Ancient Sardinia hints at Mesolithic spread of R1b-V88, and Western EEF-related expansion of Vasconic


New preprint Population history from the Neolithic to present on the Mediterranean island of Sardinia: An ancient DNA perspective, by Marcus et al. bioRxiv (2019)

Interesting excerpts (emphasis mine, edited for clarity):

On the high frequency of R1b-V88

Our genome-wide data allowed us to assign Y haplogroups for 25 ancient Sardinian individuals. More than half of them consist of R1b-V88 (n=10) or I2-M223 (n=7).

Francalacci et al. (2013) identi fied three major Sardinia-specifi c founder clades based on present-day variation within the haplogroups I2-M26, G2-L91 and R1b-V88, and here we found each of those broader haplogroups in at least one ancient Sardinian individual. Two major present-day Sardinian haplogroups, R1b-M269 and E-M215, are absent.

Compared to other Neolithic and present-day European populations, the number of identi fied R1b-V88 carriers is relatively high.

(…)ancient Sardinian mtDNA haplotypes belong almost exclusively to macro-haplogroups HV (n = 16), JT (n = 17) and U (n = 9), a composition broadly similar to other European Neolithic populations.

Geographic and temporal distribution of R1b-V88 Y-haplotypes in ancient European samples. We plot the geographic position of all ancient samples inferred to carry R1b-V88 equivalent markers. Dates are given as years BCE (means of calibrated 2s radio-carbon dates). Multiple V88 individuals with similar geographic positions are vertically stacked. We additionally color-code the status of the R1b-V88 subclade R1b-V2197, which is found in most present-day African R1b-V88 carriers.

On the origin of a Vasconic-like Paleosardo with the Western EEF

(…) the Neolithic (and also later) ancient Sardinian individuals sit between early Neolithic Iberian and later Copper Age Iberian populations, roughly on an axis that differentiates WHG and EEF populations and embedded in a cluster that additionally includes Neolithic British individuals. This result is also evident in terms of absolute genetic differentiation, with low pairwise FST ~ 0.005 +- 0.002 between Neolithic Sardinian individuals and Neolithic western mainland European populations. Pairwise outgroup-f3 analysis shows a very similar pattern, with the highest values of f3 (i.e. most shared drift) being with Neolithic and Copper Age Iberia, gradually dropping off for temporally and geographically distant populations.

In explicit admixture models (using qpAdm, see Methods) the southern French Neolithic individuals (France-N) are the most consistent with being a single source for Neolithic Sardinia (p ~ 0:074 to reject the model of one population being the direct source of the other); followed by other populations associated with the western Mediterranean Neolithic Cardial Ware expansion.

Principal Components Analysis based on the Human Origins dataset. A: Projection of ancient individuals’ genotypes onto principal component axes de fined by modern Western Eurasians (gray labels).

Pervasive Western Hunter-Gatherer ancestry in Iberian/French/Sardinian population

Similar to western European Neolithic and central European Late Neolithic populations, ancient Sardinian individuals are shifted towards WHG individuals in the top two PCs relative to early Neolithic Anatolians Admixture analysis using qpAdm infers that ancient Sardinian individuals harbour HG ancestry (~ 17%) that is higher than early Neolithic mainland populations (including Iberia, ~ 8%), but lower than Copper Age Iberians (~ 25%) and about the same as Southern French Middle-Neolithic individuals (~ 21%).

Principal Components Analysis based on the Human Origins dataset. B: Zoom into the region most relevant for Sardinian individuals.

Continuity from Sardinia Neolithic through the Nuragic

We found several lines of evidence supporting genetic continuity from the Sardinian Neolithic into the Bronze Age and Nuragic times. Importantly, we observed low genetic differentiation between ancient Sardinian individuals from various time periods.

A qpAdm analysis, which is based on simultaneously testing f-statistics with a number of outgroups and adjusts for correlations, cannot reject a model of Neolithic Sardinian individuals being a direct predecessor of Nuragic Sardinian individuals (…) Our qpAdm analysis further shows that the WHG ancestry proportion, in a model of admixture with Neolithic Anatolia, remains stable at ~17% throughout three ancient time-periods.

Present-day genetic structure in Sardinia reanalyzed with aDNA. A: Scatter plot of the rst two principal components trained on 1577 present-day individuals with grand-parental ancestry from Sardinia. Each individual is labeled with a location if at least 3 of the 4 grandparents were born in the same geographical location (\small” three letter abbreviations); otherwise with \x” or if grand-parental ancestry is missing with \?”. We calculated median PC values for each Sardinian province (large abbreviations). We also projected each ancient Sardinian individual on to the top two PCs (gray points). B/C: We plot f-statistics that test for admixture of modern Sardinian individuals (grouped into provinces) when using Nuragic Sardinian individuals as one source population. Uncertainty ranges depict one standard error (calculated from block bootstrap). Karitiana are used in the f-statistic calculation as a proxy for ANE/Steppe ancestry (Patterson et al., 2012).

Steppe influx in Modern Sardinians

While contemporary Sardinian individuals show the highest affinity towards EEF-associated populations among all of the modern populations, they also display membership with other clusters (Fig. 5). In contrast to ancient Sardinian individuals, present-day Sardinian individuals carry a modest “Steppe-like” ancestry component (but generally less than continental present-day European populations), and an appreciable broadly “eastern Mediterranean” ancestry component (also inferred at a high fraction in other present-day Mediterranean populations, such as Sicily and Greece).


Global demographic history inferred from mitogenomes

Open access Global demographic history of human populations inferred from whole mitochondrial genomes, by Miller, Manica, and Amos, Royal Society Open Science (2018).

Relevant excerpts (emphasis mine):


The Phase 3 sequence data from 20 populations, comprising five populations for each of the four main geographical regions of Europe, East Asia, South Asia and Africa, were downloaded from the 1000 Genomes Project website (, [8]), including whole mitochondrial genome data for 1999 individuals. We decided not to analyse populations from the Americas due to the region’s complex history of admixture [13,14].

The European populations were as follows: Finnish sampled in Finland (FIN); European Caucasians resident in Utah, USA (CEU); British in England and Scotland (GBR); an Iberian population from Spain (IBS) and Toscani from Italy (TSI). Representing East Asia were the Han Chinese in Beijing (CHB); Southern Han Chinese (CHS); Dai Chinese from Xishuangbanna, China (CDX); Kinh population from Ho Chi Minh City, Vietnam (KHV) and Japanese from Tokyo (JPT). The South Asian populations were Punjabi Indians from Lahore, Pakistan (PJL); Gujarati Indians in Houston, USA (GIH) as well as Indian Telugu sampled in the UK (ITU); Bengali from Bangladesh (BEB) and Sri Lankan Tamil from the UK (STU). (…)


We analysed our mtDNA data with the extended Bayesian skyline plot (EBSP) method, a Bayesian, non-parametric technique for inferring past population size fluctuations from genetic data. Building on the previous Bayesian skyline plot (BSP) approach, EBSP uses a piecewise-linear model and Markov chain Monte Carlo (MCMC) methods to reconstruct a populations’ demographic history [17] and is implemented in the software package BEAST v. 2.3.2 [11]. Alignments for each of the 20 populations were loaded separately into the Bayesian Evolutionary Analysis Utility tool (BEAUti v. 2.3.2) in NEXUS format.

Relationship between profile similarity and genetic distance, measured as Fst. Comparisons between regions, circles, are colour-coded: black ¼ AFR-EA; yellow ¼ AFR-EUR; blue ¼ AFR-SA; orange ¼ EUR-EA; green ¼ EA-SA; red ¼ EUR-SA. Comparisons within regions, squares, are coded: peach ¼ EUR; pink ¼ EA; dark blue ¼ EA; light blue ¼ AFR. Profile similarity is calculated as inferred size difference summed over 20 evenly spaced intervals (see Material and methods).

Regional demographic histories


The five European profiles are presented in figure 2. The four southerly populations all show profiles with a stable size up to approximately 14 ka followed by a sudden, rapid increase that becomes progressively less steep towards the present. There is also a north-south trend, with confidence intervals becoming broader towards the north, particularly for the oldest time-points. The Finnish population profile appears rather different, but this is to be expected both because it is so far north and because previous studies have identified Finns as a strong genetic outlier in Europe [19–22].

Inferred demographic histories of five European populations. Dotted line is the median estimate of Ne and the thin grey lines show the boundary of the 95% CPD interval. The x-axis represents time from the present in years and all plots are on the same scale. Map shows origins of sampled populations.

South Asia:

The five profiles for South Asia are shown in figure 3. All populations reveal a period of rapid growth approximately 45–40 ka which then slows. Near the present the two southerly populations, GIH and STU both show evidence of a decline. However, this may be due to these samples being drawn from populations no longer living on the subcontinent, with the downward trend capturing a bottleneck associated with moving to Europe/America, perhaps accentuated by the tendency for immigrant populations to group by region, religion and race [23].

Inferred South Asian population demographic histories. Dotted line is the median Ne estimate and the thin grey lines show the boundary of the 95% CPD intervals. The x-axis represents time from the present in thousands of years and all plots are on the same scale. The map shows location of sampled populations.


Long-term matrilineal continuity in a nonisolated region of Tuscany


New paper (behind paywall) The female ancestor’s tale: Long‐term matrilineal continuity in a nonisolated region of Tuscany, by Leonardi et al. Am J Phys Anthr (2018).

EDIT (10 SEP 2018): The main author has shared an open access link to read the PDF.

Interesting excerpts:

Here we analyze North-western Tuscany, a region that was a corridor of exchanges between Central Italy and the Western Mediterranean coast.

We newly obtained mitochondrial HVRI sequences from 28 individuals, and after gathering published data, we collected genetic information for 119 individuals from the region. Those span five periods during the last 5,000 years: Prehistory, Etruscan age, Roman age, Renaissance, and Present-day. We used serial coalescent simulations in an approximate Bayesian computation framework to test for continuity between the mentioned groups.

In all cases, a simple model of a long-term genealogical continuity proved to fit the data better, and sometimes much better, than the alternative hypothesis of discontinuity.

The low number of samples analyzed requires some caution in the interpretation. Because we did not test for gene flow, it is at this stage impossible to reject it, but our results suggest at least significant levels of genealogical continuity. Moreover, as it has not been possible to obtain more precise information on the age of the Eneolithic samples, they were grouped together considering the average archaeological period of interest, which may cause a bias in the analyses. (…)

Geographic location of the samples considered in this work

(…) clearly, our samples show high levels of continuity when considering the whole Tuscan region as a genetic reservoir during the Iron Age.

The posterior distributions of the parameters confirm a high degree of genetic isolation in the sampled population, with very small values for the female effective population sizes across time. Such values, in particular the Neolithic ones, are in accord with the estimates obtained in similar studies, both in Tuscany (Ghirotto et al., 2013) and in France (Rivollat et al., 2017).


Taken at their face value, our results do not show any major shift in the composition of the maternal ancestry of the population, across 50 centuries. This does not mean that no demographic process of relevance has affected the population, and indeed the higher diversity accumulating in time is the likely consequence of immigrating people, enriching the mitochondrial gene pool.

(…) the population of the current Lucca province appears to have retained very ancient mitochondrial features, despite occupying a geographical corridor between the Ligurian and the Tyrrhenian coast, and despite not showing the persistence of unique cultural traits through the centuries.


Another possibility is that that the different populations passing through the area (Etruscans, Romans, and Lombards) had a consistent social and/or sex bias. An example of similar patterns has been observed several times. Between the Late Neolithic and the Early Bronze Age, female exogamy in patrilocal society has been observed in Southern Germany (Knipper et al., 2017); during the Bronze Age the migrations toward Europe from the steppes appears to have consisted prevalently of males (Goldberg, Günther, Rosenberg, & Jakobsson, 2017); and in more recent periods in the Canary Islands, the female ancestry maintains a significant amount of autochthonous lineages, while the male ancestry was strongly influenced by the European colonization (Fregel et al., 2009, b).

It is well known that military invasions may not have a significant genetic impact upon the invaded population (Schiffels et al., 2016; Sokal, Oden, Walker, Di Giovanni, & Thomson, 1996;Weale,Weiss, Jager, Bradman, & Thomas, 2002), especially at the mitochondrial level, because of the limited size of a sustainable army, and of the fact that armies are generally composed mostly or only of males. Even if a substantial share of invaders decided to remain and settle the region, this form of gene flow would affect mostly or only the paternal lineages, rather than the maternal ones. We can also hypothesize the immigration of a number of people (e.g., Romans, Lombards) that may have acted as ruler of the region, remaining socially (and so genetically) separated by the local population, and leaving few (if any) traces in the gene pools of the local population.

Supporting Information, Table S1 New ancient samples genotyped

We expect to see that certain migrations since the Iron Age – like the Celtic and Roman ones – were somehow different from previous ones, where, at least since the Neolithic, male-dominated expansions were the rule.

If, however, male-biased expansions are also seen during the Iron Age – probably driven by particular subclades then – , this would certainly justify the continuity of admixture in certain regions in spite of these population expansions, and thus the importance of Y-DNA to track more recent language changes.

One of the most interesting details of the upcoming paper of Italic peoples will be the Y-DNA (and admixture) of Etruscans compared to other neighbouring peoples, given the known conflicting theories regarding their recent vs. older origin in the East before the historical record.


Y-chromosome mixture in the modern Corsican population shows different migration layers


Open access Prehistoric migrations through the Mediterranean basin shaped Corsican Y-chromosome diversity, by Di Cristofaro et al. PLOS One (2018).

Interesting excerpts:

This study included 321 samples from men throughout Corsica; samples from Provence and Tuscany were added to the cohort. All samples were typed for 92 Y-SNPs, and Y-STRs were also analyzed.

Haplogroup R represented approximately half of the lineages in both Corsican and Tuscan samples (respectively 51.8% and 45.3%) whereas it reached 90% in Provence. Sub-clade R1b1a1a2a1a2b-U152 predominated in North Corsica whereas R1b1a1a2a1a1-U106 was present in South Corsica. Both SNPs display clinal distributions of frequency variation in Europe, the U152 branch being most frequent in Switzerland, Italy, France and Western Poland. Calibrated branch lengths from whole Y chromosome sequencing [44,45] and ancient DNA studies [46] both indicated that R1a and R1b diversification began relatively recently, about 5 Kya, consistent with Bronze Age and Copper Age demographic expansion. TMRCA estimations are concordant with such expansion in Corsica.

Spatial frequency maps for haplogroups with frequencies above 3%, their Y-STR based phylogenetic networks in Corsican populations (Blue: North, Green: West, Orange: South, Black: Center and Purple: East) and their TMRCA (in years, +/- SE).

Haplogroup G reached 21.7% in Corsica and 13.3% in Tuscany. Sub-clade G2a2a1a2-L91 accounted for 11.3% of all haplogroups in Corsica yet was not present in Provence or in Tuscany. Thirty-four out of the 37 G2a2a1a2-L91 displayed a unique Y-STR profile, illustrated by the star-like profile of STR networks (Fig 1). G2a2a1a2-L91 and G2a2a-PF3147(xL91xM286) show their highest frequency in present day Sardinia and southern Corsica compared to low levels from Caucasus to Southern Europe, encompassing the Near and Middle East [21,47–50]. Ancient DNA results from Early and Middle Neolithic samples reported the presence of haplogroup G2a-P15 [51–53], consistent with gene flow from the Mediterranean region during the Neolithic transition. Td expansion time estimated by STR for P15-affiliated chromosomes was estimated to be 15,082+/-2217 years ago [49]. Ötzi, the 5,300-year-old Alpine mummy, was derived for the L91 SNP [21]. A genetic relationship between G haplogroups from Corsica and Sardinia is further supported by DYS19 duplication, reported in North Sardinia [14], and observed in the southern part of the Corsica in 9 out of 37 G2a2a1a2-L91 chromosomes and in 4 out of 5 G2a2a-PF3147(xL91xM286) chromosomes, 3 of which displayed an identical STR profile (S4 Table).

This lineage has a reported coalescent age estimated by whole sequencing in Sardinian samples of about 9,000 years ago. This could reflect common ancestors coming from the Caucasus and moving westward during the Neolithic period [48], whereas their continental counterparts would have been replaced by rapidly expanding populations associated with the Bronze Age [46,54,55]. Estimated TMRCA for L91 lineage in Corsica is 4529 +/- 853 years. G-L497 showed high frequencies in Corsica compared to Provence and Tuscany, and this haplogroup was common in Europe, but rare in Greece, Anatolia and the Middle East. Fifteen out of the 17 Corsican G2a2b2a1a1b-L497 displayed a unique Y-STR profile (S4 Table) with an estimated TMRCA of 6867 +/- 1294 years. Haplogroup G2a2b1-M406, associated with Impressed Ware Neolithic markers, along with J2a1-DYS445 = 6 and J2a1b1-M92 [22,49], had very low levels in Corsica. Conversely, G2a2b2a-P303was highly represented and seemed to be independent of the G2a2b1-M406 marker. The 7 G2a2b2a-P303(xL497xM527) Corsican chromosomes displayed a unique Y-STR profile (S4 Table).

First and second axes of the PCA based on 12 Y-chromosome haplogroup frequencies in 83 west Mediterranean populations.

Haplogroup J, mainly represented by J2a1b-M67(xM92), displayed intermediate frequencies in Corsica compared to Tuscany and Provence. J2a1b-M67(xM92) derived STR network analysis displayed a quite homogeneous profile across the island with an estimated TMRCA of 2381 +/- 449 years (Fig 1) and individuals displaying M67 were peripheral compared to Northwestern Italians (S2 Fig). The haplogroup J2a1-Page55(xM67xM530), characteristic of non-Greek Anatolia [22], was found in the north-west of Corsica. Haplogroup J2a1-DYS445 = 6 was found in the north-west with DYS391 = 10 repeats, and in the far south with DYS391 = 9 repeats, the former was associated with Anatolian Greek samples, whereas the second was found in central Anatolia [22]. The 7 J2b2a-M241 displayed a unique Y-STR profile (S4 Table), they were only detected in the Cap Corse region, this sub-haplogroup shows frequency peaks in both the southern Balkans and northern-central Italy [56] and is associated with expansion from the Near East to the Balkans during Neolithic period [57].

Haplogroup E, mainly represented by E1b1b1a1b1a-V13, displayed intermediate frequencies in Corsica compared to Tuscany and Provence. E1b1b1a1b1a-V13 was thought to have initiated a pan-Mediterranean expansion 7,000 years ago starting from the Balkans [52] and its dispersal to the northern shore of the Mediterranean basin is consistent with the Greek Anatolian expansion to the western Mediterranean [22], characteristic of the region surrounding Alaria, and consistent with the TMRCA estimated in Corsica for this haplogroup. A few E1b1a-V38 chromosomes are also observed in the same regions as V13.


Mitogenomes show Longobard migration was socially stratified and included females


New bioRxiv preprint A genetic perspective on Longobard-Era migrations, by Vai et al. (2018).

Interesting excerpts (emphasis mine):

In this study we sequenced complete mitochondrial genomes from nine early-medieval cemeteries located in the Czech Republic, Hungary and Italy, for a total of 87 individuals. In some of these cemeteries, a portion of the individuals are buried with cultural markers in these areas traditionally associated with the Longobard culture (hereby we refer to these cemeteries as LC), as opposed to burial communities in which no artifacts or rituals associated by archaeologists to Longobard culture have been found in any graves. These necropolises, hereby referred as NLC, may represent local communities or other Barbaric groups previously migrated to this region. This extended sampling strategy provides an excellent condition to investigate the degree of genetic affinity between coeval LC and NLC burials, and to shed light on early-medieval dynamics in Europe.

Geographical and genetic relationship between the newly sequenced individuals. (A) Location of the sampled necropolises. Here and through the other figures LC cemeteries are represented by a circle while NLC ones are indicated by a square. C) DAPC Scatterplot of the most supported K (7) highlighted by the kmeans analysis

Social rank

There is also no clear geographical structure between samples in our dataset, with individuals from Italy, Hungary and Czech Republic clustering together. However, the first PC clearly separates a group of 12 LC individuals found at Szólád, Collegno and Mušov from a group composed by both LC and NLC individuals. The same pattern is also found when pairwise differences among individuals are plotted by multidimensional scaling (…)

The presence in this group of LC sequences belonging to macrohaplogroups I and W, commonly found at high frequencies in northern Europe (e.g. Finland 32), suggests (although certainly does not prove) the existence of a possible link between these 12 LC individuals and northern Europe. The peculiarity of this group is strengthened by archaeological information from the Szólád cemetery, where 8 of the 12 individuals in this group originated, indicating that all these samples were found buried with typical Longobard artifacts and grave assemblages. We do not find the same tight association for the 3 samples from Collegno, where the 3 graves are indeed devoid of evident Germanic cultural markers; however they are not placed in a separate and marginal location—as for the tombs without grave goods found in Szólád —but among graves with wooden chambers and weapons. It is worth noting that weapon burials were quite scarce in 5th century Pannonia and 6th century Italy (e.g. Goths never buried weapons), and an increase in weapon burials started in Italy only after the Longobard migration. In this light, the individuals buried in this manner may have been members of the same community as well, but belonging to the lowest social level. This social condition could explain the absence of artifacts and could be related to mixed marriages, whose offspring had an inferior social rank. Finally, this group also includes an individual from the Musov graveyard. This finding is particularly interesting in light of the fact that the Musov necropolis has been only tentatively associated with Longobard occupation (see Supplementary Text for details), based on the presence of but a few archaeological markers.

Female migration

We hence estimated that about 70% of the lineages found in Collegno actually derived from the Hungarian LC groups, in agreement with previous archaeological and historical hypotheses. This supports the idea that the spread of Longobards into Italy actually involved movements of fairly large numbers of people, who gave a substantial contribution to the gene pool of the resulting populations. This is even more remarkable thinking that, in many studied cases, military invasions are movements of males, and hence do not have consequences at the mtDNA level. Here, instead, we have evidence of changes in the composition of the mtDNA pool of an Italian population, supporting the view that immigration from Central Europe involved females as well as males.


Population structure in Argentina shows most European sources of South European origin


Open access Population structure in Argentina, by Muzzio et al., PLOS One (2018).

Abstract (emphasis mine):

We analyzed 391 samples from 12 Argentinian populations from the Center-West, East and North-West regions with the Illumina Human Exome Beadchip v1.0 (HumanExome-12v1-A). We did Principal Components analysis to infer patterns of populational divergence and migrations. We identified proportions and patterns of European, African and Native American ancestry and found a correlation between distance to Buenos Aires and proportion of Native American ancestry, where the highest proportion corresponds to the Northernmost populations, which is also the furthest from the Argentinian capital. Most of the European sources are from a South European origin, matching historical records, and we see two different Native American components, one that spreads all over Argentina and another specifically Andean. The highest percentages of African ancestry were in the Center West of Argentina, where the old trade routes took the slaves from Buenos Aires to Chile and Peru. Subcontinentaly, sources of this African component are represented by both West Africa and groups influenced by the Bantu expansion, the second slightly higher than the first, unlike North America and the Caribbean, where the main source is West Africa. This is reasonable, considering that a large proportion of the ships arriving at the Southern Hemisphere came from Mozambique, Loango and Angola.

Principal component analysis.
On the x axis is PC 1 while PC2 is the y axis. Plus symbols represent Argentinian samples and circles are for reference panels. Fig 2a (left) Argentinians with YRI and LWK for African references (“African”), IBS and TSI for European references (“European”) and the PEL, MXL, PUR and CLM as a Latin American references. Fig 2b (right) samples from Argentina with IBS, MXL, CLM and PEL.


The time and place of European admixture in Ashkenazi Jewish history

Open access The time and place of European admixture in Ashkenazi Jewish history, by Xue, Lencz, Darvasi, Pe’er, & Carmi, PLOS Genetics (2018).

Abstract (emphasis mine):

The Ashkenazi Jewish (AJ) population is important in genetics due to its high rate of Mendelian disorders. AJ appeared in Europe in the 10th century, and their ancestry is thought to comprise European (EU) and Middle-Eastern (ME) components. However, both the time and place of admixture are subject to debate. Here, we attempt to characterize the AJ admixture history using a careful application of new and existing methods on a large AJ sample. Our main approach was based on local ancestry inference, in which we first classified each AJ genomic segment as EU or ME, and then compared allele frequencies along the EU segments to those of different EU populations. The contribution of each EU source was also estimated using GLOBETROTTER and haplotype sharing. The time of admixture was inferred based on multiple statistics, including ME segment lengths, the total EU ancestry per chromosome, and the correlation of ancestries along the chromosome. The major source of EU ancestry in AJ was found to be Southern Europe (≈60–80% of EU ancestry), with the rest being likely Eastern European. The inferred admixture time was ≈30 generations ago, but multiple lines of evidence suggest that it represents an average over two or more events, pre- and post-dating the founder event experienced by AJ in late medieval times. The time of the pre-bottleneck admixture event, which was likely Southern European, was estimated to ≈25–50 generations ago.

Principal Component Analysis (PCA) of the European and Middle-Eastern samples used as reference panels in our study. The analysis was performed using SmartPCA [25] with default parameters (except no outlier removal). The populations included within each region are listed in Table 1 of the main text. The PCA plot supports the partitioning of the European and Middle-Eastern populations into the broad regional groups used in the analysis.

Interesting excerpts:

(…) AJ genetics defies simple demographic theories. Hypotheses such as a wholly Khazar, Turkish, or Middle-Eastern origin have been disqualified [4–7, 17, 55], but even a model of a single Middle-Eastern and European admixture event cannot account for all of our observations. The actual admixture history might have been highly complex, including multiple geographic sources and admixture events. Moreover, due to the genetic similarity and complex history of the European populations involved (particularly in Southern Europe [51]), the multiple paths of AJ migration across Europe [10], and the strong genetic drift experienced by AJ in the late Middle Ages [9, 16], there seems to be a limit on the resolution to which the AJ admixture history can be reconstructed.

A proposed model for the recent AJ history. The proposed intervals for the dates and admixture proportions are based on multiple methods, as described in the main text.

Historical model and interpretation

Under our model, admixture in Europe first happened in Southern Europe, and was followed by a founder event and a minor admixture event (likely) in Eastern Europe. Admixture in Southern Europe possibly occurred in Italy, given the continued presence of Jews there and the proposed Italian source of the early Rhineland Ashkenazi communities [3]. What is perhaps surprising is the timing of the Southern European admixture to ≈24–49 generations ago, since Jews are known to have resided in Italy already since antiquity. This result would imply no gene flow between Jews and local Italian populations almost until the turn of the millennium, either due to endogamy, or because the group that eventually gave rise to contemporary Ashkenazi Jews did not reside in Southern Europe until that time. More detailed and/or alternative interpretations are left for future studies.

Recent admixture in Northern Europe (Western or Eastern) is consistent with the presence of Ashkenazi Jews in the Rhineland since the 10th century and in Poland since the 13th century. Evidence from the IBD analysis suggests that Eastern European admixture is more likely; however, the results are not decisive. An open question in AJ history is the source of migration to Poland in late Medieval times; various speculations have been proposed, including Western and Central Europe [2, 10]. The uncertainty on whether gene flow from Western Europeans did or did not occur leaves this question open.

The effect of gene flow from the Middle-East into Southern EU on f4 statistics. Panels (A) and (B) demonstrate f4(West-EU,YRI;AJ,ME) and f4(South-EU,YRI;AJ,ME), respectively (cf S4A Fig). Paths from the Middle-East into AJ are indicated with red arrows; paths from YRI to Western or Southern Europe with green arrows. The f4 statistic is proportional to the total overlap between these paths (black bars). Whereas panel (B) (f4(South-EU,YRI;AJ,ME)) has more overlapping branches than in (A), migration from the Middle-East into Southern EU introduces a branch where the arrows run in opposite directions (patterned bar). Hence, the observed f4 statistic in (B) may be lower (depending on branch lengths) than in (A), even if Southern EU is the true source of gene flow into AJ.

Featured image: Expulsions of Jews, from Wikipedia.

Y-DNA relevant in the postgenomic era, mtDNA study of Iron Age Italic population, and reconstructing the genetic history of Italians


Open Access Annals of Human Biology (2018), Volume 45, Issue 1, with the title Human population genetics of the Mediterranean.

Among the most interesting articles (emphasis mine):

Iron Age Italic population genetics: the Piceni from Novilara (8th–7th century BC), by Serventi, Panicucci, Bodega, et al.

Background: Archaeological data provide evidence that Italy, during the Iron Age, witnessed the appearance of the first communities with well defined cultural identities. To date, only a few studies report genetic data about these populations and, in particular, the Piceni have never been analysed.

Aims: To provide new data about mitochondrial DNA (mtDNA) variability of an Iron Age Italic population, to understand the contribution of the Piceni in shaping the modern Italian gene pool and to ascertain the kinship between some individuals buried in the same grave within the Novilara necropolis.

Subjects and methods: In a first set of 10 individuals from Novilara, we performed deep sequencing of the HVS-I region of the mtDNA, combined with the genotyping of 22 SNPs in the coding region and the analysis of several autosomal markers.

Results: The results show a low nucleotide diversity for the inhabitants of Novilara and highlight a genetic affinity of this ancient population with the current inhabitants of central Italy. No family relationship was observed between the individuals analysed here.

Conclusions: This study provides a preliminary characterisation of the mtDNA variability of the Piceni of Novilara, as well as a kinship assessment of two peculiar burials.

Reconstructing the genetic history of Italians: new insights from a male (Y-chromosome) perspective, by Grugni, Raveani, Mattioli, et al.

Background: Due to its central and strategic position in Europe and in the Mediterranean Basin, the Italian Peninsula played a pivotal role in the first peopling of the European continent and has been a crossroad of peoples and cultures since then.

Aim: This study aims to gain more information on the genetic structure of modern Italian populations and to shed light on the migration/expansion events that led to their formation.

Subjects and methods: High resolution Y-chromosome variation analysis in 817 unrelated males from 10 informative areas of Italy was performed. Haplogroup frequencies and microsatellite haplotypes were used, together with available data from the literature, to evaluate Mediterranean and European inputs and date their arrivals.

Results: Fifty-three distinct Y-chromosome lineages were identified. Their distribution is in general agreement with geography, southern populations being more differentiated than northern ones.

Conclusions: A complex genetic structure reflecting the multifaceted peopling pattern of the Peninsula emerged: southern populations show high similarity with those from the Middle East and Southern Balkans, while those from Northern Italy are close to populations of North-Western Europe and the Northern Balkans. Interestingly, the population of Volterra, an ancient town of Etruscan origin in Tuscany, displays a unique Y-chromosomal genetic structure.

Frequencies of the main Y-chromosome haplogroups E1b, J2 and R1b and their sub-clades in the 10 analysed Italian population samples. Black sectors in the primary pies are proportional to the frequency of the main haplogroup in each population. Coloured sectors in the secondary pies are proportional to the frequencies of sub-haplogroups within the relative main haplogroup.

Mitochondrial variability in the Mediterranean area: a complex stage for human migrations, by De Angelis, Scorrano, Martínez-Labarga, et al.

Context: The Mediterranean area has always played a significant role in human dispersal due to the large number of migratory events contributing to shape the cultural features and the genetic pool of its populations.

Objective: This paper aims to review and diachronically describe the mitogenome variability in the Mediterranean population and the main demic diffusions that occurred in this area over time.

Methods: Frequency distributions of the leading mitochondrial haplogroups have been geographically and chronologically evaluated. The variability of U5b and K lineages has been focussed to broaden the knowledge of their genetic histories.

Results: The mitochondrial genetic makeup of Palaeolithic hunter-gatherers is poorly defined within the extant Mediterranean populations, since only a few traces of their genetic contribution are still detectable. The Neolithic lineages are more represented, suggesting that the Neolithic revolution had a marked effect on the peopling of the Mediterranean area. The largest effect, however, was provided by historical migrations.

Conclusion: Although the mitogenome variability has been widely used to try and clarify the evolution of the Mediterranean genetic makeup throughout almost 50 000 years, it is necessary to collect whole genome data on both extinct and extant populations from this area to fully reconstruct and interpret the impact of multiple migratory waves and their cultural and genetic consequences on the structure of the Mediterranean populations.

Major migratory routes with the associated mtDNA haplogroups for the Upper Palaeolithic (solid lines) and the Neolithic (dashed lines) chronologies. Other hypothetical migratory routes are presented with dotted lines (see text for more details).

Mediterranean Y-chromosome 2.0—why the Y in the Mediterranean is still relevant in the postgenomic era, by Larmuseau & Ottoni.

Context: Due to its unique paternal inheritance, the Y-chromosome has been a highly popular marker among population geneticists for over two decades. Recently, the advent of cost-effective genome-wide methods has unlocked information-rich autosomal genomic data, paving the way to the postgenomic era. This seems to have announced the decreasing popularity of investigating Y-chromosome variation, which provides only the paternal perspective of human ancestries and is strongly influenced by genetic drift and social behaviour.

Objective: For this special issue on population genetics of the Mediterranean, the aim was to demonstrate that the Y-chromosome still provides important insights in the postgenomic era and in a time when ancient genomes are becoming exponentially available.

Methods: A systematic literature search on Y-chromosomal studies in the Mediterranean was performed.

Results: Several applications of Y-chromosomal analysis with future opportunities are formulated and illustrated with studies on Mediterranean populations.

Conclusions: There will be no reduced interest in Y-chromosomal studies going from reconstruction of male-specific demographic events to ancient DNA applications, surname history and population-wide estimations of extra-pair paternity rates. Moreover, more initiatives are required to collect population genetic data of Y-chromosomal markers for forensic research, and to include Y-chromosomal data in GWAS investigations and studies on male infertility.

Two-dimensional plot of the PCA of Y-chromosomal haplogroup frequencies of modern populations from Europe, the Near and Middle East and North Africa. Symbols are as in the legend. The inset shows the plot of factor coordinates of the variables used.

We are clearly seeing in the latest genomic papers that Y-DNA was indeed extremely important to assess ancient population movements.

See also: