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.
Ancient DNA makes it possible to directly witness natural selection by analyzing samples from populations before, during and after adaptation events. Here we report the first scan for selection using ancient DNA, capitalizing on the largest genome-wide dataset yet assembled: 230 West Eurasians dating to between 6500 and 1000 BCE, including 163 with newly reported data. The new samples include the first genome-wide data from the Anatolian Neolithic culture whose genetic material we extracted from the DNA-rich petrous bone and who we show were members of the population that was the source of Europe’s first farmers. We also report a complete transect of the steppe region in Samara between 5500 and 1200 BCE that allows us to recognize admixture from at least two external sources into steppe populations during this period. We detect selection at loci associated with diet, pigmentation and immunity, and two independent episodes of selection on height.
We report the Simons Genome Diversity Project (SGDP) dataset: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioral modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that in other non-Africans.
Modern humans arrived in Europe ~45,000 years ago, but little is known about their genetic composition before the start of farming ~8,500 years ago. We analyze genome-wide data from 51 Eurasians from ~45,000-7,000 years ago. Over this time, the proportion of Neanderthal DNA decreased from 3–6% to around 2%, consistent with natural selection against Neanderthal variants in modern humans. Whereas the earliest modern humans in Europe did not contribute substantially to present-day Europeans, all individuals between ~37,000 and ~14,000 years ago descended from a single founder population which forms part of the ancestry of present-day Europeans. A ~35,000 year old individual from northwest Europe represents an early branch of this founder population which was then displaced across a broad region, before reappearing in southwest Europe during the Ice Age ~19,000 years ago. During the major warming period after ~14,000 years ago, a new genetic component related to present-day Near Easterners appears in Europe. These results document how population turnover and migration have been recurring themes of European pre-history.
High-throughput DNA sequencing technology has transformed genetic research and is starting to make an impact on clinical practice. However, analyzing high-throughput sequencing data remains challenging, particularly in clinical settings where accuracy and turnaround times are critical. We present a new approach to this problem, implemented in a software package called Platypus. Platypus achieves high sensitivity and specificity for SNPs, indels and complex polymorphisms by using local de novo assembly to generate candidate variants, followed by local realignment and probabilistic haplotype estimation. It is an order of magnitude faster than existing tools and generates calls from raw aligned read data without preprocessing. We demonstrate the performance of Platypus in clinically relevant experimental designs by comparing with SAMtools and GATK on whole-genome and exome-capture data, by identifying de novo variation in 15 parent-offspring trios with high sensitivity and specificity, and by estimating human leukocyte antigen genotypes directly from variant calls.
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