Analysis of protein-coding genetic variation in 60,706 humans.

Analysis of protein-coding genetic variation in 60,706 humans.

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 gener...

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Prif Awduron: Lek, M, Karczewski, K, Minikel, E, Samocha, K, Banks, E, Fennell, T, O'Donnell-Luria, A, Ware, J, Hill, A, Cummings, B, Tukiainen, T, Birnbaum, D, Kosmicki, J, Duncan, L, Estrada, K, Zhao, F, Zou, J, Pierce-Hoffman, E, Berghout, J, Cooper, D, Deflaux, N, DePristo, M, Do, R, Flannick, J, Fromer, M, Gauthier, L, Goldstein, J, Gupta, N, Howrigan, D, Kiezun, A, Kurki, M, Moonshine, A, Natarajan, P, Orozco, L, Peloso, G, Poplin, R, Rivas, M, Ruano-Rubio, V, Rose, S, Ruderfer, D, Shakir, K, Stenson, P, Stevens, C, Thomas, B, Tiao, G, Tusie-Luna, M, Weisburd, B, Won, H, Yu, D, Altshuler, D, Ardissino, D, Boehnke, M, Danesh, J, Donnelly, S, Elosua, R, Florez, J, Gabriel, S, Getz, G, Glatt, S, Hultman, C, Kathiresan, S, Laakso, M, McCarroll, S, McCarthy, M, McGovern, D, McPherson, R, Neale, B, Palotie, A, Purcell, S, Saleheen, D, Scharf, J, Sklar, P, Sullivan, P, Tuomilehto, J, Tsuang, M, Watkins, H, Wilson, J, Daly, M, MacArthur, D
Fformat: Journal article
Iaith:English
Cyhoeddwyd: Nature Publishing Group 2016
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Crynodeb: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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