor Pesout
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | | | | | - Hugh E Olsen
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | | | | | - Kristof Tigyi
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, USA
| | | | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Fritz J Sedlazeck
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | | | | | | | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | | | - Melanie Sorensen
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katy M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jean Monlong
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | - Erik Garrison
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | - Evan E Eichler
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sofie Salama
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, USA
| | - David Haussler
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, USA
| | | | - Mark Akeson
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | - Adam Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | | | - Miten Jain
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA.
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28
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Shumate A, Zimin AV, Sherman RM, Puiu D, Wagner JM, Olson ND, Pertea M, Salit ML, Zook JM, Salzberg SL. Assembly and annotation of an Ashkenazi human reference genome. Genome Biol 2020; 21:129. [PMID: 32487205 PMCID: PMC7265644 DOI: 10.1186/s13059-020-02047-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [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: 04/06/2020] [Accepted: 05/15/2020] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Thousands of experiments and studies use the human reference genome as a resource each year. This single reference genome, GRCh38, is a mosaic created from a small number of individuals, representing a very small sample of the human population. There is a need for reference genomes from multiple human populations to avoid potential biases. RESULTS Here, we describe the assembly and annotation of the genome of an Ashkenazi individual and the creation of a new, population-specific human reference genome. This genome is more contiguous and more complete than GRCh38, the latest version of the human reference genome, and is annotated with highly similar gene content. The Ashkenazi reference genome, Ash1, contains 2,973,118,650 nucleotides as compared to 2,937,639,212 in GRCh38. Annotation identified 20,157 protein-coding genes, of which 19,563 are > 99% identical to their counterparts on GRCh38. Most of the remaining genes have small differences. Forty of the protein-coding genes in GRCh38 are missing from Ash1; however, all of these genes are members of multi-gene families for which Ash1 contains other copies. Eleven genes appear on different chromosomes from their homologs in GRCh38. Alignment of DNA sequences from an unrelated Ashkenazi individual to Ash1 identified ~ 1 million fewer homozygous SNPs than alignment of those same sequences to the more-distant GRCh38 genome, illustrating one of the benefits of population-specific reference genomes. CONCLUSIONS The Ash1 genome is presented as a reference for any genetic studies involving Ashkenazi Jewish individuals.
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Affiliation(s)
- Alaina Shumate
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Aleksey V Zimin
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Rachel M Sherman
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Daniela Puiu
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Justin M Wagner
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Mihaela Pertea
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Marc L Salit
- Joint Initiative for Metrology in Biology, Stanford University, Stanford, CA, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Steven L Salzberg
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
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29
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Chapman LM, Spies N, Pai P, Lim CS, Carroll A, Narzisi G, Watson CM, Proukakis C, Clarke WE, Nariai N, Dawson E, Jones G, Blankenberg D, Brueffer C, Xiao C, Kolora SRR, Alexander N, Wolujewicz P, Ahmed AE, Smith G, Shehreen S, Wenger AM, Salit M, Zook JM. A crowdsourced set of curated structural variants for the human genome. PLoS Comput Biol 2020; 16:e1007933. [PMID: 32559231 PMCID: PMC7329145 DOI: 10.1371/journal.pcbi.1007933] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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: 09/19/2019] [Revised: 07/01/2020] [Accepted: 05/07/2020] [Indexed: 11/19/2022] Open
Abstract
A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is more challenging. In this study, we manually curated 1235 SVs, which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app-SVCurator-to help GIAB curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy. SVCurator displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. 'Expert' curators were 93% concordant with each other, and 37 of the 61 curators had at least 78% concordance with a set of 'expert' curators. The curators were least concordant for complex SVs and SVs that had inaccurate breakpoints or size predictions. After filtering events with low concordance among curators, we produced high confidence labels for 935 events. The SVCurator crowdsourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.
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Affiliation(s)
- Lesley M. Chapman
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America
| | - Noah Spies
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America
- The Joint Initiative for Metrology in Biology, Stanford University, Stanford, California, United States of America
- Departments of Genetics and Pathology, Stanford University, Stanford, California, United States of America
| | - Patrick Pai
- University of Maryland - College Park, College Park, Maryland, United States of America
| | - Chun Shen Lim
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Andrew Carroll
- DNAnexus Inc, Mountain View, California, United States of America
| | - Giuseppe Narzisi
- New York Genome Center, New York, New York, United States of America
| | - Christopher M. Watson
- School of Medicine, University of Leeds, Saint James's University Hospital, Leeds, Leeds, United Kingdom
- Yorkshire Regional Genetics Service, The Leeds Teaching Hospitals NHS Trust, Saint James's University Hospital, Leeds, United Kingdom
| | - Christos Proukakis
- University College London, Institute of Neurology, London, United Kingdom
| | - Wayne E. Clarke
- New York Genome Center, New York, New York, United States of America
| | - Naoki Nariai
- Illumina, Inc. San Diego, California, United States of America
| | - Eric Dawson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, United States of America
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Garan Jones
- University of Exeter Medical School, Epidemiology and Public Health Group, Barrack Road, Exeter, Devon, United Kingdom
| | - Daniel Blankenberg
- Genomic Medicine Institute Lerner Research Institute Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Christian Brueffer
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Sree Rohit Raj Kolora
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Leipzig, Germany
- Molecular Evolution and Systematics of Animals, Institute of Biology, University of Leipzig, Leipzig, Germany
| | - Noah Alexander
- Molecular Biology Institute, University of California Los Angeles, Los Angeles, California, United States of America
| | - Paul Wolujewicz
- Weill Cornell, Belfer Research Building, New York, New York, United States of America
| | - Azza E. Ahmed
- Center for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum and Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Khartoum, Khartoum, Sudan
| | - Graeme Smith
- Guy's Hospital and St Thomas's NHS Foundation Trust Great Maze Pond, London, United Kingdom
| | - Saadlee Shehreen
- Department of Genetic Engineering & Biotechnology, University of Dhaka, Bangladesh
| | - Aaron M. Wenger
- Pacific Biosciences, Menlo Park, California, United States of America
| | - Marc Salit
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America
- The Joint Initiative for Metrology in Biology, Stanford University, Stanford, California, United States of America
| | - Justin M. Zook
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America
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30
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Llamas B, Narzisi G, Schneider V, Audano PA, Biederstedt E, Blauvelt L, Bradbury P, Chang X, Chin CS, Fungtammasan A, Clarke WE, Cleary A, Ebler J, Eizenga J, Sibbesen JA, Markello CJ, Garrison E, Garg S, Hickey G, Lazo GR, Lin MF, Mahmoud M, Marschall T, Minkin I, Monlong J, Musunuri RL, Sagayaradj S, Novak AM, Rautiainen M, Regier A, Sedlazeck FJ, Siren J, Souilmi Y, Wagner J, Wrightsman T, Yokoyama TT, Zeng Q, Zook JM, Paten B, Busby B. A strategy for building and using a human reference pangenome. F1000Res 2019; 8:1751. [PMID: 34386196 PMCID: PMC8350888 DOI: 10.12688/f1000research.19630.1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/23/2021] [Indexed: 01/27/2024] Open
Abstract
In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.
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Affiliation(s)
- Bastien Llamas
- Australian Centre for Ancient DNA, School of Biological Sciences, Environment Institute, The University of Adelaide, Adelaide, South Australia, 5005, Australia
| | | | - Valerie Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Peter A. Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Evan Biederstedt
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02215, USA
| | - Lon Blauvelt
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Peter Bradbury
- Robert W. Holley Center, USDA-ARS, Ithaca, NY, 14853, USA
| | - Xian Chang
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | | | | | - Alan Cleary
- National Center for Genome Resources 87505, Santa Fe, NM, 87505, USA
| | - Jana Ebler
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Jordan Eizenga
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Jonas A. Sibbesen
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Charles J. Markello
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Erik Garrison
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Shilpa Garg
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
| | - Glenn Hickey
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Gerard R. Lazo
- Western Regional Research Center, USDA-ARS, Albany, CA, 94710-1105, USA
| | | | - Medhat Mahmoud
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston TX, TX, 77030, USA
| | | | - Ilia Minkin
- Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Jean Monlong
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | - Sagayamary Sagayaradj
- Genome Center, University of California, Davis, Davis, CA, USA
- BASF, West Sacramento, CA, USA
| | - Adam M. Novak
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | - Allison Regier
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, 63108, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston TX, TX, 77030, USA
| | - Jouni Siren
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Yassine Souilmi
- Australian Centre for Ancient DNA, School of Biological Sciences, Environment Institute, The University of Adelaide, Adelaide, South Australia, 5005, Australia
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Travis Wrightsman
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14853, USA
| | - Toshiyuki T. Yokoyama
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Qiandong Zeng
- Laboratory Corporation of America Holdings, Westborough, MA, 01581, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Ben Busby
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
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Llamas B, Narzisi G, Schneider V, Audano PA, Biederstedt E, Blauvelt L, Bradbury P, Chang X, Chin CS, Fungtammasan A, Clarke WE, Cleary A, Ebler J, Eizenga J, Sibbesen JA, Markello CJ, Garrison E, Garg S, Hickey G, Lazo GR, Lin MF, Mahmoud M, Marschall T, Minkin I, Monlong J, Musunuri RL, Sagayaradj S, Novak AM, Rautiainen M, Regier A, Sedlazeck FJ, Siren J, Souilmi Y, Wagner J, Wrightsman T, Yokoyama TT, Zeng Q, Zook JM, Paten B, Busby B. A strategy for building and using a human reference pangenome. F1000Res 2019; 8:1751. [PMID: 34386196 PMCID: PMC8350888 DOI: 10.12688/f1000research.19630.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/23/2021] [Indexed: 11/20/2022] Open
Abstract
In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.
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Affiliation(s)
- Bastien Llamas
- Australian Centre for Ancient DNA, School of Biological Sciences, Environment Institute, The University of Adelaide, Adelaide, South Australia, 5005, Australia
| | | | - Valerie Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Evan Biederstedt
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02215, USA
| | - Lon Blauvelt
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Peter Bradbury
- Robert W. Holley Center, USDA-ARS, Ithaca, NY, 14853, USA
| | - Xian Chang
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | | | | | - Alan Cleary
- National Center for Genome Resources 87505, Santa Fe, NM, 87505, USA
| | - Jana Ebler
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Jordan Eizenga
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Jonas A Sibbesen
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Charles J Markello
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Erik Garrison
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Shilpa Garg
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
| | - Glenn Hickey
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Gerard R Lazo
- Western Regional Research Center, USDA-ARS, Albany, CA, 94710-1105, USA
| | | | - Medhat Mahmoud
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston TX, TX, 77030, USA
| | | | - Ilia Minkin
- Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Jean Monlong
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | - Sagayamary Sagayaradj
- Genome Center, University of California, Davis, Davis, CA, USA.,BASF, West Sacramento, CA, USA
| | - Adam M Novak
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | - Allison Regier
- McDonnell Genome Institute, Washington University in St Louis, St Louis, MO, 63108, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston TX, TX, 77030, USA
| | - Jouni Siren
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Yassine Souilmi
- Australian Centre for Ancient DNA, School of Biological Sciences, Environment Institute, The University of Adelaide, Adelaide, South Australia, 5005, Australia
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Travis Wrightsman
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14853, USA
| | - Toshiyuki T Yokoyama
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Qiandong Zeng
- Laboratory Corporation of America Holdings, Westborough, MA, 01581, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Ben Busby
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
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32
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Wenger AM, Peluso P, Rowell WJ, Chang PC, Hall RJ, Concepcion GT, Ebler J, Fungtammasan A, Kolesnikov A, Olson ND, Töpfer A, Alonge M, Mahmoud M, Qian Y, Chin CS, Phillippy AM, Schatz MC, Myers G, DePristo MA, Ruan J, Marschall T, Sedlazeck FJ, Zook JM, Li H, Koren S, Carroll A, Rank DR, Hunkapiller MW. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat Biotechnol 2019; 37:1155-1162. [PMID: 31406327 PMCID: PMC6776680 DOI: 10.1038/s41587-019-0217-9] [Citation(s) in RCA: 739] [Impact Index Per Article: 147.8] [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: 01/23/2019] [Accepted: 07/08/2019] [Indexed: 12/30/2022]
Abstract
The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.
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Affiliation(s)
| | | | | | | | | | | | - Jana Ebler
- Center for Bioinformatics, Saarland University, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarbrücken, Germany
- Graduate School of Computer Science, Saarland University, Saarbrücken, Germany
| | | | | | - Nathan D Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Michael Alonge
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Gene Myers
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | | | - Jue Ruan
- Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Tobias Marschall
- Center for Bioinformatics, Saarland University, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Heng Li
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
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33
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Zook JM, McDaniel J, Olson ND, Wagner J, Parikh H, Heaton H, Irvine SA, Trigg L, Truty R, McLean CY, De La Vega FM, Xiao C, Sherry S, Salit M. An open resource for accurately benchmarking small variant and reference calls. Nat Biotechnol 2019; 37:561-566. [PMID: 30936564 PMCID: PMC6500473 DOI: 10.1038/s41587-019-0074-6] [Citation(s) in RCA: 180] [Impact Index Per Article: 36.0] [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: 05/25/2018] [Accepted: 02/19/2019] [Indexed: 12/30/2022]
Abstract
Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a 'first of its kind' resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.
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Affiliation(s)
- Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Hemang Parikh
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Haynes Heaton
- 10x Genomics, Pleasanton, CA, USA
- Wellcome Trust Sanger Institute,, Hinxton, Cambridge, UK
| | | | - Len Trigg
- Real Time Genomics, Hamilton, New Zealand
| | | | - Cory Y McLean
- Verily Life Sciences, South San Francisco, CA, USA
- Google Inc., Mountain View, CA, USA
| | - Francisco M De La Vega
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Stephen Sherry
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Marc Salit
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
- Joint Initiative for Metrology in Biology, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
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34
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Krusche P, Trigg L, Boutros PC, Mason CE, De La Vega FM, Moore BL, Gonzalez-Porta M, Eberle MA, Tezak Z, Lababidi S, Truty R, Asimenos G, Funke B, Fleharty M, Chapman BA, Salit M, Zook JM. Author Correction: Best practices for benchmarking germline small-variant calls in human genomes. Nat Biotechnol 2019; 37:567. [PMID: 30899106 DOI: 10.1038/s41587-019-0108-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In the version of this article initially published online, two pairs of headings were switched with each other in Table 4: "Recall (PCR free)" was switched with "Recall (with PCR)," and "Precision (PCR free)" was switched with "Precision (with PCR)." The error has been corrected in the print, PDF and HTML versions of this article.
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Affiliation(s)
| | - Len Trigg
- Real Time Genomics, Hamilton, New Zealand
| | - Paul C Boutros
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.,The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.,The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Francisco M De La Vega
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | | | | | | | - Zivana Tezak
- Center for Devices and Radiological Health, FDA, Silver Spring, MD, USA
| | - Samir Lababidi
- Office of Health Informatics, Office of the Commissioner, FDA, Silver Spring, MD, USA
| | | | | | | | | | - Brad A Chapman
- Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marc Salit
- Joint Initiative for Metrology in Biology, Stanford University, Stanford, CA, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
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35
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Krusche P, Trigg L, Boutros PC, Mason CE, De La Vega FM, Moore BL, Gonzalez-Porta M, Eberle MA, Tezak Z, Lababidi S, Truty R, Asimenos G, Funke B, Fleharty M, Chapman BA, Salit M, Zook JM. Best practices for benchmarking germline small-variant calls in human genomes. Nat Biotechnol 2019; 37:555-560. [PMID: 30858580 DOI: 10.1038/s41587-019-0054-x] [Citation(s) in RCA: 171] [Impact Index Per Article: 34.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 01/10/2019] [Indexed: 12/12/2022]
Abstract
Standardized benchmarking approaches are required to assess the accuracy of variants called from sequence data. Although variant-calling tools and the metrics used to assess their performance continue to improve, important challenges remain. Here, as part of the Global Alliance for Genomics and Health (GA4GH), we present a benchmarking framework for variant calling. We provide guidance on how to match variant calls with different representations, define standard performance metrics, and stratify performance by variant type and genome context. We describe limitations of high-confidence calls and regions that can be used as truth sets (for example, single-nucleotide variant concordance of two methods is 99.7% inside versus 76.5% outside high-confidence regions). Our web-based app enables comparison of variant calls against truth sets to obtain a standardized performance report. Our approach has been piloted in the PrecisionFDA variant-calling challenges to identify the best-in-class variant-calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and evaluating the results.
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Affiliation(s)
| | - Len Trigg
- Real Time Genomics, Hamilton, New Zealand
| | - Paul C Boutros
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.,The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.,The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Francisco M De La Vega
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | | | | | | | - Zivana Tezak
- Center for Devices and Radiological Health, FDA, Silver Spring, MD, USA
| | - Samir Lababidi
- Office of Health Informatics, Office of the Commissioner, FDA, Silver Spring, MD, USA
| | | | | | | | | | - Brad A Chapman
- Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marc Salit
- Joint Initiative for Metrology in Biology, Stanford University, Stanford, CA, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
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36
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Lincoln SE, Truty R, Lin CF, Zook JM, Paul J, Ramey VH, Salit M, Rehm HL, Nussbaum RL, Lebo MS. A Rigorous Interlaboratory Examination of the Need to Confirm Next-Generation Sequencing-Detected Variants with an Orthogonal Method in Clinical Genetic Testing. J Mol Diagn 2019; 21:318-329. [PMID: 30610921 PMCID: PMC6629256 DOI: 10.1016/j.jmoldx.2018.10.009] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 09/28/2018] [Accepted: 10/24/2018] [Indexed: 12/17/2022] Open
Abstract
Orthogonal confirmation of next-generation sequencing (NGS)-detected germline variants is standard practice, although published studies have suggested that confirmation of the highest-quality calls may not always be necessary. The key question is how laboratories can establish criteria that consistently identify those NGS calls that require confirmation. Most prior studies addressing this question have had limitations: they have been generally of small scale, omitted statistical justification, and explored limited aspects of underlying data. The rigorous definition of criteria that separate high-accuracy NGS calls from those that may or may not be true remains a crucial issue. We analyzed five reference samples and over 80,000 patient specimens from two laboratories. Quality metrics were examined for approximately 200,000 NGS calls with orthogonal data, including 1662 false positives. A classification algorithm used these data to identify a battery of criteria that flag 100% of false positives as requiring confirmation (CI lower bound, 98.5% to 99.8%, depending on variant type) while minimizing the number of flagged true positives. These criteria identify false positives that the previously published criteria miss. Sampling analysis showed that smaller data sets resulted in less effective criteria. Our methodology for determining test- and laboratory-specific criteria can be generalized into a practical approach that can be used by laboratories to reduce the cost and time burdens of confirmation without affecting clinical accuracy.
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Affiliation(s)
| | | | - Chiao-Feng Lin
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, Maryland
| | | | | | - Marc Salit
- National Institute of Standards and Technology, Gaithersburg, Maryland; Joint Initiative for Metrology in Biology, Stanford, California
| | - Heidi L Rehm
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts; Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Robert L Nussbaum
- Invitae, San Francisco, California; Department of Medicine, University of California San Francisco, San Francisco, California
| | - Matthew S Lebo
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
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37
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Cleveland MH, Zook JM, Salit M, Vallone PM. Determining Performance Metrics for Targeted Next-Generation Sequencing Panels Using Reference Materials. J Mol Diagn 2018; 20:583-590. [PMID: 29959024 PMCID: PMC6172655 DOI: 10.1016/j.jmoldx.2018.04.005] [Citation(s) in RCA: 7] [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] [Received: 02/06/2018] [Revised: 03/28/2018] [Accepted: 04/26/2018] [Indexed: 11/20/2022] Open
Abstract
The National Institute of Standards and Technology has developed reference materials for five human genomes. DNA aliquots are available for purchase, and the data, analyses, and high-confidence small variant and homozygous reference calls are freely available on the web. These reference materials are useful for evaluating whole-genome sequencing methods and also can be used to benchmark targeted sequencing panels, which are used commonly in clinical settings. This article describes how to use the Genome in a Bottle samples to obtain performance metrics on any germline-targeted sequencing panel of interest, as well as the limitations of the reference materials. These materials are useful for understanding the limitations of, and optimizing, targeted sequencing panels and associated bioinformatics pipelines. Example figures are presented to illustrate ways to access the performance metrics of targeted sequencing panels, and a table of best practices is included.
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Affiliation(s)
- Megan H Cleveland
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland.
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland
| | - Marc Salit
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland; Joint Initiative for Metrology in Biology, Stanford, California
| | - Peter M Vallone
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland
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38
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Altman RB, Prabhu S, Sidow A, Zook JM, Goldfeder R, Litwack D, Ashley E, Asimenos G, Bustamante CD, Donigan K, Giacomini KM, Johansen E, Khuri N, Lee E, Liang XS, Salit M, Serang O, Tezak Z, Wall DP, Mansfield E, Kass-Hout T. A research roadmap for next-generation sequencing informatics. Sci Transl Med 2017; 8:335ps10. [PMID: 27099173 DOI: 10.1126/scitranslmed.aaf7314] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Next-generation sequencing technologies are fueling a wave of new diagnostic tests. Progress on a key set of nine research challenge areas will help generate the knowledge required to advance effectively these diagnostics to the clinic.
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Affiliation(s)
- Russ B Altman
- Bioengineering, Genetics, and Medicine, Stanford University, Stanford, CA 94305, USA.
| | - Snehit Prabhu
- Biomedical Data Science and Genetics, Stanford University, Stanford, CA 94305, USA
| | - Arend Sidow
- Pathology and Genetics, Stanford University, Stanford, CA 94305, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA. Material Measurement Laboratory, National Institute of Standards and Technology, Stanford University, Stanford, CA 94305, USA
| | - Rachel Goldfeder
- Biomedical Informatics, Stanford University, Stanford, CA 94305, USA
| | - David Litwack
- Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Euan Ashley
- Medicine, Genetics, and Pathology, Stanford University, Stanford, CA 94305, USA
| | | | - Carlos D Bustamante
- Biomedical Data Science and Genetics, Stanford University, Stanford, CA 94305, USA
| | | | - Kathleen M Giacomini
- Bioengineering and Therapeutic Sciences, University of California at San Francisco, San Francisco, CA 94143, USA
| | | | - Natalia Khuri
- Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Eunice Lee
- Food and Drug Administration, Silver Spring, MD 20993, USA
| | | | - Marc Salit
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA. Bioengineering, Stanford University, Stanford, CA 94305, USA. Material Measurement Laboratory, National Institute of Standards and Technology, Stanford University, Stanford, CA 94305, USA
| | | | - Zivana Tezak
- Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Dennis P Wall
- Systems Medicine and Psychiatry, Stanford University, Stanford, CA 94305, USA
| | | | - Taha Kass-Hout
- Food and Drug Administration, Silver Spring, MD 20993, USA
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39
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Abstract
The impact of structural variants (SVs) on a variety of organisms and diseases like cancer has become increasingly evident. Methods for SV detection when studying genomic differences across cells, individuals or populations are being actively developed. Currently, just a few methods are available to compare different SVs callsets, and no specialized methods are available to annotate SVs that account for the unique characteristics of these variant types. Here, we introduce SURVIVOR_ant, a tool that compares types and breakpoints for candidate SVs from different callsets and enables fast comparison of SVs to genomic features such as genes and repetitive regions, as well as to previously established SV datasets such as from the 1000 Genomes Project. As proof of concept we compared 16 SV callsets generated by different SV calling methods on a single genome, the Genome in a Bottle sample HG002 (Ashkenazi son), and annotated the SVs with gene annotations, 1000 Genomes Project SV calls, and four different types of repetitive regions. Computation time to annotate 134,528 SVs with 33,954 of annotations was 22 seconds on a laptop.
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Affiliation(s)
- Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Andi Dhroso
- Worcester Polytechnic Institute, Worcester, MA, USA
| | - Dale L Bodian
- Inova Translational Medicine Institute, Inova Health System, Falls Church, VA, USA
| | | | | | - Justin M Zook
- Genome-scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, MD, USA
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40
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Olson ND, Zook JM, Morrow JB, Lin NJ. Challenging a bioinformatic tool's ability to detect microbial contaminants using in silico whole genome sequencing data. PeerJ 2017; 5:e3729. [PMID: 28924496 PMCID: PMC5600177 DOI: 10.7717/peerj.3729] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 08/02/2017] [Indexed: 12/20/2022] Open
Abstract
High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus, Escherichia, and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.
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Affiliation(s)
- Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, United States of America
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, United States of America
| | - Jayne B Morrow
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, United States of America
| | - Nancy J Lin
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, United States of America
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41
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Lubin IM, Aziz N, Babb LJ, Ballinger D, Bisht H, Church DM, Cordes S, Eilbeck K, Hyland F, Kalman L, Landrum M, Lockhart ER, Maglott D, Marth G, Pfeifer JD, Rehm HL, Roy S, Tezak Z, Truty R, Ullman-Cullere M, Voelkerding KV, Worthey EA, Zaranek AW, Zook JM. Principles and Recommendations for Standardizing the Use of the Next-Generation Sequencing Variant File in Clinical Settings. J Mol Diagn 2017; 19:417-426. [PMID: 28315672 DOI: 10.1016/j.jmoldx.2016.12.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [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: 07/22/2016] [Revised: 12/05/2016] [Accepted: 12/23/2016] [Indexed: 11/30/2022] Open
Abstract
A national workgroup convened by the Centers for Disease Control and Prevention identified principles and made recommendations for standardizing the description of sequence data contained within the variant file generated during the course of clinical next-generation sequence analysis for diagnosing human heritable conditions. The specifications for variant files were initially developed to be flexible with regard to content representation to support a variety of research applications. This flexibility permits variation with regard to how sequence findings are described and this depends, in part, on the conventions used. For clinical laboratory testing, this poses a problem because these differences can compromise the capability to compare sequence findings among laboratories to confirm results and to query databases to identify clinically relevant variants. To provide for a more consistent representation of sequence findings described within variant files, the workgroup made several recommendations that considered alignment to a common reference sequence, variant caller settings, use of genomic coordinates, and gene and variant naming conventions. These recommendations were considered with regard to the existing variant file specifications presently used in the clinical setting. Adoption of these recommendations is anticipated to reduce the potential for ambiguity in describing sequence findings and facilitate the sharing of genomic data among clinical laboratories and other entities.
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Affiliation(s)
- Ira M Lubin
- Division of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, Georgia.
| | - Nazneen Aziz
- College of American Pathologists, Chicago, Illinois; Kaiser Permanente Research Bank, Oakland, California
| | - Lawrence J Babb
- Partners Healthcare Personalized Medicine, Cambridge, Massachusetts; GeneInsight, a Sunquest Company, Boston, Massachusetts
| | | | - Himani Bisht
- Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland
| | - Deanna M Church
- Personalis, Menlo Park, California; National Center for Biotechnology Information, NIH, Bethesda, Maryland; 10× Genomics, Pleasanton, California
| | | | - Karen Eilbeck
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah
| | | | - Lisa Kalman
- Division of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Melissa Landrum
- National Center for Biotechnology Information, NIH, Bethesda, Maryland
| | - Edward R Lockhart
- Division of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Donna Maglott
- National Center for Biotechnology Information, NIH, Bethesda, Maryland
| | - Gabor Marth
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, Utah; Boston College, Chestnut Hill, Massachusetts
| | - John D Pfeifer
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri
| | - Heidi L Rehm
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Somak Roy
- Division of Molecular and Genomic Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Zivana Tezak
- Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland
| | - Rebecca Truty
- Complete Genomics, Mountain View, California; Invitae Corporation, San Francisco, California
| | | | - Karl V Voelkerding
- Department of Pathology, University of Utah and the Institute for Clinical and Experimental Pathology, Associated Regional and University Pathologists Laboratories, Salt Lake City, Utah
| | - Elizabeth A Worthey
- Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Alexander W Zaranek
- Personal Genome Project, Harvard Medical School, Boston, Massachusetts; Curoverse, Inc., Somerville, Massachusetts
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland
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42
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Kalman LV, Datta V, Williams M, Zook JM, Salit ML, Han JY. Development and Characterization of Reference Materials for Genetic Testing: Focus on Public Partnerships. Ann Lab Med 2017; 36:513-20. [PMID: 27578503 PMCID: PMC5011103 DOI: 10.3343/alm.2016.36.6.513] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Revised: 05/08/2016] [Accepted: 07/18/2016] [Indexed: 01/29/2023] Open
Abstract
Characterized reference materials (RMs) are needed for clinical laboratory test development and validation, quality control procedures, and proficiency testing to assure their quality. In this article, we review the development and characterization of RMs for clinical molecular genetic tests. We describe various types of RMs and how to access and utilize them, especially focusing on the Genetic Testing Reference Materials Coordination Program (Get-RM) and the Genome in a Bottle (GIAB) Consortium. This review also reinforces the need for collaborative efforts in the clinical genetic testing community to develop additional RMs.
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Affiliation(s)
- Lisa V Kalman
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Vivekananda Datta
- Frederick National Laboratory for Cancer Research, National Cancer Institute, Gaithersburg, MD, USA
| | - Mickey Williams
- Frederick National Laboratory for Cancer Research, National Cancer Institute, Gaithersburg, MD, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Marc L Salit
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jin Yeong Han
- Department of Laboratory Medicine, Dong-A University College of Medicine, Busan, Korea.
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Zook JM, Catoe D, McDaniel J, Vang L, Spies N, Sidow A, Weng Z, Liu Y, Mason CE, Alexander N, Henaff E, McIntyre AB, Chandramohan D, Chen F, Jaeger E, Moshrefi A, Pham K, Stedman W, Liang T, Saghbini M, Dzakula Z, Hastie A, Cao H, Deikus G, Schadt E, Sebra R, Bashir A, Truty RM, Chang CC, Gulbahce N, Zhao K, Ghosh S, Hyland F, Fu Y, Chaisson M, Xiao C, Trow J, Sherry ST, Zaranek AW, Ball M, Bobe J, Estep P, Church GM, Marks P, Kyriazopoulou-Panagiotopoulou S, Zheng GX, Schnall-Levin M, Ordonez HS, Mudivarti PA, Giorda K, Sheng Y, Rypdal KB, Salit M. Extensive sequencing of seven human genomes to characterize benchmark reference materials. Sci Data 2016; 3:160025. [PMID: 27271295 PMCID: PMC4896128 DOI: 10.1038/sdata.2016.25] [Citation(s) in RCA: 382] [Impact Index Per Article: 47.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 03/15/2016] [Indexed: 02/01/2023] Open
Abstract
The Genome in a Bottle Consortium, hosted by the National Institute of Standards and Technology (NIST) is creating reference materials and data for human genome sequencing, as well as methods for genome comparison and benchmarking. Here, we describe a large, diverse set of sequencing data for seven human genomes; five are current or candidate NIST Reference Materials. The pilot genome, NA12878, has been released as NIST RM 8398. We also describe data from two Personal Genome Project trios, one of Ashkenazim Jewish ancestry and one of Chinese ancestry. The data come from 12 technologies: BioNano Genomics, Complete Genomics paired-end and LFR, Ion Proton exome, Oxford Nanopore, Pacific Biosciences, SOLiD, 10X Genomics GemCode WGS, and Illumina exome and WGS paired-end, mate-pair, and synthetic long reads. Cell lines, DNA, and data from these individuals are publicly available. Therefore, we expect these data to be useful for revealing novel information about the human genome and improving sequencing technologies, SNP, indel, and structural variant calling, and de novo assembly.
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Affiliation(s)
- Justin M. Zook
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - David Catoe
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Jennifer McDaniel
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Lindsay Vang
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Noah Spies
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
- Stanford University, Stanford, California 94305, USA
| | - Arend Sidow
- Stanford University, Stanford, California 94305, USA
| | - Ziming Weng
- Stanford University, Stanford, California 94305, USA
| | - Yuling Liu
- Stanford University, Stanford, California 94305, USA
| | - Christopher E. Mason
- Department of Physiology and Biophysics, the Feil Family Brain and Mind Research Institute, and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, New York 10065, USA
| | - Noah Alexander
- Department of Physiology and Biophysics, the Feil Family Brain and Mind Research Institute, and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, New York 10065, USA
| | - Elizabeth Henaff
- Department of Physiology and Biophysics, the Feil Family Brain and Mind Research Institute, and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, New York 10065, USA
| | - Alexa B.R. McIntyre
- Department of Physiology and Biophysics, the Feil Family Brain and Mind Research Institute, and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, New York 10065, USA
| | - Dhruva Chandramohan
- Department of Physiology and Biophysics, the Feil Family Brain and Mind Research Institute, and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, New York 10065, USA
| | - Feng Chen
- Illumina Mission Bay, San Francisco, California 94158, USA
| | - Erich Jaeger
- Illumina Mission Bay, San Francisco, California 94158, USA
| | - Ali Moshrefi
- Illumina Mission Bay, San Francisco, California 94158, USA
| | - Khoa Pham
- BioNano Genomics, San Diego, California 92121, USA
| | | | | | | | | | - Alex Hastie
- BioNano Genomics, San Diego, California 92121, USA
| | - Han Cao
- BioNano Genomics, San Diego, California 92121, USA
| | - Gintaras Deikus
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Eric Schadt
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Ali Bashir
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | | | | | - Natali Gulbahce
- Complete Genomics Inc., Mountain View, California 94043, USA
| | - Keyan Zhao
- Thermo Fisher Scientific, South San Francisco, California 94080, USA
| | - Srinka Ghosh
- Thermo Fisher Scientific, South San Francisco, California 94080, USA
| | - Fiona Hyland
- Thermo Fisher Scientific, South San Francisco, California 94080, USA
| | - Yutao Fu
- Thermo Fisher Scientific, South San Francisco, California 94080, USA
| | - Mark Chaisson
- Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, Maryland 20892, USA
| | - Jonathan Trow
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, Maryland 20892, USA
| | - Stephen T. Sherry
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, Maryland 20892, USA
| | | | | | - Jason Bobe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- PersonalGenomes.org, Boston, Massachusetts 02115, USA
| | - Preston Estep
- PersonalGenomes.org, Boston, Massachusetts 02115, USA
- Harvard Medical School, Boston, Massachusetts 02115, USA
| | - George M. Church
- PersonalGenomes.org, Boston, Massachusetts 02115, USA
- Harvard Medical School, Boston, Massachusetts 02115, USA
| | | | | | | | | | | | | | | | - Ying Sheng
- Department of Medical Genetics, Oslo University Hospital, Kirkeveien 166, Bygg 25, Oslo 0450, Norway
| | | | - Marc Salit
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
- Stanford University, Stanford, California 94305, USA
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44
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Olson ND, Zook JM, Samarov DV, Jackson SA, Salit ML. PEPR: pipelines for evaluating prokaryotic references. Anal Bioanal Chem 2016; 408:2975-83. [PMID: 26935931 PMCID: PMC4819933 DOI: 10.1007/s00216-015-9299-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 12/21/2015] [Accepted: 12/23/2015] [Indexed: 11/17/2022]
Abstract
The rapid adoption of microbial whole genome sequencing in public health, clinical testing, and forensic laboratories requires the use of validated measurement processes. Well-characterized, homogeneous, and stable microbial genomic reference materials can be used to evaluate measurement processes, improving confidence in microbial whole genome sequencing results. We have developed a reproducible and transparent bioinformatics tool, PEPR, Pipelines for Evaluating Prokaryotic References, for characterizing the reference genome of prokaryotic genomic materials. PEPR evaluates the quality, purity, and homogeneity of the reference material genome, and purity of the genomic material. The quality of the genome is evaluated using high coverage paired-end sequence data; coverage, paired-end read size and direction, as well as soft-clipping rates, are used to identify mis-assemblies. The homogeneity and purity of the material relative to the reference genome are characterized by comparing base calls from replicate datasets generated using multiple sequencing technologies. Genomic purity of the material is assessed by checking for DNA contaminants. We demonstrate the tool and its output using sequencing data while developing a Staphylococcus aureus candidate genomic reference material. PEPR is open source and available at https://github.com/usnistgov/pepr .
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Affiliation(s)
- Nathan D Olson
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
| | - Justin M Zook
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Daniel V Samarov
- Statistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Scott A Jackson
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Marc L Salit
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
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45
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Goldfeder RL, Priest JR, Zook JM, Grove ME, Waggott D, Wheeler MT, Salit M, Ashley EA. Medical implications of technical accuracy in genome sequencing. Genome Med 2016; 8:24. [PMID: 26932475 PMCID: PMC4774017 DOI: 10.1186/s13073-016-0269-0] [Citation(s) in RCA: 84] [Impact Index Per Article: 10.5] [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: 08/21/2015] [Accepted: 01/21/2016] [Indexed: 12/31/2022] Open
Abstract
Background As whole exome sequencing (WES) and whole genome sequencing (WGS) transition from research tools to clinical diagnostic tests, it is increasingly critical for sequencing methods and analysis pipelines to be technically accurate. The Genome in a Bottle Consortium has recently published a set of benchmark SNV, indel, and homozygous reference genotypes for the pilot whole genome NIST Reference Material based on the NA12878 genome. Methods We examine the relationship between human genome complexity and genes/variants reported to be associated with human disease. Specifically, we map regions of medical relevance to benchmark regions of high or low confidence. We use benchmark data to assess the sensitivity and positive predictive value of two representative sequencing pipelines for specific classes of variation. Results We observe that the accuracy of a variant call depends on the genomic region, variant type, and read depth, and varies by analytical pipeline. We find that most false negative WGS calls result from filtering while most false negative WES variants relate to poor coverage. We find that only 74.6 % of the exonic bases in ClinVar and OMIM genes and 82.1 % of the exonic bases in ACMG-reportable genes are found in high-confidence regions. Only 990 genes in the genome are found entirely within high-confidence regions while 593 of 3,300 ClinVar/OMIM genes have less than 50 % of their total exonic base pairs in high-confidence regions. We find greater than 77 % of the pathogenic or likely pathogenic SNVs currently in ClinVar fall within high-confidence regions. We identify sites that are prone to sequencing errors, including thousands present in publicly available variant databases. Finally, we examine the clinical impact of mandatory reporting of secondary findings, highlighting a false positive variant found in BRCA2. Conclusions Together, these data illustrate the importance of appropriate use and continued improvement of technical benchmarks to ensure accurate and judicious interpretation of next-generation DNA sequencing results in the clinical setting. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0269-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Rachel L Goldfeder
- Department of Medicine, Stanford University, Stanford, CA, 94305, USA. .,Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA.
| | - James R Priest
- Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA. .,Department of Pediatrics, Stanford University, Stanford, CA, 94305, USA.
| | - Justin M Zook
- Genome-scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
| | - Megan E Grove
- Department of Medicine, Stanford University, Stanford, CA, 94305, USA. .,Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA.
| | - Daryl Waggott
- Department of Medicine, Stanford University, Stanford, CA, 94305, USA. .,Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA.
| | - Matthew T Wheeler
- Department of Medicine, Stanford University, Stanford, CA, 94305, USA. .,Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA.
| | - Marc Salit
- Genome-scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
| | - Euan A Ashley
- Department of Medicine, Stanford University, Stanford, CA, 94305, USA. .,Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA. .,Department of Genetics, Stanford University, Stanford, CA, 94305, USA.
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46
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Parikh H, Mohiyuddin M, Lam HYK, Iyer H, Chen D, Pratt M, Bartha G, Spies N, Losert W, Zook JM, Salit M. svclassify: a method to establish benchmark structural variant calls. BMC Genomics 2016; 17:64. [PMID: 26772178 PMCID: PMC4715349 DOI: 10.1186/s12864-016-2366-2] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2015] [Accepted: 01/05/2016] [Indexed: 01/24/2023] Open
Abstract
Background The human genome contains variants ranging in size from small single nucleotide polymorphisms (SNPs) to large structural variants (SVs). High-quality benchmark small variant calls for the pilot National Institute of Standards and Technology (NIST) Reference Material (NA12878) have been developed by the Genome in a Bottle Consortium, but no similar high-quality benchmark SV calls exist for this genome. Since SV callers output highly discordant results, we developed methods to combine multiple forms of evidence from multiple sequencing technologies to classify candidate SVs into likely true or false positives. Our method (svclassify) calculates annotations from one or more aligned bam files from many high-throughput sequencing technologies, and then builds a one-class model using these annotations to classify candidate SVs as likely true or false positives. Results We first used pedigree analysis to develop a set of high-confidence breakpoint-resolved large deletions. We then used svclassify to cluster and classify these deletions as well as a set of high-confidence deletions from the 1000 Genomes Project and a set of breakpoint-resolved complex insertions from Spiral Genetics. We find that likely SVs cluster separately from likely non-SVs based on our annotations, and that the SVs cluster into different types of deletions. We then developed a supervised one-class classification method that uses a training set of random non-SV regions to determine whether candidate SVs have abnormal annotations different from most of the genome. To test this classification method, we use our pedigree-based breakpoint-resolved SVs, SVs validated by the 1000 Genomes Project, and assembly-based breakpoint-resolved insertions, along with semi-automated visualization using svviz. Conclusions We find that candidate SVs with high scores from multiple technologies have high concordance with PCR validation and an orthogonal consensus method MetaSV (99.7 % concordant), and candidate SVs with low scores are questionable. We distribute a set of 2676 high-confidence deletions and 68 high-confidence insertions with high svclassify scores from these call sets for benchmarking SV callers. We expect these methods to be particularly useful for establishing high-confidence SV calls for benchmark samples that have been characterized by multiple technologies. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2366-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hemang Parikh
- Genome-Scale Measurements Group, Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8313, Gaithersburg, MD, 20899, USA. .,Dakota Consulting Inc., 1110 Bonifant Street, Suite 310, Silver Spring, MD, 20910, USA.
| | | | - Hugo Y K Lam
- Bina Technologies, Roche Sequencing, Redwood City, CA, 94065, USA.
| | - Hariharan Iyer
- Statistical Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
| | - Desu Chen
- Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, MD, 20742, USA.
| | - Mark Pratt
- Personalis Inc., 1350 Willow Road, Suite 202, Menlo Park, CA, 94025, USA.
| | - Gabor Bartha
- Personalis Inc., 1350 Willow Road, Suite 202, Menlo Park, CA, 94025, USA.
| | - Noah Spies
- Genome-Scale Measurements Group, Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8313, Gaithersburg, MD, 20899, USA. .,Department of Pathology, Stanford University, Stanford, CA, USA.
| | - Wolfgang Losert
- Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, MD, 20742, USA.
| | - Justin M Zook
- Genome-Scale Measurements Group, Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8313, Gaithersburg, MD, 20899, USA.
| | - Marc Salit
- Genome-Scale Measurements Group, Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8313, Gaithersburg, MD, 20899, USA. .,Bioengineering Department, Stanford University, Stanford, CA, USA.
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47
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Spies N, Zook JM, Salit M, Sidow A. svviz: a read viewer for validating structural variants. Bioinformatics 2015; 31:3994-6. [PMID: 26286809 DOI: 10.1093/bioinformatics/btv478] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Accepted: 08/10/2015] [Indexed: 12/14/2022] Open
Abstract
UNLABELLED Visualizing read alignments is the most effective way to validate candidate structural variants (SVs) with existing data. We present svviz, a sequencing read visualizer for SVs that sorts and displays only reads relevant to a candidate SV. svviz works by searching input bam(s) for potentially relevant reads, realigning them against the inferred sequence of the putative variant allele as well as the reference allele and identifying reads that match one allele better than the other. Separate views of the two alleles are then displayed in a scrollable web browser view, enabling a more intuitive visualization of each allele, compared with the single reference genome-based view common to most current read browsers. The browser view facilitates examining the evidence for or against a putative variant, estimating zygosity, visualizing affected genomic annotations and manual refinement of breakpoints. svviz supports data from most modern sequencing platforms. AVAILABILITY AND IMPLEMENTATION svviz is implemented in python and freely available from http://svviz.github.io/.
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Affiliation(s)
- Noah Spies
- Department of Genetics, Stanford University, Department of Pathology, Stanford University, Genome Scale Measurements Group, National Institute of Standards and Technology, Stanford, CA, USA and
| | - Justin M Zook
- Genome Scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Marc Salit
- Genome Scale Measurements Group, National Institute of Standards and Technology, Stanford, CA, USA and
| | - Arend Sidow
- Department of Genetics, Stanford University, Department of Pathology, Stanford University
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Olson ND, Lund SP, Colman RE, Foster JT, Sahl JW, Schupp JM, Keim P, Morrow JB, Salit ML, Zook JM. Best practices for evaluating single nucleotide variant calling methods for microbial genomics. Front Genet 2015. [PMID: 26217378 PMCID: PMC4493402 DOI: 10.3389/fgene.2015.00235] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards.
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Affiliation(s)
- Nathan D Olson
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology , Gaithersburg, MD, USA
| | - Steven P Lund
- Statistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology , Gaithersburg, MD, USA
| | - Rebecca E Colman
- Division of Pathogen Genomics, Translational Genomics Research Institute , Flagstaff, AZ, USA
| | - Jeffrey T Foster
- Center for Microbial Genetics and Genomics, Northern Arizona University , Flagstaff, AZ, USA
| | - Jason W Sahl
- Division of Pathogen Genomics, Translational Genomics Research Institute , Flagstaff, AZ, USA ; Center for Microbial Genetics and Genomics, Northern Arizona University , Flagstaff, AZ, USA
| | - James M Schupp
- Division of Pathogen Genomics, Translational Genomics Research Institute , Flagstaff, AZ, USA
| | - Paul Keim
- Division of Pathogen Genomics, Translational Genomics Research Institute , Flagstaff, AZ, USA ; Center for Microbial Genetics and Genomics, Northern Arizona University , Flagstaff, AZ, USA
| | - Jayne B Morrow
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology , Gaithersburg, MD, USA
| | - Marc L Salit
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology , Gaithersburg, MD, USA ; Department of Bioengineering, Stanford University , Stanford, CA, USA
| | - Justin M Zook
- Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology , Gaithersburg, MD, USA
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Olson ND, Lund SP, Zook JM, Rojas-Cornejo F, Beck B, Foy C, Huggett J, Whale AS, Sui Z, Baoutina A, Dobeson M, Partis L, Morrow JB. International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons. Biomol Detect Quantif 2015; 3:17-24. [PMID: 27077030 PMCID: PMC4822220 DOI: 10.1016/j.bdq.2015.01.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Revised: 01/27/2015] [Accepted: 01/27/2015] [Indexed: 12/30/2022]
Abstract
This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing(®), or Ion Torrent PGM(®). The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies.
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Affiliation(s)
- Nathan D Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, 100 Bureau Dr, Gaithersburg, MD 20899, USA
| | - Steven P Lund
- Statistical Engineering Division, National Institute of Standards and Technology, 100 Bureau Dr, Gaithersburg, MD 20899, USA
| | - Justin M Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, 100 Bureau Dr, Gaithersburg, MD 20899, USA
| | | | - Brian Beck
- American Type Culture Collection, 10801 University Boulevard, Manassas, VA 20110, USA
| | - Carole Foy
- Science and Innovation Division, LGC, Queens Rd, Teddington, Middlesex TW11 0LY, UK
| | - Jim Huggett
- Science and Innovation Division, LGC, Queens Rd, Teddington, Middlesex TW11 0LY, UK
| | - Alexandra S Whale
- Science and Innovation Division, LGC, Queens Rd, Teddington, Middlesex TW11 0LY, UK
| | - Zhiwei Sui
- National Institute of Metrology, Beijing 100013, China
| | - Anna Baoutina
- National Measurement Institute, West Lindfield, NSW 2070, Australia
| | - Michael Dobeson
- National Measurement Institute, West Lindfield, NSW 2070, Australia
| | - Lina Partis
- National Measurement Institute, West Lindfield, NSW 2070, Australia
| | - Jayne B Morrow
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, 100 Bureau Dr, Gaithersburg, MD 20899, USA
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Gargis AS, Kalman L, Berry MW, Bick DP, Dimmock DP, Hambuch T, Lu F, Lyon E, Voelkerding KV, Zehnbauer BA, Agarwala R, Bennett SF, Chen B, Chin ELH, Compton JG, Das S, Farkas DH, Ferber MJ, Funke BH, Furtado MR, Ganova-Raeva LM, Geigenmüller U, Gunselman SJ, Hegde MR, Johnson PLF, Kasarskis A, Kulkarni S, Lenk T, Liu CSJ, Manion M, Manolio TA, Mardis ER, Merker JD, Rajeevan MS, Reese MG, Rehm HL, Simen BB, Yeakley JM, Zook JM, Lubin IM. Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat Biotechnol 2013; 30:1033-6. [PMID: 23138292 DOI: 10.1038/nbt.2403] [Citation(s) in RCA: 381] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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