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Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.
Taliun, Daniel; Harris, Daniel N; Kessler, Michael D; Carlson, Jedidiah; Szpiech, Zachary A; Torres, Raul; Taliun, Sarah A Gagliano; Corvelo, André; Gogarten, Stephanie M; Kang, Hyun Min; Pitsillides, Achilleas N; LeFaive, Jonathon; Lee, Seung-Been; Tian, Xiaowen; Browning, Brian L; Das, Sayantan; Emde, Anne-Katrin; Clarke, Wayne E; Loesch, Douglas P; Shetty, Amol C; Blackwell, Thomas W; Smith, Albert V; Wong, Quenna; Liu, Xiaoming; Conomos, Matthew P; Bobo, Dean M; Aguet, François; Albert, Christine; Alonso, Alvaro; Ardlie, Kristin G; Arking, Dan E; Aslibekyan, Stella; Auer, Paul L; Barnard, John; Barr, R Graham; Barwick, Lucas; Becker, Lewis C; Beer, Rebecca L; Benjamin, Emelia J; Bielak, Lawrence F; Blangero, John; Boehnke, Michael; Bowden, Donald W; Brody, Jennifer A; Burchard, Esteban G; Cade, Brian E; Casella, James F; Chalazan, Brandon; Chasman, Daniel I; Chen, Yii-Der Ida.
Afiliação
  • Taliun D; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Harris DN; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Kessler MD; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Carlson J; Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Szpiech ZA; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Torres R; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Taliun SAG; Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Corvelo A; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Gogarten SM; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Kang HM; Department of Genome Sciences, University of Washington, Seattle, WA, USA.
  • Pitsillides AN; Department of Biology, Pennsylvania State University, University Park, PA, USA.
  • LeFaive J; Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA, USA.
  • Lee SB; Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
  • Tian X; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Browning BL; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Das S; New York Genome Center, New York, NY, USA.
  • Emde AK; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Clarke WE; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Loesch DP; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Shetty AC; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
  • Blackwell TW; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Smith AV; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Wong Q; Department of Genome Sciences, University of Washington, Seattle, WA, USA.
  • Liu X; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Conomos MP; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA.
  • Bobo DM; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Aguet F; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Albert C; New York Genome Center, New York, NY, USA.
  • Alonso A; New York Genome Center, New York, NY, USA.
  • Ardlie KG; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Arking DE; Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Aslibekyan S; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Auer PL; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Barnard J; Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Barr RG; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Barwick L; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Becker LC; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Beer RL; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Benjamin EJ; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Bielak LF; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Blangero J; USF Genomics, College of Public Health, University of South Florida, Tampa, FL, USA.
  • Boehnke M; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Bowden DW; Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Brody JA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Burchard EG; Massachusetts General Hospital, Boston, MA, USA.
  • Cade BE; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
  • Casella JF; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Chalazan B; McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Chasman DI; University of Alabama, Birmingham, AL, USA.
  • Chen YI; Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI, USA.
Nature ; 590(7845): 290-299, 2021 02.
Article em En | MEDLINE | ID: mdl-33568819
ABSTRACT
The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Variação Genética / Genoma Humano / Genômica / National Heart, Lung, and Blood Institute (U.S.) / Medicina de Precisão Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Nature Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Variação Genética / Genoma Humano / Genômica / National Heart, Lung, and Blood Institute (U.S.) / Medicina de Precisão Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Nature Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos