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Post by Admin on Oct 5, 2023 19:09:53 GMT
Population genomics of Mesolithic Scandinavia: Investigating early postglacial migration routes and high-latitude adaptation Abstract Scandinavia was one of the last geographic areas in Europe to become habitable for humans after the Last Glacial Maximum (LGM). However, the routes and genetic composition of these postglacial migrants remain unclear. We sequenced the genomes, up to 57× coverage, of seven hunter-gatherers excavated across Scandinavia and dated from 9,500–6,000 years before present (BP). Surprisingly, among the Scandinavian Mesolithic individuals, the genetic data display an east–west genetic gradient that opposes the pattern seen in other parts of Mesolithic Europe. Our results suggest two different early postglacial migrations into Scandinavia: initially from the south, and later, from the northeast. The latter followed the ice-free Norwegian north Atlantic coast, along which novel and advanced pressure-blade stone-tool techniques may have spread. These two groups met and mixed in Scandinavia, creating a genetically diverse population, which shows patterns of genetic adaptation to high latitude environments. These potential adaptations include high frequencies of low pigmentation variants and a gene region associated with physical performance, which shows strong continuity into modern-day northern Europeans. Author summary The Scandinavian peninsula was the last part of Europe to be colonized after the Last Glacial Maximum. The migration routes, cultural networks, and the genetic makeup of the first Scandinavians remain elusive and several hypotheses exist based on archaeology, climate modeling, and genetics. By analyzing the genomes of early Scandinavian hunter-gatherers, we show that their migrations followed two routes: one from the south and another from the northeast along the ice-free Norwegian Atlantic coast. These groups met and mixed in Scandinavia, creating a population more diverse than contemporaneous central and western European hunter-gatherers. As northern Europe is associated with cold and low light conditions, we investigated genomic patterns of adaptation to these conditions and genes known to be involved in skin pigmentation. We demonstrate that Mesolithic Scandinavians had higher levels of light pigmentation variants compared to the respective source populations of the migrations, suggesting adaptation to low light levels and a surprising signal of genetic continuity in TMEM131, a gene that may be involved in long-term adaptation to the cold. journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2003703Genomics of Mesolithic Scandinavia reveal migration routes and high-latitude adaptation Supplementary Information www.biorxiv.org/content/biorxiv/suppl/2017/07/17/164400.DC1/164400-2.pdf |
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Post by Admin on Oct 6, 2023 3:09:09 GMT
Introduction As the ice sheet retracted from northern Europe after the Last Glacial Maximum (LGM), around 23,000 years ago, new habitable areas emerged [1], allowing plants [2,3] and animals [4,5] to recolonize the Scandinavian peninsula (hereafter referred to as Scandinavia). There is consistent evidence of human presence in the archaeological record from approximately 11,700 years before present (BP) both in southern and northern Scandinavia [6–9]. At this time, the ice sheet was still dominating the interior of Scandinavia [9,10] (Fig 1A, S1 Text), but recent climate modeling shows that the Arctic coast of (modern-day) northern Norway was ice free [10]. Similarities in late-glacial lithic technology (direct blade percussion technique) of Western Europe and the oldest counterparts of Scandinavia appearing around 11,000 calibrated (cal) BP [11] (S1 Text) have been used to argue for an early postglacial migration from southwestern Europe into Scandinavia, including areas of northern Norway. However, studies of another lithic technology, the “pressure blade” technique, which first occurred in the northern parts of Scandinavia around 10,200 cal BP, indicates contact with groups in the east and possibly an eastern origin of the early settlers [7,12–15] (S1 Text). The first genetic studies of Mesolithic human remains from central and eastern Scandinavian hunter-gatherers (SHGs) revealed similarities to two different Mesolithic European populations, the “western hunter-gatherers” (WHGs) from western, central, and southern Europe and the “eastern hunter-gatherers” (EHGs) from northeastern and eastern Europe [16–24]. Archaeology, climate modeling, and genetics suggest several possibilities for the early postglacial migrations into Scandinavia, including migrations from the south, southeast, northeast, and combinations of these; however, the early postglacial peopling of Scandinavia remains elusive [1,4,6–19,25,26]. In this study, we contrast genome sequence data and stable isotopes from Mesolithic human remains from western, northern, and eastern Scandinavia to infer the early postglacial migration routes into Scandinavia—from where people came, what routes they followed, how they were related to other Mesolithic Europeans [17–21,27]—and to investigate human adaptation to high-latitude environments.  Fig 1. Mesolithic samples and their genetic affinities. (A) Map of the Mesolithic European samples used in this study. The pie charts show the model-based [18,19] estimates of genetic ancestry for each SHG individual. The map also displays the ice sheet covering Scandinavia 10,000 cal BP (most credible [solid line] and maximum extend [dashed line] following [10]). Newly sequenced individuals are shown with bold and italic site names. SF11 is excluded from this map due to its low coverage (0.1×). Additional European EHG and WHG individuals used in this study derive from sites outside this map. The map was plotted using the R package rworldmap [28]. (B) Magnified section of genetic similarity among ancient and modern day individuals using PCA, featuring only the Mesolithic European samples (see S6 Text for the full plot). Symbols representing newly sequenced individuals have a black contour line. (C) Allele sharing between the SHGs, Latvian Mesolithic hunter-gatherers (Zv) [29], and EHGs versus WHGs measured by the statistic f4(Chimp, SHG; EHG, WHG) calculated for the captured SNPs [20]. Error bars show two block-jackknife standard errors. Data shown in this figure can be found in S1 Data. BP, before present; cal, calibrated; Chimp, Chimpanzee; EHG, eastern hunter-gatherer; PCA, principal component analysis; SHG, Scandinavian hunter-gatherer; WHG, western hunter-gatherer; Zv, Latvian Mesolithic hunter-gatherer from Zvejnieki. doi.org/10.1371/journal.pbio.2003703.g001 |
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Post by Admin on Oct 6, 2023 21:47:39 GMT
Results and discussion We sequenced the genomes of seven hunter-gatherers from Scandinavia (Table 1; S1, S2 and S3 Text) ranging from 57.8× to 0.1× genome coverage, of which four individuals had a genome coverage above 1×. The remains were directly dated to between 9,500 cal BP and 6,000 cal BP, and were excavated in southwestern Norway (Hum1, Hum2), northern Norway (Steigen), and the Baltic islands of Stora Karlsö and Gotland (SF9, SF11, SF12, and SBj), and represent 18% (6 of 33) of all known human remains in Scandinavia older than 8,000 years [30]. All samples displayed fragmentation and cytosine deamination at fragment termini characteristic for ancient DNA (aDNA) (S3 Text). Mitochondrial (mt) DNA-based contamination estimates were <6% for all individuals (confidence intervals ranging from 0% to 9.5%) and autosomal contamination was <1% for all individuals except for SF11, which showed approximately 10% contamination (Table 1, S4 Text). Four of the seven individuals were inferred to be males and three were females. All the western and northern Scandinavian individuals and one eastern Scandinavian carried U5a1 mt haplotypes, whereas the remaining eastern Scandinavians carried U4a haplotypes (Table 1, S5 Text). These individuals represent the oldest U5a1 and U4 lineages detected so far. The Y chromosomal haplotype was determined for three of the four males, all carried I2 haplotypes, which were common in pre-Neolithic Europe (Table 1, S5 Text).  Table 1. Information on the seven SHGs investigated in this study, including cal BP (corrected for the marine reservoir effect, given as a range of two standard deviations), average genome coverage, average mt coverage, mt and Y chromosome haplogroups, and contamination estimates based on the mt, the X-chromosome for males and the autosomes. doi.org/10.1371/journal.pbio.2003703.t001The high coverage and Uracil-DNA-glycosylase (UDG)-treated genome (used in order to reduce the effects of postmortem DNA damage) [31] of SF12 allowed us to confidently discover new and hitherto unknown variants at sites with 55× or higher sequencing depth (S3 Text). Based on SF12’s high-coverage and high-quality genome, we estimate the number of SNPs hitherto unknown (not recorded in dbSNP [v142]) to be approximately 10,600. This number is close to the median per European individual in the 1000 Genomes Project [32] (approximately 11,400, S3 Text), although a direct comparison is difficult due to the lower sequencing depth, different data processing, and larger sample sizes in the 1000 Genomes Project. At least 17% of these SNPs that are not found in modern-day individuals were in fact common among the Mesolithic Scandinavians (seen in the low coverage data conditional on the observation in SF12), and in total 24.2% were found in other prehistoric individuals (S3 Text), suggesting a substantial amount of hitherto unknown variation 9,000 years ago (S3 Text). Thus, many genetic variants found in Mesolithic individuals have not been carried over to modern-day groups. Among the novel variants in SF12, four (all heterozygous) are predicted to affect the function of protein coding genes [33] (S3 Text). The “heat shock protein” HSPA2 in SF12 carries an unknown mutation that changes the amino acid histidine to tyrosine at a protein–protein interaction site, which likely disrupts the function of the protein (S3 Text). Defects in HSPA2 are known to drastically reduce fertility in males [34]. It will be interesting to see how common such variants were among Mesolithic groups as more genome sequence data become available. The genomic data further allowed us to study the physical appearance of SHGs (S8 Text); for instance, they show a combination of eye color varying from blue to light brown and light skin pigmentation. This is strikingly different from the WHGs—who have been suggested to have the specific combination of blue eyes and dark skin [18,20,21,23] and EHGs—who have been suggested to be brown-eyed and light-skinned [19,20]. |
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Post by Admin on Oct 8, 2023 19:03:19 GMT
Demographic history of Mesolithic Scandinavians In order to compare the genomic sequence data of the seven SHGs to genetic information from other ancient individuals and modern-day groups, data were merged with shotgun sequence data and SNP capture data from six published Mesolithic individuals from Motala in central Scandinavia, and 47 published Stone Age (Upper Paleolithic, Mesolithic, and Early Neolithic) individuals from other parts of Eurasia (S6 Text) [17–22,26,27,29,35–38], as well as with a world-wide set of 203 modern-day populations [18,32,39]. All 13 SHGs—regardless of geographic sampling location and age—display genetic affinities to both WHGs and EHGs (Fig 1A and 1B, S6 Text). One individual, SF11, seems to be a slight genetic outlier in the principal component analysis (PCA), which could be due to the lower coverage or driven by nuclear contamination (Table 1, S6 Text). Generally, the pattern of dual ancestry is consistent with a scenario in which SHGs represent a mixed group tracing parts of their ancestry to both the WHGs and the EHGs [17–19,22,24,40]. The SHGs from northern and western Scandinavia show a distinct and significantly stronger affinity to the EHGs compared to the central and eastern SHGs (Fig 1). Conversely, the SHGs from eastern and central Scandinavia were genetically more similar to WHGs compared to the northern and western SHGs (Fig 1). Using qpAdm [19], the EHG genetic component of northern and western SHGs was estimated to 48.9% (± 5%) and differs from the 37.8% (± 3.2%) observed in eastern and south-central SHGs. The latter estimate is similar to ancestry estimates obtained for eastern Baltic hunter-gatherers from Latvia [29] (33.7% ± 4.7%, Fig 1A). Although the difference in ancestry estimates between northern and western SHG, and eastern and south-central SHG is only marginally significant (Z = 1.87, p = 0.062), this pattern is in agreement with other analyses such as ADMIXTURE and TreeMix (S6 Text). Furthermore, the direct comparison using D statistics with Chimpanzee (Chimp) as an outgroup (D(Chimp, WHG; eastern or south-central SHG, northern or western SHG) < 0, Z = −5.14 and D(Chimp, EHG; eastern or south-central SHG, northern or western SHG) > 0, Z = 1.72) show that WHG are genetically closer to eastern and south-central SHG, whereas EHG tend to share more alleles with northern and western SHGs (S2 Fig). These patterns of genetic affinity within SHGs are in direct contrast to the expectation based on geographic proximity with EHGs and WHGs. From about 11,700 cal BP, consistent archaeological evidence of human presence exists in southern Scandinavia following the retreat of the ice sheet [6,41,42] (S1 Text). Artifacts and tools found at these sites show similarities with the Ahrensburgian tradition of northern central Europe [15,43], suggesting that these hunter-gatherers likely had a southern origin from a WHG-like gene pool as no EHG ancestry has been found in central and western Europe [18,21,24,27]. Although this genetic component would have entered from today’s northern Germany and Denmark (Fig 2, Scenario a), it remains unclear how and where the EHG component entered Scandinavia (Fig 2, Scenarios b, c and/or d). The EHG-related migration likely took place after the migration of WHGs from the south as the earliest eastern-associated pressure blade finds postdate the southwestern-associated direct blade finds in Scandinavia (S1 Text). Two migrations with admixture at different time-periods would generate a genetic gradient with the highest contribution of a source close to its geographic region of entry. The observed genetic pattern is consistent with a migration of the EHGs from the northeast moving southwards along the ice-free Norwegian Atlantic coast where the two groups started mixing (Fig 2, Scenarios a and b), which would cause more EHG ancestry in western SHGs. If the EHG migration had crossed the Baltic Sea into Scandinavia, where it would meet and mix with a WHG-like population (Fig 2, combination of Scenarios a and c), a gradient with most EHG ancestry in eastern SHGs would have been created—exactly opposite to the observed pattern. A similar pattern would be expected if the EHG migration went around the Baltic Sea along current day’s Finnish west coast and down via today’s Swedish east coast (scenario not depicted in Fig 2). An EHG migration along the southern Baltic coast (Fig 2, Scenarios a and d) should cause a related pattern to a crossing of the Baltic Sea with more EHG ancestry in central and eastern SHGs. Furthermore, such a scenario would likely also make the Latvian Mesolithic hunter-gatherers the group with most EHG ancestry, which is in stark contrast to the empirical data in which the Latvian group shows the lowest proportion of EHG ancestry (33.7% ± 4.7%), and also not consistent with chronology, as the dated settlements east of the Baltic Sea are younger than the early settlements in Scandinavia (S1 Text). Thus, the only scenario consistent with both genetic and archaeological data is a migration of a WHG-related group migrating into Scandinavia from the south, followed by an EHG-related group migrating to Scandinavia from the northeast along the Norwegian Atlantic coast. Notably, such a migration along the Norwegian coast could have been facilitated by the use of the more specialized pressure blade technique (S1 Text) [12,14]. The individuals sequenced here postdate these migrations, but a genetic east-west gradient would be maintained over time in Scandinavia and only additional large-scale migrations from different sources would alter this pattern. This observation is important as the geographic pattern still holds without the chronologically much younger Steigen individual, which might represent local continuity or later migrations into north-western Scandinavia from the east.  Fig 2. Migration scenarios into postglacial Scandinavia. Maps showing potential migration routes into Scandinavia. Scenario (a) shows a migration related to the Ahrensburgian tradition from the south (S1 Text). Scenarios (b), (c), and (d) show different possible routes into Scandinavia for the EHG ancestry. The scenarios are discussed in the text and the scenario most consistent with genetic data and stone tools is a combination of routes (a) and (b). All maps were plotted using the R package rworldmap [28]. EHG, eastern hunter-gatherer. doi.org/10.1371/journal.pbio.2003703.g002Interestingly, stable nitrogen and carbon isotope analysis of northern and western SHGs revealed an extreme marine diet, suggesting a pronounced maritime subsistence, in contrast to the more mixed terrestrial and aquatic diet of eastern and central SHGs (S1 Text). Mobility is difficult to trace based solely on carbon and nitrogen isotope data; however, the patterns are consistent with a migration along the Norwegian Atlantic coast relying on local resources. |
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Post by Admin on Oct 9, 2023 21:13:41 GMT
Genetic diversity in Mesolithic Scandinavia By sequencing complete ancient genomes, we can compute unbiased estimates of genetic diversity, which are informative of past population sizes and population history. Here, we restrict the analysis to WHGs and SHGs because only SNP capture data are available for EHGs (S7 Text). In modern-day Europe, there is greater genetic diversity in the south compared to the north. During the Mesolithic period, by contrast, we find lower levels of runs of homozygosity (RoH) (Fig 3A) and linkage disequilibrium (LD) (Fig 3B) in SHGs compared to WHGs (represented by Loschbour and Bichon [18,35]). By using a multiple sequentially Markovian coalescent (MSMC) approach [44] for the high-coverage, high-quality genome of SF12, we find that right before the SF12 individual lived, the effective population size of SHGs was similar to that of WHGs (Fig 3C). At the time of the LGM and back to approximately 50,000 years ago, both the WHGs and SHGs go through a bottleneck, but the ancestors of SHGs retained a greater effective population size in contrast to the ancestors of WHGs who went through a more severe bottleneck (Fig 2C), which is consistent across 100 bootstrap replicates (S2 Fig). These differences in effective population size estimates may be attributed to the admixture in SHGs as migration events can have delayed effects on estimates of effective population size over time [45]. Around 50,000–70,000 years ago, the effective population sizes of the ancestors of SHGs, WHGs, Neolithic groups (represented by Stuttgart [18]), and Paleolithic Eurasians (represented by Ust-Ishim [38]) align, suggesting that these diverse groups all trace their ancestry back to a common ancestral group, which likely represents the early migrants out of Africa.  Fig 3. Genetic diversity in prehistoric Europe. (A) RoH for the six prehistoric humans that have been sequenced to >15× genome coverage, (Kotias is a hunter-gatherer from the Caucasus region [35], NE1 is an early Neolithic individual from modern-day Hungary [27], the other individuals are described in the text), compared to all modern-day non African individuals from the 1000 Genomes Project [32]. (B) LD decay for five prehistoric populations each represented by two individuals (eastern SHGs: SF [SF9 and SF12], western SHGs: Hum [Hum1 and Hum2], CHGs [35]: [Kotias and Satsurblia], WHGs [18,35] [Loschbour and Bichon], and early Neolithic Hungarians [27]: EN_Hungary [NE1 and NE6]). LD was scaled in each distance bin by using the LD for two modern populations [32] as 0 (TSI) and as 1 (PEL). LD was calculated from the covariance of derived allele frequencies of two haploid individuals per population (S7 Text). Error bars show two standard errors estimated during 100 bootstraps across SNP pairs. (C) Effective population size over time as inferred by PSMC’ [44] for four prehistoric humans with high genome coverage. The dashed lines show the effective population sizes for selected modern-day populations. All curves for prehistoric individuals were shifted along the x-axis according to their radiocarbon date. S4 Fig. shows 100 bootstrap replicates per individual. Data shown in this figure can be found in S1 Data. BP, before present; CHG, Caucasus hunter-gatherer; LD, linkage disequilibrium; PEL, modern-day Peruvian individual; PSMC’, pairwise sequentially Markovian coalescent; RoH, runs of homozygosity; SHG, Scandinavian hunter-gatherer; TSI, modern-day Tuscan individual; WHG, western hunter-gatherer. doi.org/10.1371/journal.pbio.2003703.g003Adaptation to high-latitude environments With the aim of detecting signs of adaptation to high-latitude environments and selection during and after the Mesolithic period, we employed two different approaches that utilize the Mesolithic genomic data. In the first approach, we assumed that SHGs adapted to high-latitude environments of low temperatures and seasonally low levels of light, and searched for gene variants that carried over to modern-day people in northern Europe. Modern-day northern Europeans trace limited amounts of genetic material back to the SHGs (due to the many additional migrations during later periods), and any genomic region that displays extraordinary genetic continuity would be a strong candidate for adaptation in people living in northern Europe across time. We designed a statistic, Dsel (S9 Text), that captures this specific signal and scanned the whole genome for gene variants that show strong continuity (little differentiation) between SHGs and modern-day northern Europeans while exhibiting large differentiation to modern-day southern European populations [46] (Fig 4A; S9 Text). Six of the top 10 SNPs with greatest Dsel values were located in the TMEM131 gene that has been found to be associated with physical performance [47], which could make it part of the physiological adaptation to cold [48]. This genomic region was more than 200 kbp (kilo base pairs) long and showed the strongest haplotypic differentiation between modern-day Tuscan individuals (TSIs) and modern-day Finnish individuals (FINs) across the genome (S9 Text). The particular haplotype was relatively common in SHGs, it is even more common among today’s Finnish population (S9 Text) and showed a strong signal of local adaptation (S9 Text). Other top hits included genes associated with a wide range of metabolic, cardiovascular, and developmental and psychological traits (S9 Text) potentially linked to physiological adaptation to cold environments [48]. |
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