“Steppe ancestry” step by step: Khvalynsk, Sredni Stog, Repin, Yamna, Corded Ware

dzudzuana_pca-large

Wang et al. (2018) is obviously a game changer in many aspects. I have already written about the upcoming Yamna Hungary samples, about the new Steppe_Eneolithic and Caucasus Eneolithic keystones, and about the upcoming Greece Neolithic samples with steppe ancestry.

An interesting aspect of the paper, hidden among so many relevant details, is a clearer picture of how the so-called Yamnaya or steppe ancestry evolved from Samara hunter-gatherers to Yamna nomadic pastoralists, and how this ancestry appeared among Proto-Corded Ware populations.

anatolia-neolithic-steppe-eneolithic
Image modified from Wang et al. (2018). Marked are in orange: equivalent Steppe_Maykop ADMIXTURE; in red, approximate limit of Anatolia_Neolithic ancestry found in Yamna populations; in blue, Corded Ware-related groups. “Modelling results for the Steppe and Caucasus cluster. Admixture proportions based on (temporally and geographically) distal and proximal models, showing additional Anatolian farmer-related ancestry in Steppe groups as well as additional gene flow from the south in some of the Steppe groups as well as the Caucasus groups.”

Please note: arrows of “ancestry movement” in the following PCAs do not necessarily represent physical population movements, or even ethnolinguistic change. To avoid misinterpretations, I have depicted arrows with Y-DNA haplogroup migrations to represent the most likely true ethnolinguistic movements. Admixture graphics shown are from Wang et al. (2018), and also (the K12) from Mathieson et al. (2018).

1. Samara to Early Khvalynsk

The so-called steppe ancestry was born during the Khvalynsk expansion through the steppes, probably through exogamy of expanding elite clans (eventually all R1b-M269 lineages) originally of Samara_HG ancestry. The nearest group to the ANE-like ghost population with which Samara hunter-gatherers admixed is represented by the Steppe_Eneolithic / Steppe_Maykop cluster (from the Northern Caucasus Piedmont).

Steppe_Eneolithic samples, of R1b1 lineages, are probably expanded Khvalynsk peoples, showing thus a proximate ancestry of an Early Eneolithic ghost population of the Northern Caucasus. Steppe_Maykop samples represent a later replacement of this Steppe_Eneolithic population – and/or a similar population with further contribution of ANE-like ancestry – in the area some 1,000 years later.

PCA-caucasus-steppe-samara

This is what Steppe_Maykop looks like, different from Steppe_Eneolithic:

steppe-maykop-admixture

NOTE. This admixture shows how different Steppe_Maykop is from Steppe_Eneolithic, but in the different supervised ADMIXTURE graphics below Maykop_Eneolithic is roughly equivalent to Eneolithic_Steppe (see orange arrow in ADMIXTURE graphic above). This is useful for a simplified analysis, but actual differences between Khvalynsk, Sredni Stog, Afanasevo, Yamna and Corded Ware are probably underestimated in the analyses below, and will become clearer in the future when more ancestral hunter-gatherer populations are added to the analysis.

2. Early Khvalynsk expansion

We have direct data of Khvalynsk-Novodanilovka-like populations thanks to Khvalynsk and Steppe_Eneolithic samples (although I’ve used the latter above to represent the ghost Caucasus population with which Samara_HG admixed).

We also have indirect data. First, there is the PCA with outliers:

PCA-khvalynsk-steppe

Second, we have data from north Pontic Ukraine_Eneolithic samples (see next section).

Third, there is the continuity of late Repin / Afanasevo with Steppe_Eneolithic (see below).

3. Proto-Corded Ware expansion

It is unclear if R1a-M459 subclades were continuously in the steppe and resurged after the Khvalynsk expansion, or (the most likely option) they came from the forested region of the Upper Dnieper area, possibly from previous expansions there with hunter-gatherer pottery.

Supporting the latter is the millennia-long continuity of R1b-V88 and I2a2 subclades in the north Pontic Mesolithic, Neolithic, and Early Eneolithic Sredni Stog culture, until ca. 4500 BC (and even later, during the second half).

Only at the end of the Early Eneolithic with the disappearance of Novodanilovka (and beginning of the steppe ‘hiatus’ of Rassamakin) is R1a to be found in Ukraine again (after disappearing from the record some 2,000 years earlier), related to complex population movements in the north Pontic area.

NOTE. In the PCA, a tentative position of Novodanilovka closer to Anatolia_Neolithic / Dzudzuana ancestry is selected, based on the apparent cline formed by Ukraine_Eneolithic samples, and on the position and ancestry of Sredni Stog, Yamna, and Corded Ware later. A good alternative would be to place Novodanilovka still closer to the Balkan outliers (i.e. Suvorovo), and a source closer to EHG as the ancestry driven by the migration of R1a-M417.

PCA-sredni-stog-steppe

The first sample with steppe ancestry appears only after 4250 BC in the forest-steppe, centuries after the samples with steppe ancestry from the Northern Caucasus and the Balkans, which points to exogamy of expanding R1a-M417 lineages with the remnants of the Novodanilovka population.

steppe-ancestry-admixture-sredni-stog

4. Repin / Early Yamna expansion

We don’t have direct data on early Repin settlers. But we do have a very close representative: Afanasevo, a population we know comes directly from the Repin/late Khvalynsk expansion ca. 3500/3300 BC (just before the emergence of Early Yamna), and which shows fully Steppe_Eneolithic-like ancestry.

afanasevo-admixture

Compared to this eastern Repin expansion that gave Afanasevo, the late Repin expansion to the west ca. 3300 BC that gave rise to the Yamna culture was one of colonization, evidenced by the admixture with north Pontic (Sredni Stog-like) populations, no doubt through exogamy:

PCA-repin-yamna

This admixture is also found (in lesser proportion) in east Yamna groups, which supports the high mobility and exogamy practices among western and eastern Yamna clans, not only with locals:

yamnaya-admixture

5. Corded Ware

Corded Ware represents a quite homogeneous expansion of a late Sredni Stog population, compatible with the traditional location of Proto-Corded Ware peoples in the steppe-forest/forest zone of the Dnieper-Dniester region.

PCA-latvia-ln-steppe

We don’t have a comparison with Ukraine_Eneolithic or Corded Ware samples in Wang et al. (2018), but we do have proximate sources for Abashevo, when compared to the Poltavka population (with which it admixed in the Volga-Ural steppes): Sintashta, Potapovka, Srubna (with further Abashevo contribution), and Andronovo:

sintashta-poltavka-andronovo-admixture

The two CWC outliers from the Baltic show what I thought was an admixture with Yamna. However, given the previous mixture of Eneolithic_Steppe in north Pontic steppe-forest populations, this elevated “steppe ancestry” found in Baltic_LN (similar to west Yamna) seems rather an admixture of Baltic sub-Neolithic peoples with a north Pontic Eneolithic_Steppe-like population. Late Repin settlers also admixed with a similar population during its colonization of the north Pontic area, hence the Baltic_LN – west Yamna similarities.

NOTE. A direct admixture with west Yamna populations through exogamy by the ancestors of this Baltic population cannot be ruled out yet (without direct access to more samples), though, because of the contacts of Corded Ware with west Yamna settlers in the forest-steppe regions.

steppe-ancestry-admixture-latvia

A similar case is found in the Yamna outlier from Mednikarovo south of the Danube. It would be absurd to think that Yamna from the Balkans comes from Corded Ware (or vice versa), just because the former is closer in the PCA to the latter than other Yamna samples. The same error is also found e.g. in the Corded Ware → Bell Beaker theory, because of their proximity in the PCA and their shared “steppe ancestry”. All those theories have been proven already wrong.

NOTE. A similar fallacy is found in potential Sintashta→Mycenaean connections, where we should distinguish statistically that result from an East/West Yamna + Balkans_BA admixture. In fact, genetic links of Mycenaeans with west Yamna settlers prove this (there are some related analyses in Anthrogenica, but the site is down at this moment). To try to relate these two populations (separated more than 1,000 years before Sintashta) is like comparing ancient populations to modern ones, without the intermediate samples to trace the real anthropological trail of what is found…Pure numbers and wishful thinking.

Conclusion

Yamna and Corded Ware show a similar “steppe ancestry” due to convergence. I have said so many times (see e.g. here). This was clear long ago, just by looking at the Y-chromosome bottlenecks that differentiate them – and Tomenable noticed this difference in ADMIXTURE from the supplementary materials in Mathieson et al. (2017), well before Wang et al. (2018).

This different stock stems from (1) completely different ancestral populations + (2) different, long-lasting Y-chromosome bottlenecks. Their similarities come from the two neighbouring cultures admixing with similar populations.

If all this does not mean anything, and each lab was going to support some pre-selected archaeological theories from the 1960s or the 1980s, coupled with outdated linguistic models no matter what – Anthony’s model + Ringe’s glottochronological tree of the early 2000s in the Reich Lab; and worse, Kristiansen’s CWC-IE + Germano-Slavonic models of the 1940s in the Copenhagen group – , I have to repeat my question again:

What’s (so much published) ancient DNA useful for, exactly?

Related

Resurge of local populations in the final Corded Ware culture period from Poland

poland-kujawy

Open access A genomic Neolithic time transect of hunter-farmer admixture in central Poland, by Fernandes et al. Scientific Reports (2018).

Interesting excerpts (emphasis mine, stylistic changes):

Most mtDNA lineages found are characteristic of the early Neolithic farmers in south-eastern and central Europe of the Starčevo-Kőrös-Criş and LBK cultures. Haplogroups N1a, T2, J, K, and V, which are found in the Neolithic BKG, TRB, GAC and Early Bronze Age samples, are part of the mitochondrial ‘Neolithic package’ (which also includes haplogroups HV, V, and W) that was introduced to Europe with farmers migrating from Anatolia at the onset of the Neolithic17,31.

A noteworthy proportion of Mesolithic haplogroup U5 is also found among the individuals of the current study. The proportion of haplogroup U5 already present in the earliest of the analysed Neolithic groups from the examined area differs from the expected pattern of diversity of mtDNA lineages based on a previous archaeological view and on the aDNA findings from the neighbouring regions which were settled by post-Linear farmers similar to BKG at that time. A large proportion of Mesolithic haplogroups in late-Danubian farmers in Kuyavia was also shown in previous studies concerning BKG samples based on mtDNA only, although these frequencies were derived on the basis of very small sample sizes.

y-dna-poland

A significant genetic influence of HG populations persisted in this region at least until the Eneolithic/Early Bronze Age period, when steppe migrants arrived to central Europe. The presence of two outliers from the middle and late phases of the BKG in Kuyavia associated with typical Neolithic burial contexts provides evidence that hunter-farmer contacts were not restricted to the final period of this culture and were marked by various episodes of interaction between two societies with distinct cultural and subsistence differences.

The identification of both mitochondrial and Y-chromosome haplogroup lineages of Mesolithic provenance (U5 and I, respectively) in the BKG support the theory that both male and female hunter-gatherers became part of these Neolithic agricultural societies, as has been reported for similar cases from the Carpathian Basin, and the Balkans. The identification of an individual with WHG affinity, dated to ca. 4300 BCE, in a Middle Neolithic context within a BKG settlement, provides direct evidence for the regional existence of HG enclaves that persisted and coexisted at least for over 1000 years, from the arrival of the LBK farmers ca. 5400 BCE until ca. 4300 BCE, in proximity with Neolithic settlements, but without admixing with their inhabitants.

poland-pca
Principal component analysis with modern populations greyed out on the background (top), ADMIXTURE results with K = 10 with samples from this study amplified (bottom).

The analysis of two Late Neolithic cultures, the GAC and CWC, shows that steppe ancestry was present only among the CWC individuals analysed, and that the single GAC individual had more WHG ancestry than previous local Neolithic individuals. (…) The CWC’s affinity to WHG, however, contrasts with results from published CWC individuals that identified steppe ancestry related to Yamnaya as the major contributor to the CWC genomes, while here we report also substantial contributions from WHG that could relate to the late persistence of pockets of WHG populations, as supported by the admixture results of N42 and the finding of the 4300-year-old N22 HG individual. These results agree with archaeological theories that suggest that the CWC interaction with incoming steppe cultures was complex and that it varied by region.

Some comments

About the analyzed CWC samples, it is remarkable that, even though they are somehow related to each other, they do not form a tight cluster. Also, their Y-DNA (I2a), and this:

When compared to previously published CWC data, our CWC group (not individuals) is genetically significantly closer to WHG than to steppe individuals (Z = −4.898), a result which is in contrast with those for CWC from Germany (Z = 2.336), Estonia (Z = 0.555), and Latvia (Z = 1.553).

ancestry-proportions-poland
Ancestry proportions based on qpAdm. Visual representation of the main results presented in Supplementary Table S5. Populations from this study marked with an asterisk. Values and populations in brackets show the nested model results marked in green in Supplementary Table S5.

Włodarczak (2017) talks about the CWC period in Poland after ca. 2600 BC as a time of emergence of an allochthnous population, marked by the rare graves of this area, showing infiltrations initially mainly from Lesser Poland, and later (after 2500 BC) from the western Baltic zone.

Since forest sub-Neolithic populations would have probably given more EHG to the typical CWC population, these samples support the resurge of ‘local’ pockets of GAC- or TRB-like groups with more WHG (and also Levant_Neolithic) ancestry.

The known presence of I2a2a1b lineages in GAC groups in Poland also supports this interpretation, and the subsistence of such pockets of pre-steppe-like populations is also seen with the same or similar lineages appearing in comparable ‘resurge’ events in Central Europe, e.g. in samples from the Únětice and Tumulus culture.

About the Bronze Age sample, we have at last official confirmation of haplogroup R1a1a (sadly no subclade*) at the very beginning of the Trzciniec period – in a region between western (Iwno) and eastern (Strzyżów) groups related to Mierzanowice – , which has to be put in relation with the samples from the final Trzciniec period in the Baltic published in Mittnik et al. (2018).

EDIT (8 OCT 2018): More specific subclades have been published, including a R1a-Z280 lineage for the Bronze Age sample (see spreadsheet).

This confirms the early resurge of R1a-Z645 (probably R1a-Z282) lineages at the core of the developing East European Bronze Age, a province of the European Bronze Age that emerged from evolving Bell Beaker groups in Poland.

bell-beakers-poland-kujawy
Arrival of Bell Beakers in Poland after ca. 2400 BC, and their origin in other BBC centres (Czebreszuk and Szmyt 2011).

I don’t have any hope that the Balto-Slavic evolution through BBC Poland → Mierzanowice/Iwno → Trzciniec → Lusatian cultures is going to be confirmed any time soon, until we have a complete trail of samples to follow all the way to historic Slavs of the Prague culture. However, I do think that the current data on central-east Europe – and the recent data we are receiving from north-east Europe and the Iranian steppes, at odds with the Indo-Slavonic alternative – supports this model.

I guess that, in the end, similar to how the Yamna vs. Corded Ware question is being solved, the real route of expansion of Proto-Balto-Slavic (supposedly spoken ca. 1500-1000 BC) is probably going to be decided by the expansion of either R1a-M458 (from the west) or R1a-Z280 lineages (from the east), because the limited precision of genetic data and analyses available today are going to show ‘modern Slavic’-like populations from the whole eastern half of Europe for the past 4,000 years…

Related

Common pitfalls in human genomics and bioinformatics: ADMIXTURE, PCA, and the ‘Yamnaya’ ancestral component

invasion-from-the-steppe-yamnaya

Good timing for the publication of two interesting papers, that a lot of people should read very carefully:

ADMIXTURE

Open access A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots, by Daniel J. Lawson, Lucy van Dorp & Daniel Falush, Nature Communications (2018).

Interesting excerpts (emphasis mine):

Experienced researchers, particularly those interested in population structure and historical inference, typically present STRUCTURE results alongside other methods that make different modelling assumptions. These include TreeMix, ADMIXTUREGRAPH, fineSTRUCTURE, GLOBETROTTER, f3 and D statistics, amongst many others. These models can be used both to probe whether assumptions of the model are likely to hold and to validate specific features of the results. Each also comes with its own pitfalls and difficulties of interpretation. It is not obvious that any single approach represents a direct replacement as a data summary tool. Here we build more directly on the results of STRUCTURE/ADMIXTURE by developing a new approach, badMIXTURE, to examine which features of the data are poorly fit by the model. Rather than intending to replace more specific or sophisticated analyses, we hope to encourage their use by making the limitations of the initial analysis clearer.

The default interpretation protocol

Most researchers are cautious but literal in their interpretation of STRUCTURE and ADMIXTURE results, as caricatured in Fig. 1, as it is difficult to interpret the results at all without making several of these assumptions. Here we use simulated and real data to illustrate how following this protocol can lead to inference of false histories, and how badMIXTURE can be used to examine model fit and avoid common pitfalls.

admixture-protocol
A protocol for interpreting admixture estimates, based on the assumption that the model underlying the inference is correct. If these assumptions are not validated, there is substantial danger of over-interpretation. The “Core protocol” describes the assumptions that are made by the admixture model itself (Protocol 1, 3, 4), and inference for estimating K (Protocol 2). The “Algorithm input” protocol describes choices that can further bias results, while the “Interpretation” protocol describes assumptions that can be made in interpreting the output that are not directly supported by model inference

Discussion

STRUCTURE and ADMIXTURE are popular because they give the user a broad-brush view of variation in genetic data, while allowing the possibility of zooming down on details about specific individuals or labelled groups. Unfortunately it is rarely the case that sampled data follows a simple history comprising a differentiation phase followed by a mixture phase, as assumed in an ADMIXTURE model and highlighted by case study 1. Naïve inferences based on this model (the Protocol of Fig. 1) can be misleading if sampling strategy or the inferred value of the number of populations K is inappropriate, or if recent bottlenecks or unobserved ancient structure appear in the data. It is therefore useful when interpreting the results obtained from real data to think of STRUCTURE and ADMIXTURE as algorithms that parsimoniously explain variation between individuals rather than as parametric models of divergence and admixture.

For example, if admixture events or genetic drift affect all members of the sample equally, then there is no variation between individuals for the model to explain. Non-African humans have a few percent Neanderthal ancestry, but this is invisible to STRUCTURE or ADMIXTURE since it does not result in differences in ancestry profiles between individuals. The same reasoning helps to explain why for most data sets—even in species such as humans where mixing is commonplace—each of the K populations is inferred by STRUCTURE/ADMIXTURE to have non-admixed representatives in the sample. If every individual in a group is in fact admixed, then (with some exceptions) the model simply shifts the allele frequencies of the inferred ancestral population to reflect the fraction of admixture that is shared by all individuals.

Several methods have been developed to estimate K, but for real data, the assumption that there is a true value is always incorrect; the question rather being whether the model is a good enough approximation to be practically useful. First, there may be close relatives in the sample which violates model assumptions. Second, there might be “isolation by distance”, meaning that there are no discrete populations at all. Third, population structure may be hierarchical, with subtle subdivisions nested within diverged groups. This kind of structure can be hard for the algorithms to detect and can lead to underestimation of K. Fourth, population structure may be fluid between historical epochs, with multiple events and structures leaving signals in the data. Many users examine the results of multiple K simultaneously but this makes interpretation more complex, especially because it makes it easier for users to find support for preconceptions about the data somewhere in the results.

In practice, the best that can be expected is that the algorithms choose the smallest number of ancestral populations that can explain the most salient variation in the data. Unless the demographic history of the sample is particularly simple, the value of K inferred according to any statistically sensible criterion is likely to be smaller than the number of distinct drift events that have practically impacted the sample. The algorithm uses variation in admixture proportions between individuals to approximately mimic the effect of more than K distinct drift events without estimating ancestral populations corresponding to each one. In other words, an admixture model is almost always “wrong” (Assumption 2 of the Core protocol, Fig. 1) and should not be interpreted without examining whether this lack of fit matters for a given question.

admixture-pitfalls
Three scenarios that give indistinguishable ADMIXTURE results. a Simplified schematic of each simulation scenario. b Inferred ADMIXTURE plots at K= 11. c CHROMOPAINTER inferred painting palettes.

Because STRUCTURE/ADMIXTURE accounts for the most salient variation, results are greatly affected by sample size in common with other methods. Specifically, groups that contain fewer samples or have undergone little population-specific drift of their own are likely to be fit as mixes of multiple drifted groups, rather than assigned to their own ancestral population. Indeed, if an ancient sample is put into a data set of modern individuals, the ancient sample is typically represented as an admixture of the modern populations (e.g., ref. 28,29), which can happen even if the individual sample is older than the split date of the modern populations and thus cannot be admixed.

This paper was already available as a preprint in bioRxiv (first published in 2016) and it is incredible that it needed to wait all this time to be published. I found it weird how reviewers focused on the “tone” of the paper. I think it is great to see files from the peer review process published, but we need to know who these reviewers were, to understand their whiny remarks… A lot of geneticists out there need to develop a thick skin, or else we are going to see more and more delays based on a perceived incorrect tone towards the field, which seems a rather subjective reason to force researchers to correct a paper.

PCA of SNP data

Open access Effective principal components analysis of SNP data, by Gauch, Qian, Piepho, Zhou, & Chen, bioRxiv (2018).

Interesting excerpts:

A potential hindrance to our advice to upgrade from PCA graphs to PCA biplots is that the SNPs are often so numerous that they would obscure the Items if both were graphed together. One way to reduce clutter, which is used in several figures in this article, is to present a biplot in two side-by-side panels, one for Items and one for SNPs. Another stratagem is to focus on a manageable subset of SNPs of particular interest and show only them in a biplot in order to avoid obscuring the Items. A later section on causal exploration by current methods mentions several procedures for identifying particularly relevant SNPs.

One of several data transformations is ordinarily applied to SNP data prior to PCA computations, such as centering by SNPs. These transformations make a huge difference in the appearance of PCA graphs or biplots. A SNPs-by-Items data matrix constitutes a two-way factorial design, so analysis of variance (ANOVA) recognizes three sources of variation: SNP main effects, Item main effects, and SNP-by-Item (S×I) interaction effects. Double-Centered PCA (DC-PCA) removes both main effects in order to focus on the remaining S×I interaction effects. The resulting PCs are called interaction principal components (IPCs), and are denoted by IPC1, IPC2, and so on. By way of preview, a later section on PCA variants argues that DC-PCA is best for SNP data. Surprisingly, our literature survey did not encounter even a single analysis identified as DC-PCA.

The axes in PCA graphs or biplots are often scaled to obtain a convenient shape, but actually the axes should have the same scale for many reasons emphasized recently by Malik and Piepho [3]. However, our literature survey found a correct ratio of 1 in only 10% of the articles, a slightly faulty ratio of the larger scale over the shorter scale within 1.1 in 12%, and a substantially faulty ratio above 2 in 16% with the worst cases being ratios of 31 and 44. Especially when the scale along one PCA axis is stretched by a factor of 2 or more relative to the other axis, the relationships among various points or clusters of points are distorted and easily misinterpreted. Also, 7% of the articles failed to show the scale on one or both PCA axes, which leaves readers with an impressionistic graph that cannot be reproduced without effort. The contemporary literature on PCA of SNP data mostly violates the prohibition against stretching axes.

pca-how-to
DC-PCA biplot for oat data. The gradient in the CA-arranged matrix in Fig 13 is shown here for both lines and SNPs by the color scheme red, pink, black, light green, dark green.

The percentage of variation captured by each PC is often included in the axis labels of PCA graphs or biplots. In general this information is worth including, but there are two qualifications. First, these percentages need to be interpreted relative to the size of the data matrix because large datasets can capture a small percentage and yet still be effective. For example, for a large dataset with over 107,000 SNPs for over 6,000 persons, the first two components capture only 0.3693% and 0.117% of the variation, and yet the PCA graph shows clear structure (Fig 1A in [4]). Contrariwise, a PCA graph could capture a large percentage of the total variation, even 50% or more, but that would not guarantee that it will show evident structure in the data. Second, the interpretation of these percentages depends on exactly how the PCA analysis was conducted, as explained in a later section on PCA variants. Readers cannot meaningfully interpret the percentages of variation captured by PCA axes when authors fail to communicate which variant of PCA was used.

Conclusion

Five simple recommendations for effective PCA analysis of SNP data emerge from this investigation.

  1. Use the SNP coding 1 for the rare or minor allele and 0 for the common or major allele.
  2. Use DC-PCA; for any other PCA variant, examine its augmented ANOVA table.
  3. Report which SNP coding and PCA variant were selected, as required by contemporary standards in science for transparency and reproducibility, so that readers can interpret PCA results properly and reproduce PCA analyses reliably.
  4. Produce PCA biplots of both Items and SNPs, rather than merely PCA graphs of only Items, in order to display the joint structure of Items and SNPs and thereby to facilitate causal explanations. Be aware of the arch distortion when interpreting PCA graphs or biplots.
  5. Produce PCA biplots and graphs that have the same scale on every axis.

I read the referenced paper Biplots: Do Not Stretch Them!, by Malik and Piepho (2018), and even though it is not directly applicable to the most commonly available PCA graphs out there, it is a good reminder of the distorting effects of stretching. So for example quite recently in Krause-Kyora et al. (2018), where you can see Corded Ware and BBC samples from Central Europe clustering with samples from Yamna:

NOTE. This is related to a vertical distorsion (i.e. horizontal stretching), but possibly also to the addition of some distant outlier sample/s.

pca-cwc-yamna-bbc
Principal Component Analysis (PCA) of the human Karsdorf and Sorsum samples together with previously published ancient populations projected on 27 modern day West Eurasian populations (not shown) based on a set of 1.23 million SNPs (Mathieson et al., 2015). https://doi.org/10.7554/eLife.36666.006

The so-called ‘Yamnaya’ ancestry

Every time I read papers like these, I remember commenters who kept swearing that genetics was the ultimate science that would solve anthropological problems, where unscientific archaeology and linguistics could not. Well, it seems that, like radiocarbon analysis, these promising developing methods need still a lot of refinement to achieve something meaningful, and that they mean nothing without traditional linguistics and archaeology… But we already knew that.

Also, if this is happening in most peer-reviewed publications, made by professional geneticists, in journals of high impact factor, you can only wonder how many more errors and misinterpretations can be found in the obscure market of so many amateur geneticists out there. Because amateur geneticist is a commonly used misnomer for people who are not geneticists (since they don’t have the most basic education in genetics), and some of them are not even ‘amateurs’ (because they are selling the outputs of bioinformatic tools)… It’s like calling healers ‘amateur doctors’.

NOTE. While everyone involved in population genetics is interested in knowing the truth, and we all have our confirmation (and other kinds of) biases, for those who get paid to tell people what they want to hear, and who have sold lots of wrong interpretations already, the incentives of ‘being right’ – and thus getting involved in crooked and paranoid behaviour regarding different interpretations – are as strong as the money they can win or loose by promoting themselves and selling more ‘product’.

As a reminder of how badly these wrong interpretations of genetic results – and the influence of the so-called ‘amateurs’ – can reflect on research groups, yet another turn of the screw by the Copenhagen group, in the oral presentations at Languages and migrations in pre-historic Europe (7-12 Aug 2018), organized by the Copenhagen University. The common theme seems to be that Bell Beaker and thus R1b-L23 subclades do represent a direct expansion from Yamna now, as opposed to being derived from Corded Ware migrants, as they supported before.

NOTE. Yes, the “Yamna → Corded Ware → Únětice / Bell Beaker” migration model is still commonplace in the Copenhagen workgroup. Yes, in 2018. Guus Kroonen had already admitted they were wrong, and it was already changed in the graphic representation accompanying a recent interview to Willerslev. However, since there is still no official retraction by anyone, it seems that each member has to reject the previous model in their own way, and at their own pace. I don’t think we can expect anyone at this point to accept responsibility for their wrong statements.

So their lead archaeologist, Kristian Kristiansen, in The Indo-Europeanization of Europé (sic):

kristiansen-migrations
Kristiansen’s (2018) map of Indo-European migrations

I love the newly invented arrows of migration from Yamna to the north to distinguish among dialects attributed by them to CWC groups, and the intensive use of materials from Heyd’s publications in the presentation, which means they understand he was right – except for the fact that they are used to support a completely different theory, radically opposed to those defended in Heyd’s model

Now added to the Copenhagen’s unending proposals of language expansions, some pearls from the oral presentation:

  • Corded Ware north of the Carpathians of R1a lineages developed Germanic;
  • R1b borugh [?] Italo-Celtic;
  • the increase in steppe ancestry on north European Bell Beakers mean that they “were a continuation of the Yamnaya/Corded Ware expansion”;
  • Corded Ware groups [] stopped their expansion and took over the Bell Beaker package before migrating to England” [yep, it literally says that];
  • Italo-Celtic expanded to the UK and Iberia with Bell Beakers [I guess that included Lusitanian in Iberia, but not Messapian in Italy; or the opposite; or nothing like that, who knows];
  • 2nd millennium BC Bronze Age Atlantic trade systems expanded Proto-Celtic [yep, trade systems expanded the language]
  • 1st millennium BC expanded Gaulish with La Tène, including a “Gaulish version of Celtic to Ireland/UK” [hmmm, dat British Gaulish indeed].

You know, because, why the hell not? A logical, stable, consequential, no-nonsense approach to Indo-European migrations, as always.

Also, compare still more invented arrows of migrations, from Mikkel Nørtoft’s Introducing the Homeland Timeline Map, going against Kristiansen’s multiple arrows, and even against the own recent fantasy map series in showing Bell Beakers stem from Yamna instead of CWC (or not, you never truly know what arrows actually mean):

corded-ware-migrations
Nørtoft’s (2018) maps of Indo-European migrations.

I really, really loved that perennial arrow of migration from Volosovo, ca. 4000-800 BC (3000+ years, no less!), representing Uralic?, like that, without specifics – which is like saying, “somebody from the eastern forest zone, somehow, at some time, expanded something that was not Indo-European to Finland, and we couldn’t care less, except for the fact that they were certainly not R1a“.

This and Kristiansen’s arrows are the most comical invented migration routes of 2018; and that is saying something, given the dozens of similar maps that people publish in forums and blogs each week.

NOTE. You can read a more reasonable account of how haplogroup R1b-L51 and how R1-Z645 subclades expanded, and which dialects most likely expanded with them.

We don’t know where these scholars of the Danish workgroup stand at this moment, or if they ever had (or intended to have) a common position – beyond their persistent ideas of Yamnaya™ ancestral component = Indo-European and R1a must be Indo-European – , because each new publication changes some essential aspects without expressly stating so, and makes thus everything still messier.

It’s hard to accept that this is a series of presentations made by professional linguists, archaeologists, and geneticists, as stated by the official website, and still harder to imagine that they collaborate within the same professional workgroup, which includes experienced geneticists and academics.

I propose the following video to close future presentations introducing innovative ideas like those above, to help the audience find the appropriate mood:

Related

The Yampil Barrow complex and the Yamna connection with forest-steppe cultures

yamna-diet-pca

Researchers involved in the investigation of the Yampil Barrow Complex are taking the opportunity of their latest genetic paper to publish and upload more papers in Academia.edu.

NOTE. These are from the free volume 22 of Baltic-Pontic Studies, Podolia “Barrow Culture” Communities: 4th/3rd-2nd Mill. BC. The Yampil Barrow Complex: Interdisciplinary Studies, whose website gives a warning depending on your browser (because of the lack of secure connection). Here is a link to the whole PDF.

Here are some of them, with interesting excerpts (emphasis mine):

1. Kurgan rites in the Eneolithic and Early Bronze age Podolia in light of materials from the funerary ceremonial centre at Yampil, by Piotr Włodarczak (2017).

The particular interest in this group stemmed from its specific location within the “Yamnaya cultural-historical entity”: its exposure to Central European Corded ware culture (further as CWC) on the one hand, and discernible contact with communities representing the Globular Amphorae culture (GAC), expanding to the south-east, on the other [e.g. Szmyt 1999; 2000]. The location on the fringes of the north-western variant of the Yamnaya culture (YC) [acc. to Merpert 1974; cf Rassamakin 2013a; 2013b; Rassamakin, Nikolova 2008] opened up an interesting perspective for tracing the transfer of Central European cultural patterns to the North Pontic area, and for determining the specificity of the cultural model of steppe communities, which due to their geographic location seemed somehow predestined for westward expansion.

yampil-barrow-complex
locations of Eneolithic and Early bronze age kurgan cemeteries in Podolia 1-7 – yampil cluster (1 – dobrianka, 2 – Klembivka, 3 – Pidlisivka, 4 – Porohy, 5 – Pysarivka, 6 – Prydnistryanske, 7 – Severynivka), 8-11 – Kamienka cluster (8 – hrustovaia, 9 – Kuzmin, 10 – Ocniţa, 11 – Podoima), 12 – mocra, 13 – Tymkove

Podolia kurgans originate from various stages of the Eneolithic and Early bronze ages, and this chronological diversity is reflected in differences in construction of mounds and central graves for which kurgans were originally built (being burials of the “kurgans’ founders”). These oldest burials link with various Eneolithic and YC communities, and the taxonomic attribution of some of the phenomena discussed here poses difficulties. This stems from the nature of the finds, which are sometimes only slightly distinctive and often retrieved from contexts difficult to interpret (e.g. from kurgans damaged to a significant degree). Another reason for the high discordance and ambiguity of opinions lies in the nature of the problem itself, since taxonomic definitions can be no more than proxies for cultural processes which are both fluid and multi-directional. This is particularly evident for phenomena associated with the Eneolithic and the very beginnings of the Bronze Age in steppe and forest-steppe areas [e.g. Rassamakin 2013; Manzura 2016], while later stages (the classic and late YC) are marked by much more regularity in terms of funeral rituals. Funerary behaviours displayed by Eneolithic steppe groups were the outcome of intercultural relationships and often combined elements borrowed from different milieus [e.g. Rassamakin 2008: 215, 216]. One consequence of this is the multitude of approaches to the description of Eneolithic phenomena proposed in the literature, with the controversies the situation creates. This is also true for the Podolia kurgans discussed here, where chronology is relatively easy to interpret while taxonomical attributions are much more difficult. A good example in this context is a recently published complex at Prydnistryanske, which has been linked either with the late Trypilia group of Gordinești [Klochko et al 2015d] or with the Eneolithic steppe formation known as Zhivotilovka-Volchansk [Manzura 2016], or recently with the Bursuceni group [Demcenko 2016].

A distinct feature of Podolia kurgans having YC burials is the multi-phase nature of their mounds, a feature recorded throughout the North Pontic area. It is particularly evident in the cases of sequences of burials (typically two burials) placed in the central parts of kurgans and connected with separate stages of the mound’s construction. In this context, the temporal and cultural relationship between the older and younger burial becomes a very interesting issue. Younger burials typically revealed traits characteristic of the YC complex, while older ones were often different and distinguished by a different shape of the grave pit and sometimes a different arrangement and orientation of the body as well. In the most evident cases, older pits held a body in the extended position, reminiscent of the Postmariupol/ Kvityana tradition (…). In such cases, the older grave often stands out with a funerary tradition diverging from model YC behaviours, in terms of orientation, body position, and constructional features.

yamna-corded-ware-podolia-yampil
Location of Yampil and Kamienka ceremonial centres, and barrows of the Yamnaya culture, Corded Ware culture, and Late Eneolithic groups of the Podolia Plateau and adjacent areas. Legend. 1 – barrows and barrow groups of the Yamnaya culture; 2 – barrows and barrow groups of the Corded Ware culture; 3 – Eneolithic barrows; 4 – barrows of undetermined cultural attribution, dated to the 3rd millennium BC [after Włodarczak 2014b, revised]

Kvitjana and Trypillia

The Pre-Yamnaya (Eneolithic) phase came to be distinguished in kurgan cemeteries from the Podolie region after the discovery of burials in extended position (i.e. of the Kvityana/Postmariupol type) at Ocniţa (Fig 10: 2, 3) [kurgans 6 and 7; Manzura et al 1992] and Tymkove (Fig 10: 1) [Subbotin et al 2000, 84, ris 3: 4]. In all these three cases the burials marked the oldest phase of mound construction, and later YC burials were dug into the central part of the kurgan, which entailed the remodelling and considerable enlargement of the mound. Both the chronological and taxonomic positions of extended burials in the North Pontic area are subjects of debate [e.g. Manzura 2010; Rassamakin 2013; Ivanova 2015, 280-282] (…)

The chronological position of graves with burials in extended position can be narrowed down thanks to stratigraphic observations made in kurgans at Bursuceni, between the Dniester and Prut rivers [Yarovoy 1978]. Graves from this site were younger than the burials representing the Zhivotilovka-Volchansk tradition and older than those linked with the early phase of YC based on a relatively compact series of radiocarbon dates obtained for graves of the Zhivotilovka-Volchansk group, the chronology of burials in extended position can be determined as the very close of the 4th – beginning of the 3rd millennia BC (most likely around 3100-2800 BC).

Early and late Yamna

A model ceremonial-funerary complex created by a YC community is a group of kurgans in Pysarivka village [harat et al 2014: 104-165]. Nine mounds have been explored there, of which eight (1, 3-9) yielded central burials of YC sharing a number of similar features (Fig 13). The deceased were placed in regular, rectangular pits having vertical walls Vykids (mounds of soil extracted while digging grave pits) formed regular narrow walls surrounding each grave, and seem to have been integral elements of sepulchral architecture. Chambers were covered with 5-7 timbers/planks arranged parallel to the grave’s longer axis. Another characteristic element was that of wooden stakes driven symmetrically into the bottom along grave chamber edges, recorded in four cases. The deceased were laid on their backs, in a contracted position with the knees up. The head was as a rule turned to W, with possible deflections towards NW or SW Skeletons bore traces of painting with ochre.

kurgan-yampil-yamna
Prydnistryanske, Yampil region reconstruction of stages of grave IV/4 construction by M. Podsiadło

The role of south-eastern connections at the early stage of YC development can also be seen in grave IV/4 at Prydnistryanske. This is indicated by a combined (wood and stone) roof construction involving stela-like slabs, and by the skull of the deceased characteristically painted with red pigment. The absolute date obtained for grave IV/4 (ca 3100-3000 bC) suggests its early provenance [Goslar et al 2015]. The grave was most likely connected with the oldest stage of enlargement of the Eneolithic barrow [Klochko et al 2015].

The middle phase of YC is quite clearly evident in Podolia kurgans, it is marked by burials dug into the existing mounds. These are either single burials inserted into different parts of the mounds, or groups of graves forming arches around a central part. Graves with steps leading to the burial chamber are typical of that stage, and they were wider than those in the centres of kurgans. Chambers were typically roofed with planks or timbers placed perpendicularly to the grave’s longer axis burials on one side and burials on the back but leaning to either side become more numerous, and upper limbs were most often placed in A, G, H, or I arrangements ceramic vessels become more common in graves, including forms indicative of contacts with GAC and CWC milieus.


2. The previously announced paper on a specific burial showing postmortem marks: Ritual position and “tattooing” techniques in the funeral practices of the “Barrow cultures” of the Pontic-Caspian steppe/forest-steppe area Porohy 3A, Yampil region, Vinnytsia Oblast: Specialist analysis research perspectives, by Żurkiewicz et al. (2018):

Based on the anatomical properties of the structure of a human body, the histological structure of the skin and location of the dye used for tattooing, having conducted an analysis of postmortem changes occurring within the skin after death, and having taken into consideration the continuous and regular nature of the pattern on the ulnae of the individual from grave no. 10, an interdisciplinary team of researchers has concluded that there is no possibility of a transfer of tattoo dye from the skin onto the surface of an individual’s bone.

The analysis of two ulnae documented in this article indicates that the patterns were made using tree tar, postmortem and directly onto the skeletonised human remains. The placement of the individual’s ulnae in grave no. 10 (Fig. 10), and the location of patterns on the upper skin surface, that is, on surfaces accessible without changing the arrangement of the body, may suggest that the patterns were created on the skeletonised remains without the need to change their placement in the pit (= in situ).

The present conclusions ought to see the beginning of a wider research programme focused on the analysis of the techniques used to create decorations on bones in “kurgan cultures” communities in the context of the Pontic-Caspian Region.

ulna-marks
Porohy, Yampil Region, barrow 3A, feature 10. Macro- and microscopic examination results: 1 – right ulna with visible decorations and close-up of the decoration; 2 – left ulna with visible decorations and close-up of the decoration. Photo by D. Lorkiewicz-Muszyńska

3. Builders and users of ritual centres, Yampil barrow complex: studies of diett based on stable carbon nitrogen isotope composition, by Goslar et al. (2017).

Foxtail millet caryopses are used to make primarily flour, groats and pancakes [lityńska-zając, wasylikowa 2005: 109]. Grains and flour are easily digestible and as such, they are recommended to infants and the elderly. Grains are also fed to fowl and poultry in Asia, foxtail millet is used to make beer and wine, while in China it is also used for medicinal purposes [Hanelt 2001 (Ed )]. Various dishes and beverages made from broomcorn and foxtail millet caryopses in Eurasia are listed by Sakamoto [1987a]. Detailed ethnobotanical studies of the cultivation, crop processing and food preparation in the Iberian Peninsula were presented by Moreno-Larrazabal et al.[2015] .

The geographical area under discussion can be related to historical and ethnographic data indicating the use of grits and groats in the diet. They had been known in the menus of European societies since the ‘pre-agrarian’ times. The isotope finding of millet domination in the diet of middle Dniester Yampil Barrow Complex, complemented by bioarchaeological data from the upper steppe Dniester area (from the similarly ‘early-barrow’ Usatovo group/culture with strongly marked ‘eastern’ civilization influences), makes it reasonable to consider the possibility that already in the prologue of late Eneolithic-Early bronze barrow culture (3300- 2800 BC) development there was a clear dividing line of millet groats use – or millet presence – that is, so-called yagla groats (yagla, yagly = millet in Old Slavic languages).

correlation-diet-dereivka-isotopic
Composition of stable carbon and nitrogen isotopes in bone collagen from the Yampil Barrow Complex against the ranges of isotopic composition expected for various diet components [after Gerling 2015: Fig 6 16] The meaning of colours and symbols concerning the Yampil Barrow Complex is the same as in Fig 3 For the sake of comparison, the isotopic composition in human >bones from two sites on the dnieper (ca 5200-5000 bC) is given, in which the share of freshwater fish in the diet was confirmed by the measurements of the reservoir effect [lillie et al. 2009]

Related

Minimal Corded Ware culture impact in Scandinavia – Bell Beakers the unifying maritime elite

copper-age-late-bell-beaker

Chapter The Sea and Bronze Age Transformations, by Christopher Prescott, Anette Sand-Eriksen, and Knut Ivar Austvoll, In: Water and Power in Past Societies (2018), Emily Holt, Proceedings of the IEMA Postdoctoral Visiting Scholar Conference on Theories and Methods in Archaeology, Vol. 6.

NOTE. You can download the chapter draft at Academia.edu.

Abstract (emphasis mine):

Along the western Norwegian coast, in the northwestern region of the Nordic Late Neolithic and Bronze Age (2350–500 BCE) there is cultural homogeneity but variable expressions of political hierarchy. Although new ideological institutions, technology (e.g., metallurgy and boat building), intensified agro‑pastoral farming, and maritime travel were introduced throughout the region as of 2350 BCE, concentrations of expressions of Bronze Age elites are intermittently found along the coast. Four regions—Lista, Jæren, Karmøy, and Sunnmøre—are examined in an exploration of the establishment and early role of maritime practices in this Nordic region. It is argued that the expressions of power and material wealth concentrated in these four regions is based on the control of bottlenecks, channels, portages, and harbors along important maritime routes of travel. As such, this article is a study of prehistoric travel, sources of power, and maritime landscapes in the Late Neolithic and Early Bronze Age of Norway.

Interesting excerpts:

(…)The [Corded Ware culture (CWC)] in Norway (or Battle Axe Culture, 2750–2400/2350 BCE) is primarily represented in Eastern Norway, with a patchy settlement pattern along the Oslo fjord’s coast through the inland valleys to Trøndelag in Central Norway (Hinsch 1956). The CWC represents an enigmatic period in Norwegian prehistory (Hinsch 1956; Østmo 1988:227–231; Prescott and Walderhaug 1995; Shetelig 1936); however the data at the moment suggests the following patterns:

  • Migration: The CWC was the result of a small‑scale immigration, but did not trigger substantial change.
  • Eastern and limited impact: The CWC was primarily located in small settlement patches in eastern Norway.
  • Terrestrial: In terms of maritime practices, the CWC does not represent a significant break from older traditions, though it seems to have a more pronounced terrestrial bearing. It is conceivable that pastures and hunting grounds were a more important political‑economic resource than waterways.

The mid‑third millennium in Norway, around 2400 BCE, represents a significant reorientation. Bell Beaker Culture (BBC) settlements in western Denmark and Norway archaeologically mark the instigation of the Nordic LN, though much of the historical process leading from the Bell Beaker to the Late Neolithic, 2500 to 2350 BCE, remains unclear (Prescott 2012; Prescott and Melheim 2009; Prieto‑Martinez 2008:116; Sarauw 2007:66; Vandkilde 2001, 2005). Still, the outcome is the establishment of the Nordic region of interaction in the Baltic, Northern Germany, Sweden, Denmark, and Norway. The distribution of artifact materials such as Bell Beakers and flint daggers attests to the far‑flung network of regular exchange and communication. This general region of interaction was reproduced through the Late Neolithic and Bronze Age.

nordic-late-neolithic
The Nordic region in the Late Neolithic and Bronze Age. Sites and regions discussed in the text are marked (ater Prescott and Glørstad 2015:fig. 1).

The transition from the preceding Neolithic period hunter‑gatherer societies was rapid and represents a dramatic termination of hunter‑gatherer traditions. It has been argued that the transformation is tied to initial migrations of people to the western coast of Norway from BBC areas, possibly from northern Jutland (Prescott 2011; Prescott and Walderhaug 1995:273). Bifacial tanged‑and‑barbed points, often referred to as “Bell Beaker points,” probably represent an early, short phase of the BBC‑transition around 2400 BCE. In Norway these points have a predominantly western and coastal distribution (Østmo 2012:64), underscoring the maritime nature of the initial BBC‑expansion.

late-neolithic-flint-daggers
Distribution routes for LN1 flint daggers type 1 suggesting communication routes and networks. (Redrawn after fig. 9, Apel 2001:17).

(…) In response to the question about what attracted people from Bell Beaker groups to western Norway, responses have hypothesized hunting products, political power, pastures, and metals. Particularly the latter has been emphasized by Lene Melheim (2012, 2015:37ff).

A recent study by Melheim and Prescott (2016) integrated maritime exploration with metal prospecting to explain initial excursions of BBC‑people along the western coast and into the fjords. Building on the archaeological concept of traveling metal prospectors as an element in the expansion of the Bell Beaker phenomenon, in combination with anthropological perspectives on prospecting, the article explores how prospecting for metal would have adjusted to the landscapes of western Scandinavia. Generally speaking, prospecting seldom leads to successful metal production, and it is difficult to study archaeologically. However, it will often create links between the prospectors’ society and indigenous groups, opening new territories, and have a significant transformative impact—on both the external and indigenous actors and societies.

While the text echoes the traditional idea that Corded Ware spread Indo-European languages, Prescott (since Prescott and Walderhaug 1995) is a supporter of the formation of a Nordic community and a Nordic (i.e. Pre-Germanic) language with the arrival of Bell Beakers.

An identification of the Corded Ware language as of a previous Proto-Indo-European stage is possible, as I have previously said (although my preference is Uralic-related languages).

This CWC language would thus still form the common substrate to both Germanic and Balto-Slavic, both being North-West Indo-European dialects, which spread with Bell Beakers over previous Corded Ware territory.

NOTE. This pre-LPIE nature could be in turn related to Kortlandt’s controversial proposal of an ealier PIE dative *-mus shared by both branches. However, that would paradoxically be against Kortlandt’s own assumption that the substrate was in fact of a non-Indo-European nature

See also: