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Biology & Genetics

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

Monkol Lek, Konrad J. Karczewski, Daniel G. MacArthur · Exome Aggregation Consortium (ExAC); first authors Lek and Karczewski, senior/corresponding author Daniel G. MacArthur. Listed in Nature as Lek M, Karczewski KJ, Minikel EV, et al.

Published 18 August 2016 · Nature · Journal article

Summary

The Exome Aggregation Consortium (ExAC) aggregates and jointly analyzes high-quality exome sequencing data from 60,706 individuals of diverse ancestries, producing the largest catalogue of human protein-coding variation at the time. The dataset reveals roughly one variant per eight exonic bases and provides direct evidence of widespread mutational recurrence. It enables improved estimation of gene-level intolerance to loss-of-function variation and refines the interpretation of pathogenic variants in clinical genetics.

Key findings

  • Catalogued protein-coding variation across 60,706 exomes, averaging about one variant every eight bases of the exome.
  • Identified 3,230 genes nearly depleted of predicted protein-truncating variants, ~72% of which had no established disease phenotype.
  • Provided evidence for widespread mutational recurrence and a resource that reclassified many previously reported pathogenic variants.

Subjects & keywords

Cite this paper

APA

Monkol Lek, Konrad J. Karczewski, & Daniel G. MacArthur [Exome Aggregation Consortium (ExAC); first authors Lek and Karczewski, senior/corresponding author Daniel G. MacArthur. Listed in Nature as Lek M, Karczewski KJ, Minikel EV, et al.] (2016). Analysis of protein-coding genetic variation in 60,706 humans. Nature. https://doi.org/10.1038/nature19057

BibTeX
@article{lek2016analysis,
  author    = {Monkol Lek and Konrad J. Karczewski and Daniel G. MacArthur and {Exome Aggregation Consortium (ExAC); first authors Lek and Karczewski, senior/corresponding author Daniel G. MacArthur. Listed in Nature as Lek M, Karczewski KJ, Minikel EV, et al.}},
  title     = {Analysis of protein-coding genetic variation in 60,706 humans},
  journal   = {Nature},
  year      = {2016},
  doi       = {10.1038/nature19057},
  url       = {https://doi.org/10.1038/nature19057}
}

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