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The extent of the devastation of the Black Death pandemic (1346-53) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at local scale in the context of the social stratification of medieval communities. Here we study 275 newly reported ancient genomes from later medieval and post-medieval Cambridgeshire, from individuals buried before, during, and after the Black Death. The majority of individuals examined had local genetic ancestries. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. Accounting for the genetic component for height accentuates the disparities between social groups in stature estimated from long bones, as a proxy for health and the quality of life. While we detect long-term shifts in local genetic ancestry in Cambridgeshire that either pre- or postdate the Black Death, we find no evidence of major changes in genetic ancestry nor, in contrast to recent claims, higher differentiation of immune loci between cohorts living before and after the Black Death.

The Finnish population is a unique example of a genetic isolate affected by a recent founder event. Previous studies have suggested that the ancestors of Finnic-speaking Finns and Estonians reached the circum-Baltic region by the 1(st) millennium BC. However, high linguistic similarity points to a more recent split of their languages. To study genetic connectedness between Finns and Estonians directly, we first assessed the efficacy of imputation of low-coverage ancient genomes by sequencing a medieval Estonian genome to high depth (23×) and evaluated the performance of its down-sampled replicas. We find that ancient genomes imputed from >0.1× coverage can be reliably used in principal-component analyses without projection. By searching for long shared allele intervals (LSAIs; similar to identity-by-descent segments) in unphased data for >143,000 present-day Estonians, 99 Finns, and 14 imputed ancient genomes from Estonia, we find unexpectedly high levels of individual connectedness between Estonians and Finns for the last eight centuries in contrast to their clear differentiation by allele frequencies. High levels of sharing of these segments between Estonians and Finns predate the demographic expansion and late settlement process of Finland. One plausible source of this extensive sharing is the 8(th)–10(th) centuries AD migration event from North Estonia to Finland that has been proposed to explain uniquely shared linguistic features between the Finnish language and the northern dialect of Estonian and shared Christianity-related loanwords from Slavic. These results suggest that LSAI detection provides a computationally tractable way to detect fine-scale structure in large cohorts.

Human herpes simplex virus 1 (HSV-1), a life-long infection spread by oral contact, today infects a majority of adults globally1, yet no ancient HSV-1 genomes have yet been published. Phylogeographic clustering of sampled diversity into European, pan-Eurasian, and African groups2, 3 has suggested that the virus co-diverged with anatomically modern humans migrating out of Africa4, although a much younger origin has also been proposed5. The lack of ancient HSV-1 genomes, high rates of recombination, and high mobility of humans in the modern era have impeded the understanding of HSV-1’s evolutionary history. Here we present three full ancient European HSV-1 genomes and one partial genome, dating to between the 3rd and 17th century CE, sequenced to up to 9.5× with paired human genomes up to 10.16×. These HSV-1 strains fall within modern Eurasian diversity. We estimate a mean mutation rate of 7.6 × 10-7 Introduction Results - Retrieved genomes are likely from typical infections - Demographic history of HSV-1 in a global context Discussion Material and Methods - Ethics statement - Sampling - Generation of aDNA libraries - Sequencing - aDNA authentication - Metagenomic screening - Targeted capture of HSV-1 - Alignment of viral data to the reference sequence - Genotyping - HSV-1 linkage disequilibrium and population genetic analysis - Compilation of comparative HSV data - Preparation of genome sequences - HSV-1 phylogenetic analysis and recombination filtering - Phylogenetic dating - Alignment of human data to the reference sequence and quality control - Genetic sex estimation, mtDNA, and Y haplotyping - Human variant calling and imputation of genotypes

Funder: Sapienza Università di Roma, 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.

INTRODUCTION: Large-scale human genome sequencing studies to date have been limited to large, metropolitan populations or to small numbers of genomes from each group. Much remains to be understood about the extent and structure of genetic variation in our species and how it was shaped by past population separations, admixture, adaptation, size changes, and gene flow from archaic human groups. Larger numbers of genome sequences from more diverse populations are needed to illuminate these questions. RATIONALE: We sequence 929 genomes from 54 geographically, linguistically and culturally diverse human populations to an average of 35x coverage, and analyze the variation among them. We also physically resolve the haplotype phase of 26 of these genomes using linked-read sequencing. RESULTS: We identify 67.3 million single-nucleotide polymorphisms (SNPs), 8.8 million small insertions or deletions (indels) and 40,736 copy number variants (CNVs). This includes hundreds of thousands of variants that had not been discovered by previous sequencing efforts but which are common in one or more population. We demonstrate benefits to the study of population relationships of genome sequences over ascertained array genotypes, particularly when involving African populations. Populations in central and southern Africa, the Americas and Oceania each harbour tens to hundreds of thousands of private, common genetic variants. The majority of these variants arose as novel mutations rather than through archaic introgression, except in Oceanian populations where many private variants derive from Denisovan admixture. While some reach high frequencies, no variants are fixed between major geographical regions. We estimate that the genetic separation between present-day human populations occurred mostly within the last 250,000 years. However, these early separations were gradual in nature and shaped by protracted gene flow. All populations thus still had some genetic contact more recently than this, but there is also evidence that a small fraction of present-day structure might be hundreds of thousands of years older. Most populations expanded in size over the last 10,000 years, but hunter-gatherer groups did not. The low diversity among the Neanderthal haplotypes segregating in present-day populations indicates that, while more than one Neanderthal individual must have contributed genetic material to modern humans, there was likely only one major episode of admixture. In contrast, Denisovan haplotype diversity reflects a more complex history involving more than one episode of admixture. We find small amounts of Neanderthal ancestry in West African genomes, most likely reflecting Eurasian admixture. Despite their very low levels or absence of archaic ancestry, African populations share many Neanderthal and Denisovan variants that are absent from Eurasia, reflecting how a larger proportion of the ancestral human variation has been maintained in Africa. CONCLUSION: The discovery of substantial amounts of common genetic variation that was previously undocumented, and is geographically restricted, highlights the continued value of anthropologically informed study designs for understanding human diversity. The genome sequences presented here are a freely available resource with relevance to population history, medical genetics, anthropology and linguistics. [Figure: see text]