The mutational constraint spectrum quantified from variation in 141,456 humans

被引：6799

作者：

Karczewski, Konrad J. ^{[1
,2
]}

Francioli, Laurent C. ^{[1
,2
]}

Tiao, Grace ^{[1
,2
]}

Cummings, Beryl B. ^{[1
,2
,3
]}

Alfoldi, Jessica ^{[1
,2
]}

Wang, Qingbo ^{[1
,2
,4
]}

Collins, Ryan L. ^{[1
,4
,5
]}

Laricchia, Kristen M. ^{[1
,2
]}

Ganna, Andrea ^{[1
,2
,6
]}

Birnbaum, Daniel P. ^{[1
,2
]}

Gauthier, Laura D. ^{[7
]}

Brand, Harrison ^{[1
,5
]}

Solomonson, Matthew ^{[1
,2
]}

Watts, Nicholas A. ^{[1
,2
]}

Rhodes, Daniel ^{[8
,9
]}

Singer-Berk, Moriel ^{[1
,2
]}

England, Eleina M. ^{[1
,2
]}

Seaby, Eleanor G. ^{[1
,2
]}

Kosmicki, Jack A. ^{[1
,2
,4
]}

Walters, Raymond K. ^{[1
,2
,10
]}

Tashman, Katherine ^{[1
,2
,10
]}

Farjoun, Yossi ^{[7
]}

Banks, Eric ^{[7
]}

Poterba, Timothy ^{[1
,2
,10
]}

Wang, Arcturus ^{[1
,2
,10
]}

Seed, Cotton ^{[1
,2
,10
]}

Whiffin, Nicola ^{[1
,2
,11
,12
,13
]}

Chong, Jessica X. ^{[14
]}

Samocha, Kaitlin E. ^{[15
]}

Pierce-Hoffman, Emma ^{[1
,2
]}

Zappala, Zachary ^{[1
,2
,16
]}

O'Donnell-Luria, Anne H. ^{[1
,2
,17
,18
]}

Minikel, Eric Vallabh ^{[1
]}

Weisburd, Ben ^{[7
]}

Lek, Monkol ^{[19
]}

Ware, James S. ^{[1
,11
,12
,13
]}

Vittal, Christopher ^{[2
,10
]}

Armean, Irina M. ^{[1
,2
]}

Bergelson, Louis ^{[7
]}

Cibulskis, Kristian ^{[7
]}

Connolly, Kristen M. ^{[20
]}

Covarrubias, Miguel ^{[7
]}

Donnelly, Stacey ^{[1
]}

Ferriera, Steven ^{[20
]}

Gabriel, Stacey ^{[20
]}

Gentry, Jeff ^{[7
]}

Gupta, Namrata ^{[1
,20
]}

Jeandet, Thibault ^{[7
]}

Kaplan, Diane ^{[7
]}

Llanwarne, Christopher ^{[7
]}

机构：

[1] Broad Inst MIT & Harvard, Program Med & Populat Genet, Cambridge, MA 02142 USA

[2] Massachusetts Gen Hosp, Analyt & Translat Genet Unit, Boston, MA 02114 USA

[3] Harvard Med Sch, Program Biol & Biomed Sci, Boston, MA 02115 USA

[4] Harvard Med Sch, Program Bioinformat & Integrat Genom, Boston, MA 02115 USA

[5] Massachusetts Gen Hosp, Ctr Genom Med, Boston, MA 02114 USA

[6] Inst Mol Med Finland, Helsinki, Finland

[7] Broad Inst MIT & Harvard, Data Sci Platform, Cambridge, MA 02142 USA

[8] Queen Mary Univ, Barts & London Sch Med & Dent, William Harvey Res Inst, Ctr Translat Bioinformat, London, England

[9] Barts Hearth NHS Trust, London, England

[10] Broad Inst MIT & Harvard, Stanley Ctr Psychiat Res, Cambridge, MA 02142 USA

[11] Imperial Coll London, Natl Heart & Lung Inst, London, England

[12] Imperial Coll London, MRC London Inst Med Sci, London, England

[13] Royal Brompton & Harefierd Hosp NHS Trust, Cardiovasc Res Ctr, London, England

[14] Univ Washington, Dept Pediat, Seattle, WA 98195 USA

[15] Wellcome Sanger Inst, Wellcome Genome Campus, Cambridge, England

[16] Vertex Pharmaceut Inc, Boston, MA USA

[17] Boston Childrens Hosp, Div Genet & Genom, Boston, MA USA

[18] Harvard Med Sch, Dept Pediat, Boston, MA 02115 USA

[19] Yale Sch Med, Dept Genet, New Haven, CT USA

[20] Broad Inst MIT & Harvard, Broad Genom, Cambridge, MA 02142 USA

[21] Harvard Med Sch, Dept Neurol, Boston, MA 02115 USA

[22] Garvan Inst Med Res, Ctr Populat Genom, Sydney, NSW, Australia

[23] UNSW Sydney, Sydney, NSW, Australia

[24] Murdoch Childrens Res Inst, Ctr Populat Genom, Melbourne, Vic, Australia

来源：

NATURE | 2020年 / 581卷 / 7809期

基金：

英国惠康基金; 英国医学研究理事会; 瑞士国家科学基金会;

关键词：

DE-NOVO MUTATIONS; VARIANTS; BURDEN; MODEL;

D O I：

10.1038/s41586-020-2308-7

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];

摘要：

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function 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(1). 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 predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

引用

页码：434 / +

页数：22

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