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Author: Exome Aggregation Consortium
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Research area: genomics
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Analysis of protein-coding genetic variation in 60,706 humans


Created on 10th May 2016

Exome Aggregation Consortium; Monkol Lek; Konrad Karczewski; Eric Minikel; Kaitlin Samocha; Eric Banks; Timothy Fennell; Anne O'Donnell-Luria; James Ware; Andrew Hill; Beryl Cummings; Taru Tukiainen; Daniel Birnbaum; Jack Kosmicki; Laramie Duncan; Karol Estrada; Fengmei Zhao; James Zou; Emma Pierce-Hoffman; Joanne Berghout; David Cooper; Nicole Deflaux; Mark DePristo; Ron Do; Jason Flannick; Menachem Fromer; Laura Gauthier; Jackie Goldstein; Namrata Gupta; Daniel Howrigan; Adam Kiezun; Mitja Kurki; Ami Levy Moonshine; Pradeep Natarajan; Lorena Orozco; Gina Peloso; Ryan Poplin; Manuel Rivas; Valentin Ruano-Rubio; Samuel Rose; Douglas Ruderfer; Khalid Shakir; Peter Stenson; Christine Stevens; Brett Thomas; Grace Tiao; Maria Tusie-Luna; Ben Weisburd; Hong-Hee Won; Dongmei Yu; David Altshuler; Diego Ardissino; Michael Boehnke; John Danesh; Stacey Donnelly; Elosua Roberto; Jose Florez; Stacey Gabriel; Gad Getz; Stephen Glatt; Christina Hultman; Sekar Kathiresan; Markku Laakso; Steven McCarroll; Mark McCarthy; Dermot McGovern; Ruth McPherson; Benjamin Neale; Aarno Palotie; Shaun Purcell; Danish Saleheen; Jeremiah Scharf; Pamela Sklar; Patrick Sullivan; Jaakko Tuomilehto; Ming Tsuang; Hugh Watkins; James Wilson; Mark Daly; Daniel MacArthur;


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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