The mutational constraint spectrum quantified from variation in 141,456 humans
Abstract 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...
| Authors: | , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2020 |
| Country: | México |
| Institution: | Instituto Nacional de Salud Pública |
| Repository: | Repositorio Institucional Abierto de Conocimiento en Salud Pública |
| Language: | Spanish |
| OAI Identifier: | oai:repositorio.insp.mx:20.500.12096/8077 |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334197/pdf/41586_2020_Article_2308.pdf https://www.doi.org/10.1038/s41586-020-2308-7 http://repositorio.insp.mx:8080/jspui/handle/20.500.12096/8077 |
| Access Level: | Open access |
| Keyword: | Adult Brain , metabolism Cardiovascular Diseases , genetics Cohort Studies Databases, Genetic Exome , genetics, Female Genes, Essential , genetics, Genetic Predisposition to Disease , genetics Genetic Variation , genetics, Genome, Human , genetics, Genome-Wide Association Study Humans Loss of Function Mutation , genetics Male Mutation Rate Proprotein Convertase 9 , genetics RNA, Messenger , genetics Reproducibility of Results Whole Exome Sequencing Whole Genome Sequencing info:eu-repo/classification/cti/3 |
| Summary: | Abstract 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 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 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. |
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