Human ancestry solves language questions? New admixture citebait

human_ancestry

A paper at Scientific Reports, Human ancestry correlates with language and reveals that race is not an objective genomic classifier, by Baker, Rotimi, and Shriner (2017).

Abstract (emphasis mine):

Genetic and archaeological studies have established a sub-Saharan African origin for anatomically modern humans with subsequent migrations out of Africa. Using the largest multi-locus data set known to date, we investigated genetic differentiation of early modern humans, human admixture and migration events, and relationships among ancestries and language groups. We compiled publicly available genome-wide genotype data on 5,966 individuals from 282 global samples, representing 30 primary language families. The best evidence supports 21 ancestries that delineate genetic structure of present-day human populations. Independent of self-identified ethno-linguistic labels, the vast majority (97.3%) of individuals have mixed ancestry, with evidence of multiple ancestries in 96.8% of samples and on all continents. The data indicate that continents, ethno-linguistic groups, races, ethnicities, and individuals all show substantial ancestral heterogeneity. We estimated correlation coefficients ranging from 0.522 to 0.962 between ancestries and language families or branches. Ancestry data support the grouping of Kwadi-Khoe, Kx’a, and Tuu languages, support the exclusion of Omotic languages from the Afroasiatic language family, and do not support the proposed Dené-Yeniseian language family as a genetically valid grouping. Ancestry data yield insight into a deeper past than linguistic data can, while linguistic data provide clarity to ancestry data.

Regarding European ancestry:

Southern European ancestry correlates with both Italic and Basque speakers (r = 0.764, p = 6.34 × 10−49). Northern European ancestry correlates with Germanic and Balto-Slavic branches of the Indo-European language family as well as Finno-Ugric and Mordvinic languages of the Uralic family (r = 0.672, p = 4.67 × 10−34). Italic, Germanic, and Balto-Slavic are all branches of the Indo-European language family, while the correlation with languages of the Uralic family is consistent with an ancient migration event from Northern Asia into Northern Europe. Kalash ancestry is widely spread but is the majority ancestry only in the Kalash people (Table S3). The Kalasha language is classified within the Indo-Iranian branch of the Indo-European language family.

Sure, admixture analysis came to save the day. Yet again. Now it’s not just Archaeology related to language anymore, it’s Linguistics; all modern languages and their classification, no less. Because why the hell not? Why would anyone study languages, history, archaeology, etc. when you can run certain algorithms on free datasets of modern populations to explain everything?

What I am criticising here, as always, is not the study per se, its methods (PCA, the use of Admixture or any other tools), or its results, which might be quite interesting – even regarding the origin or position of certain languages (or more precisely their speakers) within their linguistic groups; it’s the many broad, unsupported, striking conclusions (read the article if you want to see more wishful thinking).

This is obviously simplistic citebait – that benefits only journals and authors, and it is therefore tacitly encouraged -, but not knowledge, because it is not supported by any linguistic or archaeological data or expertise.

Is anyone with a minimum knowledge of languages, or general anthropology, actually reviewing these articles?

Related:

Featured image: Ancestry analysis of the global data set, from the article.

Neolithic and Bronze Age Basque-speaking Iberians resisted invaders from the steppe

gaul-asterix

Good clickbait, right? I have received reports about this new paper in Google Now the whole weekend, and their descriptions are getting worse each day.

The original title of the article published in PLOS Genetics (already known by its preprint in BioRxiv) was The population genomics of archaeological transition in west Iberia: Investigation of ancient substructure using imputation and haplotype-based methods, by Martiniano et al. (2017).

Maybe the title was not attractive enough, so they sent the following summary, entitled “Bronze Age Iberia received fewer Steppe invaders than the rest of Europe” (also in Phys.org. From their article, the only short reference to the linguistic situation of Iberia (as a trial to sum up potential consequences of the genetic data obtained):

Iberia is unusual in harbouring a surviving pre-Indo-European language, Euskera, and inscription evidence at the dawn of history suggests that pre-Indo-European speech prevailed over a majority of its eastern territory with Celtic-related language emerging in the west. Our results showing that predominantly Anatolian-derived ancestry in the Neolithic extended to the Atlantic edge strengthen the suggestion that Euskara is unlikely to be a Mesolithic remnant. Also our observed definite, but limited, Bronze Age influx resonates with the incomplete Indo-European linguistic conversion on the peninsula, although there are subsequent genetic changes in Iberia and defining a horizon for language shift is not yet possible. This contrasts with northern Europe which both lacks evidence for earlier language strata and experienced a more profound Bronze Age migration.

Judging from the article, more precise summaries of potential consequences would have been “Proto-Basque and Proto-Iberian peoples derived from Neolithic farmers, not Mesolithic or Palaeolithic hunter-gatherers”, or “incomplete Indo-European linguistic conversion of the Iberian Peninsula” – both aspects, by the way, are already known. That would have been quite unromantic, though.

Their carefully selected title has been unsurprisingly distorted at least as “Ancient DNA Reveals Why the Iberian Peninsula Is So Unique“, and “Ancient Iberians resisted Steppe invasions better than the rest of Europe 6,000 years ago“.

So I thought, what the hell, let’s go with the tide. Using the published dataset, I have also helped reconstruct the original phenotype of Bronze Age Iberians, and this is how our Iberian ancestors probably looked like:

Typical Iberian village during the Steppe invasion, according to my phenotype study of Martiniano et al. (2017). Notice typical invaders to the right.

And, by the way, they spoke Basque, the oldest language. Period.

Now, for those new to the article, we already knew that there is less “steppe admixture” in Iberian samples from southern Portugal after the time of east Bell Beaker expansion.

portugal-bronze-age-admixture
(A) PCA estimated from the CHROMOPAINTER coancestry matrix of 67 ancient samples ranging from the Paleolithic to the Anglo-Saxon period. The samples belonging to each one of the 19 populations identified with fineSTRUCTURE are connected by a dashed line. Samples are placed geographically in 3 panels (with random jitter for visual purposes): (B) Hunter-gatherers; (C) Neolithic Farmers (including Ötzi) and (D) Copper Age to Anglo-Saxon samples. The Portuguese Bronze Age samples (D, labelled in red) formed a distinct population (Portuguese_BronzeAge), while the Middle and Late Neolithic samples from Portugal clustered with Spanish, Irish and Scandinavian Neolithic farmers, which are termed “Atlantic_Neolithic” (C, in green).

However, there is also a clear a discontinuity in Neolithic Y-DNA haplogroups (to R1b-P312 haplogroups). That means obviously a male-driven invasion, from the North-West Indo-European-speaking Bell Beaker culture – which in turn did not have much “steppe admixture” compared to other north-eastern cultures, like the Corded Ware culture, probably unrelated to Indo-European languages.

portugal-bronze-age-haplogroup
Summary of the samples sequenced in the present study.

As always, trying to equate steppe or Yamna admixture with invasion or language is plainly wrong. Doing it with few samples, and with the wrong assumptions of what “steppe admixture” means, well…

Proto-Basque and Proto-Iberian no doubt survived the Indo-European Bell Beaker migrations, but if Y-DNA lineages were replaced already by the Bronze Age in southern Portugal, there is little reason to support an increased “resistance” of Iberians to Bell Beaker invaders compared to other marginal regions of Europe (relative to the core Yamna expansion in eastern and central Europe).

As you know, Aquitanian (the likely ancestor of Basque) and Iberian were just two of the many non-Indo-European languages spoken in Europe at the dawn of historical records, so to speak about Iberia as radically different than Italy, Greece, Northern Britain, Scandinavia, or Eastern Europe, is reminiscent of the racism (or, more exactly, xenophobia) that is hidden behind romantic views certain people have of their genetic ancestry.

Some groups formed by a majority of R1b-DF27 lineages, now prevalent in Iberia, spoke probably Iberian languages during the Iron Age in north and eastern Iberia, before their acculturation during the expansion of Celtic-speaking peoples, and later during the expansion of Rome, when most of them eventually spoke Latin. In Mediaeval times, these lineages probably expanded Romance languages southward during the Reconquista.

Before speaking Iberian languages, R1b-DF27 lineages (or older R1b-P312) were probably Indo-European speakers who expanded with the Bell Beaker culture from the lower Danube – in turn created by the interaction of Yamna with Proto-Bell Beaker cultures, and adopted probably the native Proto-Basque and Proto-Iberian languages (or possibly the ancestor of both) near the Pyrenees, either by acculturation, or because some elite invaders expanded successfully (their Y-DNA haplogroup) over the general population, for generations.

Maybe some kind of genetic bottleneck happened, that expanded previously not widespread lineages, as with N1c subclades in Finland.

There is nothing wrong with hypothetic models of ancient genetic prehistory: there are still too many potential scenarios for the expansion of haplogroup R1b-DF27 in Iberia. But, please, stop supporting romantic pictures of ethnolinguistic continuity for modern populations. It’s embarrassing.


Featured image from Wikipedia, and Pinterest, with copyright from Albert Uderzo and publisher company Hachette.

Images from the article, licensed CC-by-sa, as all articles from PLOS.

How to do modern phylogeography: Relationships between clans and genetic kin explain cultural similarities over vast distances

yakut-phylogeography

A preprint paper has been published in BioRxiv, Relationships between clans and genetic kin explain cultural similarities over vast distances: the case of Yakutia, by Zvenigorosky et al (2017).

Abstract:

Archaeological studies sample ancient human populations one site at a time, often limited to a fraction of the regions and periods occupied by a given group. While this bias is known and discussed in the literature, few model populations span areas as large and unforgiving as the Yakuts of Eastern Siberia. We systematically surveyed 31,000 square kilometres in the Sakha Republic (Yakutia) and completed the archaeological study of 174 frozen graves, assembled between the 15th and the 19th century. We analysed genetic data (autosomal genotypes, Y-chromosome haplotypes and mitochondrial haplotypes) for all ancient subjects and confronted it to the study of 190 modern subjects from the same area and the same population. Ancient familial links and paternal clan were identified between graves up to 1500 km apart and we provide new data concerning the origins of the contemporary Yakut population and demonstrate that cultural similarities in the past were linked to (i) the expansion of specific paternal clans, (ii) preferential marriage among the elites and (iii) funeral choices that could constitute a bias in any ancient population study.

Even if you are not interested in the cultural and anthropological evolution of this Turkic-speaking people of the Russian Far Eastern region, the method used is an excellent example of how to use archaeology and genetics (especially Y-DNA and mtDNA data) to obtain meaningful results when investigating ancient populations.

For quite some time, probably since the first renown admixture analyses of ancient DNA samples were published, we have been living under the impression that phylogeography, or simply archaeogenetics as it was called back in the day, is not needed.

Cavalli-Sforza’s assertion that the study of modern populations could offer a clear picture of past population movements is now considered wrong, and the study of Y-DNA and mtDNA haplogroups is today mostly disregarded as of secondary importance, even among geneticists. Whole genomic investigation (and especially admixture analyses) have been leading the new wave of overconfidence in genetic results, tightly joint with the ignorance of its shortcomings (and commercial interests based on desires of ethnic identification), and haplogroups are usually just reported with other, not entirely meaningful aspects of ancient DNA analyses.

While it is undeniable that admixture analyses are offering quite interesting results, they must be carefully balanced against known archaeological and linguistic knowledge. Phylogeography – and especially Y-DNA haplogroup assessment – is quite interesting in investigating kinship and clans in patrilocal communities – i.e. most communities in prehistoric and historic periods, unless proven otherwise.

Luckily enough, there are those researchers who still strive to obtain meaningful information from haplotypes. The article referenced in this post is quite interesting due to its phylogeographic method’s applicability to ancient cultures and peoples.

When some geneticists look at simplistic prehistoric maps, like those depicting Yamna, Afanasevo, Corded Ware, and Bell Beaker cultures together, they forget that 1) cultural regions are selected more or less arbitrarily (we only have certain scattered sites for each of these cultures); 2) economic or population contacts are difficult to ascertain and to represent graphically; and 3) time periods for archaeological sites are important – in fact, they are probably THE most important aspect in assessing how accurate a map (and its “arrows” of migration or exchange) represents reality.

A careful, detailed study like this one, if applied to the Pontic-Caspian steppe, would probably reveal how R1b subclades dominated steppe clans, beginning at least during the Suvorovo-Novodanilovka expansion to the west, and certainly representing the vast majority of lineages during the internal expansion in the Early Yamna period and its later expansion east and west of the steppe…

Featured image from the article, summing up Geography, Archaeology, and Genetics of Yakutia – including Y-DNA and mtDNA haplogroups from ancient populations.

Related:

New pre-print papers on ancient and modern population genetics

phenotype-height

Two pre-print papers reposted or published recently, interesting for the genetic analysis of ancient and modern populations (emphasis mine):

Assessing the relationship of ancient and modern populations, by Joshua G Schraiber (2017) Abstract:

Genetic material sequenced from ancient samples is revolutionizing our understanding of the recent evolutionary past. However, ancient DNA is often degraded, resulting in low coverage, error-prone sequencing. Several solutions exist to this problem, ranging from simple approach such as selecting a read at random for each site to more complicated approaches involving genotype likelihoods. In this work, we present a novel method for assessing the relationship of an ancient sample with a modern population while accounting for sequencing error by analyzing raw read from multiple ancient individuals simultaneously. We show that when analyzing SNP data, it is better to sequencing more ancient samples to low coverage: two samples sequenced to 0.5x coverage provide better resolution than a single sample sequenced to 2x coverage. We also examined the power to detect whether an ancient sample is directly ancestral to a modern population, finding that with even a few high coverage individuals, even ancient samples that are very slightly diverged from the modern population can be detected with ease. When we applied our approach to European samples, we found that no ancient samples represent direct ancestors of modern Europeans. We also found that, as shown previously, the most ancient Europeans appear to have had the smallest effective population sizes, indicating a role for agriculture in modern population growth.

Polygenic Adaptation has Impacted Multiple Anthropometric Traits, by Jeremy J Berg, Xinjun Zhang, and Graham Coop (2017). Abstract:

Most of our understanding of the genetic basis of human adaptation is biased toward loci of large phenotypic effect. Genome wide association studies (GWAS) now enable the study of genetic adaptation in highly polygenic phenotypes. Here we test for polygenic adaptation among 187 world- wide human populations using polygenic scores constructed from GWAS of 34 complex traits. By comparing these polygenic scores to a null distribution under genetic drift, we identify strong signals of selection for a suite of anthropometric traits including height, infant head circumference (IHC), hip circumference (HIP) and waist-to-hip ratio (WHR), as well as type 2 diabetes (T2D). In addition to the known north-south gradient of polygenic height scores within Europe, we find that natural selection has contributed to a gradient of decreasing polygenic height scores from West to East across Eurasia, and that this gradient is consistent with selection on height in ancient populations who have contributed ancestry broadly across Eurasia. We find that the signal of selection on HIP can largely be explained as a correlated response to selection on height. However, our signals in IHC and WC/WHR cannot, suggesting a response to selection along multiple axes of body shape variation. Our observation that IHC, WC, and WHR polygenic scores follow a strong latitudinal cline in Western Eurasia support the role of natural selection in establishing Bergmann’s Rule in humans, and are consistent with thermoregulatory adaptation in response to latitudinal temperature variation.

Featured image from the second article: Polygenic Height Scores for 187 population samples (combined Human origin panel and 1000 genomes datasets), plotted on geographic coordinates. Blue corresponds to populations with the “tallest” polygenic height scores, and yellow the “shortest”.

Indo-European and Central Asian admixture in Indian population, dependent on ethnolinguistic and geodemographic divisions

indian-population-genetics

Preprint paper at BioRxiv, Dissecting Population Substructure in India via Correlation Optimization of Genetics and Geodemographics, by Bose et al. (2017), a mixed group from Purdue University and IBM TJ Watson Research Center. A rather simple paper, which is nevertheless interesting in its approach to the known multiple Indian demographic divisions, and in its short reported methods and results.

Abstract:

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification operating in concert. To date, no study has attempted to model and evaluate how these evolutionary forces have interacted to shape the patterns of genetic diversity within India. Geography has been shown to closely correlate with genetic structure in other parts of the world. However, the strict endogamy imposed by the Indian caste system, and the large number of spoken languages add further levels of complexity. We merged all publicly available data from the Indian subcontinent into a data set of 835 individuals across 48,373 SNPs from 84 well-defined groups. Bringing together geography, sociolinguistics and genetics, we developed COGG (Correlation Optimization of Genetics and Geodemographics) in order to build a model that optimally explains the observed population genetic sub-structure. We find that shared language rather than geography or social structure has been the most powerful force in creating paths of gene flow within India. Further investigating the origins of Indian substructure, we create population genetic networks across Eurasia. We observe two major corridors towards mainland India; one through the Northwestern and another through the Northeastern frontier with the Uygur population acting as a bridge across the two routes. Importantly, network, ADMIXTURE analysis and f3 statistics support a far northern path connecting Europe to Siberia and gene flow from Siberia and Mongolia towards Central Asia and India.

Among the most interesting results (emphasis mine):

Our meta-analysis of the ADMIXTURE output shows that the IE and DR populations across castes shared very high ancestry, indicating the autochthonous origin of the caste system in India (Figure 2). f3 statistics show that most of the castes and tribes in India are admixed, with contributions from other castes and/or tribes, across languages affiliations (Supplementary Table 4 and Supplementary Note). The geographically isolated Tibeto-Burman tribes and the Dravidian speaking tribes appear to be the most isolated in India. Linear Discriminant Analysis on the normalized data set clearly supports genetic strati cation by castes and languages in the Indian sub-continent

(…)

Our meta-analysis of the ADMIXTURE plot in Figure 4A quantifies the ADMIXTURE results (darker colors indicate higher pairwise shared ancestry). Indian populations show a greater proportion of shared ancestry with the so-called Indian Northwestern Frontier populations, namely the tribal populations spanning Afghanistan and Pakistan. Central Asian populations share higher degrees of ancestry with IE and DR Froward castes. Uygurs share high degrees of ancestry with Indian populations.

(…)

f3 statistics (all negative Z-scores are shown) indicate Chinese and Siberian ancestry contributing to the Tibeto-Burman tribal speakers. On the other hand, the Mongols and the Europeans have contributed significant amounts of ancestry to the Indo-European and Tibeto-Burman forward castes. F3 statistics also show that the Central Asians are an admixed population with signs of admixture from Caucasus and other parts of Europe.

Among the results for proportions of shared ancestry between Indians and Eurasians (FIG. 4), there is an obvious influence of European admixture (Caucasus, and Southern, Central, and Northern EU), potentially from the Yamna-Corded Ware expansion, in IE_ForwardCaste, which is lessened in IE_BackwardCaste and also in IE_Tribal, while DR_ForwardCaste shows again more admixture than IE_Tribal, but diminishing with lower castes and quite low in DR_Tribal.

Ancestry from Central Asia is strong with a similar pattern, which hints at the influence of Sintashta, Andronovo, and BMAC influence in the expansion of the Steppe component, even more than a later Turkic component.

On the other hand, the influence from Turkey is difficult to assess, given the complex genetic history of Anatolia, but the map contained in Fig. 6 doesn’t feel right, not only from a genetic viewpoint, but also from linguistic and archaeological points of view. This is the typical map created with admixture analyses that is wrong because of not taking into account anthropological theories.

Quite interesting is then the influence of admixture in these different ethnolinguistic groups, Indo-European and Dravidic, which points to an initially greater expansion of Indo-European speakers, and later resurge of Dravidian languages.

Featured image contains simplified origin and data of samples studied, from the article.

Related:

My European Family: The First 54,000 years, by Karin Bojs

steppe-expansion-corded-ware

I have recently read the book My European Family: The First 54,000 years (2015), by Karin Bojs, a known Swedish scientific journalist, former science editor of the Dagens Nyheter.

my-european-family
My European Family: The First 54,000 Years
It is written in a fresh, dynamic style, and contains general introductory knowledge to Genetics, Archaeology, and their relation to language, and is written in a time of great change (2015) for the disciplines involved.

The book is informed, it shows a balanced exercise between responsible science journalism and entertaining content, and it is at times nuanced, going beyond the limits of popular science books. It is not written for scholars, although you might learn – as I did – interesting details about researchers and institutions of the anthropological disciplines involved. It contains, for example, interviews with known academics, which she uses to share details about their personalities and careers, which give – in my opinion – a much needed context to some of their publications.

Since I am clearly biased against some of the findings and research papers which are nevertheless considered mainstream in the field (like the identification of haplogroup R1a with the Proto-Indo-European expansion, or the concept of steppe admixture), I asked my wife (who knew almost nothing about genetics, or Indo-European studies) to read it and write a summary, if she liked it. She did. So much, that I have convinced her to read The Horse, the Wheel, and Language: How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World (2007), by David Anthony.

Here is her summary of the book, translated from Spanish:

The book is divided in three main parts: The Hunters, The Farmers, and The Indo-Europeans, and each has in turn chapters which introduce and break down information in an entertaining way, mixing them with recounts of her interactions and personal genealogical quest.

Part one, The Hunters, offers intriguing accounts about the direct role music had in the development of the first civilizations, the first mtDNA analyses of dogs (Savolainen), and the discovery of the author’s Saami roots. Explanations about the first DNA studies and their value for archaeological studies are clear and comprehensible for any non-specialized reader. Interviews help give a close view of investigations, like that of Frederic Plassard’s in Les Combarelles cave.

Part two, The Farmers, begins with her travel to Cyprus, and arouses the interest of the reader with her description of the circular houses, her notes on the Basque language, the new papers and theories related to DNA analyses, the theory of the decision of cats to live with humans, the first beers, and the houses built over graves. Karin Bojs analyses the subgroup H1g1 of her grandmother Hilda, and how it belonged to the first migratory wave into Central Europe. This interest in her grandmother’s origins lead her to a conference in Pilsen about the first farmers in Europe, where she knows firsthand of the results of studies by János Jakucs, and studies of nuclear DNA. Later on she interviews Guido Brandt and Joachim Burguer, with whom she talks about haplogroups U, H, and J.

The chapter on Ötzi and the South Tyrol Museum of Archaeology (Bolzano) introduces the reader to the first prehistoric individual whose DNA was analysed, belonging to haplogroup G2a4, but also revealing other information on the Iceman, such as his lactose intolerance.

Part three, dealing with the origin of Indo-Europeans, begins with the difficulties that researchers have in locating the origin of horse domestication (which probably happened in western Kazakhstan, in the Russian steppe between the rivers Volga and Don). She mentions studies by David Anthony and on the Yamna culture, and its likely role in the diffusion of Proto-Indo-European. In an interview with Mallory in Belfast, she recalls the potential interest of far-right extremists in genetic studies (and early links of the Journal of Indo-European Studies to certain ideology), as well as controversial statements of Gimbutas, and her potentially biased vision as a refugee from communist Europe. During the interview, Mallory had a copy of the latest genetic paper sent to Nature Magazine by Haak et al., not yet published, for review, but he didn’t share it.

Then haplogroups R1a and R1b are introduced as the most common in Europe. She visits the Halle State Museum of Prehistory (where the Nebra sky disk is exhibited), and later Krakow, where she interviews Slawomir Kadrow, dealing with the potential creation of the Corded Ware culture from a mix of Funnelbeaker and Globular Amphorae cultures. New studies of ancient DNA samples, published in the meantime, are showing that admixture analyses between Yamna and Corded Ware correlate in about 75%.

In the following chapters there is a broad review of all studies published to date, as well as individuals studied in different parts of Europe, stressing the importance of ships for the expansion of R1b lineages (Hjortspring boat).

The concluding chapter is dedicated to vikings, and is used to demystify them as aggressive warmongers, sketching their relevance as founders of the Russian state.

To sum up, it is a highly documented book, written in a clear style, and is capable of awakening the reader’s interest in genetic and anthropological research. The author enthusiastically looks for new publications and information from researchers, but is at the same time critic with them, showing often her own personal reactions to new discoveries, all of which offers a complex personal dynamic often shared by the reader, engaged with her first-person account the full length of the book.

Mayte Batalla (July 2017)

DISCLAIMER: The author sent me a copy of the book (a translation into Spanish), so there is a potential conflict of interest in this review. She didn’t ask for a review, though, and it was my wife who did it.