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Open AccessJournal ArticleDOI

A global reference for human genetic variation.

Adam Auton, +517 more
- 01 Oct 2015 - 
- Vol. 526, Iss: 7571, pp 68-74
TLDR
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.

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Citations
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Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes

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Improving polygenic prediction in ancestrally diverse populations

TL;DR: In this paper , a new polygenic risk score (PRS) construction method, PRS-CSx, was proposed to improve cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations.
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Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status.

TL;DR: Analysis of gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource indicates that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score.
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