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• • Altmetric: 961 • Citations: 906 • Article Open Analysis of protein-coding genetic variation in 60,706 humans •,,, •,, •,,, •,,,, •, •, •,,, •,,,,, •,,, •,,, •,, •, •,,,, •,,, •,, •,, •, •,, •,, •, •, •, •,,,, •,, •,,,,, •, •,,, •, •,,, •, •,, •, •,,,, •, •,,, •, •, •, •, •,,, •, •, •, •,, •, •, •, •, •,,,, •,, •, •, •, •, •, •,,, •, •,,, •,,, •, •,,,, •, •,, •,,, •, •, •,,, •,,,, •,,, •,,, •,,,,, •,,,,, •,, •, •, •,, •, •,,, •,, • &. 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.

Over the last five years, the widespread availability of high-throughput DNA sequencing technologies has permitted the sequencing of the whole genomes or exomes of hundreds of thousands of humans. In theory, these data represent a powerful source of information about the global patterns of human genetic variation, but in practice, are difficult to access for practical, logistical, and ethical reasons; in addition, their utility is complicated by the heterogeneity in the experimental methodologies and variant calling pipelines used to generate them. Current publicly available data sets of human DNA sequence variation contain only a small fraction of all sequenced samples: the Exome Variant Server, created as part of the NHLBI Exome Sequencing Project (ESP), contains frequency information spanning 6,503 exomes; and the 1000 Genomes Project (1000G), which includes individual-level genotype data from whole-genome and exome sequence data for 2,504 individuals. Databases of genetic variation are important for our understanding of human population history and biology,,,,, but also provide critical resources for the clinical interpretation of variants observed in patients who have rare Mendelian diseases. The filtering of candidate variants by frequency in unselected individuals is a key step in any pipeline for the discovery of causal variants in Mendelian disease patients, and the efficacy of such filtering depends on both the size and the ancestral diversity of the available reference data. Here we describe the joint variant calling and analysis of high-quality variant calls across 60,706 human exomes, assembled by the Exome Aggregation Consortium (ExAC; ). This call set exceeds previously available exome-wide variant databases, by nearly an order of magnitude, providing substantially increased resolution for the analysis of very low-frequency genetic variants.

We demonstrate the application of this data set to the analysis of patterns of genetic variation including the discovery of widespread mutational recurrence, the inference of gene-level constraint against truncating variation, the clinical interpretation of variation in Mendelian disease genes, and the discovery of human knockout variants in protein-coding genes. Sequencing data processing, variant calling, quality control and filtering was performed on over 91,000 exomes (see Methods), and sample filtering was performed to produce a final data set spanning 60,706 individuals (). To identify the ancestry of each ExAC individual, we performed principal component analysis (PCA) to distinguish the major axes of geographic ancestry and to identify population clusters corresponding to individuals of European, African, South Asian, East Asian, and admixed American (hereafter referred to as Latino) ancestry (; ); we note that the apparent separation between East Asian and other samples reflects a deficiency of Middle Eastern and Central Asian samples in the data set. We further separated Europeans into individuals of Finnish and non-Finnish ancestry given the enrichment of this bottlenecked population; the term European hereafter refers to non-Finnish European individuals. A, The size and diversity of public reference exome data sets.

ExAC exceeds previous data sets in size for all studied populations. B, Principal component analysis (PCA) dividing ExAC individuals into five continental populations.

PC2 and PC3 are shown; additional PCs are in. C, The allele frequency spectrum of ExAC highlights that the majority of genetic variants are rare and novel (absent from prior databases of genetic variation, such as dbSNP).

D, The proportion of possible variation observed by mutational context and functional class. Over half of all possible CpG transitions are observed.

Error bars represent standard error of the mean. E, f, The number ( e), and frequency distribution (proportion singleton; f) of indels, by size. Compared to in-frame indels, frameshift variants are less common (have a higher proportion of singletons, a proxy for predicted deleteriousness on gene product). Career Switcher Program Va Gmu Patriot. What Is This Thing Called Knowledge Pritchard Pdf Writer.

Error bars indicate 95% confidence intervals. • We identified 10,195,872 candidate sequence variants in ExAC. We further applied stringent depth and site/genotype quality filters to define a subset of 7,404,909 high-quality variants, including 317,381 insertions or deletions (indels) (), corresponding to one variant for every 8 base pairs (bp) within the exome intervals. The majority of these are very low-frequency variants absent from previous smaller call sets (), of the high-quality variants, 99% have a frequency of.

The density of protein-coding sequence variation in ExAC reveals a number of properties of human genetic variation that are undetectable in smaller data sets. For example, 7.9% of high-quality sites in ExAC are multiallelic (multiple different sequence variants observed at the same site), close to the Poisson expectation of 8.3%, given the observed density of variation, and far higher than that observed in previous data sets of 0.48% in the 1000G (exome intervals) and 0.43% in the ESP data sets. The size of ExAC makes it possible to directly observe mutational recurrence: instances in which the same mutation has occurred multiple times independently throughout the hist.