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Post by Admin on May 20, 2022 18:50:12 GMT
Extended Data Fig. 8. Fine-scale structure in Late Neolithic Scandinavians. (A)-(E) Geographic locations and PCA based on pairwise IBD sharing (middle) of 148 European individuals predating 3,000 BP. Geographic locations are shown for 65 individuals belonging to the five genetic clusters observed in 38 ancient Scandinavians (temporal sequence shown in timeline in centre of plot). Individual assignments and frequency distribution of major Y chromosome haplogroups are indicated in maps and timeline. Plot symbols with black circles indicate the 38 Scandinavian individuals in the PCA panels. Ancestry proportions for the 38 Scandinavian individuals estimated using proximal source groups from outside Scandinavia (“postNeolScand” source set) are shown on the right of the respective cluster results. Extended Data Fig. 9. Genetic transformations across the Eurasian Steppe. (A)-(C) Principal component analysis of modern and ancient individuals from Eurasia, Oceania and the Americas, highlighting estimated ancestry proportions from “deep” Siberian ancestry sources (individuals highlighted with dashed line). Present-day individuals are shown in gray, with population labels corresponding to their median coordinates. (D)-(E) Moon charts showing spatial distribution of estimated ancestry proportions of Siberian hunter-gatherers before 5,000 BP from “deep” Siberian ancestry sources (names and locations indicated with coloured symbols). Estimated ancestry proportions are indicated by size and amount of fill of moon symbols. (G) Timelines of ancestry proportions from “postNeol” sources in Central and North Asian ancient individuals after 5,000 BP. Symbol shape and colour indicate the genetic cluster of each individual.
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Post by Admin on May 20, 2022 20:49:41 GMT
Extended Data Fig. 10. Selection at the HLA locus. Results for the pan-ancestry analysis (ALL) plus the four marginal ancestries: Western hunter-gatherers (WHG), Eastern hunter-gatherers (EHG), Caucasus hunter-gatherers (CHG) and Anatolian farmers (ANA). Row one shows zoomed Manhattan plots of the p-values for each ancestry (significant SNPs sized by their selection coefficients), and row two shows allele trajectories for the top SNPs across all ancestries (grey shading for the marginal ancestries indicates approximate temporal extent of the pre-admixture population). Extended Data Fig. 11. Selective sweep at the SLC22A4 locus. Results for the pan-ancestry analysis (ALL) plus the four marginal ancestries: Western hunter-gatherers (WHG), Eastern hunter-gatherers (EHG), Caucasus hunter-gatherers (CHG) and Anatolian farmers (ANA). Row one shows zoomed Manhattan plots of the p-values for each ancestry (significant SNPs sized by their selection coefficients), and row two shows allele trajectories for the top SNPs across all ancestries (grey shading for the marginal ancestries indicates approximate temporal extent of the pre-admixture population). Extended Data Fig. 12. Selective sweep at the HECTD4 locus. Results for the pan-ancestry analysis (ALL) plus the four marginal ancestries: Western hunter-gatherers (WHG), Eastern hunter-gatherers (EHG), Caucasus hunter-gatherers (CHG) and Anatolian farmers (ANA). Row one shows zoomed Manhattan plots of the p-values for each ancestry (significant SNPs sized by their selection coefficients), and row two shows allele trajectories for the top SNPs across all ancestries (grey shading for the marginal ancestries indicates approximate temporal extent of the pre-admixture population).
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Post by Admin on May 26, 2022 18:56:27 GMT
Stable population structure in Europe since the Iron Age, despite high mobility
Abstract Ancient DNA research in the past decade has revealed that European population structure changed dramatically in the prehistoric period (14,000-3,000 years before present, YBP), reflecting the widespread introduction of Neolithic farmer and Bronze Age Steppe ancestries. However, little is known about how population structure changed in the historical period onward (3,000 YBP - present). To address this, we collected whole genomes from 204 individuals from Europe and the Mediterranean, many of which are the first historical period genomes from their region (e.g. Armenia, France). We found that most regions show remarkable inter-individual heterogeneity. Around 8% of historical individuals carry ancestry uncommon in the region where they were sampled, some indicating cross-Mediterranean contacts. Despite this high level of mobility, overall population structure across western Eurasia is relatively stable through the historical period up to the present, mirroring the geographic map. We show that, under standard population genetics models with local panmixia, the observed level of dispersal would lead to a collapse of population structure. Persistent population structure thus suggests a lower effective migration rate than indicated by the observed dispersal. We hypothesize that this phenomenon can be explained by extensive transient dispersal arising from drastically improved transportation networks and the Roman Empire’s mobilization of people for trade, labor, and military. This work highlights the utility of ancient DNA in elucidating finer scale human population dynamics in recent history.
Introduction Ancient DNA (aDNA) sequencing has provided immense insight into previously unanswered questions about human population history. Initially, sequencing efforts were focused on identifying the main ancestry groups and transitions during prehistoric times, where there is no written record. Recently, aDNA sampling has expanded to more recent times, allowing the study of movements of people through genetic data alongside the well-studied historical record. However, we lack a comprehensive assessment of historical genetic structure, including characterizing genetic heterogeneity and interactions across regions. Integrating historical period genetics will be instrumental to better understanding the development of European and Mediterranean population structure from prehistoric to present-day.
Prehistoric ancient genomes have allowed disentangling the movements of people and technologies across two major demographic transitions in prehistoric western Eurasia: first the farming transition ∼7,500 BCE (Lazaridis et al., 2014; Skoglund et al., 2012), and later the Bronze Age Steppe migrations ∼3,500 BCE (Haak et al., 2015). Over the course of generations, genetically differentiated peoples across western Eurasia came together and admixed. As a result, most present-day European genomes can be modeled as a three-way mixture of these prehistoric groups: Western Hunter-Gatherers, Neolithic farmers, and Bronze Age Herders from the Steppe (Haak et al., 2015; Lazaridis et al., 2014) with minor contributions from other groups (Antonio et al., 2019; Fernandes et al., 2020; Lazaridis et al., 2016; Marcus et al., 2020; Mathieson et al., 2018). By the end of the Bronze Age, the ancestry composition resembles that of present-day individuals. This suggests that the genetic landscape of present-day western Eurasia was largely established following the two major transitions, ultimately leading to the pattern observed today, where the genetic structure of Europe mirrors its geography (Novembre et al., 2008).
However, recent studies of historical period genomes from individual regions paint a picture of heterogeneity and mobility, rather than of stable population structure. In the city of Rome alone, the population was dynamic and harbored a large diversity of ancestries from across Europe and the Mediterranean from the Iron Age (∼1000 BCE) through the Imperial Roman period (27 BCE-300 CE) (Antonio et al., 2019). Historical genomes from the Iberian Peninsula also highlight gene flow from across the Mediterranean (Olalde et al., 2019).
These localized reports fit well with archaeological and historical records. By the Iron Age, sea travel was already common, enabling peoples from across the Mediterranean to come into contact for trade (Abulafia, 2011; Broodbank, 2013).
Subsequently, the Roman Empire leveraged its organization, labor force, and military prowess to build upon existing waterways and roads throughout Europe and create a united Mediterranean for the only time in history (Beard, 2015; Harper, 2017; Symonds, 2017). Not only did the Empire provide a means for movement, it also provided a reason for individuals to move. Empire building activities, broadly categorized into military, labor, and trade, pulled in people and resources from inside and outside the Empire (Scheidel, 2019).
To reconcile the expectation of overall demographic stability in western Eurasia with localized reports of heterogeneous, mobile populations, we sequenced 204 new historical period genomes from across Europe and the Mediterranean. By analyzing genetic similarities between individuals across historical Eurasia, we were able to quantify individual movements during this time. Based on population genetic simulations, we hypothesize how population structure may be maintained in the face of frequent individual dispersal.
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Post by Admin on May 27, 2022 18:21:51 GMT
Results 204 new historical genomes from Europe and the Mediterranean We collected whole genomes from 204 individuals across 53 archaeological sites in 18 countries spanning Europe and the Mediterranean (Figure 1 - figure supplement 1), 26 of these individuals were recently reported (Moots et al., 2022). This collection includes the first historical genomes from present-day Armenia, Algeria, Austria, and France. Dates for 126 samples were directly determined through radiocarbon dating, and were used alongside archaeological contexts to infer dates for the remaining samples. DNA was extracted from either the powdered cochlear portion of the petrous bone (n = 203) or from teeth (n = 1). Libraries were partially treated with uracil-DNA glycosylase (UDG) and screened for ancient DNA damage patterns, high endogenous DNA content, and low contamination. We performed whole genome sequencing to a median depth of 0.92x (0.16x to 2.38x). For downstream integration with published data, pseudohaploid genotypes were called for the 1240k SNP panel (Mathieson et al., 2015), resulting in a median of 685,058 SNPs (167,000 to 1,029,345) per sample. We analyzed newly reported genomes in conjunction with 1,715 present-day genomes and 3,232 ancient genomes, including 991 historical period genomes (Allen Ancient DNA Resource, 2021; Clemente et al., 2021; Kovacevic et al., 2014; Pagani et al., 2016; Saupe et al., 2021; Žegarac et al., 2021). Genomes were grouped by regions and time periods (Figure 1) and analyzed using principal component analysis (PCA) and qpWave and qpAdm modeling (Haak et al., 2015). Figure 1. Timeline of new and published genomes. (A) 204 newly reported genomes (black circles) are shown alongside published genomes (gray circles), ordered by time and region (colored the same way as in B). (B) Sampling locations of newly reported (black) and published (gray) genomes are indicated by diamonds, sized according to the number of genomes at each location.
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Post by Admin on May 28, 2022 18:33:29 GMT
Local historical population structure varies across regions To investigate historical population structure, we categorized the data into 11 geographical regions, split into three sub-periods of the historical period: Iron Age (1000-1 BCE), Imperial Rome & Late Antiquity (1-700 CE), and Medieval Ages & Early Modern (700-1950 CE). We then characterized inter-individual heterogeneity within these spatio-temporal groups by examining (1) variation of projections onto a PCA space of present-day genomes (Figure 2 - figure supplement 1), (2) genetic groups identified by qpWave and clustering across time within a region, and (3) admixture modeling of genetic groups. A majority of regions have highly heterogeneous populations in at least one historical time period (Figure 2 - figure supplement 2). The visual spread in PCA is corroborated by clustering of individuals based on pairwise qpWave modeling, which results in genetically distinct clusters of individuals. On average, we identified 10 genetic clusters within each region, with a minimum of two and a maximum of 27. With genetically similar samples grouped together, we have more power to perform admixture modeling on clusters of interest using qpAdm (Haak et al., 2015; Harney et al., 2021). Regional vignettes reveal various patterns of historical population structure. In Armenia, for example, the population is highly homogeneous at any given time (Figure 2). Across time periods, there are two distinct genetic clusters, corresponding to a temporal split around 772-403 BCE (Figure 2BC). The earlier cluster (C1) includes newly reported samples (n=5) from Beniamin and published ones (n=6) from five other sites. This cluster cannot be modeled by any single source of ancestry using existing data. The later cluster (C2), which contains newly reported samples (n=12) from Beniamin dating between 403 BCE-500 CE, is genetically similar to present-day Armenians (excluding two Kurdish individuals; Figure 2C). Despite the split, there is evidence of partial continuity between the earlier and later clusters: the later (C2) can be modeled using around 50% of the earlier cluster (C1) and an additional source of Steppe ancestry. Historical genomes from Northern Europe, particularly newly reported genomes from Lithuania and Poland, exhibit a similar level of homogeneity (Figure 2 - figure supplement 2). Figure 2. Armenia: two homogeneous genetic clusters distinguished by a temporal shift. (A) Sampling locations of ancient genomes (open circles) colored by their genetic cluster identified using qpWave modeling. (B) Date ranges for the genomes: each line represents the 95% confidence interval for the radiocarbon date or the upper and lower limit of the inferred date, and the point represents the midpoint of that range. (C) Projections of the genomes onto a PCA of present-day genomes (gray points labeled by their population). Present-day genomes from Armenia are shown with black open circles.
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