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Analysis of protein-coding genetic variation in 60,706 humans

Monkol Lek; Konrad J. Karczewski; Eric Vallabh Minikel; Kaitlin E. Samocha; Eric Banks; Timothy R. Fennell; Anne O’Donnell‐Luria; James S. Ware · Nature · 2016

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Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries 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 predicted protein-truncating variants, with 72% of these genes 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. Exome sequencing data from 60,706 people of diverse geographic ancestry is presented, providing insight into genetic variation across populations, and illuminating the relationship between DNA variants and human disease. As part of the Exome Aggregation Consortium (ExAC) project, Daniel MacArthur and colleagues report on the generation and analysis of high-quality exome sequencing data from 60,706 individuals of diverse ancestry. This provides the most comprehensive catalogue of human protein-coding genetic variation to date, yielding unprecedented resolution for the analysis of very rare variants across multiple human populations. The catalogue is freely accessible and provides a critical reference panel for the clinical interpretation of genetic variants and the discovery of disease-related genes.

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APA 7

Lek, M, Karczewski, K. J, Minikel, E. V, Samocha, K. E, Banks, E, Fennell, T. R, O’Donnell‐Luria, A, & Ware, J. S. (2016). Analysis of protein-coding genetic variation in 60,706 humans. https://doi.org/10.1038/nature19057

MLA

Lek, Monkol, et al. "Analysis of protein-coding genetic variation in 60,706 humans." 2016. https://doi.org/10.1038/nature19057.

Chicago

Lek, Monkol, Konrad J. Karczewski, Eric Vallabh Minikel, Kaitlin E. Samocha, Eric Banks, Timothy R. Fennell, Anne O’Donnell‐Luria, and James S. Ware. 2016. "Analysis of protein-coding genetic variation in 60,706 humans.". https://doi.org/10.1038/nature19057.

Harvard

Lek, M. et al. 2016, Analysis of protein-coding genetic variation in 60,706 humans, Nature, available at: https://doi.org/10.1038/nature19057 [Accessed 6 Aug. 2026].

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Title
Analysis of protein-coding genetic variation in 60,706 humans
Author / contributors
Monkol Lek; Konrad J. Karczewski; Eric Vallabh Minikel; Kaitlin E. Samocha; Eric Banks; Timothy R. Fennell; Anne O’Donnell‐Luria; James S. Ware
Publisher
Nature
Publication year
2016
Language
English

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