Genome sequences from diverse human groups are needed to understand the structure of genetic variation in our species and the history of, and relationships between, different populations. We present 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. Analyses of these genomes reveal an excess of previously undocumented common genetic variation private to southern Africa, central Africa, Oceania, and the Americas, but an absence of such variants fixed between major geographical regions. We also find deep and gradual population separations within Africa, contrasting population size histories between hunter-gatherer and agriculturalist groups in the past 10,000 years, and a contrast between single Neanderthal but multiple Denisovan source populations contributing to present-day human populations.

30Genome sequences from diverse human groups are needed to understand the structure of genetic variation in our species and the history of, and relationships between, different populations. We present 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. Analyses of these genomes reveal an excess of previously undocumented private genetic variation in 35 southern and central Africa and in Oceania and the Americas, but an absence of fixed, private variants between major geographical regions. We also find deep and gradual population separations within Africa, contrasting population size histories between hunter-gatherer and agriculturalist groups in the last 10,000 years, a potentially major population growth episode after the peopling of the Americas, and a contrast between single Neanderthal but multiple 40Denisovan source populations contributing to present-day human populations. We also demonstrate benefits to the study of population relationships of genome sequences over ascertained array genotypes. These genome sequences are freely available as a resource with no access or analysis restrictions.

Human populations outside of Africa have experienced at least two bouts of introgression from archaic humans, from Neanderthals and Denisovans. In Papuans there is prior evidence of both these introgressions. Here we present a new approach to detect segments of individual genomes of archaic origin without using an archaic reference genome. The approach is based on a hidden Markov model that identifies genomic regions with a high density of single nucleotide variants (SNVs) not seen in unadmixed populations. We show using simulations that this provides a powerful approach to identifying segments of archaic introgression with a low rate of false detection, given data from a suitable outgroup population is available, without the archaic introgression but containing a majority of the variation that arose since initial separation from the archaic lineage. Furthermore our approach is able to infer admixture proportions and the times both of admixture and of initial divergence between the human and archaic populations. We apply the model to detect archaic introgression in 89 Papuans and show how the identified segments can be assigned to likely Neanderthal or Denisovan origin. We report more Denisovan admixture than previous studies and find a shift in size distribution of fragments of Neanderthal and Denisovan origin that is compatible with a difference in admixture time. Furthermore, we identify small amounts of Denisova ancestry in South East Asians and South Asians.

Although ancient DNA data have become increasingly more important in studies about past populations, it is often not feasible or practical to obtain high coverage genomes from poorly preserved samples. While methods of accurate genotype imputation from > 1 × coverage data have recently become a routine, a large proportion of ancient samples remain unusable for downstream analyses due to their low coverage. Here, we evaluate a two-step pipeline for the imputation of common variants in ancient genomes at 0.05–1 × coverage. We use the genotype likelihood input mode in Beagle and filter for confident genotypes as the input to impute missing genotypes. This procedure, when tested on ancient genomes, outperforms a single-step imputation from genotype likelihoods, suggesting that current genotype callers do not fully account for errors in ancient sequences and additional quality controls can be beneficial. We compared the effect of various genotype likelihood calling methods, post-calling, pre-imputation and post-imputation filters, different reference panels, as well as different imputation tools. In a Neolithic Hungarian genome, we obtain ~ 90% imputation accuracy for heterozygous common variants at coverage 0.05 × and > 97% accuracy at coverage 0.5 ×. We show that imputation can mitigate, though not eliminate reference bias in ultra-low coverage ancient genomes.

Ancient genomes reveal structural shifts after the arrival of Steppe-related ancestry in the Italian Peninsula Highlights d 22 genomes from Northeastern and Central Italy dated between 3200 and 1500 BCE d Arrival of Steppe-related ancestry in the central Italian Peninsula by 1600 BCE d Close patrilineal kinship patterns within commingled Chalcolithic cave burials d Roman Imperial period had a stronger effect on phenotype shifts than the Bronze Age

In the fourth millennium BCE a cultural phenomenon of monumental burial structures spread along the Atlantic façade. Megalithic burials have been targeted for aDNA analyses, but a gap remains in East Anglia, where Neolithic structures were generally earthen or timber. An early Neolithic (3762-3648 cal. BCE) burial monument at the site of Trumpington Meadows, Cambridgeshire, UK, contained the partially articulated remains of at least three individuals. To determine whether this monument fits a pattern present in megalithic burials regarding sex bias, kinship, diet and relationship to modern populations, teeth and ribs were analysed for DNA and carbon and nitrogen isotopic values, respectively. Whole ancient genomes were sequenced from two individuals to a mean genomic coverage of 1.6 and 1.2X and genotypes imputed. Results show that they were brothers from a small population genetically and isotopically similar to previously published British Neolithic individuals, with a level of genome-wide homozygosity consistent with a small island population sourced from continental Europe, but bearing no signs of recent inbreeding. The first Neolithic whole genomes from a monumental burial in East Anglia confirm that this region was connected with the larger pattern of Neolithic megaliths in the British Isles and the Atlantic façade.

Human herpes simplex virus 1 (HSV-1), a life-long infection spread by oral contact, infects a majority of adults globally. Phylogeographic clustering of sampled diversity into European, pan-Eurasian, and African groups has suggested the virus codiverged with human migrations out of Africa, although a much younger origin has also been proposed. We present three full ancient European HSV-1 genomes and one partial genome, dating from the 3rd to 17th century CE, sequenced to up to 9.5× with paired human genomes up to 10.16×. Considering a dataset of modern and ancient genomes, we apply phylogenetic methods to estimate the age of sampled modern Eurasian HSV-1 diversity to 4.68 (3.87 to 5.65) ka. Extrapolation of estimated rates to a global dataset points to the age of extant sampled HSV-1 as 5.29 (4.60 to 6.12) ka, suggesting HSV-1 lineage replacement coinciding with the late Neolithic period and following Bronze Age migrations.

No abstract