دورية أكاديمية
The mutational constraint spectrum quantified from variation in 141,456 humans
العنوان: | The mutational constraint spectrum quantified from variation in 141,456 humans |
---|---|
المؤلفون: | Karczewski, KJ, Francioli, LC, Tiao, G, Cummings, BB, Alföldi, J, Wang, Q, Collins, RL, Laricchia, KM, Ganna, A, Birnbaum, DP, Gauthier, LD, Brand, H, Solomonson, M, Watts, NA, Rhodes, D, Singer-Berk, M, England, EM, Seaby, EG, Kosmicki, JA, Walters, RK, Tashman, K, Farjoun, Y, Banks, E, Poterba, T, Wang, A, Seed, C, Whiffin, N, Chong, JX, Samocha, KE, Pierce-Hoffman, E, Zappala, Z, O’Donnell-Luria, AH, Vallabh Minikel, E, Weisburd, B, Lek, M, Ware, JS, Vittal, C, Armean, IM, Bergelson, L, Cibulskis, K, Connolly, JM, Covarrubias, M, Donnelly, S, Ferriera, S, Gabriel, S, Gentry, J, Gupta, N, Jeandet, T, Kaplan, D, Llanwarne, C, Munshi, J, Novod, S, Petrillo, N, Roazen, D, Ruano-Rubio, V, Saltzman, A, Schleicher, M, Soto, J, Tibbetts, K, Tolonen, C, Wade, G, Talkowski, ME, Genome Aggregation Database (gnomAD) Consortium, Neale, BM, Daly, MJ, MacArthur, DG |
المساهمون: | Wellcome Trust, Rosetrees Trust |
المصدر: | 443 ; 434 |
بيانات النشر: | Nature Research |
سنة النشر: | 2020 |
المجموعة: | Imperial College London: Spiral |
مصطلحات موضوعية: | Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, DE-NOVO MUTATIONS, VARIANTS, BURDEN, MODEL, Adult, Brain, Cardiovascular Diseases, Cohort Studies, Databases, Genetic, Exome, Female, Genes, Essential, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Loss of Function Mutation, Male, Mutation Rate, Proprotein Convertase 9, RNA, Messenger, Reproducibility of Results |
الوصف: | 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 sizes1. 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 human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance 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. |
نوع الوثيقة: | article in journal/newspaper |
اللغة: | unknown |
تدمد: | 0028-0836 |
العلاقة: | Nature; http://hdl.handle.net/10044/1/79060Test; 107469/Z/15/Z; M735 |
DOI: | 10.1038/s41586-020-2308-7 |
الإتاحة: | https://doi.org/10.1038/s41586-020-2308-7Test http://hdl.handle.net/10044/1/79060Test |
حقوق: | © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0Test/. |
رقم الانضمام: | edsbas.80E2726A |
قاعدة البيانات: | BASE |
تدمد: | 00280836 |
---|---|
DOI: | 10.1038/s41586-020-2308-7 |