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.


Genetic landscapes showing human genetic diversity aligning with geography


New preprint at BioRxiv, Genetic landscapes reveal how human genetic diversity aligns with geography, by Peter, Petkova, and Novembre (2017).


Summarizing spatial patterns in human genetic diversity to understand population history has been a persistent goal for human geneticists. Here, we use a recently developed spatially explicit method to estimate “effective migration” surfaces to visualize how human genetic diversity is geographically structured (the EEMS method). The resulting surfaces are “rugged”, which indicates the relationship between genetic and geographic distance is heterogenous and distorted as a rule. Most prominently, topographic and marine features regularly align with increased genetic differentiation (e.g. the Sahara desert, Mediterranean Sea or Himalaya at large scales; the Adriatic, inter-island straits in near Oceania at smaller scales). We also see traces of historical migrations and boundaries of language families. These results provide visualizations of human genetic diversity that reveal local patterns of differentiation in detail and emphasize that while genetic similarity generally decays with geographic distance, there have regularly been factors that subtly distort the underlying relationship across space observed today. The fine-scale population structure depicted here is relevant to understanding complex processes of human population history and may provide insights for geographic patterning in rare variants and heritable disease risk.

Regional patterns of genetic diversity. a: scale bar for relative effective migration rate. Posterior effective migration surfaces for b: Western Eurasia (WEA) e: Central/Eastern Eurasia (CEA) g: Africa (AFR) h Southern African hunter-gatherers (SAHG) k: and Southeast Asian (SEA) analysis panels. ‘X’ marks locations of samples noted as displaced or recently admixed, ‘H’ denotes Hunter-Gatherer populations (both ‘X’ and ‘H’ samples are omitted from the EEMS model fit); in panel g, red circles indicate Nilo-Saharan speakers and in panel h, ‘B’ denotes Bantu-speaking populations. Approximate location of troughs are shown with dashed lines (see Extended Data Figure 4). PCA plots: c: WEA d:Europeans in WEA f: CEA i: SAHG j: AFR l: SEA. Individuals are displayed as grey dots. Large dots reflect median PC position for a sample; with colors reflecting geography matched to the corresponding EEMS figure. In the EEMS plots, approximate sample locations are annotated. For exact locations, see annotated Extended Data Figure 4 and Table S1. Features discussed in the main text and supplement are labeled. FST values per panelemphasize the low absolute levels of differentiation.”

Among ‘effective migration surfaces‘ (or potential past migration routes), the Pontic-Caspian steppe and its most direct connection with the Carpathian basin, the Danubian plains, appear maybe paradoxically as a constant ‘trough’ (below average migration rate) in all maps.

After all, we could have agreed that this region should be a priori thought as the route of many migrations from the steppe and Asia into Central Europe (and thus of ‘effective migration’) in prehistoric, proto-historic and historic times, such as Suvorovo-Novodanilovka (Pre-Anatolian), Yamna (Late Indo-European), probably Srubna, Scythian-Cimmerian, Sarmatian, Huns, Goths, Avars, Slavs, Mongols

It most likely (at least partially) represents a rather recent historical barrier to admixture, involving successive Byzantine, South Slavic, and Ottoman spheres of influence positioned against Balto-Slavic societies of Eastern Europe.

Location of troughs in West Eurasia (below average migration rate in more than 95% of MCMC iterations) are given in brown. Sample locations and EEMS grid are displayed for the West Eurasian analysis panel. FST values are provided per panel to emphasize the low absolute levels of differentiation.

Featured image, from the article: “Large-scale patterns of population structure. a: EEMS posterior mean effective migration surface for Afro-Eurasia (AEA) panel. ‘X’ marks locations of samples excluded as displaced or recently admixed. ‘H marks locations of excluded hunter-gatherer populations. Regions and features discussed in the main text are labeled. Approximate locations of troughs are annotated with dashed lines (see Extended Data Figure 4). b: PCA plot of AEA panel: Individuals are displayed as grey dots, colored dots reflect median of sample locations; with colors reflecting geography and matching with the EEMS plot. Locations displayed in the EEMS plot reflect the position of populations after alignment to grid vertices used in the model (see methods).”

Images and text available under a CC-BY-NC-ND 4.0 International License.

Discovered via Razib Khan’s blog.