The Yamnaya Steppe Herders from Russia

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The Yamnaya Steppe Herders from Russia Apr 27, 2018 18:38:06 GMT

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Genome-wide analysis of ancient DNA has emerged as a transformative technology for studying prehistory, providing information that is comparable in power to archaeology and linguistics. Realizing its promise, however, requires collecting genome-wide data from an adequate number of individuals to characterize population changes over time, which means not only sampling a succession of archaeological cultures2, but also multiple individuals per culture. To make analysis of large numbers of ancient DNA samples practical, we used in-solution hybridization capture10,11 to enrich next generation sequencing libraries for a target set of 394,577 single nucleotide polymorphisms (SNPs) (‘390k capture’), 354,212 of which are autosomal SNPs that have also been genotyped using the Affymetrix Human Origins array in 2,345 humans from 203 populations4,12. This reduces the amount of sequencing required to obtain genome-wide data by a minimum of 45-fold and a median of 262-fold (Supplementary Data 1). This strategy allows us to report genomic scale data on more than twice the number of ancient Eurasians as has been presented in the entire preceding literature1–8 (Extended Data Table 1).

Figure 1
Location and SNP coverage of samples included in this study
(a) Geographic location and time-scale (central European chronology) of the 69 newly typed ancient individuals from this study (black outline) and 25 from the literature for which shotgun sequencing data was available (no outline). (b) Number of SNPs covered at least once in the analysis dataset of 94 individuals.

We used this technology to study population transformations in Europe. We began by preparing 212 DNA libraries from 119 ancient samples in dedicated clean rooms, and testing these by light shotgun sequencing and mitochondrial genome capture (Supplementary Information section 1, Supplementary Data 1). We restricted the analysis to libraries with molecular signatures of authentic ancient DNA (elevated damage in the terminal nucleotide), negligible evidence of contamination based on mismatches to the mitochondrial consensus13 and, where available, a mitochondrial DNA haplogroup that matched previous results using PCR4,14,15 (Supplementary Information section 2). For 123 libraries prepared in the presence of uracil-DNA-glycosylase16 to reduce errors due to ancient DNA damage17, we performed 390k capture, carried out paired-end sequencing and mapped the data to the human genome. We restricted analysis to 94 libraries from 69 samples that had at least 0.06-fold average target coverage (average of 3.8-fold) and used majority rule to call an allele at each SNP covered at least once (Supplementary Data 1). After combining our data (Supplementary Information section 3) with 25 ancient samples from the literature — three Upper Paleolithic samples from Russia1,6,7, seven people of European hunter gatherer ancestry2,4,5,8, and fifteen European farmers2,3,4,8—we had data from 94 ancient Europeans. Geographically, these came from Germany (n=41), Spain (n=10), Russia (n=14), Sweden (n=12), Hungary (n=15), Italy (n=1) and Luxembourg (n=1) (Extended Data Table 2). Following the central European chronology, these included 19 hunter gatherers (∼43,000–2,600 BC), 28 Early Neolithic farmers (∼6,000–4,000 BC), 11 Middle Neolithic farmers (∼4,000–3,000 BC) including the Tyrolean Iceman3, 9 Late Copper/Early Bronze Age individuals (Yamnaya:∼3,300–2,700 BC), 15 Late Neolithic individuals (∼2,500– 2,200 BC), 9 Early Bronze Age individuals (∼2,200–1,500 BC), two Late Bronze Age individuals (∼1,200–1,100 BC) and one Iron Age individual (∼900 BC). Two individuals were excluded from analyses as they were related to others from the same population. The average number of SNPs covered at least once was 212,375 and the minimum was 22,869 (Fig. 1).

We determined that 34 of the 69 newly analysed individuals were male and used 2,258 Y chromosome SNPs targets included in the capture to obtain high resolution Y chromosome haplogroup calls (Supplementary Information section 4). Outside Russia, and before the Late Neolithic period, only a single R1b individual was found (early Neolithic Spain) in the combined literature (n=70). By contrast, haplogroups R1a and R1b were found in 60% of Late Neolithic/Bronze Age Europeans outside Russia (n=10), and in 100% of the samples from European Russia from all periods (7,500–2,700 BC; n=9). R1a and R1b are the most common haplogroups in many European populations today18,19, and our results suggest that they spread into Europe from the East after 3,000 BC. Two hunter-gatherers from Russia included in our study belonged to R1a (Karelia) and R1b (Samara), the earliest documented ancient samples of either haplogroup discovered to date. These two hunter gatherers did not belong to the derived lineages M417 within R1a and M269 within R1b that are predominant in Europeans today18,19, but all 7 Yamnaya males did belong to the M269 subclade18 of haplogroup R1b. Principal components analysis (PCA) of all ancient individuals along with 777 present-day West Eurasians4 (Fig. 2a, Supplementary Information section 5) replicates the positioning of present-day Europeans between the Near East and European hunter-gatherers4,20, and the clustering of early farmers from across Europe with present day Sardinians3,4, suggesting that farming expansions across the Mediterranean to Spain and via the Danubian route to Hungary and Germany descended from a common stock. By adding samples from later periods and additional locations, we also observe several new patterns.

Figure 2
Population transformations in Europe
(a) PCA analysis, (b) ADMIXTURE analysis. The full ADMIXTURE analysis including present-day humans is shown in Supplementary Information section 6.

All samples from Russia have affinity to the ∼24,000-year-old MA1(ref. 6), the type specimen for the Ancient North Eurasians (ANE) who contributed to both Europeans4 and Native Americans4,6,8. The two hunter-gatherers from Russia (Karelia in the northwest of the country and Samara on the steppe near the Urals) form an ‘eastern European hunter-gatherer’ (EHG) cluster at one end of a hunter-gatherer cline across Europe; people of hunter-gatherer ancestry from Luxembourg, Spain, and Hungary sit at the opposite ‘western European hunter-gatherer’4 (WHG) end, while the hunter-gatherers from Sweden4,8 (SHG) are intermediate. Against this background of differentiated European hunter-gatherers and homogeneous early farmers, multiple population turnovers transpired in all parts of Europe included in our study. Middle Neolithic Europeans from Germany, Spain, Hungary, and Sweden from the period, ∼4,000–3,000 BC are intermediate between the earlier farmers and the WHG, suggesting an increase of WHG ancestry throughout much of Europe. By contrast, in Russia, the later Yamnaya steppe herders of ∼3,000 BC plot between the EHG and the present-day Near East/Caucasus, suggesting a decrease of EHG ancestry during the same time period. The Late Neolithic and Bronze Age samples from Germany and Hungary2 are distinct from the preceding Middle Neolithic and plot between them and the Yamnaya. This pattern is also seen in ADMIXTURE analysis (Fig. 2b, Supplementary Information section 6), which implies that the Yamnaya have ancestry from populations related to the Caucasus and South Asia that is largely absent in 38 Early or Middle Neolithic farmers but present in all 25 Late Neolithic or Bronze Age individuals. This ancestry appears in Central Europe for the first time in our series with the Corded Ware around 2,500 BC (Supplementary Information section 6, Fig. 2b).

The Corded Ware shared elements of material culture with steppe groups such as the Yamnaya although whether this reflects movements of people has been contentious21. Our genetic data provide direct evidence of migration and suggest that it was relatively sudden. The Corded Ware are genetically closest to the Yamnaya ∼2,600km away, as inferred both from PCA and ADMIXTURE (Fig. 2) and FST (0.011±0.002) (Extended Data Table 3). If continuous gene flow from the east, rather than migration, had occurred, we would expect successive cultures in Europe to become increasingly differentiated from the Middle Neolithic, but instead, the Corded Ware are both the earliest and most strongly differentiated from the Middle Neolithic population. ‘Outgroup’ f3 statistics6 (Supplementary Information section 7),which measure shared genetic drift between a pair of populations (Extended Data Fig. 1), support the clustering of hunter-gatherers, Early/Middle Neolithic, and Late Neolithic/Bronze Age populations into different groups as in the PCA (Fig. 2a).We also analysed f4 statistics, which allow us to test whether pairs of populations are consistent with descent from common ancestral populations, and to assess significance using a normally distributed Z score. Early European farmers from the Early and Middle Neolithic were closely related but not identical. This is reflected in the fact that Loschbour, a WHG individual fromLuxembourg4, shared more alleles with post-4,000 BC European farmers from Germany, Spain, Hungary, Sweden and Italy than with early farmers of Germany, Spain, and Hungary, documenting an increase of hunter-gatherer ancestry in multiple regions of Europe during the course of the Neolithic. The two EHG form a clade with respect to all other present-day and ancient populations (|Z|<1.9), and MA1 shares more alleles with them (|Z|>4.7) than with other ancient or modern populations, suggesting that they may be a source for the ANE ancestry in present Europeans4,12,22 as they are geographically and temporally more proximate than Upper Paleolithic Siberians.

The Yamnaya differ from the EHG by sharing fewer alleles with MA1 (|Z|=6.7) suggesting a dilution of ANE ancestry between 5,000–3,000 BC on the European steppe. This was likely due to admixture of EHG with a population related to present-day Near Easterners, as the most negative f3 statistic in the Yamnaya (giving unambiguous evidence of admixture) is observed when we model them as a mixture of EHG and present-day Near Eastern populations like Armenians (Z=-6.3); Supplementary Information section 7). The Late Neolithic/Bronze Age groups of central Europe share more alleles with Yamnaya than the Middle Neolithic populations do (|Z|=12.4) and more alleles with the Middle Neolithic than the Yamnaya do (|Z|=12.5), and have a negative f3 statistic with the Middle Neolithic and Yamnaya as references (Z=-20.7), indicating that they were descended from a mixture of the local European populations and new migrants from the east. Moreover, the Yamnaya share more alleles with the CordedWare (|Z|≥3.6) than with any other Late Neolithic/Early Bronze Age group with at least two individuals (Supplementary Information section 7), indicating that they had more eastern ancestry, consistent with the PCA and ADMIXTURE patterns (Fig. 2). Modelling of the ancient samples shows that while Karelia is genetically intermediate between Loschbour and MA1, the topology that considers Karelia as a mixture of these two elements is not the only one that can fit the data (Supplementary Information section 8). To avoid biasing our inferences by fitting an incorrect model, we developed new statistical methods that are substantial extensions of a previously reported approach4, which allow us to obtain precise estimates of the proportion of mixture in later Europeans without requiring a formal model for the relationship among the ancestral populations. The method (Supplementary Information section 9) is based on the idea that if a Test population has ancestry related to reference populations Ref1, Ref2 , …, RefN in proportions α1,α2,…,αN, and the references are themselves differentially related to a triple of outgroup populations A, B, C, then:

Last Edit: Apr 28, 2018 18:31:17 GMT by Admin

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The Yamnaya Steppe Herders from Russia Apr 28, 2018 18:29:03 GMT

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Figure 3
Admixture proportions
We estimate mixture proportions using a method that gives unbiased estimates even without an accurate model for the relationships between the test populations and the outgroup populations (Supplementary Information section 9). Population samples are grouped according to chronology (ancient) and Yamnaya ancestry (present-day humans).

By using a large number of outgroup populations we can fit the admixture coefficients αi and estimate mixture proportions (Supplementary Information section 9, Extended Data Fig. 2). Using 15 outgroups from Africa, Asia, Oceania and the Americas, we obtain good fits as assessed by a formal test (Supplementary Information section 10), and estimate that the Middle Neolithic populations of Germany and Spain have ∼18–34% more WHG-related ancestry than Early Neolithic populations and that the Late Neolithic and Early Bronze Age populations of Germany have ∼22–39% more EHG-related ancestry than the Middle Neolithic ones (Supplementary Information section 9). If we model them as mixtures of Yamnaya-related and Middle Neolithic populations, the inferred degree of population turnover is doubled to 48–80% (Supplementary Information sections 9 and 10). To distinguish whether a Yamnaya or an EHG source fits the data better, we added ancient samples as outgroups (Supplementary Information section 9). Adding any Early or Middle Neolithic farmer results in EHG-related genetic input into Late Neolithic populations being a poor fit to the data (Supplementary Information section 9); thus, Late Neolithic populations have ancestry that cannot be explained by a mixture of EHG and Middle Neolithic. When using Yamnaya instead of EHG, however, we obtain a good fit (Supplementary Information sections 9 and 10). These results can be explained if the new genetic material that arrived in Germany was a composite of two elements: EHG and a type of Near Eastern ancestry different from that which was introduced by early farmers (also suggested by PCA and ADMIXTURE; Fig. 2, Supplementary Information sections 5 and 6). We estimate that these two elements each contributed about half the ancestry of the Yamnaya (Supplementary Information sections 6 and 9), explaining why the population turnover inferred using Yamnaya as a source is about twice as high compared to the undiluted EHG.

The estimate of Yamnaya related ancestry in the Corded Ware is consistent when using either present populations or ancient Europeans as outgroups (Supplementary Information sections 9 and 10), and is 73.1±2.2% when both sets are combined (Supplementary Information section 10). The best proxies for ANE ancestry in Europe4 were initially Native Americans12,22, and then the Siberian MA1 (ref. 6), but both are geographically and temporally too remote for what appears to be a recent migration into Europe4. We can now add three new pieces to the puzzle of how ANE ancestry was transmitted to Europe: first by the EHG, then the Yamnaya formed by mixture between EHG and a Near Eastern related population, and then the Corded Ware who were formed by a mixture of the Yamnaya with Middle Neolithic Europeans. We caution that the sampled Yamnaya individuals from Samara might not be directly ancestral to Corded Ware individuals from Germany. It is possible that a more western Yamnaya population, or an earlier (pre-Yamnaya) steppe population may have migrated into central Europe, and future work may uncover more missing links in the chain of transmission of steppe ancestry. By extending our model to a three-way mixture of WHG, Early Neolithic and Yamnaya, we estimate that the ancestry of the Corded Ware was 79% Yamnaya-like, 4% WHG, and 17% Early Neolithic (Fig. 3). A small contribution of the first farmers is also consistent with uniparentally inherited DNA: for example, mitochondrial DNA haplogroup N1a and Y chromosome haplogroup G2a, common in early central European farmers14,23, almost disappear during the Late Neolithic and Bronze Age, when they are largely replaced by Y haplogroups R1a and R1b (Supplementary Information section 4)and mtDNA haplogroups I,T1,U2,U4, U5a,W, and subtypes of H14,23,24 (Supplementary Information section 2). The uniparental data not only confirm a link to the steppe populations but also suggest that both sexes participated in the migrations (Supplementary Information sections 2 and 4 and Extended Data Table 2). The magnitude of the population turnover that occurred becomes even more evident if one considers the fact that the steppe migrants may well have mixed with eastern European agriculturalists on their way to central Europe. Thus, we cannot exclude a scenario in which the Corded Ware arriving in today's Germany had no ancestry at all from local populations.

Our results support a view of European pre-history punctuated by two major migrations: first, the arrival of the first farmers during the Early Neolithic from the Near East, and second, the arrival of Yamnaya pastoralists during the Late Neolithic from the steppe. Our data further show that both migrations were followed by resurgences of the previous inhabitants: first, during the Middle Neolithic, when hunter-gatherer ancestry rose again after its Early Neolithic decline, and then between the Late Neolithic and the present, when farmer and hunter-gatherer ancestry rose after its Late Neolithic decline. This second resurgence must have started during the Late Neolithic/Bronze Age period itself, as the Bell Beaker and Unetice groups had reduced Yamnaya ancestry compared to the earlier Corded Ware, and comparable levels to that in some present-day Europeans (Fig. 3). Today, Yamnaya related ancestry is lower in southern Europe and higher in northern Europe, and all European populations can be modelled as a three-way mixture of WHG, Early Neolithic, and Yamnaya, whereas some outlier populations show evidence for additional admixture with populations from Siberia and the Near East (Extended Data Fig. 3, Supplementary Information section 9).

Extended Data Figure 4

Further data are needed to determine whether the steppe ancestry arrived in southern Europe at the time of the Late Neolithic/Bronze Age, or is due to migrations in later times from northern Europe25,26. Our results provide new data relevant to debates on the origin and expansion of Indo-European languages in Europe (Supplementary Information section 11). Although the findings from ancient DNA are silent on the question of the languages spoken by preliterate populations, they do carry evidence about processes of migration which are invoked by theories on Indo-European language dispersals. Such theories make predictions about movements of people to account for the spread of languages and material culture (Extended Data Fig. 4). The technology of ancient DNA makes it possible to reject or confirm the proposed migratory movements, as well as to identify new movements that were not previously known. The best argument for the ‘Anatolian hypothesis’27 that Indo-European languages arrived in Europe from Anatolia ∼8,500 years ago is that major language replacements are thought to require major migrations, and that after the Early Neolithic when farmers established themselves in Europe, the population base was likely to have been so large that later migrations would not have made much of an impact27,28. However, our study shows that a later major turnover did occur, and that steppe migrants replaced ∼75% of the ancestry of central Europeans. An alternative theory is the ‘steppe hypothesis’, which proposes that early Indo-European speakers were pastoralists of the grasslands north of the Black and Caspian Seas, and that their languages spread into Europe after the invention of wheeled vehicles9. Our results make a compelling case for the steppe as a source of at least some of the Indo-European languages in Europe by documenting a massive migration ∼4,500 years ago associated with the Yamnaya and Corded Ware cultures, which are identified by proponents of the steppe hypothesis as vectors for the spread of Indo-European languages into Europe. These results challenge the Anatolian hypothesis by showing that not all Indo-European languages in Europe can plausibly derive from the first farmer migrations thousands of years earlier (Supplementary Information section 11). We caution that the location of the proto-Indo-European9,27,29,30 homeland that also gave rise to the Indo-European languages of Asia, as well as the Indo-European languages of southeastern Europe, cannot be determined from the data reported here (Supplementary Information section 11). Studying the mixture in the Yamnaya themselves, and understanding the genetic relationships among a broader set of ancient and present-day Indo- European speakers, may lead to new insight about the shared homeland.

Nature. 2015 Jun 11; 522(7555): 207–211.

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The Yamnaya Steppe Herders from Russia Jun 17, 2018 18:22:10 GMT

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The oldest Gaelic literature describes the origins of the Irish people as a series of ancient invasions, and the archaeological record in Ireland, as elsewhere in Europe, exhibits several horizons where major cultural shifts are apparent (1). The two most transformative are the arrival of agriculture (∼3750 BC) followed by the onset of metallurgy (∼2300 BC). The Neolithic package characterized by animal husbandry, cereal crops, ceramics, and timber houses reached the shores of Ireland some 5,000 years after its beginnings in the Near East. The second great wave of change starts with the appearance of copper mines, associated with Bell Beaker pottery, which are quickly followed by Bronze tool-making, weaponry, and gold-working, with distinct Food Vessel pottery succeeding from the earlier beakers (2). This period coincides with the end of the large passage graves of Neolithic Ireland in favor of single burials and smaller wedge tombs.

Twentieth-century archaeology was dominated by two non-mutually-exclusive paradigms for how such large scale social change occurs (3). The first, demic diffusion, linked archaeological change with the displacement and disruption of local populations by inward migrations. However, from the 1960s onwards, this assertion was challenged by a paradigm of cultural diffusion whereby social change happened largely through indigenous processes.

High-throughput sequencing has opened the possibility for genome-wide comparisons of genetic variation in ancient populations, which may be informatively set in the context of extensive modern data (4⇓⇓⇓⇓⇓–10). In Europe, these clearly show population replacement by migrating farmers from southwest Asia at the onset of the Neolithic with some retrenchment of the earlier Mesolithic genome at later stages (5⇓⇓⇓–9, 11, 12). Three longitudinal genome studies have also shown later genome-wide shifts around the beginnings of the Bronze Age in central Europe with substantial introgression originating with the Yamnaya steppe herders (7, 9, 10). However, replacement coupled to archaeological horizons is unlikely to be a universal phenomenon, and whether the islands of Britain and Ireland, residing at the temporal and geographical edges of both the Neolithic and steppe migrations, were subject to successive substantial population influxes remains an open and debated question. For example, a recent survey of archaeological opinion on the origins of agriculture in Ireland showed an even split between adoption and colonization as explanatory processes (13). Recent archaeological literature is also divided on the origins of the insular Bronze Age, with most opinion favoring incursion of only small numbers of technical specialists (1, 2, 14, 15).

To address this controversy, we present here the first, to our knowledge, genome-wide data from four ancient Irish individuals, a Neolithic woman (3343–3020 cal BC) from Ballynahatty, Co. Down, found in the context of an early megalithic passage-like grave, and three Early Bronze Age men from a cist burial in Rathlin Island, Co. Antrim (2026–1534 cal BC) with associated Food Vessel pottery (16) (SI Appendix, Section S1).

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The Yamnaya Steppe Herders from Russia Jun 18, 2018 18:21:59 GMT

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Fig. 1.
Genetic affinities of ancient individuals. (A and B) Genotypes from 82 ancient samples are projected onto the first two principal components defined by a set of 354,212 SNPs from Eurasian populations in the Human Origins dataset (29) (SI Appendix, Section S9.1 and S10). (A) This PCA projects ancient Eurasian Hunter–Gatherers and Neolithic Farmers, where they separate clearly into Early Neolithic, MN (including the Irish Ballynahatty genome), and several hunter–gatherer groups. (B) PCA projection of Late Neolithic, Copper, and Bronze Age individuals where the three Rathlin genomes adopt a central position within a large clustering of European Bronze Age individuals. (C) A plot of ADMIXTURE ancestry components (K = 11) of these same ancient genomes. In West and Central Europe, ancient individuals are composed almost entirely of two dominant strands of ancestry, linked to hunter–gatherer (red) and early farmer (orange) populations, until the Late Neolithic. At this point, a third (green) Caucasus component features. Previously, this component was only seen in ancient Steppe and Siberian populations such as the Yamnaya. The three Rathlin genomes each display this Caucasus strand of ancestry whereas the Irish Neolithic does not.

Principal Component Analysis and ADMIXTURE.
A projection principal component analysis (PCA) was used to investigate the genetic affinities of our four ancient Irish genomes, alongside 78 published ancient samples (SI Appendix, Table S9.1; selection criteria detailed in SI Appendix, Section S4) (5⇓⇓⇓⇓–10, 21⇓⇓⇓⇓–26) using 677 modern individuals from Western Eurasia (8) as a reference population (Fig. 1 A and B and SI Appendix, Sections S9.1 and S10). In Fig. 1A, we see a clear division between hunter–gatherer and early farmer individuals, with the Ballynahatty female plotting with five other MN samples from Germany, Spain, and Scandinavia. However, a large shift in genetic variation is seen between Ballynahatty and the three Irish Early Bronze Age samples, Rathlin1, Rathlin2, and Rathlin3, who fall in a separate central region of the graph along with Unetice and other Early Bronze Age genomes from Central and North Europe. These plots imply that ancient Irish genetic affinities segregate within European archaeological horizons rather than clustering geographically within the island.

Model-based approaches allow the decomposition of individuals into coefficients contributed by a set number (K) of ancestral populations. We investigated this by using ADMIXTURE (Version 1.23) (27) with ancient individuals included in the analysis alongside 1,941 modern samples from diverse worldwide populations (8) (SI Appendix, Section S11). Fig. 1C shows the plot of estimated ancestry proportions for each ancient genome at a value of K = 11. These partition similarly to previous analyses (7, 9, 10), with three major ancestral coefficients manifesting in west and central Europe. The first (colored red) forms the near totality of ancestry in hunter–gatherer samples, and admixes with a second (orange) component found at high levels in Neolithic and also modern Near Eastern populations (SI Appendix, Section S11.1). Ballynahatty is similar to other MN samples with a majority orange “early farmer” component but with an elevated level of the red “hunter–gatherer” component compared with Early Neolithic genomes. The ancestry of Yamnaya, Early Bronze Age herders from the Pontic Steppe, is evenly divided between this same red component and the third major European coefficient, colored in green, which has been identified with a Caucasus origin (28). This Caucasus component is encountered subsequently, introduced via Yamnaya, in Late Neolithic and Bronze Age samples in central Europe (9, 10) and features in the three Irish Early Bronze Age samples within profiles similar to continental Bronze Age genomes.

Irish

Neolithic Origins.
D and f statistics (29, 30) (Dataset S1 and SI Appendix, Section S12) support identification of Ballynahatty with other MN samples who show a majority ancestry from Near Eastern migration but with some western Mesolithic introgression. Outgroup f3 statistics indicated that Ballynahatty shared most genetic drift with other Neolithic samples with maximum scores observed for Spanish Middle, Epicardial, and Cardial Neolithic populations, and the Scandinavian individual Gok2 (SI Appendix, Section S12.1). D statistics confirmed these affinities. Interestingly, both the Spanish MN individuals and Gok2 also belong to Megalithic passage tomb cultures. Along with other MNs, Ballynahatty displays increased levels of hunter–gatherer introgression compared with earlier farming populations. D statistics revealed that, out of the three Mesolithic hunter–gatherer groupings from Haak et al. (9), eastern hunter–gatherer (EHG), Scandinavian hunter–gatherer (SHG), and western hunter–gatherer (WHG), Ballynahatty shares the most alleles with WHG and furthermore has the strongest preference for WHG over EHG and SHG out of all contemporaneous Neolithic individuals so far sampled. However, Ballynahatty forms a clade with other MN genomes to the exclusion of WHG and, symmetrically, WHG genomes form a clade to the exclusion of Ballynahatty. Of the three WHG individuals, Ballynahatty appeared to share the least amount of affinity with LaBrana (Spain) and the largest amount of affinity with Loschbour (Luxembourg). To gauge the proportion of Ballynahatty’s ancestry derived from WHG, we used the f4 ratio, f4(Mbuti, Loschbour; Ballynahatty, Dai)/f4(Mbuti, Loschbour; KO1, Dai) (29), to estimate a hunter–gatherer component of 42 ± 2% within a predominantly early farmer genome. Thus, we deduce migration has a primary role in Irish agricultural origins.

Bronze Age Replacement.
Prior studies (7, 9, 10) convincingly demonstrate that Central European genomes from the late Neolithic and Early Bronze Age differ from the preceding MN due to a substantial introgression originating with Steppe herders linked to cultures such as the Yamnaya. Accordingly, we used a series of tests to gauge whether the ancestries of the Rathlin Early Bronze Age genomes were subject to this influence. D statistics confirmed that Ballynahatty and other MN individuals form clades with each other to the exclusion of these Irish Bronze Age samples. Specific disruption of continuity between the Irish Neolithic and Bronze Age is clear with significant evidence of both Yamnaya and EHG introgression into Irish Bronze Age samples when placed in a clade with any MN. However, like other European Bronze Age samples, this introgression is incomplete, as they also show significant MN ancestry when placed in a clade with Yamnaya. The highest levels of MN ancestry were observed when either Ballynahatty or Gok2 (Scandinavian) was the sample under study. However, when paired with central European Bronze Age populations, the Rathlin samples show no trace of significant introgression from Ballynahatty, suggesting that earlier Irish populations may not have been a source of their partial MN ancestry.

These analyses, taken with the PCA and ADMIXTURE results, indicate that the Irish Bronze Age is composed of a mixture of European MN and introgressing Steppe ancestry (9, 10). To estimate the proportion of Yamnaya to MN ancestry in each Irish Bronze Age sample, we took three approaches. First, from ADMIXTURE analysis (Fig. 1), we examined the green Caucasus ancestry component. We presume an ultimate source of this as the Yamnaya where it features at a proportion of 40% of their total ancestry. In our three Irish Bronze Age samples, it is present at levels between 6–13%, which, when scaled up to include the remaining 60% of Yamnaya ancestry, imply a total of 14–33% Yamnaya ancestry and therefore 67–86% MN in the Irish Bronze Age. Second, for each Bronze Age Irish individual, we calculated the proportion of MN ancestry by using the ratio f4(Mbuti, Ballynahatty; X, Dai)/f4(Mbuti, Ballynahatty; Gok2, Dai), which gave estimates between 72 ± 4% to 74 ± 5%, implying again a substantial Yamnaya remainder. Third, we followed the methods described in Haak et al. (9), which use a collection of outgroup populations, to estimate the mixture proportions of three different sources, Linearbandkeramik (Early Neolithic; 35 ± 6%), Loschbour (WHG; 26 ± 12%), and Yamnaya (39 ± 8%), in the total Irish Bronze Age group. These three approaches give an overlapping estimate of ∼32% Yamnaya ancestry.

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The Yamnaya Steppe Herders from Russia Jun 19, 2018 18:34:04 GMT

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Fig. 2.
Estimated distribution of ROH for ancient samples, placed in the context of values from modern populations. This plot shows total length of ROH for a series of length categories in 32 modern and 6 ancient individuals. Of these modern individuals, 18 were selected from a subset of 1000 Genomes populations (33) with no evidence of recent historical admixture. These individuals represented the median value of total length of ROH for their population. Thirteen modern individuals from the Simons Genome Diversity Project (34) were also included. ROH calls for each sample were based on 1.6M autosomal transversions with minor allele frequencies above 0.5%.

Runs of Homozygosity.
We coanalyzed Ballynahatty, Rathlin1, and the four other ancient Europeans sequenced to high coverage (7, 8) to estimate the fraction of each genome under runs of homozygosity (ROH) (SI Appendix, Section S13). This approach may be useful to inform on past demography; long contiguous homozygous segments indicate recent endogamy, whereas shorter runs result from older restrictions in ancestral population size (31, 32). Fig. 2 plots these ROH estimates in a background of data from modern genomes of diverse origins (33, 34). The single ancient hunter–gatherer genome in this analysis, Loschbour, shows extremely high levels of ROH, indicative of a restricted ancestral population size. However, Ballynahatty and the two early Neolithic genomes, Stuttgart and NE1, each show levels of ROH comparable to those seen in modern East Asians. This pattern argues against a genetic bottleneck, such as that due to a narrow pioneer colonization, in the ancestry of this Irish Neolithic genome and supports the idea of large-scale Neolithic migration rather than assimilation of farming by local hunter–gatherers. The Bronze Age genomes, Rathlin1 and BR2, both show further reductions of ROH, producing distributions similar to each other and to that of modern Europeans.

Haplotype-Based Resolution of Continuity.
Haplotype-based approaches are more powerful than those using unlinked genetic loci in identifying fine genetic structure, such as that displayed among Europeans, and are relatively robust to bias from marker ascertainment (35, 36). We ran ChromoPainter in fineSTRUCTURE (Version 2) (35) to decompose each ancient genome into a series of haplotypic chunks, and identified which modern individuals from a diverse set of Eurasian populations (37) shared the same, or most similar, haplotype at each given chunk. We then considered the pattern of chunk donation between each ancient genome and modern populations.

Unsurprisingly, the pattern of haplotypic affinity of Ballynahatty among modern European populations is strongly correlated to that of the earlier Neolithic samples (SI Appendix, Fig. S14.2; r > 0.74, P < 10−7), with southern Mediterranean samples in each analysis showing highest levels of chunk copying. However, some differences are discernable; the Hungarian and Stuttgart Neolithic genomes tend toward higher values in eastern Mediterranean (Sicilian, Italian, and Greek samples; Fig. 3 and SI Appendix, Fig. S14.1), and the Irish Neolithic has highest values in the west (Sardinian and Spanish). A further difference lies in the comparison of each to the affinities shown by the Luxembourg WHG, Loschbour, which shows no correlation in its modern affinities with the earlier continental Neolithics but does show a significant relationship (P = 5.4 × 10−4) with those of Ballynahatty, undoubtedly because of greater WHG admixture in her ancestry.

Fig. 3.
Comparison of Irish and Central European ancient genomes for haplotype-based affinity to modern populations. Interpolated heatmaps comparing relative haplotype donations by two Irish (Ballynahatty, Rathlin1) and two Hungarian (NE1, BR2) ancient genomes.

The most striking feature of the haplotype sharing by the Irish Bronze Age genome is its high median donation levels to Irish, Scottish, and Welsh populations (Fig. 3). In regression with results from the other ancient genomes, these insular Celtic populations, and to a lesser degree the English, show an excess of sharing with Rathlin1, suggesting some level of local continuity at the edge of Europe persisting over 4,000 y. The Hungarian Bronze Age genome shows more affinity with central European populations. Interestingly, for both Bronze Age genomes, the modern Basque population displays outlying low-affinity scores compared with neighboring western European samples, supporting recent findings that suggest a continuity between the Basques and Iberian Chalcolithic groups (25).

Phenotypic Analysis.
Ireland is unusual in displaying world maximum frequencies of a number of important genetic variants, particularly those involved in lactase persistence and two recessive diseases: cystic fibrosis and hemochromatosis (38⇓⇓–41, 42, 43). Interestingly, both the high coverage Neolithic and Bronze Age individuals were heterozygous for the hemochromatosis alleles H63D and C282Y, respectively. Modern Irish allele frequencies are 15% and 11% for these variants, with the latter, more penetrant variant responsible for a world maximum of this disease in Ireland (44, 45). Additionally and in accordance with other data suggesting a late spread of the lactase persistence phenotype now prevalent in western Europe (7, 10), the Neolithic Ballynahatty was homozygous for the nonpersistent genotype and Rathlin1 was heterozygous and thus tolerant of drinking raw milk into adulthood.

We were able to deduce that Neolithic Ballynahatty had a dark hair shade (99.5% probability), most likely black (86.1% probability), and brown eyes (97.3% probability) (46). Bronze Age Rathlin1 probably had a light hair shade (61.4%) and brown eyes (64.3%). However, each Rathlin genome possessed indication of at least one copy of a haplotype associated with blue eye color in the HERC2/OCA2 region.