Lek, MonkolKarczewski, KonradMinikel, EricSamocha, Kaitlin E.Banks, EricFennell, TimothyO'Donnell-Luria, Anne HWare, James SHill, Andrew JCummings, BerylTukiainen, TaruBirnbaum, Daniel PKosmicki, JackDuncan, Laramie EEstrada, KarolZhao, FengmeiZou, JamesPierce-Hoffman, EmmaBerghout, JoanneCooper, David NDeflaux, NicoleDePristo, MarkDo, RonFlannick, JasonFromer, MenachemGauthier, LauraGoldstein, JackieGupta, NamrataHowrigan, DanielKiezun, AdamKurki, MitjaMoonshine, Ami LevyNatarajan, PradeepOrozco, LorenaPeloso, Gina MPoplin, RyanRivas, Manuel ARuano-Rubio, ValentinRose, Samuel ARuderfer, Douglas MShakir, KhalidStenson, Peter DStevens, ChristineThomas, Brett PTiao, GraceTusie-Luna, Maria TWeisburd, BenWon, Hong-HeeYu, DongmeiAltshuler, DavidArdissino, DiegoBoehnke, MichaelDanesh, JohnDonnelly, StaceyElosua, RobertoFlorez, JoseGabriel, Stacey BGetz, GadGlatt, Stephen JHultman, Christina MKathiresan, SekarLaakso, MarkkuMcCarroll, StevenMcCarthy, Mark IMcGovern, DermotMcPherson, RuthNeale, BenjaminPalotie, AarnoPurcell, Shaun MSaleheen, DanishScharf, JeremiahSklar, PamelaSullivan, Patrick FTuomilehto, JaakkoTsuang, Ming TWatkins, Hugh CWilson, James GDaly, MarkMacArthur, Daniel2017-03-282016Lek, M., K. J. Karczewski, E. V. Minikel, K. E. Samocha, E. Banks, T. Fennell, A. H. O'Donnell-Luria, et al. 2016. “Analysis of protein-coding genetic variation in 60,706 humans.” Nature 536 (7616): 285-291. doi:10.1038/nature19057. http://dx.doi.org/10.1038/nature19057.http://nrs.harvard.edu/urn-3:HUL.InstRepos:31731822Summary Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. 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). This 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 have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having 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.en-USJournal Article2017-03-2810.1038/nature19057