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Post by Admin on May 27, 2021 0:41:01 GMT
Touching the Void Marc Vander Linden Institute of Archaeology, University College London, United Kingdom Hardly a single week seems to pass without the publication of another aDNA paper on later European prehistory, bringing its sense of repetition in terms of methods and, most worryingly, results and limited archaeological contextualization. And yet, despite the magnitude of this data-cascade, archaeological reactions remain comparatively limited and subdued (but see Hofmann, 2014; Vander Linden, 2016). From this point of view, this important contribution by Martin Furholt, and the decision by the EJA editorial team to attach to it a full discussion, must be applauded. Obviously, the relevance of Furholt's piece reaches well beyond its mere existence and lies first and foremost in its intrinsic quality and the key points it raises.
Furholt rightly stresses the uncomfortable position of archaeologists regarding aDNA. On the one hand, here is a method which demonstrates exquisite technical refinements, but, on the other hand, its interpretations are plagued, at least to the archaeologist's trained eye, by an outdated framework which treats migrations as securely identified historical events to be mapped and documented, rather than explained and understood. Even if these papers are published in the highest-ranking journals, one is left with the uneasy feeling that, in archaeological terms, very little has actually been learned. Whether for the Early or the Late European Neolithic, the existence of migrating populations has indeed been long suspected; although, as any student of our discipline knows all too well, their exact role in explaining change in past human societies has been systematically minimized since the 1960s.
The point is simple. As processual archaeology rose from the ashes of the pyre it had set on migration, the topic became, until relatively recently, a no-go area for most archaeologists. Furholt might be able to invoke several key papers when advocating a more complex take on migration, but the field remains in its infancy. Likewise, the excessive liberty taken by geneticists with archaeological cultures reflects, in a distorted way, the unease of our discipline with this core concept and, beyond that, how poor we generally are at describing material variability, let alone interpreting it (see Shennan, 2013). All in all, Furholt's outlook reflects the state of uncertainty where the discipline has been lingering for too long.
In many respects, thus, we created a void waiting to be filled, which geneticists did on the back of undeniable technical prowess. This being said, it is obvious that geneticists do not engage that much with archaeology and archaeologists, the latter often appearing as passive sample providers rather than active intellectual contributors in these publications. At the core of the problem lies the assumed identity between biological populations and archaeological cultures, both considered as expressions of coherent, self-bounded units, a fallacy denounced fifteen years ago when modern DNA was hailed as revolutionary (e.g. MacEachern, 2000). Two simple points, also made by Furholt, demonstrate the negative impact of this simplistic and false assumption.
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Post by Admin on May 27, 2021 6:03:22 GMT
Firstly, aDNA papers often stem from a limited number of samples, from which any pattern is then generalized across the entire geographical and temporal extent of the corresponding archaeological culture. The nature of aDNA data partly overcomes this problem (Li & Durbin, 2011) and further—hopefully more systematic—sampling will by definition improve the resolution. However, the limitations of this approach are obvious as the narrow range of samples does not allow one to explore possible differences within the geographical and temporal lapse of a given archaeological culture. Secondly, the question of relatedness between populations is central to the genetic entreprise, and reflected in ADMIXTURE and PCA graphs which provide statistically-informed depictions of this measure. The reasons for this preference lie deeply in the project of describing and understanding the variation of the modern Europe genetic variation. The difficulty lies when one attempts to translate biological relatedness in social terms, materialized by archaeological artefacts. This tension is well exemplified when genetic relations between central and eastern European third millennium bc samples are linked to corresponding material affinities between the Yamnaya and Corded Ware complexes while, as Furholt elegantly reminds us, the latter is pretty much typologically-related to all archaeological cultures before, after, and around it.
The above remarks arguably stem from a genuine lack of archaeological sophistication in most aDNA papers, in many ways repeating and prolonging the mistakes made by archaeologists for several decades. Are we thus in a theoretical impasse? Or is it that aDNA can only provide information with which we cannot do much? Most surely not. The bulk of the work has, so far, been carried out in a deceptively empirical way, taking advantage of a so-called golden phase where each sample is bound to tell us something that we by definition did not know about the genetic make-up of past populations. This strategy, while efficient in the short term, is hardly sustainable. The only viable alternative lies in complex hypotheses, informed and tested by several categories of evidence, all considered on equal footings.
Population history, including migration, provides a robust framework for such hypotheses to be elaborated. Indeed, the main result gained from aDNA, as well as from other studies, is that Neolithic populations were in constant flux, as suggested by ever-changing levels of admixture. This simple observation opens countless possibilities for future research. For instance, reading the literature, one can be left with the impression that the Early and Late Neolithic migration events were interchangeable, while they obviously happened under different demographic regimes, under different logistics, that is, in fundamentally different ways. Were small or large groups moving? Did the migration involve all categories of people, or were they sex-biased? Both questions can partly be answered by bioinformatic treatments of the data (e.g. Pemberton et al., 2012; Goldberg et al., 2017). Further fine-grained structure in these migrations will, without doubt, be unravelled by re-examining in parallel the aDNA and wider archaeological records. However, when doing so, and as hinted at by Furholt, we need to drive away from our implicit will to align neatly all signals to write simple, elegant, yet inherently faulty narratives. Genes and material culture, in their own complexity, do not operate in the same spheres of action, nor do they unfold upon the same spatial and temporal scales. We need to take advantage of their respective complexity to test alternative hypotheses, and get towards a more textured representation of the past.
To conclude, aDNA is, without any doubt, a fantastic technique, whose amazing potential we only begin to grasp. It is, however, worth remembering that this potential only applies to a narrow part of the archaeological agenda (e.g. Kintigh et al., 2014) and will only be unfolded by testing proper hypotheses, rather than chasing ghosts of our discipline's past. Of all social sciences, archaeology has assuredly the best track record at inter-disciplinarity and, thus, at overcoming a range of responses from extreme confidence to total disenchantment with new techniques. In this sense, the difficulties we encounter with aDNA are hardly new. Let us just not forget that any improvement will not simply come from ‘us’ teaching ‘them’, but also from us giving a hard look at ourselves in the mirror.
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Post by Admin on May 27, 2021 20:52:25 GMT
Reply to the Comments Martin Furholt Institute of Prehistoric and Protohistoric Archaeology, Kiel University, Germany The comments from two archaeologists and two geneticists represent a spectrum of critique, approval, and extension of the main issues discussed in my article, and will hopefully help to push forward the necessary interdisciplinary dialogue. Wolfgang Haak defends his view that the data indicate a rather rapid migration process that would coincide with the beginning of the Corded Ware, arguing that the ever-increasing number of samples has now confirmed that all individuals connected to Corded Ware so far analysed have steppe ancestry, while those connected to the slightly earlier Globular Amphora Complex do not. Of course, it is not impossible that the first appearance of steppe ancestry in central Europe coincides sharply with the first appearance of Corded Ware, and I have no problem with this interpretation, as long as it is empirically proven. What I criticize in my paper is the presupposition of a biological similarity of individuals connected to specific units of archaeological material. This is a premise that derives from and feeds into an unholy reification and biologisation of cultures as closed and homogeneous social units. More importantly, it is empirically false. Looking at the clusters of samples on the PCA in Figure 2 (i.e. the Early/Middle Neolithic cluster or the Late Neolithic/Steppe ancestry cluster), one can see that they contain a mix of samples associated to different archaeological cultures. This is even more obvious in the newer, updated versions of the same PCA (i.e. Mathieson et al., 2017: fig. 1). These clusters represent units in space and time (i.e. sixth to fourth millennia bc in southern and central Europe, or third and second millennia bc in central Europe); they do not differentiate between archaeological cultures. Clearly, by the third millennium cal bc, a major change in the genetic pool of central Europe has taken place; but the data do not, at present, suggest a very rapid, event-like process. Nine individuals from two sites connected to Globular Amphora from Poland and Ukraine without steppe ancestry do not adequately represent the entire pre-Corded Ware situation in Europe. As I argue in the article, and as was recently stressed by Volker Heyd (2017) archaeologically, steppe influence, which is visible in burial rites among other practices, can be traced back to the fifth millennium cal bc in south-eastern Europe and the Carpathian basin; and it clearly played an important role during the fourth millennium cal bc in different parts of Europe. The study Haak mentions (Mathieson et al., 2017) also presents two individuals from Bulgaria who date to the fifth millennium cal bc (Varna I and Smyadovo) and show a stronger steppe ancestry component in the ADMIXTURE plot. All this indicates the possibility of a deeper, longer-term history of interaction, characterized by regular and repeated human movement between the steppes and south-eastern and central Europe, instead of a rapid, massive migration event.
However, as Eva Fernández-Domínguez makes clear, the geneticists also have to deliver in order to enable a more sophisticated interdisciplinary discussion, be more aware of the limitations of their datasets, and take seriously the conceptual pitfalls—sample size, the reification of cultures, ambiguous use of the term migration—and work on ways to avoid them through a more intensive collaboration across disciplinary borders. She positively evaluates the new paper by Kristiansen et al. (2017) as an example of a more elaborated re-theorization of the Allentoft et al. (2015) migration narrative. This new scenario—Corded Ware being formed as a consequence of migration of individuals with steppe ancestry into central Europe, followed by interaction with local individuals, adaptation, admixture, and hybridization—is a hypothesis that can be tested against the biomolecular and archaeological datasets. For example, in such a scenario, we should expect to find steppe ancestry in central Europe connected to pre-Corded Ware archaeological complexes. Yet, to return again to Hofmann's and Vander Linden's commentaries, although Kristiansen et al. (2017) provide an appealing broad-stroke narrative, and propose concrete social mechanisms (female exogamy), it is a one-size-fits-all approach that should be elaborated by incorporating a stronger acknowledgement of and emphasis on local variability and potentially different social mechanisms that are strongly suggested by the variability visible in the archaeological record.
Although discussions of these topics are already gaining speed, we still have a long way to go until we will have developed an anthropologically informed integration of bio-molecular and archaeological data, yielding an identification of realistic social processes. While a stronger bottom-up component is surely crucial, we should also explore a broader range of anthropologically studied mechanisms of mobility, migration, and population circulation, and systematically explore the ways in which such phenomena are discernible by studying the archaeological record and genetic datasets.
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Post by Admin on Jan 22, 2022 0:09:35 GMT
Genetic ancestry changes in Stone to Bronze Age transition in the East European plain
Transition from the Stone to the Bronze Age in Central and Western Europe was a period of major population movements originating from the Ponto-Caspian Steppe. Here, we report new genome-wide sequence data from 28 individuals from the territory north of this source area – from the under-studied Western part of present-day Russia, including Stone Age hunter-gatherers (10,800–4,250 cal BC) and Bronze Age farmers from the Corded Ware complex called Fatyanovo Culture (2,900–2,050 cal BC). We show that Eastern hunter-gatherer ancestry was present in Northwestern Russia already from around 10,000 BC. Furthermore, we see a clear change in ancestry with the arrival of farming – the Fatyanovo Culture individuals were genetically similar to other Corded Ware cultures, carrying a mixture of Steppe and European early farmer ancestry and thus likely originating from a fast migration towards the northeast from somewhere in the vicinity of modern-day Ukraine, which is the closest area where these ancestries coexisted from around 3,000 BC.
Introduction The western part of the present territory of Russia has been a focal point of several prehistoric processes yet remains heavily under-represented in ancient DNA (aDNA) studies. Some of the oldest genetically studied individuals from Europe come from this region1–3, but overall, ancient genetic information is sparse.
The colonization of the Eastern and Northern European forest belt took place in two large waves during the end of the Paleolithic and the beginning of the Mesolithic period (bordering ca 9,700 cal BC). In both cases, groups of peoples with similar material cultures to those spread in wide areas of Europe took part in the colonization process. In regard to the Mesolithic settlements in the area, a number of distinct archaeological cultures (Butovo, Kunda, Veretye, Suomusjärvi etc.) have been identified4–7. In older stages of habitation, the material culture is so similar that it has also been handled as a single cultural area. However, from the middle of the 9th millennium cal BC, local population groups with clearly distinguished cultural differences already existed in the area8. Despite a series of small changes occurring during the Mesolithic period (as well as the Early Neolithic period according to the Russian periodization based on pottery production), the cultural continuities as a general trend of those groups are observable across time until the beginning of the 5th millennium, in some areas up to the beginning of the 4th millennium cal BC, when the so-called Pit-Comb Ware and Comb Ware cultures formed in wide areas of Europe9. In the territory of the Volga-Oka interfluvial area in Russia, Lyalovo Culture with pit-comb pottery and its local variants were described10. It is likely that the people from this cultural realm gave the starting boost to a series of developments in archaeological cultures specific to the 4th to 3rd millenniums cal BC, in particular to the Volosovo Culture, distinguishable in large areas of Russia11.
Genetic studies have shown that the Yamnaya Culture people spread out of the Steppe region of the Eastern European Plain and contributed significantly to the ancestry of the European populations12–14 that started to produce Corded Ware around 2,900–2,800 cal BC15. Furthermore, the migration of the Yamnaya population was two times faster than the Anatolian early farmer (EF) migration into Europe a few thousand years earlier and coincided with a decrease in broad-leaf forests and increase in grasslands/pastures in Western Europe16. The Corded Ware Culture (CWC) was spread on a wide area, reaching Tatarstan in the East, the southern parts of Finland, Sweden and Norway in the North, Belgium and Netherlands in the West, and Switzerland and Ukraine in the South17–19. Its easternmost extension – Fatyanovo Culture – is a prominent Eastern European CWC branch, that was spread over a large area in European Russia and introduced animal husbandry and probably crop cultivation into the forest belt20,21. So far, only 14 radiocarbon dates have been published for Fatyanovo Culture, placing it to 2,750–2,500 (2,300) cal BC21. The burial customs characteristic of the culture included the placement of the dead in flat earth graves (less often in barrows), mostly flexed and on their side – men mostly on the right and women on the left side – and shaft-hole stone axes, flint tools and ceramic vessels etc. as grave goods20,22.
European Mesolithic hunter-gatherers (HG) can be divided into groups based on their ancestry. The so-called Western group (WHG) was spread from Iberia to the Balkans and reached as far as the Late Mesolithic Eastern Baltic23–28. The Eastern group (EHG) had genetic influences from further east (a genetic connection to modern Siberians) and so far includes 6 individuals from Western Russia14,29,28,30. The genomes of four of these individuals have been previously studied from Karelia in the northwest from 7,500–5,000 BC14,28,29 and two from the Samara region in the eastern part of European Russia from 9,400–5,500 BC14,30.
The Yamnaya Culture pastoralists shared ancestry with EHG and Caucasus hunter-gatherers (CHG)31. Genetic studies have revealed that CWC individuals, with predominantly Yamnaya ancestry, showed some admixture with European EF of Anatolian ancestry and were most similar to modern populations from Eastern and Northern Europe13,14,29,32,28. Lactase persistence, frequent in contemporary Central and Northern Europe, was still at low frequency in the CWC individuals13,28,29,33 but underwent strong selection soon after28,33,34. It has also been shown that the Yamnaya expansion was male-biased35, while the Anatolian EF ancestry in the CWC individuals was acquired more through the female lineage32.
In this study, we aim to shed light on the demographic processes accompanying the change from a hunting-gathering lifestyle to crop cultivation and animal husbandry in the forest belt of Northeast Europe and to look into the genetic changes involved in the transition from the Stone to the Bronze Age in the western part of present-day Russia. We add almost 30 new radiocarbon dates from Western Russia and characterize the genetic affinities of the HG and Fatyanovo Culture farmers. As part of the study, we set out to examine if and how the major population movements seen in other parts of Europe during the Holocene have affected this area. Additionally, our aim is to shed light on local processes like the potential admixture between Volosovo and Fatyanovo Culture people suggested by archaeologists6,17,36.
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Post by Admin on Jan 22, 2022 2:54:46 GMT
Results Samples and archaeological background In this study, we have extracted DNA from the apical tooth roots of 48 individuals from 18 archaeological sites in modern-day Western Russia and Estonia (Fig. 1, Supplementary Data 1, Supplementary Data 2, Supplementary Note 1). The 28 individuals with better preservation yielded 13– 82% endogenous DNA and <3% contamination (Supplementary Data 2). We have shotgun sequenced these individuals to an average genomic coverage of around 0.1x (n=18), 1x (n=9) and 4x (PES001) (Table 1, Supplementary Data 2). Figure 1. Map of the geographical locations of the individuals of this study. Numbers in brackets behind site names indicate the number of individuals included from this site (if more than one). Arrow indicates the proposed direction of migration of the predecessors of the Fatyanovo Culture people. Table 1. Archaeological information, genetic sex, mtDNA and Y chromosome haplogroups and average genomic coverage of the individuals of this study. Date (cal BC) – calibrated using OxCal v4.2.4121 and IntCal13 atmospheric curve122; Morph. – morphological; Gen. – genetic; MT hg – mitochondrial DNA haplogroup; Y hg – Y chromosome haplogroup; Av. Cov. – average genomic coverage. The presented genome-wide data is derived from 3 Stone Age hunter-gatherers (WeRuHG; 10,800–4,250 cal BC) and 24 Bronze Age Fatyanovo Culture farmers from Western Russia (Fatyanovo; 2,900–2,050 cal BC), and 1 Corded Ware Culture individual from Estonia (EstCWC; 2,850–2,500 cal BC) (Fig. 1, Supplementary Data 1, Supplementary Data 2, Supplementary Note 1). We analyzed the data in the context of published ancient and modern populations. Affinities of Western Russian hunter-gatherers First, we assessed the mitochondrial DNA (mtDNA) and Y chromosome (chrY) variation of the 3 Stone Age HG from Western Russia. The oldest individual PES001 belonged to mtDNA haplogroup (hg) U4 (Table 1, Supplementary Data 2), which has been found before in EHG and Scandinavian HG individuals37,14,27,32,28,26. The other two represented mtDNA hgs T2 and K1 (Table 1, Supplementary Fig. 5, Supplementary Data 2), which is noteworthy since hg U was by far the most frequent in European HG before the spread of farming, but hgs H11 and T2 have also been found previously in HG individuals 28,26. The chrY lineages carried by PES001 and BER001 were R1a5-YP1272 and Q1-L54, respectively (Table 1, Supplementary Data 2) – both hgs have also been found previously in EHG individuals14,29,32,28,26. Next, we compared the WeRuHG individuals to a set of available ancient and modern populations using autosomal data. We performed principal component analysis (PCA), by projecting ancient individuals onto components calculated on Western Eurasian individuals from the Estonian Biocentre Illumina genotyping array dataset (EBC-chipDB). The PCA revealed that all three WeRuHG individuals cluster together with individuals positioned at the EHG end of the European HG cline (Fig. 2A). We then projected ancient individuals onto a world-wide modern sample set from the EBC-chipDB using ADMIXTURE analysis. We ran the calculations on K=3 to K=18 (Supplementary Fig. 1C–D) but discuss K=9 (Fig. 2B, Supplementary Fig. 1A–B). This K level had the largest number of inferred genetic clusters for which >10% of the runs that reached the highest Log Likelihood values yielded very similar results. The analysis again shows that WeRuHG individuals are most similar to EHG, being made up of mostly the blue component maximized in WHG and a considerable proportion of the yellow component most frequent in modern Khanty (Fig. 2B, Supplementary Fig. 1AB).
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