Analysis of protein-coding genetic variation in 60,706 humans
By
Exome Aggregation Consortium,
Monkol Lek,
Konrad J. Karczewski,
Eric Vallabh Minikel,
Kaitlin E. Samocha,
Eric Banks,
Timothy Fennell,
Anne H. O’Donnell-Luria,
James Ware,
Andrew J. Hill,
Beryl B. Cummings,
Taru Tukiainen,
Daniel P. Birnbaum,
Jack A. Kosmicki,
Laramie E Duncan,
Karol Estrada,
Fengmei Zhao,
James Zou,
Emma Pierce-Hoffman,
Joanne Berghout,
David N. Cooper,
Nicole Deflaux,
Mark DePristo,
Ron Do,
Jason Flannick,
Menachem Fromer,
Laura Gauthier,
Jackie Goldstein,
Namrata Gupta,
Daniel Howrigan,
Adam Kiezun,
Mitja I. Kurki,
Ami Levy Moonshine,
Pradeep Natarajan,
Lorena Orozco,
Gina M Peloso,
Ryan Poplin,
Manuel A. Rivas,
Valentin Ruano-Rubio,
Samuel A Rose,
Douglas M Ruderfer,
Khalid Shakir,
Peter D. Stenson,
Christine Stevens,
Brett P Thomas,
Grace Tiao,
Maria T Tusie-Luna,
Ben Weisburd,
Hong-Hee Won,
Dongmei Yu,
David M Altshuler,
Diego Ardissino,
Michael Boehnke,
John Danesh,
Stacey Donnelly,
Roberto Elosua,
Jose C Florez,
Stacey B Gabriel,
Gad A. Getz,
Stephen J. Glatt,
Christina M Hultman,
Sekar Kathiresan,
Markku Laakso,
Steven McCarroll,
Mark I. McCarthy,
Dermot McGovern,
Ruth McPherson,
Benjamin M. Neale,
Aarno Palotie,
Shaun M Purcell,
Danish Saleheen,
Jeremiah M. Scharf,
Pamela Sklar,
Patrick F Sullivan,
Jaakko Tuomilehto,
Ming T. Tsuang,
Hugh C Watkins,
James G Wilson,
Mark J. Daly,
Daniel G MacArthur
Posted 30 Oct 2015
bioRxiv DOI: 10.1101/030338
(published DOI: 10.1038/nature19057)
Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). The resulting catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We show that this catalogue can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 72% of which have no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human knockout variants in protein-coding genes.
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