East Anglian early Neolithic monument burial linked to contemporary Megaliths

Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation

We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. By applying this to 8433 West Eurasians who lived over the past 14000 years and 6510 contemporary people, we find an order of magnitude more genome-wide significant signals than previous studies: 347 independent loci with >99% probability of selection. Previous work showed that classic hard sweeps driving advantageous mutations to fixation have been rare over the broad span of human evolution, but in the last ten millennia, many hundreds of alleles have been affected by strong directional selection. Discoveries include an increase from ~0% to ~20% in 4000 years for the major risk factor for celiac disease at HLA-DQB1; a rise from ~0% to ~8% in 6000 years of blood type B; and fluctuating selection at the TYK2 tuberculosis risk allele rising from ~2% to ~9% from ~5500 to ~3000 years ago before dropping to ~3%. We identify instances of coordinated selection on alleles affecting the same trait, with the polygenic score today predictive of body fat percentage decreasing by around a standard deviation over ten millennia, consistent with the "Thrifty Gene" hypothesis that a genetic predisposition to store energy during food scarcity became disadvantageous after farming. We also identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). These traits are measured in modern industrialized societies, so what phenotypes were adaptive in the past is unclear. We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.

Low Genetic Impact of the Roman Occupation of Britain in Rural Communities

The Roman period saw the empire expand across Europe and the Mediterranean, including much of what is today Great Britain. While there is written evidence of high mobility into and out of Britain for administrators, traders, and the military, the impact of imperialism on local, rural population structure, kinship, and mobility is invisible in the textual record. The extent of genetic change that occurred in Britain during the Roman military occupation remains underexplored. Here, using genome-wide data from 52 ancient individuals from eight sites in Cambridgeshire covering the period of Roman occupation, we show low levels of genetic ancestry differentiation between Romano-British sites and indications of larger populations than in the Bronze Age and Neolithic. We find no evidence of long-distance migration from elsewhere in the Empire, though we do find one case of possible temporary mobility within a family unit during the Late Romano-British period. We also show that the present-day patterns of genetic ancestry composition in Britain emerged after the Roman period.

The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change

Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 y, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets.

The Allen Ancient DNA Resource (AADR) a curated compendium of ancient human genomes

More than two hundred papers have reported genome-wide data from ancient humans. While the raw data for the vast majority are fully publicly available testifying to the commitment of the paleogenomics community to open data, formats for both raw data and meta-data differ. There is thus a need for uniform curation and a centralized, version-controlled compendium that researchers can download, analyze, and reference. Since 2019, we have been maintaining the Allen Ancient DNA Resource (AADR), which aims to provide an up-to-date, curated version of the world's published ancient human DNA data, represented at more than a million single nucleotide polymorphisms (SNPs) at which almost all ancient individuals have been assayed. The AADR has gone through six public releases at the time of writing and review of this manuscript, and crossed the threshold of >10,000 individuals with published genome-wide ancient DNA data at the end of 2022. This note is intended as a citable descriptor of the AADR.

Windows into the past: recent scientific techniques in dental analysis

Teeth are the hardest and most chemically stable tissues in the body, are well-preserved in archaeological remains and, being resistant to decomposition in the soil, survive long after their supporting structures have deteriorated. It has long been recognised that visual and radiographic examination of teeth can provide considerable information relating to the lifestyle of an individual. This paper examines the latest scientific approaches that have become available to investigate recent and ancient teeth. These techniques include DNA analysis, which can be used to determine the sex of an individual, indicate familial relationships, study population movements, provide phylogenetic information and identify the presence of disease pathogens. A stable isotopic approach can shed light on aspects of diet and mobility and even research climate change. Proteomic analysis of ancient dental calculus can reveal specific information about individual diets. Synchrotron microcomputed tomography is a non-invasive technique which can be used to visualise physiological impactful events, such as parturition, menopause and diseases in cementum microstructure - these being displayed as aberrant growth lines.

Genetic history of Cambridgeshire before and after the Black Death

The extent of the devastation of the Black Death pandemic (1346-1353) 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 the local scale. Here, we report 275 ancient genomes, including 109 with coverage >0.1×, from later medieval and postmedieval Cambridgeshire of individuals buried before and after the Black Death. 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. While we detect long-term shifts in local genetic ancestry in Cambridgeshire, we find no evidence of major changes in genetic ancestry nor higher differentiation of immune loci between cohorts living before and after the Black Death.

The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change

Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 years, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets.

Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using large correlation matrices, but this approach is inefficient, especially in ancestrally diverse studies. In the present study, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We published LDGMs and ancestry-specific LDGM precision matrices for 18 million common variants (minor allele frequency >1%) in five ancestry groups, validated their accuracy and demonstrated order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implemented an extremely fast multiancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally diverse genetic association data across millions of variants and individuals.

Provenancing antiquarian museum collections using multi-isotope analysis

Many of the most significant archaeological sites in Europe were excavated by antiquarians over one hundred years ago. Modern museum collections therefore frequently contain human remains that were recovered during the nineteenth and early twentieth centuries. Here we apply multi-isotope analysis (⁸⁷Sr/⁸⁶Sr, δ ¹⁸O, δ ¹³C, δ ¹⁵N) and ¹⁴C dating to evaluate the provenance of human remains within a collection that is thought to have been recovered from one of the most important archaeological sites in Britain. Excavated in 1910, the site of Coldrum in Kent is a megalithic burial monument that may be one of the earliest sites associated with the transition to farming in Britain. The interpretation of this site is therefore key to understanding how agriculture began. Using isotope analysis we show that although the human skeletal collections attributed to Coldrum do contain some of the earliest dated Neolithic human remains in Britain, they also contain the remains of individuals of fifth to seventh centuries AD date. We evaluate subsistence and mobility patterns of early Neolithic populations and provide new information about the origins of those individuals in the collection that date to the fifth to seventh centuries AD. We demonstrate the utility of employing isotope analysis to provide direct and independent information about the provenance of human remains in museum collections.

Sex bias in Neolithic megalithic burials

Objectives

A statistical study comparing osteological and ancient DNA determinations of sex was conducted in order to investigate whether there are sex biases in United Kingdom and Irish Neolithic megalithic burials.

Materials and Methods

Genetic and osteological information from human individuals from 32 megalithic sites in the UK and Ireland dating from 4000 to 2500 cal. BCE was collected and statistically analyzed to test whether there is a true over‐representation of males at these sites. The published dataset from the study by Sánchez‐Quinto et al. in 2019 was initially analyzed before being refined and included in a larger dataset. Osteological analysis of sex bias was limited to adults with available sex estimations, and genetic analysis limited to published data

Results

Two sites consistently returned significant p ‐values suggesting a potential over‐representation in osteological males at one site (Knowe of Midhowe, Orkney) and genetic males in the other (Primrose Grange, Ireland). Cumulative statistical analyses point towards a male bias in the representation of sexes in Neolithic megalithic burials, but these results do not reflect the site‐by‐site and regional variation found in this study.

Discussion

The interpretation of sex bias, that is, the over‐representation of one sex over another ‐ depends on other socio‐cultural variables (e.g., kinship) and the emphasis placed on statistical significance. The trend towards males being over‐represented in Neolithic megalithic burials is not as clear as previously thought, and requires further testing and data collection to uncover.

Ancient Maltese genomes and the genetic geography of Neolithic Europe

Archaeological consideration of maritime connectivity has ranged from a biogeographical perspective that considers the sea as a barrier to a view of seaways as ancient highways that facilitate exchange. Our results illustrate the former. We report three Late Neolithic human genomes from the Mediterranean island of Malta that are markedly enriched for runs of homozygosity, indicating inbreeding in their ancestry and an effective population size of only hundreds, a striking illustration of maritime isolation in this agricultural society. In the Late Neolithic, communities across mainland Europe experienced a resurgence of hunter-gatherer ancestry, pointing toward the persistence of different ancestral strands that subsequently admixed. This is absent in the Maltese genomes, giving a further indication of their genomic insularity. Imputation of genome-wide genotypes in our new and 258 published ancient individuals allowed shared identity-by-descent segment analysis, giving a fine-grained genetic geography of Neolithic Europe. This highlights the differentiating effects of seafaring Mediterranean expansion and also island colonization, including that of Ireland, Britain, and Orkney. These maritime effects contrast profoundly with a lack of migratory barriers in the establishment of Central European farming populations from Anatolia and the Balkans.

A unified genealogy of modern and ancient genomes

The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.

Ancient DNA at the edge of the world: Continental immigration and the persistence of Neolithic male lineages in Bronze Age Orkney

The Orcadian Neolithic has been intensively studied and celebrated as a major center of cultural innovation, whereas the Bronze Age is less well known and often regarded as a time of stagnation and insularity. Here, we analyze ancient genomes from the Orcadian Bronze Age in the context of the variation in Neolithic Orkney and Bronze Age Europe. We find clear evidence for Early Bronze Age immigration into Orkney, but with an extraordinary pattern: continuity from the Neolithic on the male line of descent but immigration from continental Europe on the female side, echoed in the genome-wide picture. This suggests that despite substantial immigration, indigenous male lineages persisted for at least a thousand years after the end of the Neolithic.

Orkney was a major cultural center during the Neolithic, 3800 to 2500 BC. Farming flourished, permanent stone settlements and chambered tombs were constructed, and long-range contacts were sustained. From ∼3200 BC, the number, density, and extravagance of settlements increased, and new ceremonial monuments and ceramic styles, possibly originating in Orkney, spread across Britain and Ireland. By ∼2800 BC, this phenomenon was waning, although Neolithic traditions persisted to at least 2500 BC. Unlike elsewhere in Britain, there is little material evidence to suggest a Beaker presence, suggesting that Orkney may have developed along an insular trajectory during the second millennium BC. We tested this by comparing new genomic evidence from 22 Bronze Age and 3 Iron Age burials in northwest Orkney with Neolithic burials from across the archipelago. We identified signals of inward migration on a scale unsuspected from the archaeological record: As elsewhere in Bronze Age Britain, much of the population displayed significant genome-wide ancestry deriving ultimately from the Pontic-Caspian Steppe. However, uniquely in northern and central Europe, most of the male lineages were inherited from the local Neolithic. This suggests that some male descendants of Neolithic Orkney may have remained distinct well into the Bronze Age, although there are signs that this had dwindled by the Iron Age. Furthermore, although the majority of mitochondrial DNA lineages evidently arrived afresh with the Bronze Age, we also find evidence for continuity in the female line of descent from Mesolithic Britain into the Bronze Age and even to the present day.

A high-resolution picture of kinship practices in an Early Neolithic tomb

To explore kinship practices at chambered tombs in Early Neolithic Britain, here we combined archaeological and genetic analyses of 35 individuals who lived about 5,700 years ago and were entombed at Hazleton North long cairn¹. Twenty-seven individuals are part of the first extended pedigree reconstructed from ancient DNA, a five-generation family whose many interrelationships provide statistical power to document kinship practices that were invisible without direct genetic data. Patrilineal descent was key in determining who was buried in the tomb, as all 15 intergenerational transmissions were through men. The presence of women who had reproduced with lineage men and the absence of adult lineage daughters suggest virilocal burial and female exogamy. We demonstrate that one male progenitor reproduced with four women: the descendants of two of those women were buried in the same half of the tomb over all generations. This suggests that maternal sub-lineages were grouped into branches whose distinctiveness was recognized during the construction of the tomb. Four men descended from non-lineage fathers and mothers who also reproduced with lineage male individuals, suggesting that some men adopted the children of their reproductive partners by other men into their patriline. Eight individuals were not close biological relatives of the main lineage, raising the possibility that kinship also encompassed social bonds independent of biological relatedness.

Ancient genomes reveal structural shifts after the arrival of Steppe-related ancestry in the Italian Peninsula

Across Europe, the genetics of the Chalcolithic/Bronze Age transition is increasingly characterized in terms of an influx of Steppe-related ancestry. The effect of this major shift on the genetic structure of populations in the Italian Peninsula remains underexplored. Here, genome-wide shotgun data for 22 individuals from commingled cave and single burials in Northeastern and Central Italy dated between 3200 and 1500 BCE provide the first genomic characterization of Bronze Age individuals (n = 8; 0.001-1.2× coverage) from the central Italian Peninsula, filling a gap in the literature between 1950 and 1500 BCE. Our study confirms a diversity of ancestry components during the Chalcolithic and the arrival of Steppe-related ancestry in the central Italian Peninsula as early as 1600 BCE, with this ancestry component increasing through time. We detect close patrilineal kinship in the burial patterns of Chalcolithic commingled cave burials and a shift away from this in the Bronze Age (2200-900 BCE) along with lowered runs of homozygosity, which may reflect larger changes in population structure. Finally, we find no evidence that the arrival of Steppe-related ancestry in Central Italy directly led to changes in frequency of 115 phenotypes present in the dataset, rather that the post-Roman Imperial period had a stronger influence, particularly on the frequency of variants associated with protection against Hansen's disease (leprosy). Our study provides a closer look at local dynamics of demography and phenotypic shifts as they occurred as part of a broader phenomenon of widespread admixture during the Chalcolithic/Bronze Age transition.

Heterogeneous Hunter-Gatherer and Steppe-Related Ancestries in Late Neolithic and Bell Beaker Genomes from Present-Day France

The transition from the Late Neolithic to the Bronze Age has witnessed important population and societal changes in western Europe.¹ These include massive genomic contributions of pastoralist herders originating from the Pontic-Caspian steppes^2,3 into local populations, resulting from complex interactions between collapsing hunter-gatherers and expanding farmers of Anatolian ancestry.^4-8 This transition is documented through extensive ancient genomic data from present-day Britain,^9,10 Ireland,^11,12 Iberia,¹³ Mediterranean islands,^14,15 and Germany.⁸ It remains, however, largely overlooked in France, where most focus has been on the Middle Neolithic (n = 63),^8,9,16 with the exception of one Late Neolithic genome sequenced at 0.05× coverage.¹⁶ This leaves the key transitional period covering ∼3,400-2,700 cal. years (calibrated years) BCE genetically unsampled and thus the exact time frame of hunter-gatherer persistence and arrival of steppe migrations unknown. To remediate this, we sequenced 24 ancient human genomes from France spanning ∼3,400-1,600 cal. years BCE. This reveals Late Neolithic populations that are genetically diverse and include individuals with dark skin, hair, and eyes. We detect heterogeneous hunter-gatherer ancestries within Late Neolithic communities, reaching up to ∼63.3% in some individuals, and variable genetic contributions of steppe herders in Bell Beaker populations. We provide an estimate as late as ∼3,800 years BCE for the admixture between Neolithic and Mesolithic populations and as early as ∼2,650 years BCE for the arrival of steppe-related ancestry. The genomic heterogeneity characterized underlines the complex history of human interactions even at the local scale.

Evaluating genotype imputation pipeline for ultra-low coverage ancient genomes

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.

Efficiently Summarizing Relationships in Large Samples: A General Duality Between Statistics of Genealogies and Genomes

As a genetic mutation is passed down across generations, it distinguishes those genomes that have inherited it from those that have not, providing a glimpse of the genealogical tree relating the genomes to each other at that site. Statistical summaries of genetic variation therefore also describe the underlying genealogies. We use this correspondence to define a general framework that efficiently computes single-site population genetic statistics using the succinct tree sequence encoding of genealogies and genome sequence. The general approach accumulates sample weights within the genealogical tree at each position on the genome, which are then combined using a summary function; different statistics result from different choices of weight and function. Results can be reported in three ways: by site, which corresponds to statistics calculated as usual from genome sequence; by branch, which gives the expected value of the dual site statistic under the infinite sites model of mutation, and by node, which summarizes the contribution of each ancestor to these statistics. We use the framework to implement many currently defined statistics of genome sequence (making the statistics' relationship to the underlying genealogical trees concrete and explicit), as well as the corresponding branch statistics of tree shape. We evaluate computational performance using simulated data, and show that calculating statistics from tree sequences using this general framework is several orders of magnitude more efficient than optimized matrix-based methods in terms of both run time and memory requirements. We also explore how well the duality between site and branch statistics holds in practice on trees inferred from the 1000 Genomes Project data set, and discuss ways in which deviations may encode interesting biological signals.

A dynastic elite in monumental Neolithic society

The nature and distribution of political power in Europe during the Neolithic era remains poorly understood¹. During this period, many societies began to invest heavily in building monuments, which suggests an increase in social organization. The scale and sophistication of megalithic architecture along the Atlantic seaboard, culminating in the great passage tomb complexes, is particularly impressive². Although co-operative ideology has often been emphasised as a driver of megalith construction1, the human expenditure required to erect the largest monuments has led some researchers to emphasize hierarchy³—of which the most extreme case is a small elite marshalling the labour of the masses. Here we present evidence that a social stratum of this type was established during the Neolithic period in Ireland. We sampled 44 whole genomes, among which we identify the adult son of a first-degree incestuous union from remains that were discovered within the most elaborate recess of the Newgrange passage tomb. Socially sanctioned matings of this nature are very rare, and are documented almost exclusively among politico-religious elites⁴—specifically within polygynous and patrilineal royal families that are headed by god-kings^5,6. We identify relatives of this individual within two other major complexes of passage tombs 150 km to the west of Newgrange, as well as dietary differences and fine-scale haplotypic structure (which is unprecedented in resolution for a prehistoric population) between passage tomb samples and the larger dataset, which together imply hierarchy. This elite emerged against a backdrop of rapid maritime colonization that displaced a unique Mesolithic isolate population, although we also detected rare Irish hunter-gatherer introgression within the Neolithic population.

Inference of natural selection from ancient DNA

Evolutionary processes, including selection, can be indirectly inferred based on patterns of genomic variation among contemporary populations or species. However, this often requires unrealistic assumptions of ancestral demography and selective regimes. Sequencing ancient DNA from temporally spaced samples can inform about past selection processes, as time series data allow direct quantification of population parameters collected before, during, and after genetic changes driven by selection. In this Comment and Opinion, we advocate for the inclusion of temporal sampling and the generation of paleogenomic datasets in evolutionary biology, and highlight some of the recent advances that have yet to be broadly applied by evolutionary biologists. In doing so, we consider the expected signatures of balancing, purifying, and positive selection in time series data, and detail how this can advance our understanding of the chronology and tempo of genomic change driven by selection. However, we also recognize the limitations of such data, which can suffer from postmortem damage, fragmentation, low coverage, and typically low sample size. We therefore highlight the many assumptions and considerations associated with analyzing paleogenomic data and the assumptions associated with analytical methods.