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.
Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18X per individual. Genes showing population-specific allele frequency changes, which represent strong candidates for altitude adaptation, were identified. The strongest signal of natural selection came from EPAS1, a transcription factor involved in response to hypoxia. One SNP at EPAS1 shows a 78% frequency difference between Tibetan and Han samples, representing the fastest allele frequency change observed at any human gene to date. This SNP’s association with erythrocyte abundance supports the role of EPAS1 in adaptation to hypoxia. Thus, a population genomic survey has revealed a functionally important locus in genetic adaptation to high altitude.
The genetic diversity of Yersinia pestis, the etiologic agent of plague, is extremely limited because of its recent origin coupled with a slow clock rate. Here we identified 2,326 SNPs from 133 genomes of Y. pestis strains that were isolated in China and elsewhere. These SNPs define the genealogy of Y. pestis since its most recent common ancestor. All but 28 of these SNPs represented mutations that happened only once within the genealogy, and they were distributed essentially at random among individual genes. Only seven genes contained a significant excess of nonsynonymous SNP, suggesting that the fixation of SNPs mainly arises via neutral processes, such as genetic drift, rather than Darwinian selection. However, the rate of fixation varies dramatically over the genealogy: the number of SNPs accumulated by different lineages was highly variable and the genealogy contains multiple polytomies, one of which resulted in four branches near the time of the Black Death. We suggest that demographic changes can affect the speed of evolution in epidemic pathogens even in the absence of natural selection, and hypothesize that neutral SNPs are fixed rapidly during intermittent epidemics and outbreaks.infectious disease | molecular clock | phylogenomics | NGS | molecular epidemiology
Whole-genome sequencing enables complete characterization of genetic variation, but geographic clustering of rare alleles demands many diverse populations be studied. Here we describe the Genome of the Netherlands (GoNL) Project, in which we sequenced the whole genomes of 250 Dutch parent-offspring families and constructed a haplotype map of 20.4 million single-nucleotide variants and 1.2 million insertions and deletions. The intermediate coverage (∼13×) and trio design enabled extensive characterization of structural variation, including midsize events (30-500 bp) previously poorly catalogued and de novo mutations. We demonstrate that the quality of the haplotypes boosts imputation accuracy in independent samples, especially for lower frequency alleles. Population genetic analyses demonstrate fine-scale structure across the country and support multiple ancient migrations, consistent with historical changes in sea level and flooding. The GoNL Project illustrates how single-population whole-genome sequencing can provide detailed characterization of genetic variation and may guide the design of future population studies.
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