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

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

^aAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
^bInstitute for Neuroscience and Muscle Research, Children's Hospital at Westmead, Sydney, New South Wales 2145, Australia
^cProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
^dSchool of Paediatrics and Child Health, University of Sydney, Sydney, New South Wales 2145, Australia
^eAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA
^fProgram in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts 02115, USA
^gStanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
^hProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, Massachusetts, USA
ⁱDivision of Genetics and Genomics, Boston Children’s Hospital, Boston, 02115, Massachusetts, USA
^jDepartment of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
^kMRC Clinical Sciences Centre, Imperial College London, London SW7 2AZ, UK
^lNIHR Royal Brompton Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, London SW3 6NP, UK
^mNational Heart and Lung Institute, Imperial College London, London SW7 2AZ, UK
ⁿGenome Sciences, University of Washington, Seattle, Washington 98195, USA
^oProgram in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, Massachusetts 02115, USA
^pCenter for Biomedical Informatics and Biostatistics, University of Arizona, Tucson, Arizona 85721, USA
^qMouse Genome Informatics, Jackson Laboratory, Bar Harbor, Maine 04609, USA
^rMouse Genome Informatics, Jackson Laboratory, Bar Harbor, 04609, Maine, USA
^sInstitute of Medical Genetics, Cardiff University, Cardiff CF10 3XQ, UK
^tInstitute of Medical Genetics, Cardiff University, Cardiff, CF10 3XQ, UK
^uGoogle, Mountain View, California 94043, USA
^vGoogle, Mountain View, California, 94043, USA
^wBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
^xBroad Institute of MIT and Harvard, Cambridge, 02142, Massachusetts, USA
^yDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
^zInstitute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
^aaThe Center for Statistical Genetics, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
^abThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
^acDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA
^adDepartment of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
^aeDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA

Abstract

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.

TL;DRThe 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) provides direct evidence for the presence of widespread mutational recurrence. (Semantic Scholar)

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

Abstract

Plain-language summary

Discussion