E. Willerslev’s research while affiliated with University of Bremen and other places

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Publications (118)


Steppe Ancestry in Western Eurasia and the Spread of the Germanic Languages
  • Preprint
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March 2024

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3,311 Reads

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4 Citations

Hugh McColl

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Guus Kroonen

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[...]

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Eske Willerslev

Today, Germanic languages, including German, English, Frisian, Dutch and the Nordic languages, are widely spoken in northwest Europe. However, key aspects of the assumed arrival and diversification of this linguistic group remain contentious 1—3 . By adding 712 new ancient human genomes we find an archaeologically elusive population entering Sweden from the Baltic region by around 4000 BP. This population became widespread throughout Scandinavia by 3500 BP, matching the contemporaneous distribution of Palaeo-Germanic, the Bronze Age predecessor of Proto-Germanic 4—6 . These Baltic immigrants thus offer a new potential vector for the first Germanic speakers to arrive in Scandinavia, some 800 years later than traditionally assumed 7—12 . Following the disintegration of Proto-Germanic 13—16 , we find by 1650 BP a southward push from Southern Scandinavia into presumed Celtic-speaking areas, including Germany, Poland and the Netherlands. During the Migration Period (1575—1375 BP), we see this ancestry representing West Germanic Anglo-Saxons in Britain, and Langobards in southern Europe. We find a related large-scale northward migration into Denmark and South Sweden corresponding with historically attested Danes and the expansion of Old Norse. These movements have direct implications for multiple linguistic hypotheses. Our findings show the power of combining genomics with historical linguistics and archaeology in creating a unified, integrated model for the emergence, spread and diversification of a linguistic group.

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Genetic structure of the 317 herein-reported ancient genomes
a–d, PCA of 3,316 modern and ancient individuals from Eurasia, Oceania and the Americas (a,b), as well as restricted to 2,126 individuals from western Eurasia (west of the Urals) (c,d). Shown are analyses with principal components inferred either using both modern and imputed ancient genomes passing all filters, and projecting low coverage ancient genomes (a,c); or only modern genomes and projecting all ancient genomes (b,d). Ancient genomes sequenced in this study are indicated either with black circles (imputed genomes) or grey diamonds (projected genomes). e, Model-based clustering results using ADMIXTURE for 284 newly reported genomes (excluding close relatives and individuals flagged for possible contamination). Results shown are based on ADMIXTURE runs from K = 2 to K = 15 on 1,593 ancient individuals, corresponding to the full set of 1,492 imputed genomes passing filters as well as 101 low coverage genomes represented by pseudo-haploid genotypes (flags “lowcov” or “lowGpAvg”, Supplementary Data 7; indicated with alpha transparency in plot).
Imputation accuracy of ancient DNA
a, Imputation accuracy across 42 high-coverage ancient genomes when downsampled to lower depth of coverage values (see Supplementary Note 2 and Supplementary Table 2.1). b, Imputation accuracy for 1× depth of coverage across 9 prehistoric European genomes; c, across 5 Viking age genomes; and d, across 7 ancient genomes from Early Medieval Hungary. In all panels, imputation accuracy is shown as the squared Pearson correlation between imputed and true genotype dosages as a function of MAF of the target variant sites.
Genetic clustering of ancient individuals
Characterization of genetic clusters for 1,401 imputed ancient individuals from Eurasia (that is, excluding 91 individuals from Africa and Americas), inferred from pairwise IBD sharing (indicated using coloured symbols throughout), a, Temporal distribution of clustered individuals, grouped by broad ancestry cluster. b,c, Geographical distribution of clustered individuals, shown for individuals predating 3,000 bp (b) and after 3,000 bp (c). d, Network graph of pairwise IBD sharing between 596 ancient Eurasians predating 3,000 bp, highlighting within- and between-cluster relationships. Each node represents an individual, and the width of edges connecting nodes indicates the fraction of the genome shared IBD between the respective pair of individuals. Network edges were restricted to the 10 highest sharing connections for each individual, and the layout was computed using the force-directed Fruchterman-Reingold algorithm. e, Neighbour-joining tree showing relationships between genetic clusters, inferred using total variation distance (TVD) of IBD painting palettes. f,g, PCA of 3,119 Eurasian (f) or 2,126 west Eurasian (g) ancient and modern individuals (“HO” dataset).
Genetic structure of European HGs after the LGM
a, Supervised ancestry modelling using non-negative least squares on IBD sharing profiles. Panels show estimated ancestry proportions for target individuals from genetic clusters representing European HGs, using different sets of increasingly proximal source groups. Individuals used as sources in a particular set are indicated with black crosses and coloured bars with 100% ancestry proportion. Black lines indicate 1 standard error for the respective ancestry component. b, Residuals for model fit of target individuals from selected genetic clusters across different source sets. c, Moon charts showing spatial distribution of ancestry proportions in European HGs deriving from four European source groups (set “hgEur2”; source origins shown with coloured symbol). Estimated ancestry proportions are indicated by both size and amount of fill of moon symbols. Note that ‘Italy_15000BP_9000BP’ and ‘RussiaNW_11000BP_8000BP’ correspond to ‘WHG’ and ‘EHG’ labels used in previous studies. d, Maps showing networks of highest between-cluster IBD sharing (top 10 highest sharing per individual) for individuals from two genetic clusters representing Scandinavian HGs. See Supplementary Data 1 and 7 for details of individual sample IDs presented here.
Ancestry modelling for HG and Neolithic farmer-associated genetic clusters
Supervised ancestry modelling using non-negative least squares on IBD sharing profiles. Panels show estimated ancestry proportions of two global Eurasian clusters, corresponding to European HGs before 4,000 bp and individuals from Europe and western Asia from around 10,000 bp until historical times, including Anatolian-associated (Neolithic) farmers, Caucasus HGs and recent individuals with genetic affinity to the Levant. Columns show results of modelling target individuals using three panels of increasingly distal source groups: “postBA”: Bronze Age and Neolithic source groups; “postNeol”, Bronze Age and later targets using Late Neolithic/early Bronze Age and earlier source groups; “deep”, Mesolithic and later targets using deep ancestry source groups. Individuals used as sources in a particular set are indicated with black crosses and coloured bars with 100% ancestry proportion. Black lines indicate 1 standard error for the respective ancestry component.

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Population genomics of post-glacial western Eurasia

January 2024

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2,335 Reads

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87 Citations

Nature

Western Eurasia witnessed several large-scale human migrations during the Holocene1–5. Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes—mainly from the Mesolithic and Neolithic periods—from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a ‘great divide’ genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 bp, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 bp, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a ‘Neolithic steppe’ cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.


Seventy-two ancient wolf genomes
a, Sampling locations of ancient wolves and one ancient dhole analysed here, on a base map from Natural Earth (naturalearthdata.com). b, Ages and sequencing coverage of ancient wolves. c, PC1 from a PCA on outgroup f3-statistics plotted against sample age. PCs were calculated from ancient wolves only, with present-day wolves and dogs projected onto the plot. d, Heterozygosity estimates from sampling of two reads at sites ascertained as heterozygous in a coyote. Bars denote 95% CIs from block jackknifing.
One hundred thousand years of wolf population history
a, Admixture graph fit by qpGraph to selected ancient wolves, with two outlier (|Z| > 3) f-statistics (worst = 3.16). b, Best-fitting qpAdm models for post-LGM and present-day wolves. An ancient dhole was used as the outgroup for Eurasian wolves to capture any unsampled divergent ancestry, while a coyote was used as the outgroup for North American wolves. Bars denote ±1 standard error estimated from a block jackknife. c, FST for pairs of sample groups with mean dates separated by ≤12,500 years. Bars denote ±1.96 standard errors d, MSMC2 results for pairs of male X chromosomes, with sample ages indicated by blue lines. A sharp upwards spike in the curve corresponds to population divergence, with estimated timings indicated by red lines. Example curves for two pairs of wolves (left and middle) and a summary of results for all pairs (right) are shown. kyr, thousand years.
Natural selection in the ancient wolf time series
a, –log10(P values) (two sided, not adjusted for multiple comparisons) from linear regression for association between allele frequency and sample age. b, Quantile–quantile plot comparing the P values in a to those expected under a uniform distribution (top) and likewise for results from a simulated neutrally evolving population (effective population size (Ne) = 50,000) (bottom). c, Allele observations in ancient wolves and frequencies in present-day populations for lead variants from the three strongest peaks. Bars denote 95% binomial CIs. d, Local P values (from a) and TMRCA inferred using Relate on modern wolves and dogs for the region surrounding IFT88. The genome-wide histogram (quantiles in grey lines) shows that this locus has the most recent TMRCA in the genome.
The ancestry of dogs
a, PCA on post-LGM and present-day wolves (X), based on f4-statistics only of the form f4(X,A;B,C), where A, B and C are any of 21 wolves predating 28 ka. Dogs are projected, and coloured by f4(AndeanFox,X;Zhokhov dog 9.5 ka,Tel Hreiz dog 7.2 ka). b, For dogs (X), f4(AndeanFox,X;Zhokhov dog 9.5 ka,Tel Hreiz dog 7.2 ka) horizontally against f4(AndeanFox,X;Belaya Gora wolf 18 ka,Hohle Fels wolf 13 ka) vertically (Pearson’s r = 0.86, P = 3 × 10–23). Bars denote ±1 standard error estimated from a block jackknife. Silhouettes from phylopic.org. c, log10(P values) for qpAdm models fit to dog targets, where a low P value means the model can be rejected. An ancient dhole was used to represent unsampled, divergent ancestry; models including this source have black outlines. Points are jittered horizontally to avoid overlap. d, qpAdm ancestry proportions for dogs, using the Zhokhov (9.5 ka) dog and a present-day Syrian wolf as proxies for eastern and western dog progenitor ancestry, respectively. Bars denote ±1 standard error estimated from a block jackknife. e, Map of early and relevant later dogs and their ancestry proportions as in d. Black crosses indicate the locations of wolves from 25–10 ka that can be rejected as dog progenitors. Base map from the mapdata R package. k, thousand years. f, Admixture graph model of major dog lineage relationships, fit by qpGraph with no outlier f-statistics. Edge lengths are in units of FST (×1,000).
Grey wolf genomic history reveals a dual ancestry of dogs

July 2022

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2,807 Reads

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115 Citations

Nature

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1–8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located.


Fig 1. Sample overview and broad scale genetic structure. (A), (B) Geographic and temporal distribution of the 317 ancient genomes reported here. Age and geographic region of ancient individuals are indicated by plot symbol colour and shape, respectively. Random jitter was added to geographic coordinates to avoid overplotting. (C), (D) Principal component analysis of 3,316 modern and ancient individuals from Eurasia, Oceania, and the Americas (C), as well as restricted to 2,126 individuals from western Eurasia (west of Urals) (D). Principal components were defined using both modern and imputed ancient genomes passing all filters, with the remaining low-coverage ancient genomes projected. Ancient genomes sequenced in this study are indicated with black circles (imputed genomes passing all filters, n=213) or grey diamonds (pseudo-haploid projected genomes, n=104). Genomes of modern individuals are shown in grey, with population labels corresponding to their median coordinates.
Fig 2. Genetic structure of European hunter-gatherers (A) Ancestry proportions in 113 imputed ancient genomes representing European hunter-gatherer contexts (right) estimated from supervised non-negative least squares analysis using deep Eurasian source groups (left). Individuals from target groups are grouped by genetic clusters. (B)-(D) Moon charts showing spatial distribution of ancestry proportions in European hunter-gatherers deriving from three deep Eurasian source groups; Italy_15000BP_9000BP; Ukraine_10000BP_4000BP; RussiaNW_11000BP_8000BP (source origins shown with coloured symbol). Estimated ancestry proportions are indicated by both size and amount of fill of moon symbols.
Fig 5. The genetic legacy of Stone Age ancestry in modern populations. From top left clockwise: Neolithic Farmer, Yamnaya, Caucasus hunter-gatherer, Eastern hunter-gatherer, Western hunter-gatherer. Panels show average admixture proportion in modern individuals per country estimated using NNLS (large maps), average per county within the UK (top left insert), and PCA (PC2 vs PC1) of admixture proportions, with the top 10 highest countries by admixture fraction labelled and PCA loadings for that ancestry.
Fig 6. Patterns of co-ancestry. (A)-(D) Panels show within-cluster genetic relatedness over time, measured either as the total length of genomic segments shared IBD between individuals (A, B) or the proportion of individual genomes found in a run of homozygosity f(ROH) (C,D). Results for both measures are shown separately for individuals from western (A, C) or eastern Eurasia (B, D). Small grey dots indicate estimates for individual pairs (A, B) or individuals (C, D), with larger coloured symbols indicating median values within genetic clusters. (E) Distribution of ROH lengths for 39 individuals with evidence for recent parental relatedness (>50 cM total in ROHs > 20 cM).
Population Genomics of Stone Age Eurasia

May 2022

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8,029 Reads

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42 Citations

Western Eurasia witnessed several large-scale human migrations during the Holocene. To investigate the cross-continental impacts we shotgun-sequenced 317 primarily Mesolithic and Neolithic genomes from across Northern and Western Eurasia. These were imputed alongside published data to obtain diploid genotypes from >1,600 ancient humans. Our analyses revealed a 'Great Divide' genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers (HGs) were highly genetically differentiated east and west of this zone, and the impact of the neolithisation was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacements of HGs in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, while east of the Urals relatedness remained high until ~4,000 BP, consistent with persistence of localised HG groups. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive but we demonstrate that HGs from the Middle Don region contributed ancestry to them. Yamnaya-groups later admixed with individuals associated with the Globular Amphora Culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a 'Neolithic steppe' cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.


Genetic population structure across Brittany and the downstream Loire basin provides new insights on the demographic history of Western Europe

February 2022

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250 Reads

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8 Citations

European genetic ancestry originates from three main ancestral populations - Western hunter-gatherers, early European farmers and Yamnaya Eurasian herders - whose edges geographically met in present-day France. Despite its central role to our understanding of how the ancestral populations interacted and gave rise to modern population structure, the population history of France has remained largely understudied. Here, we analysed 856 high-coverage whole-genome sequences along with genome-wide genotyping data of 3,234 present-day individuals from the northern half of France and merged them with publicly available present-day and ancient Europe-wide genotype datasets. We also analysed, for the first time, the whole-genome sequences of six medieval individuals (300-1100 CE) from Western France to gain insights into the genetic impact of what is commonly known as the Migration Period in Europe. We found extensive fine-scale population structure across Brittany and the downstream Loire basin, emphasizing the need for investigating local populations to better understand the distribution of rare and putatively deleterious variants across space. Overall, we observed an increased population differentiation between the northern and southern sides of the river Loire, which are characterised by different proportions of steppe vs. Neolithic-related ancestry. Samples from Western Brittany carry the largest levels of steppe ancestry and show high levels of allele sharing with individuals associated with the Bell Beaker complex, levels that are only comparable with those found in populations lying on the northwestern edges of Europe. Together, our results imply that present-day individuals from Western Brittany retain substantial legacy of the genetic changes that occurred in Northwestern Europe following the arrival of the Bell Beaker people c. 2500 BCE. Such genetic legacy may explain the sharing of disease-related alleles with other present-day populations from Western Britain and Ireland.


An Ancient Baboon Genome Demonstrates Long-Term Population Continuity in Southern Africa

February 2020

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142 Reads

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15 Citations

Genome Biology and Evolution

Baboons are one of the most abundant large nonhuman primates and are widely studied in biomedical, behavioral and anthropological research. Despite this, our knowledge of their evolutionary and demographic history remains incomplete. Here, we report a 0.9-fold coverage genome sequence from a 5800-year-old baboon from the site of Ha Makotoko in Lesotho. The ancient baboon is closely related to present-day Papio ursinus individuals from southern Africa-indicating a high degree of continuity in the southern African baboon population. This level of population continuity is rare in recent human populations, but may provide a good model for the evolution of Homo and other large primates over similar timespans in structured populations throughout Africa.


Figure 1. Equine Archaeological Remains (A) Location of archaeological sites. Pie charts are proportional to the total number of specimens providing DNA data compatible with the determination of sex, species and hybrid status. The names and temporal ranges (years ago) of the sites where hybrids and non-caballine species could be genetically identified are indicated. (B) Temporal distribution of ancient specimens. Eight individuals showing uncertain age determination are not included. See also Tables S1, S2, S3, and S4.
Figure 3. TreeMix Phylogenetic Relationships
Graphical abstract
• Two now-extinct horse lineages lived in Iberia and Siberia some 5,000 years ago

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 Iberian and Siberian horses contributed limited ancestry to modern domesticates

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 Oriental horses have had a strong genetic influence within the last millennium

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 Modern breeding practices were accompanied by a significant drop in genetic diversity
Tracking Five Millennia of Horse Management with Extensive Ancient Genome Time Series

May 2019

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4,477 Reads

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265 Citations

Cell

Horse domestication revolutionized warfare and accelerated travel, trade, and the geographic expansion of languages. Here, we present the largest DNA time series for a non-human organism to date, including genome-scale data from 149 ancient animals and 129 ancient genomes (≥1-fold coverage), 87 of which are new. This extensive dataset allows us to assess the modern legacy of past equestrian civilizations. We find that two extinct horse lineages existed during early domestication, one at the far western (Iberia) and the other at the far eastern range (Siberia) of Eurasia. None of these contributed significantly to modern diversity. We show that the influence of Persian-related horse lineages increased following the Islamic conquests in Europe and Asia. Multiple alleles associated with elite-racing, including at the MSTN “speed gene,” only rose in popularity within the last millennium. Finally, the development of modern breeding impacted genetic diversity more dramatically than the previous millennia of human management.




Citations (27)


... During Antiquity, both regions were part of the Roman Empire. While the Rhine-Main area belonged to the province of Germania Superior that persisted until the end of the 3rd century, the Danube-Isar region belonged to the province of Raetia Secunda until the Western Roman Empire collapsed in the late 5th (4), Hassleben (5), Hiddestorf (6), Anderten (7), Liebenau (8), Drantum (9), Midlum (10), Groningen (11), Zetel (12), Issendorf (13), Schortens (14), Ljubljana (15), Hács (16), Fonyód (17), Szólád (18), Balatonszemes (19), Komárno (20), Klosterneuburg (21), Sarrebourg (22), Metz (20). ...

Reference:

Historic Genomes Uncover Demographic Shifts and Kinship Structures in Post-Roman Central Europe
Steppe Ancestry in Western Eurasia and the Spread of the Germanic Languages

... Between ca. 2700 and 1200 BCE, corresponding to the end of the late-Middle Neolithic period through to the Bronze Age, a steep decline in shell midden activity took place, although shell middens continued to be used sporadically for the burial of human remains in some regions, particularly northern Jutland and the Limfjord (Allentoft et al., 2024a(Allentoft et al., , 2024bFrei et al., 2019;Price et al., 2007;Sluis et al., 2019;van der Sluis and Reimer, 2021). ...

Population genomics of post-glacial western Eurasia

Nature

... The dog is widely regarded as the first domesticated animal in human history, and its incorporation into human society has had profound effects on human cultural adaptations (Morey, 2010;Losey et al., 2018). Despite decades of research, identifying the origin of dogs has been elusive (Benecke, 1987;Germonpré et al., 2009;Drake et al., 2015;Perri, 2016;Botigué et al., 2017;Thalmann and Perri, 2019), although recent findings suggest dogs may have been independently domesticated in more than one geographical region (Frantz et al., 2016;Bergström et al., 2022). The process of dog domestication has likewise been contentious, with one hypothesis arguing that humans actively captured and hand-raised wolves, with these socialized wolves becoming reproductively isolated from wild populations, ultimately giving rise to early dogs (Serpell, 1989(Serpell, , 2021Müller, 2005;Germonpré et al., 2018Germonpré et al., , 2021Mech and Janssens, 2022;Brumm et al., 2023). ...

Grey wolf genomic history reveals a dual ancestry of dogs

Nature

... In recent years, however, the long-standing debates about culture historical entities have been revived and given a new significance by the results of the whole genome aDNA studies of prehistoric populations that have appeared, many of them focused on populations of the last ten thousand years in Europe that have been central to culture historical studies (e.g. Allentoft et al. 2015;Haak et al. 2015;Hofmanová et al. 2016;Lazaridis et al. 2016). The reason for the controversy is that the findings seem to support some of the classic culture history claims that archaeological cultures correspond to biological populations (Frieman & Hofmann 2019;Furholt 2018;Kristiansen 2022). ...

Population Genomics of Stone Age Eurasia

... Although from distinct material cultures, all PWC and FBC individuals are broadly contemporaneous from the same period of the Nordic Middle Neolithic (circa 3200 − 2300BCE). The raw sequence data was processed according to [48] and [47]. See Appendix section "Data processing" for how genotypes were called. ...

Genetic population structure across Brittany and the downstream Loire basin provides new insights on the demographic history of Western Europe
  • Citing Preprint
  • February 2022

... 2008; Horsburgh and Rhines 2010;Fregel et al. 2018;Mathieson et al. 2020) (Gifford-Gonzalez 2013). However, studies that focus on samples from the African continent have so far mostly concentrated on human remains and on DNA enrichment approaches and only rarely investigate animal fossils (e.g., Mathieson et al. 2020). ...

An Ancient Baboon Genome Demonstrates Long-Term Population Continuity in Southern Africa

Genome Biology and Evolution

... In the fifteen years since the genome sequence of a Thoroughbred mare called Twilight was published (Raudsepp et al. 2019;Wade et al. 2009), and the ensuing successful methods to extract and sequence ancient horse DNA were developed (Orlando et al. 2011), probably nothing has impacted our understanding of horse domestication as much as a series of landmark papers that reported the aDNA analysis from hundreds of ancient horses throughout Eurasia (Cieslak et al. 2016;Fages et al. 2019;Gaunitz et al. 2018;Guimaraes et al. 2020;Librado et al. 2015Librado et al. , 2016Librado et al. , 2017Librado et al. , 2021Librado et al. , 2024Lippold et al. 2011;Lira Garrido et al. 2010;Ludwig et al. 2009Ludwig et al. , 2014Makvandi-Nejad et al. 2010 Analysing genome-scale data from 149 ancient horses, along with 129 ancient horse genomes, Fages et al. (2019) found two lineages of horses present during the early phases of domestication processes which are now extinct, one in Iberia (IBE) and another in Siberia (ELEN) ( Figure 1a). The ancient Iberian horses are genetically distinct from DOM1 and DOM2 horses, effectively ruling out Iberia as the region that produced the ancestors of modern horses. ...

Tracking Five Millennia of Horse Management with Extensive Ancient Genome Time Series

Cell

... This may be due to insufficient coverage of the relatively large plastid genomes given that these are the off-target fraction of our sequenced reads, as well as abundant mis-mapping between related prokaryotes. There is also the possibility that longterm active repair mechanisms may minimize the deamination signal from prokaryotes (Johnson et al., 2007). ...

Ancient bacteria show evidence of DNA repair (Proceedings of the National Academy of Sciences of the United States of America (2007) 104, 36 (14401-14405) (DOI: 10.1073/pnas.0706787104)
  • Citing Article
  • December 2007

Proceedings of the National Academy of Sciences

... However, due to the broad amplification spectrum and high sensitivity of the VertU primers, cross-contaminations and false-positive detection will likely become issues and should be carefully dealt with, as discussed in previous studies (Ficetola et al., 2015;Wilson et al., 2015). In addition, besides collecting eDNA from water samples, there are many other ways to collect eDNAs nowadays, generating, for example, airborne, soil, or even blood-sucking insect eDNAs (Andersen et al., 2012;Schnell et al., 2012;Clare et al., 2021). We recommend future studies to apply the VertU primer sets with more eDNA sampling approaches to monitor vertebrate biodiversity. ...

Erratum: Screening mammal biodiversity using dna from leeches (Current Biology (2012) 22 (R262-R263))
  • Citing Article
  • October 2012

Current Biology

... The rapid dispersal of humans in South America is suggested by archaeological records, which date the earliest human presence in North Patagonia, the southernmost tip of the Americas, to 14,500 ya (19). However, the number of basal divergences, founding populations, admixture, and the degrees of isolation among Native South American populations remain a subject of debate (20)(21)(22)(23)(24)(25)(26)(27)(28)(29), with most of the current understanding coming from analyses of genome-wide genotyping or ancient DNA data. Additionally, fine-scale population genetic studies based on high-coverage whole-genome sequencing datasets for contemporary populations of North Eurasia and South America have not been performed to date. ...

Genomic insights into the origin and diversification of late maritime hunter-gatherers from the Chilean Patagonia

Proceedings of the National Academy of Sciences