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Journal ArticleDOI

A global reference for human genetic variation.

Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature (Nature Publishing Group)-Vol. 526, Iss: 7571, pp 68-74
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
Citations
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Journal ArticleDOI
TL;DR: It is suggested that A3B and A3H-I, together, explain the bulk of ‘APOBEC signature' mutations in cancer.
Abstract: Cytosine mutations within TCA/T motifs are common in cancer. A likely cause is the DNA cytosine deaminase APOBEC3B (A3B). However, A3B-null breast tumours still have this mutational bias. Here we show that APOBEC3H haplotype I (A3H-I) provides a likely solution to this paradox. A3B-null tumours with this mutational bias have at least one copy of A3H-I despite little genetic linkage between these genes. Although deemed inactive previously, A3H-I has robust activity in biochemical and cellular assays, similar to A3H-II after compensation for lower protein expression levels. Gly105 in A3H-I (versus Arg105 in A3H-II) results in lower protein expression levels and increased nuclear localization, providing a mechanism for accessing genomic DNA. A3H-I also associates with clonal TCA/T-biased mutations in lung adenocarcinoma suggesting this enzyme makes broader contributions to cancer mutagenesis. These studies combine to suggest that A3B and A3H-I, together, explain the bulk of 'APOBEC signature' mutations in cancer.

142 citations

Journal ArticleDOI
14 Jun 2018-Cell
TL;DR: The effects of >50 million variations from five strains of mice on mRNA, nascent transcription, transcription start sites, and transcription factor binding in resting and activated macrophages are investigated.

142 citations

Journal ArticleDOI
01 Nov 2016-Genetics
TL;DR: It is argued that natural populations may experience the amount of recent positive selection required to skew inferences, and results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.
Abstract: The availability of large-scale population genomic sequence data has resulted in an explosion in efforts to infer the demographic histories of natural populations across a broad range of organisms. As demographic events alter coalescent genealogies, they leave detectable signatures in patterns of genetic variation within and between populations. Accordingly, a variety of approaches have been designed to leverage population genetic data to uncover the footprints of demographic change in the genome. The vast majority of these methods make the simplifying assumption that the measures of genetic variation used as their input are unaffected by natural selection. However, natural selection can dramatically skew patterns of variation not only at selected sites, but at linked, neutral loci as well. Here we assess the impact of recent positive selection on demographic inference by characterizing the performance of three popular methods through extensive simulation of data sets with varying numbers of linked selective sweeps. In particular, we examined three different demographic models relevant to a number of species, finding that positive selection can bias parameter estimates of each of these models—often severely. We find that selection can lead to incorrect inferences of population size changes when none have occurred. Moreover, we show that linked selection can lead to incorrect demographic model selection, when multiple demographic scenarios are compared. We argue that natural populations may experience the amount of recent positive selection required to skew inferences. These results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.

142 citations


Cites background from "A global reference for human geneti..."

  • ...…more genome sequences are available, in many cases finding support for large changes in population size (Groenen et al. 2012; Albert et al. 2013; Prado-Martinez et al. 2013; Zhan et al. 2013; Freedman et al. 2014; Green et al. 2014; Wallberg et al. 2014; Auton et al. 2015; Lamichhaney et al. 2015)....

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Journal ArticleDOI
TL;DR: The synthetic-diploid (Syndip) benchmark dataset, constructed from two fully homozygous long-read assemblies, provides more accurate assessments of error rates in small-variant-calling algorithms than existing benchmarks.
Abstract: Existing benchmark datasets for use in evaluating variant-calling accuracy are constructed from a consensus of known short-variant callers, and they are thus biased toward easy regions that are accessible by these algorithms. We derived a new benchmark dataset from the de novo PacBio assemblies of two fully homozygous human cell lines, which provides a relatively more accurate and less biased estimate of small-variant-calling error rates in a realistic context.

142 citations

Journal ArticleDOI
TL;DR: An NMD escape intolerance score is developed to rank genes based on the depletion of PTVs that would render them able to escape NMD using the Atherosclerosis Risk in Communities Study and the Exome Aggregation Consortium (ExAC) control databases, which was further used to screen the Baylor-Center for Mendelian Genomics disease database.
Abstract: Premature termination codon (PTC)-bearing transcripts are often degraded by nonsense-mediated decay (NMD) resulting in loss-of-function (LoF) alleles. However, not all PTCs result in LoF mutations, i.e., some such transcripts escape NMD and are translated to truncated peptide products that result in disease due to gain-of-function (GoF) effects. Since the location of the PTC is a major factor determining transcript fate, we hypothesized that depletion of protein-truncating variants (PTVs) within the gene region predicted to escape NMD in control databases could provide a rank for genic susceptibility for disease through GoF versus LoF. We developed an NMD escape intolerance score to rank genes based on the depletion of PTVs that would render them able to escape NMD using the Atherosclerosis Risk in Communities Study (ARIC) and the Exome Aggregation Consortium (ExAC) control databases, which was further used to screen the Baylor-Center for Mendelian Genomics disease database. This analysis revealed 1,996 genes significantly depleted for PTVs that are predicted to escape from NMD, i.e., PTVesc; further studies provided evidence that revealed a subset as candidate genes underlying Mendelian phenotypes. Importantly, these genes have characteristically low pLI scores, which can cause them to be overlooked as candidates for dominant diseases. Collectively, we demonstrate that this NMD escape intolerance score is an effective and efficient tool for gene discovery in Mendelian diseases due to production of truncated or altered proteins. More importantly, we provide a complementary analytical tool to aid identification of genes associated with dominant traits through a mechanism distinct from LoF.

142 citations

References
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06 Sep 2012-Nature
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13,548 citations

Journal ArticleDOI
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10,164 citations