Spread of Y. pestis, earlier than previously thought, may have caused Neolithic decline


Open access Emergence and Spread of Basal Lineages of Yersinia pestis during the Neolithic Decline, by Rascovan et al. Cell (2018)

Abstract (emphasis mine):

Between 5,000 and 6,000 years ago, many Neolithic societies declined throughout western Eurasia due to a combination of factors that are still largely debated. Here, we report the discovery and genome reconstruction of Yersinia pestis, the etiological agent of plague, in Neolithic farmers in Sweden, pre-dating and basal to all modern and ancient known strains of this pathogen. We investigated the history of this strain by combining phylogenetic and molecular clock analyses of the bacterial genome, detailed archaeological information, and genomic analyses from infected individuals and hundreds of ancient human samples across Eurasia. These analyses revealed that multiple and independent lineages of Y. pestis branched and expanded across Eurasia during the Neolithic decline, spreading most likely through early trade networks rather than massive human migrations. Our results are consistent with the existence of a prehistoric plague pandemic that likely contributed to the decay of Neolithic populations in Europe.

(A) Schematic representation of the trajectories and time periods (thousand years before present, kyr) of major known human migrations in Eurasia during the Neolithic and Bronze Age. The observed geographic distribution and divergence times of Y. pestis strains from the Gok2 and Bronze Age clades cannot be explained by the timings and routes of these human movements.
(B) Geographic distribution of the use of animal traction and wheeled transport across Neolithic and Bronze Age populations in Eurasia, which broadly expanded during the period of 5,500 and 5,000 BP. The expansion of these technological innovations overlaps the predicted period for the expansion of the basal Y. pestis strains.
(C) Timeline indicating the proposed key historical events that contributed to the emergence and spread of plague during the Neolithic.

We have evolved in the interpretation of the plague from 1) a Corded Ware-driven disease, to 2) a steppe disease that was spread by Yamna and Corded Ware, and now 3) a (potentially) Trypillia-driven disease that spread to the west earlier than Yamna and Corded Ware, but probably also later east and west with both.

At least it still seems that the plague and its demographic consequences were a good reason for the expansion of Indo-Europeans and Uralians into Europe, as we thought…

Featured image, from the paper: “The predicted model of early dispersion of Y. pestis during Neolithic and Bronze Age was built by integrating phylogenetic information of Y. pestis strains from this period (Figure 1E), their divergence times (Figure 3), the geographic locations, carbon dating and genotypes of the individuals, and the archaeological record. The model suggests that early Y. pestis strains likely emerged and spread from mega-settlements in Eastern Europe (built by the Trypillia Culture) into Europe and the Eurasian steppe, most likely through human interaction networks. This was facilitated by wheeled and animal-powered transports, which are schematized in the map with red lines with arrows pointing in both senses. Our model builds upon a previous model (Andrades Valtuena et al., 2017) that proposed the spread of plague to be associated with large-scale human migrations (blue line).


Eastern pressure blade technology in west Scandinavia associated with WHG

New interesting preprint Ancient DNA from chewing gums connects material culture and genetics of Mesolithic hunter-gatherers in Scandinavia, by Kashuba et al. (2018).

Interesting excerpts (emphasis mine):

Mitochondrial genomes from all three individuals belong to the U5a2d haplogroup. (…) The mitochondrial U5a2d haplogroup is consistent with earlier published results for ancient individuals from Scandinavia, U5a being the most common within SHG. Of the 16 Mesolithic individuals from Scandinavia published prior to our study, seven belong to the U5a haplogroup, nine share the U2 and U4 haplogroups

We divided the SHG group into two groups: SHGa and SHGb (ancient individuals found in contemporary Norway and Sweden, respectively). We based this on both the geographical distribution and the previous studies demonstrating the close relation of SHGa to EHG group and SHGb to WHG group. To further explore the demography within the SHG group, we compared the ancestry of BLE individuals within SHGa and SHGb groups. This comparison revealed a high relative shared drift between BLE individuals and the SHGb group

Admixture analysis showing the major mode for K=15. The figure represents 11 runs out of 20 replicates (Greedy algorithm ran with the Jaccard distance and a 0.97 similarity threshold)

The results from Huseby Kiev allow us to finally connect the SHG group with the eastern pressure blade technology. However, the higher genetic affinity between Huseby Kiev individuals and the WHG group challenges the earlier suggested tie between eastern technology and EHG genetics. Our results suggest either early cultural transmission, or a more complex course of events involving both non- and co-dependent cultural and genetic admixture.


Seeing how culture is indeed usually associated with the expansion of a certain population, especially at such an early date, I guess this similarity with WHG of incoming eastern peoples comes from an originally EHG population expanding into a mainly WHG area in the west (similar to what happens e.g. with Bell Beakers), or being replaced later by a WHG population which adopted the culture (similar to what happened with late Corded Ware populations in central-east Europe after the expansion of Bell Beakers).

Unlike later periods, it will always be difficult to judge such ancient population movements with few samples covering thousands of years… Probably specific Y-DNA haplogroups would help differentiate between both expanding populations from east and west.


Biparental inheritance of mitochondrial DNA in humans


New paper Biparental Inheritance of Mitochondrial DNA in Humans, by Luo et al. PNAS (2018).

Interesting excerpts (emphasis mine):


Although there has been considerable debate about whether paternal mitochondrial DNA (mtDNA) transmission may coexist with maternal transmission of mtDNA, it is generally believed that mitochondria and mtDNA are exclusively maternally inherited in humans. Here, we identified three unrelated multigeneration families with a high level of mtDNA heteroplasmy (ranging from 24 to 76%) in a total of 17 individuals. Heteroplasmy of mtDNA was independently examined by high-depth whole mtDNA sequencing analysis in our research laboratory and in two Clinical Laboratory Improvement Amendments and College of American Pathologists-accredited laboratories using multiple approaches. A comprehensive exploration of mtDNA segregation in these families shows biparental mtDNA transmission with an autosomal dominantlike inheritance mode. Our results suggest that, although the central dogma of maternal inheritance of mtDNA remains valid, there are some exceptional cases where paternal mtDNA could be passed to the offspring. Elucidating the molecular mechanism for this unusual mode of inheritance will provide new insights into how mtDNA is passed on from parent tooffspring and may even lead to the development of new avenues for the therapeutic treatment for pathogenic mtDNA transmission.

An example

Compared with Family A, a strikingly similar mtDNA transmission pattern was demonstrated in Families B and C. Taking Family B for illustration, II-3 having 29 heteroplasmic and seven homoplasmic variants should have inherited mtDNA from both his father (I-1, haplogroup of K1b2a) and his mother (I-10, haplogroup of H), who were supposed to possess 34 and nine homoplasmic variants, respectively. II-3 further transmitted his mtDNA that he inherited from I-1 to his son (III-2), who also inherited all of his mother’s mtDNA (II-30, carrying 34 variants and a haplogroup of T2a1a). However, III-2’s sister (III-1) and half-brother (III-5) only inherited the maternal mtDNA. Fresh blood sampling and repeated mtDNA sequencing in a second independent laboratory were also performed to rule out the possibility of sample mix-up for III-2 (III-2, column F-G and H-I). Additionally, these samples were further verified using Pacific Bio single molecular sequencing (see Materials and Methods) and by restriction fragment length polymorphism (RFLP) analysis of Family A, and these results were fully consistent with the previous sequencing.

Biparental mtDNA inheritance pattern shown in Family B. (A) Pedigree of Family B. The black filled symbols indicate the two family members (II-3 and III-2) showing biparental mtDNA transmission. The IDs of five family members tested by whole mtDNA sequencing analysis have been underlined in the pedigree. (B) Schematic of the mtDNA genotype defined by the homoplasmic and/or heteroplasmic variants aligned from the reference mitochondrial genome. Blue bars represent the genotype of paternally derived mtDNA, whereas purple-red and orange-red bars represent maternally derived mtDNA. Entries labeled (D) represent deduced mtDNA genotypes. (C) Summary of the haplogroup and mtDNA variant numbers in Family B.

A Resurgence of the Paternal Transmission Hypothesis

The results presented in this paper make a robust case for paternal transmission of mtDNA. Here, we report biparental mtDNA inheritance (either directly or indirectly) in 17 members in three multigeneration families. Thirteen of these individuals were identified directly by sequencing of the mitochondrial genome, whereas four could be inferred based on preexisting maternal heteroplasmy caused by biparental inheritance in the previous generation.

To further confirm these remarkable results and to exclude the possibility of sample mix-up and/or contamination, the whole mtDNA sequencing procedure was repeated independently in at least two different laboratories by different laboratory technicians with newly obtained blood samples. All results were reproducible, indicating no artifacts or contamination exist. More importantly, the multiple mtDNA variants that were paternally transmitted differ in both number and position among each of these three families as well as the related haplogroup (R0a1 in Family A, K1b2a in Family B, and K2b1a1a in Family C, respectively), providing two distinct forms of evidence supporting transmission of the paternal mtDNA.

Therefore, we have unequivocally demonstrated the existence of biparental mtDNA inheritance as evidenced by the high number and level of mtDNA heteroplasmy in these three unrelated multigeneration families. Most interestingly, the mixed haplogroups in these samples are very reminiscent of the mixed haplogroups found in the 20 studies that were dismissed by Bandelt et al. as due to contamination or sample mix-up. One is forced to wonder how many other instances of individuals with biparental mtDNA inheritance have been dismissed as technical errors, and whether Schwartz and Vissing’s original discovery has really been given the proper follow-up that it deserves. We suspect that these results will initiate a broader reassessment of the topic.

We propose that the paternal mtDNA transmission in these families should be accompanied by segregation of a mutation in one nuclear gene involved in paternal mitochondrial elimination and that there is a high probability that the gene in question operates through one of the pathways identified above.

If I have to be honest, I was stuck with the paternal transmission hypothesis which we were taught in class long ago. I didn’t know it was controversial or dismissed, I just thought it was really exceptional, and I never thought about learning more on the subject.

This paper proves it may be more complicated than that, especially for population genomics purposes, because biparental mtDNA transmission with autosomal dominant-like inheritance puts a serious barrier to a general, simplistic interpretation of mtDNA.

I don’t think it is a blow to all interpretations based on mtDNA, though, because the traditional interpretation should often work statistically. However, one has to be always very careful when saying “if it’s mtDNA from region X, it’s about female exogamy”, especially when samples are from neighbouring regions and similar periods.

The term “uniparental marker” for mtDNA is obviously misleading and shouldn’t be used, and many research papers and interpretations taking mtDNA as strictly uniparental should be taken with a pinch of salt.


A very “Yamnaya-like” East Bell Beaker from France, probably R1b-L151


Interesting report by Bernard Sécher on Anthrogenica, about the Ph.D. thesis of Samantha Brunel from Institut Jacques Monod, Paris, Paléogénomique des dynamiques des populations humaines sur le territoire Français entre 7000 et 2000 (2018).

NOTE. You can visit Bernard Sécher’s blog on genetic genealogy.

A summary from user Jool, who was there, translated into English by Sécher (slight changes to translation, and emphasis mine):

They have a good hundred samples from the North, Alsace and the Mediterranean coast, from the Mesolithic to the Iron Age.

There is no major surprise compared to the rest of Europe. On the PCA plot, the Mesolithic are with the WHG, the early Neolithics with the first farmers close to the Anatolians. Then there is a small resurgence of hunter-gatherers that moves the Middle Neolithics a little closer to the WHGs.

From the Bronze Age, they have 5 samples with autosomal DNA, all in Bell Beaker archaeological context, which are very spread on the PCA. A sample very high, close to the Yamnaya, a little above the Corded Ware, two samples right in the Central European Bell Beakers, a fairly low just above the Neolithic package, and one last full in the package. The most salient point was that the Y chromosomes of their 12 Bronze Age samples (all Bell Beakers) are all R1b, whereas there was no R1b in the Neolithic samples.

Finally they have samples of the Iron Age that are collected on the PCA plot close to the Bronze Age samples. They could not determine if there is continuity with the Bronze Age, or a partial replacement by a genetically close population.

Image modified from Wang et al. (2018). Samples projected in PCA of 84 modern-day West Eurasian populations (open symbols). Previously known clusters have been marked and referenced. Marked and labelled are interesting samples; In red, likely position of late Yamna Hungary / early East Bell Beakers An EHG and a Caucasus ‘clouds’ have been drawn, leaving Pontic-Caspian steppe and derived groups between them. See the original file here. To understand the drawn potential Caucasus Mesolithic cluster, see above the PCA from Lazaridis et al. (2018).

The sample with likely high “steppe ancestry“, clustering closely to Yamna (more than Corded Ware samples) is then probably an early East Bell Beaker individual, probably from Alsace, or maybe close to the Rhine Delta in the north, rather than from the south, since we already have samples from southern France from Olalde et al. (2018) with high Neolithic ancestry, and samples from the Rhine with elevated steppe ancestry, but not that much.

This specific sample, if confirmed as one of those reported as R1b (then likely R1b-L151), as it seems from the wording of the summary, is key because it would finally link Yamna to East Bell Beaker through Yamna Hungary, all of them very “Yamnaya-like”, and therefore R1b-L151 (hence also R1b-L51) directly to the steppe, and not only to the Carpathian Basin (that is, until we have samples from late Repin or West Yamna…)

NOTE. The only alternative explanation for such elevated steppe ancestry would be an admixture between a ‘less Yamnaya-like’ East Bell Beaker + a Central European Corded Ware sample like the Esperstedt outlier + drift, but I don’t think that alternative is the best explanation of its position in the PCA closer to Yamna in any of the infinite parallel universes, so… Also, the sample from Esperstedt is clearly a late outlier likely influenced by Yamna vanguard settlers from Hungary, not the other way round…

Unexpectedly, then, fully Yamnaya-like individuals are found not only in Yamna Hungary ca. 3000-2500 BC, but also among expanding East Bell Beakers later than 2500 BC. This leaves us with unexplained, not-at-all-Yamnaya-like early Corded Ware samples from ca. 2900 BC on. An explanation based on admixture with locals seems unlikely, seeing how Corded Ware peoples continue a north Pontic cluster, being thus different from Yamna and their ancestors since the Neolithic; and how they remained that way for a long time, up to Sintashta, Srubna, Andronovo, and even later samples… A different, non-Indo-European community it is, then.

Image modified from Olalde et al. (2018). PCA of 999 Eurasian individuals. Marked is the Espersted Outlier with the approximate position of Yamna Hungary, probably the source of its admixture. Different Bell Beaker clines have been drawn, to represent approximate source of expansions from Central European sources into the different regions. In red, likely zone of Yamna Hungary and reported early East Bell Beaker individual from France.

Let’s wait and see the Ph.D. thesis, when it’s published, and keep observing in the meantime the absurd reactions of denial, anger, bargaining, and depression (stages of grief) among BBC/R1b=Vasconic and CWC/R1a=Indo-European fans, as if they had lost something (?). Maybe one of these reactions is actually the key to changing reality and going back to the 2000s, who knows…

Featured image: initial expansion of the East Bell Beaker Group, by Volker Heyd (2013).


A Late Proto-Indo-European self-learning language course


Fernando López-Menchero has just published the first part of his A Practical Guidebook for Modern Indo-European Explorers (2018).

It is a great resource to learn Late Proto-Indo-European as a modern language, from the most basic level up to an intermediate level (estimated B1–B2, depending on one’s previous background in Indo-European and classical languages).

Instead of working on unending details and discussions of the language reconstruction, it takes Late Proto-Indo-European as a learned, modern language that can be used for communication, so that people not used to study with university manuals on comparative grammar can learn almost everything necessary about PIE in the most comfortable way.

(see also the announcement on Facebook)

NOTE. Even though we help each other with our works, Fernando is not the least interested in genetics (the “steppe ancestry” or the “R1b–R1a” question, or any other issue involving population genomics), or even too much about archaeology or the homeland question (although he uses the mainstream view that Late Proto-Indo-Europeans expanded from Yamna). His only interest is language reconstruction, and I doubt you can find anything else in his works but pure love for linguistics, including this one.

I was starting to call his project of a self-learning method The Winds of Winter, seeing how it appeared to be always in the making, but never actually finished. It seems that the publication of this first part will make my revision of the Indo-European demic diffusion model become the true The Winds of Winter here, in this our common series of books on Late Proto-Indo-European and its dialects…

As you can see, I am publishing less and less in this blog lately, and it’s all just to be able to finish a revision in time (that is, before more new genetic research compels me to delay it again…). It is a very thorough revision, so those of you who liked it are not going to be disappointed.

I hoped to have it ready for mid-December, but, as it turns out, due to different unexpected delays, I am now more confident about a mid-January / February date, and that only if everything goes well.


Genetic landscape and past admixture of modern Slovenians


Open access Genetic Landscape of Slovenians: Past Admixture and Natural Selection Pattern, by Maisano Delser et al. Front. Genet. (2018).

Interesting excerpts (emphasis mine):


Overall, 96 samples ranging from Slovenian littoral to Lower Styria were genotyped for 713,599 markers using the OmniExpress 24-V1 BeadChips (Figure 1), genetic data were obtained from Esko et al. (2013). After removing related individuals, 92 samples were left. The Slovenian dataset has been subsequently merged with the Human Origin dataset (Lazaridis et al., 2016) for a total of 2163 individuals.

Y chromosome

First, Y chromosome genetic diversity was assessed. A total of 52 Y chromosomes were analyzed for 195 SNPs. The majority of individuals (25, 48.1%) belong to the haplogroup R1a1a1a (R-M417) while the second major haplogroup is represented by R1b (R-M343) including 15 individuals (28.8%). Twelve samples are assigned to haplogroup I (I M170): five and two samples belong to haplogroup I2a (I L460) and I1 (I M253), respectively, while the remaining five samples did not have enough information to be further assigned.

PCA of Slovenian samples with European populations (Slovenian_HO_EU dataset). For details regarding the populations included, see Supplementary Table 1.


Considering the unbalanced sample size of the Slovenian population compared to the other populations included in the dataset, a subset of 20 Slovenian individuals randomly sampled was used.

All Slovenian samples group together with Hungarians, Czechs, and some Croatians (“Central-Eastern European” cluster) as also suggested by the PCA. All Basque individuals with few French and Spanish cluster together (“Basque” cluster) while a “Northern-European” cluster is made of the majority of French, English, Icelanders, Norwegians, and Orcadians. Five populations contributed to the “Eastern-European” cluster including Belarusians, Estonians, Lithuanians, Mordovians, and Russians. Western and South Europe is split into two cluster: the first (“Western European” cluster) includes all Spanish individuals, few French, and some Italians (North Italy) while the second (“Southern-European” cluster) groups Sicilians, Greeks, some Croatians, Romanians, and some Italians (North Italy).

Admixture Pattern and Migration

Modified image, from the paper (Central-East Europeans marked). Unsupervised admixture analysis of Slovenians. Results for K = 5 are showed as it represents the lowest cross-validation error. Slovenian samples show an admixture pattern similar to the neighboring populations such as Croatians and Hungarians. The major ancestral components are: the blue one which is shared with Lithuanians and Russians, followed by the dark green one that is mostly present in Greek samples and the light blue which characterizes Orcadians and English. For population acronyms see Supplementary Table 1.

All Slovenian individuals share common pattern of genetic ancestry, as revealed by ADMIXTURE analysis. The three major ancestry components are the North East and North West European ones (light blue and dark blue, respectively, Figure 3), followed by a South European one (dark green, Figure 3). Contribution from the Sardinians and Basque are present in negligible amount. The admixture pattern of Slovenians mimics the one suggested by the neighboring Eastern European populations, but it is different from the pattern suggested by North Italian populations even though they are geographically close.

Using ALDER, the most significant admixture event was obtained with Russians and Sardinians as source populations and it happened 135 ± 9.31 generations ago (Z-score = 11.54). (…) When tested for multiple admixture events (MALDER), we obtained evidence for one admixture event 165.391 ± 17.1918 generations ago corresponding to ∼2620 BCE (CI: 3101–2139) considering a generation time of 28 years (Figure 4), with Kalmyk and Sardinians as sources.

We then modeled the Slovenian population as target of admixture of ancient individuals from Haak et al. (2015) while computing the f3(Ancient 1, Ancient 2, Slovenian) statistic. The most significant signal was obtained with Yamnaya and HungaryGamba_EN (Z-score = -10.66), followed by MA1 with LBK_EN (Z-score -9.7) and Yamnaya with Stuttgart (Z-score = -8.6) used as possible source populations (Supplementary Figure 5).

We found a significant signal of admixture by using both pairs as ancient sources. Specifically, for the pair Yamnaya and Hungary_EN the admixture event is dated at 134.38 ± 23.69 generations ago (Z-score = 5.26, p-value of 1.5e-07) while for Yamnaya and LBK_EN at 153.65 ± 22.19 generations ago (Z-score = 6.92, p-value 4.4e-12). Outgroup f3 with Yamnaya put Slovenian population close to Hungarians, Czechs, and English, indicating a similar shared drift between these population with the Steppe populations (Supplementary Figure 6).

Admixture events identified with ALDER and MALDER. The gray dots represent significant admixture events detected with ALDER using Slovenians as target, the solid line represents the single admixture event detected using MALDER, dashed lines represent the confidence interval. Only the significant results after multiple testing correction are plotted. For ALDER results see Supplementary Table 5.

Not that any of this would come as a surprise, but:

  • R1a-M458 and some R1a-Z280 (xR1a-Z92) lineages (found among Slovenes) were associated with the Slavic expansion, likely with the Prague-Korchak culture, originally stemming probably from peoples of the Lusatian culture. Other R1a-Z280 lineages remained associated with Uralic peoples, and some became Slavicized only recently.
  • PCA keeps supporting the common cluster of certain West, South, and East Slavs in a “Central-Eastern European” cluster, distinct from the “North-Eastern European” cluster formed by modern Finno-Ugrians, as well as ancient Finno-Ugrians of north-eastern Europe who were only recently Slavicized.
  • Admixture supports the same ancient ‘western’ (a core West+South+East Slavic) cluster, and the admixture event with Yamna + Hungary_EN is logically a proxy for Yamna Hungary being at the core of ancestral Central-East population movements related to Bell Beakers in the mid- to late 3rd millennium.

The theory that East Slavs are at the core of the Slavic expansion makes no sense, in terms of archaeology (see Florin Curta’s dismissal of those recent eastern ‘Slavic’ finds, his commentary on 19th century Pan-Slavic crap, or his book on Slavic migrations), in terms of ancient DNA (the earliest Slavs sampled cluster with modern West Slavs, distant from the steppe cluster, unlike Finno-Ugrians), or in terms of modern DNA.

I don’t know where exactly this impulse for the theory of Russia being the cradle of Slavs comes from today (although there are some obvious political trends to revive 19th c. ideas), but it was always clear for everyone, including Russians, that East Slavs had migrated to the east and north and assimilated indigenous Finno-Ugrians, apart from Turkic-, Iranian-, and Caucasian-speaking peoples to the east. Genetics is only confirming what was clear from other disciplines long ago.


The complex origin of Samoyedic-speaking populations


Open access Siberian genetic diversity reveals complex origins of the Samoyedic-speaking populations, by Karafet et al. Am J Hum Biol (2018) e23194.

Interesting excerpts (emphasis mine):

Siberian groups

Consistent with their origin, Mongolic-speaking Buryats demonstrate genetic similarity with Mongols, and Turkic-speaking Altai-Kizhi and Teleuts are drawn close to CAS groups. The Tungusic-speaking Evenks collected in central and eastern Siberia cluster together and overlap with Yukagirs. Dolgans are widely scattered in the plot, justifying their recent origin from one Evenk clan, Yakuts, and Russian peasants in the 18th century (Popov, 1964). Uralic-speaking populations comprise a very wide cluster with Komi drawn to Europe, and Khants showing a closer affinity with Selkups, Tundra and Forest Nentsi. Yenisey-speaking Kets are intermingled with Selkups. Interestingly, Samoyedic-speaking Nganasans from the Taymyr Peninsula form a separate tight cluster closer to Evenks, Yukagirs, and Koryaks.

Principal component analysis (PCA) using the “drop one in” technique for 27 present-day (N = 424) and 6 ancient populations (N = 20). PCA was performed on 281 093 SNPs from the intersection of our data with publicly available ancient Siberian samples

ADMIXTURE and the “Siberian component”

Among Siberians, the Komi are primarily Europeans, while Nganasans, Evenks, Yukagirs, and Koryaks are nearly 100% East Asians. At K = 4 finer scale subcontinental structure can be distinguished with the emergence of a “Siberian” component. This component is highly pronounced in the Nganasans. Outside Siberia, this component is present in Germany and in CAS at low frequency. Within ancient cultures, this component has the highest frequency in three BA Karasuk samples. It is also found in Mal’ta, ENE Afanasievo and BA Andronovo, but not in Ust’-Ishim and BA Okunevo. At K = 5, the “Siberian” component is roughly subdivided into two components with different geographic distributions. The “Nganasan” component is frequent in nearly all Siberian populations, except the Komi, Kets and Selkups. The newly derived “Selkup-Ket” component is found at high frequencies in western Siberian populations. It is observed in BA Karasuk and in Mal’ta. At K = 6, the western Siberian “Nentsi-Khant” ancestry component was developed in Forest and Tundra Nentsi, Khants. This component is also present at low levels in EUR, CAS, Tibet, and southern Siberia.


The Dolgans share more segments with the Nganasans than within themselves (54.13 vs 41.72, Mann-Whitney test, P = .000000000001562546). The result is not surprising as the demographic data showed that the Nganasans were subjected to intense assimilation by the Dolgans in the second half of the 20th century (Goltsova, Osipova, Zhadanov, & Villems, 2005). Tundra Nentsi share more IBD with Forest Nentsi than within themselves (83.96 vs 50.3, P = .000055) possibly due to the common origin and long-term gene flow. The Ket and Selkup populations allocate significantly more IBD blocks between populations than with individuals from their own population (121.2 cM vs 85.9 cM for Kets, P = .000008, and 121.2 cM vs 114.9 cM for Selkups, P = .043).

ADMIXTURE plot. Clustering of 444 individuals from 27 present-day and 6 ancient populations (281 093 SNPs) assuming K6 to K7 clusters. Individuals are shown as vertical bars colored in ratio to their estimated ancestry within each cluster

Haplogroup N in Siberia

Although Siberia exhibits 42 haplogroups, the vast majority of Siberian Y-chromosomes belong only to 4 of the 18 major clades (N = 46.2%; C = 20.9%; Q = 14.4%; and R = 15.2%). The Y-chromosome haplogroup N is widely spread across Siberia and Eastern Europe (Ilumae et al., 2016; Karafet et al., 2002; Wong et al., 2016) and reaches its maximum frequency among Siberian populations such as Nganasans (94.1%) and Yakuts (91.9%). Within Siberia, two sister subclades N-P43 and N-L708 show different geographic distributions. N-P43 and derived haplogroups N-P63 and N- P362 (phylogenetically identical to N-B478* and N-B170, respectively) (Ilumae et al., 2016) are extremely rare in other major geographic regions. Likely originating in western Siberia, they are limited almost entirely to northwest Siberia, the Volga- Uralic regions, and the Taymyr Peninsula (ie, do not extend to eastern Siberia). Conversely, clade N-L708 is frequent in all Siberian populations except the Kets and Selkups, reaching its highest frequency in the Yakuts (91.9%).

Surprisingly, not a single sign of the proposed reindeer pastoralist horde led by Nganasans into north-eastern Europe. This is strange because “Siberian” migrants hypothetically imposed their language over Indo-Europeans quite recently, apparently after the Iron Age

Interesting comparisons among Siberian groups, though.


Deep population history of North, Central and South America


Open access Reconstructing the Deep Population History of Central and South America, by Posth et al. Cell (2018).


We report genome-wide ancient DNA from 49 individuals forming four parallel time transects in Belize, Brazil, the Central Andes, and the Southern Cone, each dating to at least ∼9,000 years ago. The common ancestral population radiated rapidly from just one of the two early branches that contributed to Native Americans today. We document two previously unappreciated streams of gene flow between North and South America. One affected the Central Andes by ∼4,200 years ago, while the other explains an affinity between the oldest North American genome associated with the Clovis culture and the oldest Central and South Americans from Chile, Brazil, and Belize. However, this was not the primary source for later South Americans, as the other ancient individuals derive from lineages without specific affinity to the Clovis-associated genome, suggesting a population replacement that began at least 9,000 years ago and was followed by substantial population continuity in multiple regions.

Interesting excerpts:

The D4h3a mtDNA haplogroup has been hypothesized to be a marker for an early expansion into the Americas along the Pacific coast (Perego et al., 2009). However, its presence in two Lapa do Santo individuals and Anzick-1 (Rasmussen et al., 2014) makes this hypothesis unlikely.

The patterns we observe on the Y chromosome also force us to revise our understanding of the origins of present-day variation. Our ancient DNA analysis shows that the Q1a2a1b-CTS1780 haplogroup, which is currently rare, was present in a third of the ancient South Americas. In addition, our observation of the currently extremely rare C2b haplogroup at Lapa do Santo disproves the suggestion that it was introduced after 6,000 BP (Roewer et al., 2013).

(…) Our discovery that the Clovis-associated Anzick-1 genome at ∼12,800 BP shares distinctive ancestry with the oldest Chilean, Brazilian, and Belizean individuals supports the hypothesis that an expansion of people who spread the Clovis culture in North America also affected Central and South America, as expected if the spread of the Fishtail Complex in Central and South America and the Clovis Complex in North America were part of the same phenomenon (direct confirmation would require ancient DNA from a Fishtail-context) (Pearson, 2017). However, the fact that the great majority of ancestry of later South Americans lacks specific affinity to Anzick-1 rules out the hypothesis of a homogeneous founding population. Thus, if Clovis-related expansions were responsible for the peopling of South America, it must have been a complex scenario involving arrival in the Americas of sub-structured lineages with and without specific Anzick-1 affinity, with the one with Anzick-1 affinity making a minimal long-term contribution. While we cannot at present determine when the non-Anzick-1 associated lineages first arrived in South America, we can place an upper bound on the date of the spread to South America of all the lineages represented in our sampled ancient genomes as all are ANC-A and thus must have diversified after the ANC-A/ANC-B split estimated to have occurred ∼17,500–14,600 BP (Moreno-Mayar et al., 2018a).


New paper (behind paywall) Early human dispersals within the Americas, by Moreno-Mayar et al. Science (2018).


Studies of the peopling of the Americas have focused on the timing and number of initial migrations. Less attention has been paid to the subsequent spread of people within the Americas. We sequenced 15 ancient human genomes spanning Alaska to Patagonia; six are ≥10,000 years old (up to ~18× coverage). All are most closely related to Native Americans, including an Ancient Beringian individual, and two morphologically distinct “Paleoamericans.” We find evidence of rapid dispersal and early diversification, including previously unknown groups, as people moved south. This resulted in multiple independent, geographically uneven migrations, including one that provides clues of a Late Pleistocene Australasian genetic signal, and a later Mesoamerican-related expansion. These led to complex and dynamic population histories from North to South America.

Interesting excerpts:

The Australasian signal is not present in USR1 or Spirit Cave, but only appears in Lagoa Santa. None of these individuals has UPopA/Mesoamerican-related admixture, which ap-parently dampened the Australasian signature in South American groups, such as the Karitiana. These findings suggest the Australasian signal, possibly present in a structured ancestral NA population, was absent in NA prior to the Spirit Cave/Lagoa Santa split. Groups carrying this signal were either already present in South America when the ancestors of Lagoa Santa reached the region, or Australasian-related groups arrived later but before 10.4 ka (the Lagoa Santa 14C age). That this signal has not been previously documented in North America implies that an earlier group possessing it had disappeared, or a later-arriving group passed through North America without leaving any genetic trace. If such a signal is ultimately detected in North America it could help determine when groups bear-ing Australasian ancestry arrived, relative to the divergence of SNA groups.

Although we detect the Australasian signal in one of the Lagoa Santa individuals identified as a “Paleoamerican,” it is absent in other “Paleoamericans” (2, 10), including Spirit Cave with its strong genetic affinities to Lagoa Santa. This indicates the “Paleoamerican” cranial form is not associated with the Australasian genetic signal, as previously suggested (6), or any other specific NA clade (2). The cause of this cranial form, if it is representative of broader population pat-terns, evidently did not result from separate ancestry, but likely multiple factors, including isolation and drift and non-stochastic mechanisms.

f-statistics–based tests show a rapid dispersal into South America, followed by Mesoamerican-related admixture. Schematic representation of a model for SNA formation. This model represents a reasonable fit to most present-day populations.

Open access The genetic prehistory of the Andean highlands 7000 years BP though European contact, by Lindo et al. Science Advances (2018).


The peopling of the Andean highlands above 2500 m in elevation was a complex process that included cultural, biological, and genetic adaptations. Here, we present a time series of ancient whole genomes from the Andes of Peru, dating back to 7000 calendar years before the present (BP), and compare them to 42 new genome-wide genetic variation datasets from both highland and lowland populations. We infer three significant features: a split between low- and high-elevation populations that occurred between 9200 and 8200 BP; a population collapse after European contact that is significantly more severe in South American lowlanders than in highland populations; and evidence for positive selection at genetic loci related to starch digestion and plausibly pathogen resistance after European contact. We do not find selective sweep signals related to known components of the human hypoxia response, which may suggest more complex modes of genetic adaptation to high altitude.