The Caucasus as an Asymmetric Semipermeable Barrier to Ancient Human Migrations (original) (raw)

Journal Article

,

1Estonian Biocentre, Tartu, Estonia

2Institute of Biochemistry and Genetics, Ufa Research Center, Russian Academy of Sciences, Ufa, Russia

3Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia

†

These authors contributed equally to this work.

Search for other works by this author on:

,

1Estonian Biocentre, Tartu, Estonia

†

These authors contributed equally to this work.

Search for other works by this author on:

,

1Estonian Biocentre, Tartu, Estonia

4Department of Evolutionary Biology, University of Tartu, Tartu, Estonia

†

These authors contributed equally to this work.

Search for other works by this author on:

,

1Estonian Biocentre, Tartu, Estonia

2Institute of Biochemistry and Genetics, Ufa Research Center, Russian Academy of Sciences, Ufa, Russia

3Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia

Search for other works by this author on:

,

1Estonian Biocentre, Tartu, Estonia

Search for other works by this author on:

,

4Department of Evolutionary Biology, University of Tartu, Tartu, Estonia

Search for other works by this author on:

,

1Estonian Biocentre, Tartu, Estonia

Search for other works by this author on:

,

4Department of Evolutionary Biology, University of Tartu, Tartu, Estonia

Search for other works by this author on:

,

1Estonian Biocentre, Tartu, Estonia

5Human Genetics Group, Institute of Molecular Biology, Academy of Sciences of Armenia, Yerevan, Armenia

Search for other works by this author on:

,

2Institute of Biochemistry and Genetics, Ufa Research Center, Russian Academy of Sciences, Ufa, Russia

3Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia

Search for other works by this author on:

... Show more

†

These authors contributed equally to this work.

Associate editor: Sohini Ramachandran

Author Notes

Published:

13 September 2011

• PDF
• Split View
• • Article contents
  • Figures & tables
  • Video
  • Audio
  • Supplementary Data
• Cite

Cite

Bayazit Yunusbayev, Mait Metspalu, Mari Järve, Ildus Kutuev, Siiri Rootsi, Ene Metspalu, Doron M. Behar, Kärt Varendi, Hovhannes Sahakyan, Rita Khusainova, Levon Yepiskoposyan, Elza K. Khusnutdinova, Peter A. Underhill, Toomas Kivisild, Richard Villems, The Caucasus as an Asymmetric Semipermeable Barrier to Ancient Human Migrations, Molecular Biology and Evolution, Volume 29, Issue 1, January 2012, Pages 359–365, https://doi.org/10.1093/molbev/msr221
Close

Navbar Search Filter Mobile Enter search term Search

Abstract

The Caucasus, inhabited by modern humans since the Early Upper Paleolithic and known for its linguistic diversity, is considered to be important for understanding human dispersals and genetic diversity in Eurasia. We report a synthesis of autosomal, Y chromosome, and mitochondrial DNA (mtDNA) variation in populations from all major subregions and linguistic phyla of the area. Autosomal genome variation in the Caucasus reveals significant genetic uniformity among its ethnically and linguistically diverse populations and is consistent with predominantly Near/Middle Eastern origin of the Caucasians, with minor external impacts. In contrast to autosomal and mtDNA variation, signals of regional Y chromosome founder effects distinguish the eastern from western North Caucasians. Genetic discontinuity between the North Caucasus and the East European Plain contrasts with continuity through Anatolia and the Balkans, suggesting major routes of ancient gene flows and admixture.

Introduction

The earliest evidence of the dispersal of the genus Homo outside Africa comes from the Caucasus, a mountainous region between the Black and Caspian Seas, linking the Near/Middle East and the East European Plain (Lieberman 2007; Lordkipanidze et al. 2007). Anatomically modern humans appeared there at least 42,000 years ago (Adler et al. 2008). The early Upper Paleolithic (UP) sites in the Caucasus (Bar-Yosef et al. 2006; Pinhasi et al. 2008) and the adjacent East European Plain (Krause et al. 2010) are nearly contemporary, whereas the lower Danube Basin UP temporal estimates (Mellars 2006) predate the northern Pontocaspian UP by several thousands of years. This makes the two paths—across the Caucasus and via Anatolia and the Balkans—equally plausible for the pioneer phase of peopling of East Europe. Likewise, people from both the Caucasus and the East European Last Glacial Maximum (LGM) refugia (Adams and Faure 1997; Tarasov et al. 2000) may have been the source population for the repopulation of East Europe after the LGM, whereas the route across the Caucasus may have been used by early farmers to reach the northern areas. A second set of intriguing issues is related to the linguistic diversity of the Caucasus. Although the Abkhazian-Adyghe (Northwest [NW] Caucasian), Nakh-Dagestanian (Northeast [NE] Caucasian), and Kartvelian (South Caucasian) language families are indigenous for the area, several additional languages of the Indo-European and Turkic families have been brought to the Caucasus by people migrating from elsewhere, presumably much later, and are spoken there at present (Comrie 2008) (fig. 1A). But the role of the Caucasus in human dispersals in Eurasia has remained obscure, and the extent to which the unique cultural and linguistic diversity of the Caucasus is reflected in the genetic diversity of the extant populations in the region has been studied only from the uniparental perspective (Nasidze et al. 2003; Nasidze et al. 2004; Roostalu et al. 2007; Underhill et al. 2010; Balanovsky et al. 2011; Myres et al. 2011). Accordingly, here, we address several so far unsolved problems: Does the present-day genetic structuring of Eurasian populations offer an insight to the peopling of the Caucasus and to later prehistoric and historic migrations to and from the Caucasus? How and to what extent is the present-day remarkable linguistic diversity of the region reflected in its autosomal and gender-specific genetic variation?

FIG. 1.

(A) geographical map of the populations of the Caucasus included in this study. The language family affiliation of each population is given. Adapted from Wikipedia. (B) Pairwise _F_ST distances between the Caucasus and neighboring populations, ranging from red (low) to blue (high), based on autosomal data. The populations (data from this study and the literature; Li et al. 2008; Behar et al. 2010) are divided into regional groups. (C) Plot of the first and second components of the PCA of the Caucasus and neighboring populations based on autosomal data, with the clustering of populations approximating geography. The thick lines denote probable directions of movements of people, interrupted between the North Caucasus and Eastern Europe. Despite the genetic discontinuity between the Caucasus and the East European Plain, some admixture (denoted by the thin two-pointed arrow) has occurred, apparent from the several samples occupying the gap between the regions. For population abbreviations see supplementary table S1 (Supplementary Material online). (D) Population structure inferred by ADMIXTURE analysis of the autosomal data at K = 7. Each individual is represented by a vertical (100%) stacked column of ancestry probabilities in the seven constructed ancestral populations. Populations introduced in this study and analyzed together with data from Li et al. (2008), Behar et al. (2010) and Rasmussen et al. (2010) are labeled in red. Language families of the Caucasus populations are also denoted: AA, Abkhazian-Adyghe; ND, Nakh-Dagestanian; KV, Kartvelian; IE, Indo-European; TU, Turkic.

Materials and Methods

DNA samples from all the subregions and major language groups of the Caucasus (fig. 1A) were analyzed using whole genome, Y chromosome, and mitochondrial DNA (mtDNA) markers. DNA samples were obtained from unrelated male volunteers after getting informed consent in accordance with the guidelines of the ethical committees of the institutions involved. DNA was purified from blood by the phenol/chloroform extraction method. DNA concentrations were determined by spectrometry (NanoDrop products, Wilmington, DE).

Autosomal Analyses

Two hundred and four samples from this study were genotyped with the Illumina 610 K single nucleotide polymorphism (SNP) array and used for whole-genome analysis together with 929 samples from the literature (Li et al. 2008; Behar et al. 2010; Rasmussen et al. 2010) (supplementary tableS1, Supplementary Material online).

Genetic Clustering Analysis

We used ADMIXTURE (Alexander et al. 2009) implementing a structure-like (Pritchard et al. 2000) model-based maximum likelihood clustering algorithm to assess population structure. We used PLINK software 1.05 (Purcell et al. 2007) to filter the combined data set to include only SNPs on the 22 autosomal chromosomes with minor allele frequency >1% and genotyping success >97%. Because background linkage disequilibrium (LD) can affect both principal component analysis (PCA) and structure-like analysis, we thinned the marker set by excluding SNPs in strong LD (pairwise genotypic correlation _r_2 > 0.4) in a window of 200 SNPs (sliding the window by 25 SNPs at a time). The final data set consisted of 210,575 SNPs and 1119 individuals that were used in subsequent analyses.

PCA and _F_ST

Since the PCA method (Patterson et al. 2006) assumes that markers are unlinked, we thinned our marker set for this analysis with PLINK software 1.05 (Purcell et al. 2007) according to the same parameters used for genetic clustering analysis in order to mitigate background LD. However, LD pruning was carried out after the exclusion of the populations from Africa (except Egyptians), East Asia, and Siberia and also Hazaras, Kurds, Uygurs, and Altaians, resulting in a final data set of 212,398 markers and 848 individuals. PCA was carried out in the smartpca program (Patterson et al. 2006) using outlier removal procedure (5 outliers were removed, leaving 843 individuals). Pairwise genetic differentiation indices (_F_ST values) were also estimated using smartpca software based on the same thinned marker set. The Gplots R package (http://cran.r-project.org/web/packages/gplots/index.html) was used to graphically represent genetic similarities between populations by color-coding pairwise _F_ST values on a heatmap.

Geodesic Distances between Populations

For each pair of populations, we calculated geodesic distances in kilometers using “distonearth” R function (Banerjee 2005). Geographic coordinates for populations in the HGDP data set are given as ranges of longitude and latitude in Cann et al. (2002). Geographic coordinates for HGDP populations were computed as a central point in a range of longitude and latitude values.

Multiple Regression on Distance Matrices

We used multiple regression on distance matrices (MRM) (Manly 1986; Smouse et al. 1986; Legendre et al. 1994; Goslee and Urban 2007) to explore various explanatory variables (genetic distance, barriers to gene flow), predicting the genetic distances between populations. In this method, a single dependent distance matrix Y is considered as a function of multiple independent distance matrices Xi (independent variables), and the statistical significance of regression coefficients for each independent variable Xi is tested based on matrix permutations (Legendre et al. 1994). The corresponding permutation procedure is described in Legendre et al. (1994) and implemented in the “ecodist” R package (Goslee and Urban 2007).

In order to test whether factors other than geographic distance can explain the observed variation in genetic distances between populations and whether the contribution of each variable is statistically significant, we considered a matrix of pairwise _F_ST distances between populations as a response matrix and included explanatory variables into the regression model either separately or in combinations, defining them as putative barriers (supplementary table S2; supplementary note 1, Supplementary Material online).

Y Chromosome Analyses

A total of 1952 samples from 24 populations from the Caucasus were analyzed for Y chromosome markers. The samples were typed for 52 Y chromosome SNP markers, analyzed by PCR/AFLP, PCR/RFLP, or PCR/sequencing methods. The haplogroup designation in this study follows the most recent YCC nomenclature presented in Karafet et al. (2008). Genotyping results are presented in supplementary table S3 (Supplementary Material online).

In addition, a subset of the samples was analyzed for 19 Y chromosome STR markers. The phylogenetic network of the data obtained was constructed with the program Network 4.5.0.0 (Fluxus-Engineering), using the median-joining algorithm (supplementary fig. S1, Supplementary Material online). Spatial frequency maps (supplementary figs. S2–S4, Supplementary Material online) were drawn with the program Surfer 8 (Golden Software Inc., Cold Spring Harbor, NY). Coalescence ages (supplementary table S4, Supplementary Material online) were calculated according to the ASD0 method (Zhivotovsky et al. 2004).

mtDNA Analyses

The haplogroups of 2262 mtDNA samples from 24 Caucasus populations were determined by typing HVSI, HVSII, and coding region markers (supplementary table S5, Supplementary Material online), analyzed by PCR/RFLP or PCR/sequencing methods. The nomenclature of the Global Human Mitochondrial DNA Phylogenetic Tree (http://www.phylotree.org) was used. Genotyping results are presented in Supplementary DataSupplementary Data (Supplementary Material online).

Both Y chromosome and mtDNA haplogroup frequency data of the Caucasus populations together with data of neighboring populations from the literature were used for PCA using the POPSTR software (http://harpending.humanevo.utah.edu/popstr/). The methods used are described in greater detail in supplementary note 1 (Supplementary Material online).

Results and Discussion

Our autosomal data, in the form of a heatmap plot of _F_ST distances (fig. 1B) reveal three clusters of low genetic distance, encompassing geographically nearby populations: the Near/Middle East, the Caucasus, and Europe. Note that these clusters overlap partially in phylogeographically informative ways. Europe is not as homogenous as the other clusters, with the French Basques and Volga Basin Turkic-speaking Chuvashes being clearly more distant from their immediate neighbor populations, whereas geographically somewhat southern populations, from the Atlantic to the Black Sea (French, Italians, Bulgarians, and Romanians), exhibit particularly low interpopulation genetic distances. The populations of the Caucasus, irrespective of their linguistic differences, show the lowest autosomal genetic distances to one another, followed closely by their distance to the populations of the Near/Middle East, Turks in particular (fig. 1B). The Indo-European-speaking Armenians and Ossetians follow the same pattern and do not show higher genetic similarity to Indo-European-speaking populations from Europe or the Near/Middle East. The smooth transition from the Caucasus to Anatolia (Turks) and Iran and from the latter to Syrians, Lebanese, Jordanians and further southward contrasts with the sharp border between the Caucasians and the Slavic, Finno-Ugric– and Turkic-speaking populations of the East European Plain. However, the same heatmap plot reveals a range of low genetic distances starting from the populations of the Levant and Syria, extending to the East European Plain. Importantly, this series proceeds around the western flank of the Black Sea: from Turks to Bulgarians to Romanians to Ukrainians to Russians, ending with Mordvins, but does not extend through the Caucasus. We suggest that this “similarity gradient” reflects most likely a combination of several ancient human migrations, perhaps also including elements of the spread of the Neolithic. A previous study based on eight Alu insertion loci found the Caucasus populations to exhibit high levels of between-population differentiation, with an average _F_ST of 0.113, a value which is almost as large as the _F_ST of 0.157 for worldwide populations (Nasidze et al. 2001). Our results, based on genome-wide data, reveal instead that the populations of the Caucasus region show between population differentiation (average _F_ST = 0.004) that is slightly lower than that for the Near East (0.006) and Europe (0.006) and are thus more consistent with the results of Bulayeva et al. (2003).

Similarly to our _F_ST analysis, PCA of the autosomal data shows the within-region clustering of the Caucasian populations and reveals a noticeable gap between the Caucasus and the East European Plain, contrasting the continuous transition from the Near/Middle East to the Caucasus (fig. 1C; supplementary fig. S5 and S6, Supplementary Material online). Geography rather than language-based clustering can also be observed in the PC analysis of Y chromosome data (supplementary fig. S7, Supplementary Material online). Indeed, we see a clustering of Georgians, who belong to the Kartvelian language family, and Indo-European–speaking Armenians from the South Caucasus, together with the peoples of the NW Caucasus, of which the Karachays and Balkars speak Turkic, the Ossetians Indo-Iranian, and the remainder Abkhazian-Adyghe languages (supplementary fig. S7, Supplementary Material online). The Nakh and Dagestanian language speakers, however, differ considerably both from each other and the rest of the Caucasian populations due to the unique structure of Y chromosome haplogroup frequencies in the NE Caucasus (supplementary note 2, Supplementary Material online), but this distinction is not supported by autosomal or mtDNA data, consistent with the results of an earlier study where highland Dagestanian populations were found to have reduced Y chromosomal but not mitochondrial or autosomal genetic diversity (Marchani et al. 2008). The Caucasian populations do not differ in common mtDNA haplogroup frequencies to an extent that would allow the discrimination of geographic subregions or language groups (supplementary fig. S8, Supplementary Material online).

We also analyzed the autosomal data of the Caucasus and reference populations (Li et al. 2008; Behar et al. 2010; Rasmussen et al. 2010) using a structure-like (Pritchard et al. 2000) clustering approach (Alexander et al. 2009). At K = 7, the major ancestry component of the Caucasus populations (shown in blue) has comparable presence in the Near/Middle East but is almost absent among the immediate northern neighbors of the Caucasus—the populations of the East European Plain (fig. 1D; supplementary fig. S9, Supplementary Material online). Similarly to the blue ancestry component, the green component is also ubiquitously present among the Caucasus populations, irrespective of their linguistic affinities, but at much lower frequencies than blue. The green component is most frequent in the Indus basin (Pakistan), extending to Central Asia and the Near/Middle East, but fading away in Europe. Structure-like clustering cannot be readily interpreted into (human) migrations. Thus, this pattern might reflect shared ancestry or suggest a gene flow from South Asia to the west and northwest. The ancestry component depicted with orange, ubiquitous in East Asia, is almost absent in the South Caucasus and remains at very low frequencies among the North Caucasian populations as well, with an only slightly stronger presence among the Turkic-speaking Balkars. Due to their distinct population history (see below), the Kuban Nogays, living on the northern slopes of the Caucasus, form an exception. The only population in the Caucasus that shares the other major Near/Middle Eastern, North, and East African ancestry component, depicted in light blue (fig. 1D), are the Armenians, indicating the introduction of a genetic component novel to the region.

Nevertheless, the mountain range that divides the Caucasus into the North and South Caucasus has apparently not been an impenetrable barrier for gene flows. This is illustrated by the relative similarity of the ancestry component patterns of the Caucasus populations on either side of the High Caucasus Mountain Range (fig. 1D). However, the dark blue ancestry component, dominant among the Slavic-, Turkic-, and Finnic-speaking East European Plain populations, reaches the North Caucasus (10–20%), but just barely (∼5%) crosses the High Caucasus to the three linguistically distinct South Caucasus populations—Armenians, Georgians, and Abkhazians (fig. 1D). Remarkably, the decrease of Y chromosome haplogroup G and J1 frequencies toward the Eastern European populations inhabiting the area adjacent to the North Caucasus, such as southern Russians and Ukrainians (Balanovsky et al. 2008), forms an abrupt boundary (supplementary figs. S2 and S3, Supplementary Material online), indicating that patrilineal gene flow from the Caucasus in the northern direction has been negligible. This sets a frontier of genetic discontinuity not at the mountain range itself but between the North Caucasus and East European Plain. However, similarly to autosomal data, there is some evidence of opposite gene flow from East Europe into the populations of NW Caucasus, as demonstrated by the presence of Y chromosome haplogroups R1a1, including the European-specific lineage R1a1-M458 (Underhill et al. 2010; Balanovsky et al. 2011) and I2a (supplementary table S3, Supplementary Material online) and of certain sublineages of the mtDNA haplogroup H (Roostalu et al. 2007). Equally importantly, these Y chromosome data also show a genetic continuity between the NW Caucasus and South Caucasus populations that sets them apart from the populations inhabiting the NE Caucasus (supplementary fig. S7, Supplementary Material online).

Thus, several lines of evidence suggest a genetic discontinuity between the Caucasus and the East European Plain. To test whether this pattern is statistically significant, we used multiple regression on distance matrices (Legendre et al. 1994; Goslee and Urban 2007) to model genetic distances based on geographic distances. We built a series of distance matrices (see Materials and Methods for details), incorporated additional factors known to increase genetic dissimilarity as putative barriers (supplementary table S2; supplementary note 1, Supplementary Material online), and used multiple regression to estimate their relative importance in predicting genetic distances and statistical significance (Legendre et al. 1994; Goslee and Urban 2007). Three of the putative barriers we tested first were geographic—the Caucasus barrier between North Caucasus and Eastern Europe, the Balkans barrier between Anatolia and Europe, and the South Asian barrier between South Asia and the Near/Middle East. The South Asian barrier, a presumably nonexistent factor, was intentionally considered as a control of the method, and only a slight increase in the coefficient of determination (_r_2 increased by 0.1%) was observed, most likely by chance since the regression coefficient for this factor is not statistically significant (supplementary table S2, Supplementary Material online). The other barriers tested separated populations that are known isolates/outliers due to religion, language, or different origin—the Jewish groups, Kuban Nogays, French Basques, Druze, and Burusho—from their respective surrounding populations. Geographic distance by itself explained only 43% (coefficient of determination _r_2 = 0.43) of the variation in genetic distances between populations, measured by _F_ST. The putative Kuban Nogay, French Basque, Druze, Iraqi Jewish, Georgian Jewish, and Burusho barriers did not prove to be statistically significant (supplementary table S2, Supplementary Material online). The largest improvement in the fit of the observed _F_ST distances between populations to the model was achieved with the assumption of a Caucasus barrier—_r_2 increased by 0.12 (supplementary table S2, Supplementary Material online).

It should be noted that the effect of the Caucasus barrier is observed between the populations of the northern flank of the High Caucasus Mountain Range and the East European Plain, not at the mountain range itself, since the populations of North and South Caucasus are autosomally more similar to each other than either group is to Eastern European populations. A putative post-LGM northward progression of people (recolonization?) could have been halted due to pre-existing inhabitation of the East European Plain, possibly at higher population densities than in the mountains and may have been additionally inhibited by the Khvalynian transgression, a connection between the Black and Caspian Seas dated 12–14,000 years BP (Badyukova 2007; Svitoch 2009), which may have served as a natural barrier (see also supplementary note 2, Supplementary Material online).

The Kuban Nogays and the Kara Nogays (fig. 1A) have a special status among the Caucasian populations due to their recent, late 18th to early 19th century arrival from the Pontocaspian steppes (Kolga et al. 2001). It has been shown earlier that the Nogays possess 40% of East Eurasian mtDNA lineages (Bermisheva et al. 2004). Although the Kara Nogays have more (∼35%) typical eastern Y chromosome lineages than the Kuban Nogays (17%) (supplementary table S3, Supplementary Material online), it is perhaps more interesting that both the Kuban Nogays and the Kara Nogays preserve a certain combination of STR haplotypes in the Y chromosome haplogroup C, the so-called Genghis Khan modal haplotype (Zerjal et al. 2003). Because the historic Nogay Khan, a powerful late 13th century general of the Golden Horde, was indeed a great-grandson of Genghis Khan, such a coincidence is intriguing.

Conclusions

We conclude that irrespective of the Early UP presence of anatomically modern humans both south and north of the Caucasus (Mellars 2006; Adler et al. 2008; Krause et al. 2010), the combined autosomal and gender-specific genetic variation of the Caucasian populations testifies to their predominantly southern, Near/Middle Eastern descent. Y chromosomal variants under strong founder events, seen in particular among populations inhabiting the northern flank of the High Caucasus Mountain Range, appear to never have expanded to the East European Plain, whereas the nomadic people of the latter, once settled down predominantly on the northern slopes of the Caucasus, have likely preserved, to different extent, some of their earlier genetic heritage. In sum, though the Caucasus may well have served as a corridor for numerous invasive expeditions in the past, this has had only a minor influence on the largely sedentary core populations of the region, characterized by much greater autosomal uniformity than that might be expected from a region of deep linguistic and cultural diversity. This suggests that the core of the autosomal genetic structure of the Caucasian populations may have formed before its present-day linguistic diversity, including the language families autochthonous for the region, arose.

We thank the individuals who provided DNA samples for this study, and Mari Nelis, Georgi Hudjashov, and Viljo Soo for conducting the autosomal genotyping. This work was supported by the European Commission, Directorate-General for Research (FP7 Ecogene grant number 205419 to R.V. and D.M.B.); the European Union Regional Development Fund through the Centre of Excellence in Genomics to R.V.; the Estonian Ministry of Education and Research (Basic Research grant numbers SF 0270177As08 to R.V. and SF 0270177Bs08 to E.M.); the Swedish Collegium for Advanced Studies to R.V.; the Estonian Science Foundation (grant numbers 7445 to S.R., 7858 to E.M., and 8973 to M.M.); the Russian Academy of Sciences Program for Fundamental Research “Biodiversity and dynamics of gene pools” to E.K.K.; the Ministry of Education and Science of the Russian Federation (state contracts P-325 and 02.740.11.07.01 to E.K.K.); the Russian Foundation for Basic Research (grant numbers 04-04-48678-a and 07-04-01016-a to E.K.K. and 08-06-97011 to I.K.); the President of the Russian Federation (grant of state support for young Russian scientists number MK-488.2006.4 to I.K.); and the Sorenson Molecular Genealogy Foundation to P.A.U.

References

Preliminary vegetation maps of the world since the last glacial maximum: an aid to archaeological understanding

,

J Archaeol Sci.

,

1997

, vol.

24

(pg.

623

-

647

)

Dating the demise: neandertal extinction and the establishment of modern humans in the southern Caucasus

,

J Hum Evol.

,

2008

, vol.

55

(pg.

817

-

833

)

Fast model-based estimation of ancestry in unrelated individuals

,

Genome Res.

,

2009

, vol.

19

(pg.

1655

-

1664

)

Age of Khvalynian transgressions in the Caspian Sea region

,

Oceanology

,

2007

, vol.

47

(pg.

400

-

405

)

et al.

(23 co-authors)

Parallel evolution of genes and languages in the Caucasus region

,

Mol Biol Evol.

,

2011

, vol.

28

(pg.

2905

-

2920

)

et al.

(11 co-authors)

Two sources of the Russian patrilineal heritage in their Eurasian context

,

Am J Hum Genet.

,

2008

, vol.

82

(pg.

236

-

250

)

On geodetic distance computations in spatial modeling

,

Biometrics

,

2005

, vol.

61

(pg.

617

-

625

)

The implications of the Middle-Upper Paleolithic chronological boundary in the Caucasus to Eurasian prehistory

,

Anthropologie

,

2006

, vol.

XLIV

(pg.

49

-

60

)

et al.

(21 co-authors)

The genome-wide structure of the Jewish people

,

Nature

,

2010

, vol.

466

(pg.

238

-

242

)

Phylogeografic analysis of mitochondrial DNA in the Nogays: the high level of mixture of maternal lineages from Eastern and Western Eurasia

,

Mol Biol (Mosk).

,

2004

, vol.

38

(pg.

617

-

624

)

Genetics and population history of Caucasus populations

,

Hum Biol.

,

2003

, vol.

75

(pg.

837

-

853

)

et al.

(41 co-authors)

A human genome diversity cell line panel

,

Science

,

2002

, vol.

296

(pg.

261

-

262

)

Linguistic diversity in the Caucasus

,

Annu Rev Anthropol.

,

2008

, vol.

37

(pg.

131

-

143

)

The ecodist package for dissimilarity-based analysis of ecological data

,

J Stat Softw.

,

2007

, vol.

22

(pg.

1

-

19

)

New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree

,

Genome Res.

,

2008

, vol.

18

(pg.

830

-

838

)

,

The red book of the peoples of the Russian Empire

,

2001

Tallinn (Estonia)

NGO Red Book

A complete mtDNA genome of an early modern human from Kostenki, Russia

,

Curr Biol.

,

2010

, vol.

20

(pg.

231

-

236

)

Modeling brain evolution from behavior: a permutational regression approach

,

Evolution

,

1994

, vol.

48

(pg.

1487

-

1499

)

et al.

(11 co-authors)

Worldwide human relationships inferred from genome-wide patterns of variation

,

Science

,

2008

, vol.

319

(pg.

1100

-

1104

)

Palaeoanthropology: homing in on early Homo

,

Nature

,

2007

, vol.

449

(pg.

291

-

292

)

et al.

(18 co-authors)

Postcranial evidence from early Homo from Dmanisi, Georgia

,

Nature

,

2007

, vol.

449

(pg.

305

-

310

)

Randomization and regression methods for testing for associations with geographical, environmental and biological distances between populations

,

Res Popul Ecol.

,

1986

, vol.

28

(pg.

201

-

218

)

Culture creates genetic structure in the Caucasus: autosomal, mitochondrial, and Y-chromosomal variation in Daghestan

,

BMC Genet.

,

2008

, vol.

9

pg.

47

A new radiocarbon revolution and the dispersal of modern humans in Eurasia

,

Nature

,

2006

, vol.

439

(pg.

931

-

935

)

et al.

(20 co-authors)

A major Y-chromosome haplogroup R1b Holocene era founder effect in Central and Western Europe

,

Eur J Hum Genet.

,

2011

, vol.

19

(pg.

95

-

101

)

et al.

(17 co-authors)

Mitochondrial DNA and Y-chromosome variation in the Caucasus

,

Ann Hum Genet.

,

2004

, vol.

68

(pg.

205

-

221

)

Alu insertion polymorphisms and the genetic structure of human populations from the Caucasus

,

Eur J Hum Genet.

,

2001

, vol.

9

(pg.

267

-

272

)

Testing hypotheses of language replacement in the Caucasus: evidence from the Y-chromosome

,

Hum Genet.

,

2003

, vol.

112

(pg.

255

-

261

)

Population structure and eigenanalysis

,

PLoS Genet.

,

2006

, vol.

2

(pg.

2074

-

2093

)

et al.

(13 co-authors)

Hovk 1 and the Middle and Upper Paleolithic of Armenia: a preliminary framework

,

J Hum Evol.

,

2008

, vol.

55

(pg.

803

-

816

)

Inference of population structure using multilocus genotype data

,

Genetics

,

2000

, vol.

155

(pg.

945

-

959

)

et al.

(11 co-authors)

PLINK: a tool set for whole-genome association and population-based linkage analyses

,

Am J Hum Genet.

,

2007

, vol.

81

(pg.

559

-

575

)

et al.

(52 co-authors)

Ancient human genome sequence of an extinct Palaeo-Eskimo

,

Nature

,

2010

, vol.

463

(pg.

757

-

762

)

Origin and expansion of haplogroup H, the dominant human mitochondrial DNA lineage in West Eurasia: the Near Eastern and Caucasian perspective

,

Mol Biol Evol.

,

2007

, vol.

24

(pg.

436

-

448

)

Multiple regression and correlation extensions of the mantel test of matrix correspondence

,

Syst Zool.

,

1986

, vol.

35

(pg.

627

-

632

)

Khvalynian transgression of the Caspian Sea was not a result of water overflow from the Siberian Proglacial lakes, nor a prototype of the Noachian flood

,

Quatern Int.

,

2009

, vol.

197

(pg.

115

-

125

)

et al.

(13 co-authors)

Last glacial maximum biomes reconstructed from pollen and plant macrofossil data from northern Eurasia

,

J Biogeogr.

,

2000

, vol.

27

(pg.

609

-

620

)

et al.

(34 co-authors)

Separating the post-Glacial coancestry of European and Asian Y chromosomes within haplogroup R1a

,

Eur J Hum Genet.

,

2010

, vol.

18

(pg.

479

-

484

)

et al.

(23 co-authors)

The genetic legacy of the Mongols

,

Am J Hum Genet.

,

2003

, vol.

72

(pg.

717

-

721

)

et al.

(17 co-authors)

The effective mutation rate at Y chromosome short tandem repeats, with application to human population-divergence time

,

Am J Hum Genet.

,

2004

, vol.

74

(pg.

50

-

61

)

Author notes

†

These authors contributed equally to this work.

Associate editor: Sohini Ramachandran

© The Author 2011. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Supplementary data

Citations

Views

Altmetric

Metrics

Total Views 13,634

11,634 Pageviews

2,000 PDF Downloads

Since 11/1/2016

Citations

124 Web of Science

×

Email alerts

Email alerts

See also

• Commentary

  • The Caucasus as an Asymmetric Semipermeable Barrier to Ancient Human Migrations

Citing articles via

• Latest

• Most Read

• Most Cited

More from Oxford Academic