TY - JOUR T1 - Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes JF - bioRxiv DO - 10.1101/531210 SP - 531210 AU - Konrad J. Karczewski AU - Laurent C. Francioli AU - Grace Tiao AU - Beryl B. Cummings AU - Jessica Alföldi AU - Qingbo Wang AU - Ryan L. Collins AU - Kristen M. Laricchia AU - Andrea Ganna AU - Daniel P. Birnbaum AU - Laura D. Gauthier AU - Harrison Brand AU - Matthew Solomonson AU - Nicholas A. Watts AU - Daniel Rhodes AU - Moriel Singer-Berk AU - Eleanor G. Seaby AU - Jack A. Kosmicki AU - Raymond K. Walters AU - Katherine Tashman AU - Yossi Farjoun AU - Eric Banks AU - Timothy Poterba AU - Arcturus Wang AU - Cotton Seed AU - Nicola Whiffin AU - Jessica X. Chong AU - Kaitlin E. Samocha AU - Emma Pierce-Hoffman AU - Zachary Zappala AU - Anne H. O’Donnell-Luria AU - Eric Vallabh Minikel AU - Ben Weisburd AU - Monkol Lek AU - James S. Ware AU - Christopher Vittal AU - Irina M. Armean AU - Louis Bergelson AU - Kristian Cibulskis AU - Kristen M. Connolly AU - Miguel Covarrubias AU - Stacey Donnelly AU - Steven Ferriera AU - Stacey Gabriel AU - Jeff Gentry AU - Namrata Gupta AU - Thibault Jeandet AU - Diane Kaplan AU - Christopher Llanwarne AU - Ruchi Munshi AU - Sam Novod AU - Nikelle Petrillo AU - David Roazen AU - Valentin Ruano-Rubio AU - Andrea Saltzman AU - Molly Schleicher AU - Jose Soto AU - Kathleen Tibbetts AU - Charlotte Tolonen AU - Gordon Wade AU - Michael E. Talkowski AU - The Genome Aggregation Database Consortium AU - Benjamin M. Neale AU - Mark J. Daly AU - Daniel G. MacArthur Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/01/30/531210.abstract N2 - Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organism’s function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes. Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved model of human mutation, we classify human protein-coding genes along a spectrum representing intolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases. ER -