Indo-Europeans preceded Finno-Ugrians in Finland and Estonia

According to an abstract of a Ph.D thesis (below). This would appear to work well with the dating of the signature Y-chromosome haplogroup of Finno-Ugrians. 

Bidrag till Fennoskandiens språkliga förhistoria i tid och rum (Heikkilä, Mikko)

My academic dissertation "Bidrag till Fennoskandiens språkliga förhistoria i tid och rum" ("Spatiotemporal Contributions to the Linguistic Prehistory of Fennoscandia") is an interdisciplinary study of the linguistic prehistory of Northern Europe chiefly in the Iron Age (ca. 700 BC―AD 1200), but also to some extent in the Bronze Age (ca. 1700―700 BC) and the Early Finnish Middle Ages (ca. AD 1200―1323). The disciplines represented in this study are Germanistics, Nordistics, Finnougristics, history and archaeology. The language-forms studied are Proto-Germanic, Proto-Scandinavian, Proto-Finnic and Proto-Sami. This dissertation uses historical-comparative linguistics and especially loanword study to examine the relative and absolute chronology of the sound changes that have taken place in the proto-forms of the Germanic, Finnic and Samic languages. Phonetic history is the basis of historical linguistics studying the diachronic development of languages. To my knowledge, this study is the first in the history of the disciplines mentioned above to examine the systematic dating of the phonetic development of these proto-languages in relation to each other. In addition to the dating and relating of the phonetic development of the proto-languages, I study Fennoscandian toponyms. The oldest datable and etymologizable place-names throw new light on the ethnic history and history of settlement of Fennoscandia. For instance, I deal with the etymology of the following place-names: Ahvenanmaa/Åland, Eura(joki), Inari(järvi), Kemi(joki), Kvenland, Kymi(joki), Sarsa, Satakunta, Vanaja, Vantaa and Ähtäri. 

My dissertation shows that Proto-Germanic, Proto-Scandinavian, Proto-Finnic and Proto-Sami all date to different periods of the Iron Age. I argue that the present study along with my earlier published research also proves that a (West-)Uralic language – the pre-form of the Finnic and Samic languages – was spoken in the region of the present-day Finland in the Bronze Age, but not earlier than that. In the centuries before the Common Era, Proto-Sami was spoken in the whole region of what is now called Finland, excluding Lapland. At the beginning of the Common Era, Proto-Sami was spoken in the whole region of Finland, including Southern Finland, from where the Sami idiom first began to recede. An archaic (Northwest-)Indo-European language and a subsequently extinct Paleo-European language were likely spoken in what is now called Finland and Estonia, when the linguistic ancestors of the Finns and the Sami arrived in the eastern and northern Baltic Sea region from the Volga-Kama region probably at the beginning of the Bronze Age. For example, the names Suomi ʻFinlandʼ and Viro ʻEstoniaʼ are likely to have been borrowed from the Indo-European idiom in question. (Proto-)Germanic waves of influence have come from Scandinavia to Finland since the Bronze Age. A considerable part of the Finnic and Samic vocabulary is indeed Germanic loanwords of different ages which form strata in these languages. Besides mere etymological research, these numerous Germanic loanwords make it possible to relate to each other the temporal development of the language-forms that have been in contact with each other. That is what I have done in my extensive dissertation, which attempts to be both a detailed and a holistic treatise.

The Indo-European invasion of the Baltic

In some recent posts, I showed that South Asian populations (North Indian Brahmins, South Indian Brahmins) can be seen as mixtures of West Eurasian and South Indian populations, but also that West Eurasians (Bulgarians, Greeks, Armenians, and French) can be seen as mixtures of South Asian and Sardinian populations.

This may seem strange, but can be explained if we understand how f3-statistics and rolloff actually work. These methods do not require pure or unadmixed ancestral populations, but exploit allele frequency differences in the reference populations together with either (i) allele frequencies in the mixed population, in the case of f3-statistics, or (ii) admixture linkage disequilibrium in the mixed population, in the case of rolloff.

If a and b are allele frequencies in two ancestral populations A and B that mix, then:

• The frequency of a will shift towards b if A experiences gene flow from B
• The frequency of a will randomly shift if A experiences gene flow from an "outgroup" population
• The frequency of a will shift towards b if A experiences gene flow from a third population that is geographically and genetically intermediate between A and B

An application to the Europe-South Asia cline

I took the following set of populations, and calculated all 1,365 possible f3-statistics:

"FIN30"         "Lithuanians"   "Russian"       "Pathan"        "Balochi"       "North_Kannadi" "Polish_D"      "Russian_D"     "Mixed_Slav_D"  "Bulgarian_D"   "Serb_D"        "Ukrainian_D"   "Belorussian"   "Bulgarians_Y"  "Ukranians_Y"

In the following table, I report the lowest Z-scores for each target population (third column). So, for example, Polish_D can be seen as a mixture of Lithuanians and Balochi. Only negative scores are indicative of admixture. I highlight in bold the significant negative scores (Z less than -3)


Lithuanians North_Kannadi FIN30 0.001606 0.000259 6.193 280043
Ukrainian_D Belorussian Lithuanians 0.00078 0.000299 2.614 268493
Lithuanians North_Kannadi Russian -0.002738 0.000248 -11.045 279965
North_Kannadi Polish_D Pathan -0.006959 0.000229 -30.344 280220
North_Kannadi Bulgarians_Y Balochi -0.003636 0.000246 -14.781 281604
Pathan Ukrainian_D North_Kannadi 0.033802 0.000623 54.237 271858
Lithuanians Balochi Polish_D -0.001171 0.000178 -6.581 279519
Lithuanians Pathan Russian_D -0.001829 0.000166 -11.026 280658
Lithuanians Pathan Mixed_Slav_D -0.001715 2e-04 -8.594 277635
Lithuanians Balochi Bulgarian_D -0.001247 0.000313 -3.979 272342
Lithuanians Balochi Serb_D -0.00091 0.000377 -2.416 270807
Lithuanians Balochi Ukrainian_D -0.002222 0.000358 -6.211 270399
Lithuanians Balochi Belorussian -0.000897 0.00027 -3.325 273076
Balochi Polish_D Bulgarians_Y -0.001198 0.000185 -6.481 279632
Lithuanians Balochi Ukranians_Y -0.001727 0.000187 -9.236 278677

It is clear, that what I have described holds here: European populations appear like mixtures of Lithuanians and South Asians; conversely, South Asian populations appear like mixtures of Europeans and North Kannadi.

This does not mean that the populations that appear unadmixed (FIN30, Lithuanians, North_Kannadi, and Serbs) are in fact so, for at least two reasons:

1. The f3 statistic confirms, but does not reject the presence of admixture; in particular, it fails to find real admixture in highly drifted populations
2. The f3 statistics exploits allele frequency correlations between populations: but the North Kannadi and Lithuanians/Finns occupy opposite ends of the studied cline, so their lack of signal of admixture may be due to the non-existence of populations that are even more unadmixed than themselves.

In the case of South Indians, we are completely sure that this is the case. Reich et al. (2009) managed to show this not because there are any unadmixed Ancestral South Indians (ASI) left, but because they exploited the existence of the Onge, an isolated group from the Andaman Islands that was a sister group to the ASI. So, we can be fairly sure that southern Indians themselves have West Eurasian-like admixture, even the ones that are at the end of the West Eurasia-South India cline on its southern end.

The problem is: there is no isolated group of unadmixed Europeans left in existence that might serve a similar proxy function as the Onge did for South Asians.

Enter Pickrell et al. (2012) to the rescue. In that paper, the authors studied admixture in the Khoe-San of South Africa. Now, many of the Khoe-San sub-groups appeared to be admixed, but the "Juj'hoan North" population appeared to be at the "end of the cline": it's impossible to detect admixture in them using alelle frequency differences, because, quite simply, there are no populations that are less unadmixed than them: they're as pure descendants of "Ancestral Bushman" as exist on the earth today.

But, the clever thing is, that we don't have to detect admixture only using allele frequency differences, but also using admixture LD, i.e., by exploiting the correlation between linkage disequilibrium (the co-inheritance of physically separated markers on a chromosome) and allele frequency differences between populations. Pickrell el al. were able to do this not by conjuring up a more unadmixed population than the "Juj'hoan North" one available to them, but by splitting up that population, and using one half to find allele frequency differences, and the other half to detect admixture LD.

Admixture LD signal in Lithuanians

Using the aforementioned idea, I set out to see whether Lithuanians, who occupy the European end of the Europe-South Asia cline present such a signal of admixture LD. I used the Lithuanian_D sample from the Dodecad Project and the Balochi HGDP sample as reference populations (to calculate allele frequency differences), and the Behar et al. (2010) Lithuanians for admixture LD. There were only ~300k SNPs usuable in this set, but sufficient to detect the signal of admixture LD:

The admixture time estimate is 200.350 +/- 61.608 generations, or 5,810 +/- 1790 years. This is not very precise, probably because of the small number of SNPs and individuals used, but it certainly points to the Neolithic-to-Bronze Age for the occurrence of this admixture. The date is certainly reminiscent of the expansion of the Kurgan culture out of eastern Europe, or, the later Corded Ware culture of northern Europe.

So, it may well appear that at least some of the people participating in these groups of cultures, were indeed influenced by the Indo-Europeans as they expanded from their West Asian homeland. These intruders mixed with eastern Europeans who vacillated during the late Neolithic between a northern Europeoid pole akin to Mesolithic hunter gatherers from Gotland and Iberia, and a widely dispersed Sardinian-like population that is in evidence at least in the Sweden-Italian Alps-Bulgaria triangle. The gradual appearance of non-mtDNA U related lineages in Siberia and Ukraine is most likely related to this phenomenon.

It would seem that the Proto-Indo-Europeans mixed with different substrata in the four directions of their expansion: Sardinian-like people in southern Europe, Lithuanian-like people in northern Europe, South Indian-like people in South Asia, and East Eurasians in Siberia and east central Asia. Extant groups are descendants of divergent Neolithic population groups, brought closer together (genetically) because of variable admixture with the PIE population and its early offshoots.

Conclusion

There are mutual signals of admixture across a Europe-South Asia cline: Europeans appear to be mixed with South Asians, and South Asians appear to be mixed with Europeans. The simplest explanation for this pattern involves expansion of a third, geographically and genetically intermediate population that affected both Europe and South Asia. We can use the signal of admixture LD to prove that this expansion affected some of the most unadmixed populations in Europe (e.g., Lithuanians), just as it did the most unadmixed populations of India (e.g., Dravidians).

It will be interesting to use these techniques to study signals of admixture in other "end of the line" populations such as Sardinians, South Indians, etc.

UPDATE I (rolloff analysis of Poles):

I have carried out rolloff analysis of my 25-strong Polish_D sample using Lithuanians and Pathans as references:

The signal is fairly distinct, and corresponds to 149.296 +/- 38.783 generations or 4330 +/- 1120 years. I am guessing that either the different reference population (Pathans vs. Balochi), or, more likely the increased number of target individuals (25 vs. 10) have contributed to the narrowing down of the uncertainty. It will be interesting to explore this signal further with more population pairs.

UPDATE II (rolloff analysis of Finns):

I have also used the 1000 Genomes Finnish sample (FIN) in a similar manner as Lithuanians, using 15 individuals to estimate allele frequency differences, and 15 ones for admixture LD, and using the Pathans as a South Asian reference population. There is a clear signal of admixture:

This dates to 104.967 +/- 14.797 generations, or 3,040 +/- 430 years. Finland came under the influence of both Europeans (and likely Indo-Europeans) during the Bronze Age period (a mixture of Battle Axe with local Comb Ceramic seems to have occurred), as well as likely non-European (and likely Uralic) intrusions during the same time frame, as part of the Seima-Turbino phenomenon. It will be interesting to repeat this analysis with an East Eurasian reference population to isolate potential signals of admixture dating to either the Comb Ceramic or Seima-Turbino episodes of migration.

(Note; added Oct 14): I carried out rolloff analysis using Nganassans as suggested in the above paragraph here.

UPDATE III (rolloff analysis of Ukrainians):

I have used the Yunusbayev et al. sample of Ukrainians, and estimated its admixture time using Lithuanians and Balochi as reference populations:

The admixture time estimate is 191.078 +/- 35.079 generations, or 5,540 +/- 1,020 years. It seems very similar to that in Lithuanians, with a smaller standard error, perhaps on account of either the larger number of SNPs or larger number of individuals.

It is tempting to associate this admixture signal with the Maikop culture which appeared at around this time. Assuming that North_European/West_Asian (or Lithuanian-like and Balochi-like) gene pools existed north and south of the Pontic-Caspian-Caucasus set of geographical barriers, then the Maikop culture which shows links to both the early Transcaucasian culture and those of Eastern Europe would have been an ideal candidate region for the admixture picked up by rolloff to have taken place. There are, of course, other possibilities.

UPDATE IV (rolloff analysis of Lithuanians with Pathan reference):

I repeated the first analysis of this post, but this time, I used Pathans, rather than Balochi as a reference population:

The admixture time estimate of 217.501 +/- 51.170 generations, or 6,310 +/- 1,480 years appears to be similar with the original estimate of 5,810 +/- 1790 years, so it does not appear that the use of Balochi or Pathan as a reference population much affects this result.

ESHG 2011 abstracts are online

From here. I didn't find much of interest this year, except a long-overdue look at Bulgarian Y-chromosomes but with not a very informative abstract.

Y-Chromosome genetic variation of modern Bulgarians
S. Karachanak et al.

To date, Bulgarian Y chromosomes have been studied only in macrogeographic context or in the lineage-based approach. Therefore, in order to comprehensively characterize Bulgarian Y-chromosome variation, we have performed high-resolution phylogenetic analysis of 812 healthy,unrelated Bulgarian males and compared the results with Y-chromosome data from other Eurasian populations.
The genotyping of 60 biallelic markers was performed in hierarchical order by RFLP and DHPLC analyses. The position of Bulgarians among other populations was visualized by Principal Component (PC) analysis.
About 80% of the total genetic variation in Bulgarians falls within haplogroups E-M35, I-M170, J-M172, R-M17 and R-M269. This finding shows that the Bulgarian haplogroup profile is congruent with those described for most European populations.
Among the prehistoric events marked by the observed haplogroups, the greatest contribution comes from the range expansion of local Mesolithic foragers triggered by adoption of agriculture introduced by a cadre of Near Eastern farmers. The Bulgarian Y chromosome gene pool also bears signals of the recolonization from different glacial refugia, the spread of agriculture from the Near East and the expansion of early farmers along the Central and East European river basins.
As for the interpopulation analysis, similarly to mtDNA, Bulgarians belong to the cluster of European populations, still being slightly distant from them. Bulgarians are distant from Turks (despite geographical proximity), Arabic and Caucasus populations and Indians. These trends in the PCA graph likely reflect not only prehistoric, but also more recent demographic events that have shaped the Y chromosome structure of modern Bulgarians.

An abstract on Yakuts seems to report the link between the Altaic-Turkic Yakut and the Altaic-Tungusic Evenk that I also discovered recently.

Autosomal and uniparental genetic diversity of the populations of Sakha (Yakutia): Implications for the peopling of Northeast Eurasia
S. A. Fedorov et al.

Sakha Autonomous Republic occupies a quarter of Siberian total land area in its northeastern part, is an important region for understanding the colonization of the Northern Eurasia by anatomically modern humans. To characterize the genetic variation in Sakha both the haploid mitochondrial DNA (mtDNA) and Y chromosomal as well as diploid autosomal loci (650 000 SNPs) of genome were analyzed in five native populations of Sakha (Yakuts, Evenks, Evens, Dolgans and Yukaghirs).
While striking prevalence of Y chromosome haplogroup N1c in gene pool differentiates Yakuts from other populations, the mtDNA and autosomal analyses demonstrate genetic similarity of all native populations of Sakha, in particular Yakuts and Evenks. The results also demonstrate closest genetic proximity of the populations of Sakha with southern Siberians. Both mtDNA and autosomal analyses reveal deep genetic discontinuity between Siberian and Beringian populations. MtDNA haplogroups A2 and G1b, prevalent in Beringian populations, are either minor or even absent in Sakha, where haplogroups C and D dominate. Autosomal analysis also differentiates Beringian populations from those of Sakha. Our results support the scenario that the territory of Sakha was colonized from the regions west and eastward of Lake Baikal with only minor gene flow from Lower Amur/Southern Okhotsk region and/or Kamchatka.

An abstract on Lithuanian Y-chromosomes

The place of the population of Lithuania between Northern and Eastern Europe: Y chromosome analysis
I. Uktverytė et al.

The population of Lithuania is constituted of 6 dialectal groups which form two major ethno-linguistic groups known as Aukštaitish and Žemaitish, both speaking Baltic languages of Indo-European family. Neighbouring Finno-Ugric (Northern and Eastern Europe), Slavonic (Eastern Europe) and Germanic (Northern Europe) populations surrounding the Baltic sea region influenced historical formation of Lithuanian ethno-linguistic groups. Analysis of the Lithuanian population genetic composition helps to understand the origin, history and place among other populations.
Y chromosome analysis was performed for 301 individuals from 6 dialectal groups. 25 SNPs were genotyped (TaqMan) to determine Y haplogroup and 17 STR were analysed to determine haplotype for each individual. Most frequent haplogroups in the population of Lithuania are R1a1a (42.2%, R1a1a1g compose 8.97% in studied population) and N1c1 (40.5%) and less frequent haplogroups are R1b1b1, I1, I2a, E1b1b1 (<5% each). AMOVA showed no statistically significant differences between two major ethno-linguistic groups Aukštaitish and Žemaitish (among groups p-value=0.897, among population within groups p-value=0.194, within populations p-value=0.282 based on 10100 permutations). MDS of genetic distances based on Y-biallelic markers showed that Lithuanians are closer to Latvian and Estonian populations than to Slavic populations (European part of Russia, Poland, Ukraine, Belorussia, stress=0.029). According to the frequencies of haplogroups, no statistically significant differences between ethno-linguistic groups were detected (p>0.05), moreover, MDS analysis sets the population of Lithuania between Northern and Eastern European populations.

An abstract on Sardinian population structure.

A genome-wide analysis of Sardinian population structure
M. Steri et al.

Sardinia is particular attractive for human genetic studies, being one of the larger isolated populations and thus suitable for large-scale studies. Several attempts have been made to explore its genetic structure, but they either analyzed a large set of markers in very few samples or thousands of individuals at specific loci. Here we genotyped 2,615 individuals with the Affymetrix 6.0 array. Samples were recruited from the north, south and central east areas of the Island, and initially considered as 3 distinct populations. Genotype calling was performed with Birdseed-v2, considering all samples as a unique cluster to avoid batch effects. Subsequently, we applied standard filters for samples and SNP quality, and used IBD sharing to detect, and discard, hidden relatives. Using principal component analysis, we identified outliers and reassigned each individual accordingly. An analysis of molecular variance indicated that only 0.21% of the variability could be attributable to inter-population variation (Fst=0.002), confirming a lack of large-scale substructure. We thus considered the Sardinians as a unique sample. Compared to HapMap3 populations, as expected, higher similarity was observed with Tuscany and CEPH samples (Fst=0.005 and 0.010, respectively). A genome-wide search for SNPs highly differentiated between Sardinians and these European populations confirmed the specialness of HLA and LCT regions, and also showed elevated Fst values (>0.27) at the CR1 gene, known to be related to malaria severity. We are now integrating sequencing data of many individuals to provide a more comprehensive analysis of variants in addition to the common SNPs in current genotyping platforms.

A major new study on Arabian mtDNA

Phylogeographic analyses; mitochondrial DNA; Arabian Peninsula
V. Fernandes et al.

Phylogeographic analyses of mitochondrial DNA (mtDNA) provide insights into modern human evolution. In recent years, worldwide studies of contemporary mtDNAs have indicated that modern humans left Africa ~60,000-70,000 years ago along the “southern coastal route”, across the Red Sea and via the Arabian Peninsula. Yet no obvious signs of the passage though Arabia have been found in genetics and archaeology fields. The aims of this work are to seek for possible mtDNA relicts of the initial dispersal from Africa in Arabia and to investigate the origins of lineages that arrived later. We are doing this by sequencing the complete mtDNA molecule (~16,568 bp) from unclassified lineages (referred to as the paraphyletic clusters L3*, N* and R*) and poorly studied haplogroups within the Eurasian macrohaplogroup N, which is predominant in Arabian populations today (86% in Saudi Arabia, 66% in Yemen and 79% in Dubai), in 90 samples from Dubai, Yemen, North/East Africa, the Near East and Europe. Our results will allow to test hypotheses about the settlement of the Arabian Peninsula.

Celto-Germans vs. Balto-Slavs

Here are the first two dimensions of a multidimensional scaling plot of the following samples:

• Dodecad Ancestry Project: 6 Poles, 12 Russians (Russian_D), 11 Germans, 19 Scandinavians, 6 Mixed Slavs (various West and East Slav combinations), 17 Britons, 17 Irish
• HGDP: 25 Russians from Vologda
• Behar et al. (2010): 10 Lithuanians, 9 Belorussians

Applying MCLUST over these first two dimensions and with K=2, the following breakup of individuals ensues:

It's fascinating that Cluster #1 (which corresponds to the assortment of individuals on the left of the MDS plot) includes only Balto-Slavic individuals (65 in total), while Cluster #2 (on the right, includes all 64 Celto-Germanic individuals plus 2 Poles and a mixed Slav.

This surprising concordance is even more striking once we consider that one of the "mixed Slavs" in my sample may be of Prussian origin within present-day Poland. I will be happy to tell the Poles in my sample which cluster they belong to if they write to me at the Dodecad Project e-mail address.

A lot has transpired since the ancient ethnographers divided the little-known peoples of the far north into Keltoi and Skythai, or since the Franco-Russian anthropologist Deniker divided the light-pigmented Northern Europeans into a race nordique and a race orientale. So, it is a bit surprising to see that a basic division of northern Europeans into East and West has stood the test of time. (*)

(*) Minus the Finnic peoples of northeastern Europe who, as has become clear, owe their genetic distinctiveness to a Siberian element in their ancestry, tying them to their linguistic cousins in the east.

Modern Scandinavians descended (maybe) from Neolithic TRB but not Mesolithic Pitted Ware ancestors

Coming shortly after Bramanti et al. (2009) which discovered a discontinuity between Neolithic farmers from Central and Eastern Europe and the pre-existing hunter-gatherers, a new study examines ancient DNA from northern European populations, extending the picture of discontinuity all the way to Scandinavia. This is one more nail in the coffin of the cultural diffusion hypothesis, and in favor for a demic diffusion of agriculture all the way to the northernmost reaches of Europe.

More on this after I read the full paper.

UPDATE (Sep 25):

From the paper:

Although the hunter-gatherers of Denmark and southern Sweden adopted pottery early on, the Neolithization first took real shape with the appearance of the Funnel Beaker Cultural complex (FBC, also known as the Trichterbecher Kultur [TRB]) some 6,000 years BP (the oldest evidence possible dating back some 6,200 years BP [9]). Atthis time domestic cattle and sheep, cereal cultivation, and the characteristic TRB pottery were introduced into most of Denmark and southern parts of Sweden [6]. Nevertheless,the Neolithization process was slow in Scandinavia, and large are as remained populated by hunter-gatherer groups until the end of the 5th millennium BP.

One of these last hunter-gatherer complexes was the Pitted Ware culture (PWC), which can be identified by its single-inhumation graves distributed over the coastal areas of Sweden and the Baltic Sea islands that lie closest to the Swedish coast. Intriguingly, the PWC first appears in the archaeological record of Scandinavia after the arrival of the TRB (some 5,300 yearsBP) and existed in parallel with farmers for more than a millennium before vanishing about 4,000 years BP (Figure 1).

The authors sampled 3 TRB individuals from "one passage tomb, Gokhem, dated to 5,500–4,500 years BP" which were found to belong to haplogroups H, J, and T, and 19 PWC individuals "from three different sites on the Baltic island of Gotland dated to 4,800–4,000 years BP" which were found to belong to haplogroups J, T, V (one each), "Other" (two), U5 and U5a (three each), and U4/H1b (eight samples).

From the paper:

Given our results, it remains possible that the PWC represent remnants of a larger northern European Mesolithic hunter gather complex. However, it appears unlikely that population continuity exists between the PWC and contemporary Scandinavians or Saami. Thus, our findings are in agreement with archaeological theories suggesting Neolithic or post-Neolithic population introgression or replacement in Scandinavia. To what extent this holds true for other parts of Europe requires further direct testing, although morphological [24, 25], ancient [26], and modern [4, 5] genetic data suggest that this is probably the case.

The results indicate that the PWC was dominated by haplogroup U (about three quarters of the mtDNA gene pool). The inability to resolve between U4 and H1b is due to the portion of the mtDNA sampled. Given (i) the absence of other H subgroups in the large sample, (ii) the higher frequency of U4 in modern populations, (iii) the presence of U4 but not H1b in other pre-farming populations of Europe (after Bramanti et al.), (iv) the absence of U4 in Neolithic populations, (v) the higher coalescence age of U4 compared to H1b, suggesting a deeper ancestry, I am inclined to think that most, if not all of the U4/H1b is actually just U4.

UPDATE II:

Fst between the PWC and modern populations ranged between 0.036 (Latvians) and Saami (0.25). For Swedes and Norwegians they were 0.051 and 0.061. A few conclusions can be drawn from this:

1. The notion of Saami as unmixed descendants of pre-farming Europeans is debunked.
2. Latvians and other populations of the eastern Baltic are the closest (although by no means very close) to the PWC.
3. Swedes and Norwegians are somewhat closer to the pre-farming inhabitants than is the case for Central Europe where Fst=0.086 was estimated by Bramanti et al. (2009)

Traditional physical anthropology held that there were three main elements in northern Europe, which have been given different names, but can be summarized as follows:

1. Narrow- and high-faced populations, a new element in the region, similar to that of Central Europe
2. Broad-faced massive Proto-Europoid populations, the aboriginal inhabitants of northern and eastern Europe
3. Flat-nosed populations with eastern affiliations

To quote Raisa Denisova:

Latvia's most ancient inhabitants tended to be large in size, with large skulls, a distinctly oblong head shape, a broad, high face and a distinctly protruding nose (Denisova 1975). Looking at this data in the context of synchronous populations elsewhere in Europe, we can find specific geographic differentials. This is especially true of the facial width of residents, a factor which has great weight in the specification of race (Denisova 1978). Differences in facial width in Europe became particularly distinctive at the beginning of the Atlantic period, when farming was begun in Europe. At this time, facial width distinctly separated morphological forms in Northern Europe from those in the Mediterranean region -- two distinct geographic regions. Massive, broad-faced morphological forms dominated in northern and northeastern Europe, while gracile, narrow-faced forms are found most often in Middle Europe and the continent's southeastern reaches. During the Atlantic period, narrow-faced populations gradually moved in the northerly and northeasterly direction. They reached the Baltic region only during the Bronze Age. For this reason, during the Mesolithic and Neolithic period, people in the Baltic region (and surrounding regions) had broad faces, a fact which affirms their links to the late Paleolithic populations of Europe.

Modern Scandinavians are more (1) than (2), while modern Balts are more (2) than (1). The mtDNA picture seems fairly consistent with a greater persistence of Proto-Europoid elements among the Balts.

A related public release:

Scandinavians are descended from Stone Age immigrants

Today's Scandinavians are not descended from the people who came to Scandinavia at the conclusion of the last ice age but, apparently, from a population that arrived later, concurrently with the introduction of agriculture. This is one conclusion of a new study straddling the borderline between genetics and archaeology, which involved Swedish researchers and which has now been published in the journal Current Biology.

"The hunter-gatherers who inhabited Scandinavia more than 4,000 years ago had a different gene pool than ours," explains Anders Götherström of the Department of Evolutionary Biology at Uppsala University, who headed the project together with Eske Willerslev of the Centre for GeoGenetics at the University of Copenhagen.

The study, a collaboration among research groups in Sweden, Denmark and the UK, involved using DNA from Stone Age remains to investigate whether the practices of cultivating crops and keeping livestock were spread by immigrants or represented innovations on the part of hunter-gatherers.

"Obtaining reliable results from DNA from such ancient human remains involves very complicated work," says Helena Malmström of the Department of Evolutionary Biology at Uppsala University.

She carried out the initial DNA sequencings of Stone Age material three years ago. Significant time was then required for researchers to confirm that the material really was thousands of years old.

"This is a classic issue within archaeology," says Petra Molnar at the Osteoarchaeological Research Laboratory at Stockholm University. "Our findings show that today's Scandinavians are not the direct descendants of the hunter-gatherers who lived in the region during the Stone Age. This entails the conclusion that some form of migration to Scandinavia took place, probably at the onset of the agricultural Stone Age. The extent of this migration is as of yet impossible to determine."

Related:

• Ancient mtDNA from Iceland
• Roman Age, Viking Age, and Eskomo mtDNA
• Ancient Viking mtDNA from Denmark
• Ancient British mtDNA
• Y chromosomes and mtDNA from Eulau
• Central European farmers not descended from local hunter-gatherers

Current Biology doi:10.1016/j.cub.2009.09.017

Ancient DNA Reveals Lack of Continuity between Neolithic Hunter-Gatherers and Contemporary Scandinavians

Helena Malmström et al.

Abstract

The driving force behind the transition from a foraging to a farming lifestyle in prehistoric Europe (Neolithization) has been debated for more than a century [1], [2] and [3]. Of particular interest is whether population replacement or cultural exchange was responsible [3], [4] and [5]. Scandinavia holds a unique place in this debate, for it maintained one of the last major hunter-gatherer complexes in Neolithic Europe, the Pitted Ware culture [6]. Intriguingly, these late hunter-gatherers existed in parallel to early farmers for more than a millennium before they vanished some 4,000 years ago [7] and [8]. The prolonged coexistence of the two cultures in Scandinavia has been cited as an argument against population replacement between the Mesolithic and the present [7] and [8]. Through analysis of DNA extracted from ancient Scandinavian human remains, we show that people of the Pitted Ware culture were not the direct ancestors of modern Scandinavians (including the Saami people of northern Scandinavia) but are more closely related to contemporary populations of the eastern Baltic region. Our findings support hypotheses arising from archaeological analyses that propose a Neolithic or post-Neolithic population replacement in Scandinavia [7]. Furthermore, our data are consistent with the view that the eastern Baltic represents a genetic refugia for some of the European hunter-gatherer populations.

Link

Migrations in the Baltic region inferred from Y chromosomes and mtDNA

From the paper on Y-haplogroup I1a:

Haplogroup I1a is suggested to have its origins in the Iberian refugium, from where it spread northward and now has its highest frequencies in Northern Europe (Rootsi et al. 2004). The haplotype matches to Germany and Poland imply that I1a has arrived to the Nordic countries from the Southern Baltic Sea region, which is historically plausible. The coalescense age of the haplogroup is about 5000 years lower than the age of the earliest archaeological findings from the Northern Baltic Sea region, which suggests a Neolithic arrival. There are two possible migration routes from Central Europe to the Northern Baltic Sea region: an exclusive western route via Sweden, an eastern route via the Baltic states, or via both to Eastern Finland and Karelia (Fig. 5). The surprisingly high diversities of I1a among the eastern Finnish and Baltic populations, and the lack of association between the Western Finns and the Swedes in SAMOVA analysis suggest that I1a has been involved in bifurcating migrations both via Sweden and the Baltic states, and that the presence of the haplogroup in Finland and Karelia is not merely due to Swedish influence. The low frequency of I1a among the Baltic populations may be due to later effects of genetic drift or replacement.

I am personally doubtful of the Iberian origin of Y-haplogroup I1a. Its presence in Iberia and France, as well as its high diversity there may be the result of migration from northern Europe, a genetic trace of the Germanic Volkerwanderung. One certainly needs to consider this effect. There are probably a couple of papers just waiting to be written by looking at Y-chromosomes of Germanic descendants in Southwestern Europe by looking at either surnames or early cemetaries.

With regard to Y-haplogroup N3:

The frequency distribution and age of haplogroup N3 in our study sample was consistent with the earlier studies (Lahermo et al. 1999, Zerjal et al. 2001, Tambets et al. 2004, Karlsson et al. 2006, Rootsi et al. 2007). According to the YHRD database, the haplotypes most common in Finland and Karelia were relatively unique, which is not unexpected, since data from most Eurasian populations where N3 is common is not publicly available. It seems evident that the Finns and Karelians share a history regarding haplogroup N3. In the database comparisons, we also observed that N3 may mark a westward diffusion in the north from Finland to Sweden and in the south from the Baltic countries to Poland and Germany.

The researchers also reiterated the previous idea of a dual origin of N3, as shown in the figure, with different clades being represented in Finland and the Baltic states, with Estonia being intermediate between the two.

With regard to Y-haplogroup R1a1:

It is plausible that both R1a1 and I1a were carried to the Baltic Sea region via the same Neolithic migrations from Germany/Poland. The higher coalescence age and the starlike network structure of R1a1 are consistent with the probable higher diversity and frequency of R1a1 in the original source population(s), a consequence of the wider geographical distribution of the haplogroup. It is an important observation that in the Baltic Sea region R1a1 is mainly associated to Central European rather than eastern or Russian influence. However, haplotype frequency comparisons (Derenko et al. 2006, Willuweit & Roewer 2007) give some indication of Russian gene flow as a partial source of R1a1 in Karelia, which would be plausible given the long period of admixture with Slavs (Fig. 5). However, the Y-chromosomal diversity in Karelia has been heavily affected by drift and founder effects. Another haplogroup with eastern affinity is I1b (Rootsi et al. 2004), whose presence in Karelia and the Baltic states is probably a sign of Russian gene flow.

This is an important discovery, and a great first step in uncovering the structure within this widespread haplogroup. Even though R1a1 Y-chromosomes were studied in a lot of populations, including e.g., the Balkans, India, the Altai, unfortunately we know next to nothing about its phylogenetic substructure. Without such knowledge, R1a1 spread has been variously interpreted as a signal of postglacial colonization, Kurgan expansions, or the spread of Slavic languages.

Finally, the genetic legacy of the Saami is visible in mtDNA:

The eastern elements in the mtDNA variation of the Baltic Sea region are intertwined with the Saami influence. Recent studies of the mtDNA variation among the Saami show a link to the Volga-Ural region (Tambets et al. 2004, Ingman & Gyllensten 2006), which is now shown to exist also among the Karelians and, to a lesser degree, among the other populations from the Baltic Sea region as well. Additionally, the presence of U4 in the Eastern Baltic Sea populations may represent eastern influence, since it is typical for the Volga-Ural region (Bermisheva et al. 2002). The high diversity of this haplogroup in the Baltic region, observable in the haplotype network, suggests a complex history, and rules genetic drift out as a cause of the high frequency. All in all, these mtDNA haplogroups may be maternal reflections of the eastern influence that can be most clearly observed in the Y-chromosomal haplogroup N3.

Annals of Human Genetics doi:10.1111/j.1469-1809.2007.00429.x

Migration Waves to the Baltic Sea Region

T. Lappalainen et al.

In this study, the population history of the Baltic Sea region, known to be affected by a variety of migrations and genetic barriers, was analyzed using both mitochondrial DNA and Y-chromosomal data. Over 1200 samples from Finland, Sweden, Karelia, Estonia, Setoland, Latvia and Lithuania were genotyped for 18 Y-chromosomal biallelic polymorphisms and 9 STRs, in addition to analyzing 17 coding region polymorphisms and the HVS1 region from the mtDNA. It was shown that the populations surrounding the Baltic Sea are genetically similar, which suggests that it has been an important route not only for cultural transmission but also for population migration. However, many of the migrations affecting the area from Central Europe, the Volga-Ural region and from Slavic populations have had a quantitatively different impact on the populations, and, furthermore, the effects of genetic drift have increased the differences between populations especially in the north. The possible explanations for the high frequencies of several haplogroups with an origin in the Iberian refugia (H1, U5b, I1a) are also discussed.

Link

ASHG 2006 abstracts

The meeting of the American Society of Human Genetics took place this October and the abstracts of the meeting are online in a big pdf file. A few items of interest:

The genetic variation and population history in the Baltic Sea region

Sharp genetic borders within a geographically restricted region are known to exist among the populations around the northern Baltic Sea on the northern edge of Europe. We studied the population history of this area in greater detail from paternal and maternal perspectives with Y chromosomal and mitochondrial DNA markers. Over 1700 DNA samples from Finland, Karelia, Estonia, Latvia, Lithuania and Sweden were genotyped for 18 Y-chromosomal biallelic polymorphisms and 8 microsatellite loci, together with 18 polymorphisms from the coding area of mtDNA and sequencing of the HVR1. Y chromosomal haplogroups from the biallelic data indicate both various phases of gene flow and existence of genetic barriers within the Baltic region. Haplogroup N3, being abundant on the eastern side of the Baltic, differentiates between eastern and western sides of the Baltic Sea, just like R1b that has a reverse frequency pattern to N3. The typically Scandinavian haplogroup Ia1 has a high frequency of up to 40%, separating not only Sweden but also Western Finland from the other populations. The frequency of haplogroup R1a1, most characteristic to Slavic peoples, varied substantially across the populations. In addition to biallelic markers, Y-chromosomal microsatellite loci were analyzed for a more detailed approach to the history of the paternal lineages in the region. We also analyzed mtDNA markers with special interest for sub-haplogroups of H and U, that among other haplogroups, show substantial variation between the populations (e.g. haplogroups H1, H2, T and J1). In conclusion, our current Y-chromosomal and mtDNA data suggest various incidents of gene flow from different sources, each reaching partly different areas of the Baltic region, which can be thus seen as a meeting point of a not only culturally but also genetically diverse set of populations.

Asian Nomads traces in the mitochondrial gene pool of Slavs.

Mitochondrial DNA (mtDNA) variability was studied in a sample of 179 individuals representing Czech population from west Bohemia. MtDNA analysis revealed that the majority of Czech mtDNAs belongs to the common West Eurasian mitochondrial haplogroups. However, about 3 per cent of Czech mtDNAs encompass East Eurasian lineages (A, N9a, D4, M*). Comparative analysis of published data has shown that different Slavonic populations contain small but marked amount of East Eurasian mtDNAs (e.g. 1.3 per cent in Eastern Slavs, 1.8 per cent in Western Slavs, and 1.2 per cent in Southern Slavs). It is noteworthy that Baltic populations (Latvians, Lithuanians and Estonians) have avoided a marked influence of maternal lineages of East Eurasian origin (0.3-0.6 per cent). The two East Eurasian mtDNA haplogroups, Z1 and D5, are present in gene pools of North European Finnic populations (Saami, Finns, and Karelians). Unlike them, Slavonic populations in general are characterized by heterogeneous mtDNA structure, defined, in addition to Z1 and D5, by haplogroups A, C, D4, G2a, M*, N9a, F and Y. Therefore, different scenarios of female-mediated East Eurasian genetic influence on Northern and Eastern Europeans should be highlighted: (1) the most ancient, probably originated in the early Holocene, influx of Asian tribes, which brought a few selected East Asian mtDNA haplotypes (like Z and D5) to Fennoscandia (Tambets et al. 2004), and (2) gradual gene flows of historic times occurred mostly in the Middle Ages due to migrations of nomadic peoples (such as the Huns, Avars, Bulgars, Mongols) to Eastern and Central European territories inhabited mainly by Slavonic tribes. We suggest that the presence of East Eurasian mtDNA haplotypes is not original feature of gene pool of the proto-Slavs, but mostly is a consequence of admixture with Central Asian nomadic tribes, who migrated into Central and Eastern Europe in the early middle Ages.

Use of Forensic Markers in the Assessment of Population Stratification.

Assignment of individuals to population groups is important to genetic case control association studies, admixture mapping, medical risk assessment, genealogy, and forensic studies. Polymorphic sequences can be used to infer ancestry but their utility for such an application is related to the number of alleles and relative frequency differences of these alleles between the population groups under study. Multiple study designs differing in numbers and types of polymorphic markers with differing levels of informativeness make comparison of studies difficult. The use of commercially-available highly-informative markers that are used internationally in forensic applications could provide a universal first tier analysis for assignment of individuals to population groups prior to inclusion in association and admixture studies. We evaluated the utility of the PowerPlex kit of 16 markers from Promega for this purpose. Multiple population groups including African, Bengalis, Chinese, Japanese, Koreans, Crypto Jews, Sephardic Jews, and Dutch were genotyped using the PowerPlex kit. The data were analyzed with STRUCTURE (Pritchard et al.) using an admixture model, correlated alleles and 3 clusters. Africans, Asians (Bengalis, Koreans, Chinese and Japanese), and Caucasians (Dutch, Sephardic Jews, and Crypto Jews) were clearly delineated. Individuals showing admixture were detectable and their removal resulted in more discrete clustering. An independently collected and genotyped set of Dutch individuals was indistinguishable from the original Dutch group providing reproducibility across data sets. The sensitivity conferred by the number of markers used in the analysis was assessed by removing markers. Delineation of population groups was apparent when 14 markers were used, although clusters were noisier; however it was not possible to delineate population groups when only 8 markers were used. The use of forensic markers is a promising strategy for clustering individuals into population groups and will be an inevitable outcome of their forensic use.

Evaluation of Ancestry and Linkage Disequilibrium Sharing in Admixed Population in Mexico

National Institute of Genomic Medicine, Mexico. More than 80% of the Mexican population is considered Mestizo, resulting from the admixture of ethnic groups with Spaniards. To generate an initial estimate of ancestral contribution (AC) of populations from Europe, Africa and Asia to the Mexican Mestizos, we genotyped 104 samples from the states of Sonora (n=20), Yucatan (n=17), Guerrero (n=21), Zacatecas (n=19), Veracruz (n=18) and Guanajuato (n=8) using the 100K Affymetrix SNP array, and used data from the International HapMap Project as the parental population information. From 3,055 ancestry informative SNPs reported by Smith et al. and Choudhry et al., we identified 105 present in the 100K array and used them to calculate AC from each population to our sample. To infer AC we used Structure software under the admixture model. Based on this analysis, the average AC in our samples is 58.96% European, 10.03% African and 31.05% Asian. Sonora shows the highest European contribution (70.63%) and Guerrero the lowest (51.98%) where we also observe the highest Asian contribution (37.17%). African contribution ranges from 7.8% in Sonora to 11.13% in Veracruz. Based on these data, we grouped our population according to European AC (<50%,>70%). We used the Carlson algorithm to derive European tagSNPs from the 100K marker set. To explore Linkage Disequlibrium Sharing (LDS) between Mestizos and Europeans, we calculated the proportion of tagSNP-marker pairs that maintained an r2≥0.8 in each evaluated population. In general, comparison of LDS between European and Asian population is ~73%, whereas comparison with African population is ~40%. Mestizos from Guerrero show the lowest LDS (74%), whereas those from Sonora show the highest (77%). Similar results are seen in the group of lower (<50%)>70%) European ancestry. Our results suggest that the Mexican Mestizo population shows ancestry-based stratification that will requiere the appropriate corrections to avoid spurius results in association studies. Our results show that admixed populations have unique patterns of LD depending on levels of ancestral contribution.

European mitochondrial haplogroups exhibit differential risk of developing presbycusis.

The genetic basis of human presbycusis (age-related hearing loss) is unknown. This common disorder is characterized by difficulty understanding conversation, particularly in noisy backgrounds. Audiograms of presbycusics show sloping hearing loss, with greatest deficiencies at the highest frequencies, and over time an individual’s hearing loss progresses into the lower frequencies that are more important for understanding speech. We investigated the hypothesis that the mitochondrial (mt) genome plays a role in presbycusis. Subjects of European ancestry, all over age 58, were tested using both classical and advanced audiometric measures and then genotyped to determine mt haplogroups. We found that subjects belonging to haplogroup H (N=93) had better hearing than other Europeans (N=80), with the greatest differences observed in the right ear at 3 kHz (p=0.017) and 10-14 kHz (p=0.016). The difference at 3 kHz correlates with the common noise notch location, and thus may indicate a difference in susceptibility to noise damage. Distortion product otoacoustic emissions also indicated better hair cell health in haplogroup H subjects, at higher frequencies and in the right ear (average DPOAEfor 4-6 kHz, p= 0.010). These results support the hypothesis that a mitochondrial factor influences susceptibility to the development of presbycusis. We are currently investigating the mt genome for causative mutations linked to the haplogroups.

Estimating the split time of Human and Neanderthal populations

Previous genetic studies of Neanderthal ancestry have used mtDNA and thus have been limited in their conclusions on the relationship of humans and Neanderthals. We present here the first use of Neanderthal genomic DNA to assess the joint history of human and Neanderthal populations. Our data consist of 37kb of short fragments of genomic DNA sequenced in Neanderthal. By studying the degree to which modern human diversity is shared with Neanderthal we can assess the time at which the human and Neanderthal populations split. We use a flexible simulation based approach that demonstrates the power of using human variation data in such analyses. We find that the two populations split ~400,000 years, predating the emergence of modern humans. Our best fitting model predicts that the Neanderthal lineage will be outgroup to the human population ~52% of the time.

The Genetic Structure of Human Populations in Africa.

Africa contains the greatest levels of human genetic variation and is the source of the worldwide range expansion of all modern humans. Knowledge of the genetic population boundaries within Africa has important implications for the design and implementation of genetic epidemiologic studies of Africans and African Americans, and for reconstructing modern human origins. A dataset consisting of ~3.7 million genotypes has been generated from the Marshfield panel of 773 microsatellites and 392 in-del polymorphic genetic markers. These markers were genotyped in ~3,200 individuals from >100 diverse ethnic populations across Africa as well as in 118 African Americans and in the CEPH Human Genome Diversity Panel, consisting of 1048 individuals from 51 globally diverse populations. Preliminary analysis of population structure using the program STRUCTURE1 indicates considerably more substructure amongst global populations (estimate for the number of genetic clusters, K, is 12) and amongst African populations (K = 9) than had previously been recognized2. Population clusters are correlated with self-described ethnicity and shared cultural and/or linguistic properties (e.g. Pygmies, Khoisan-speakers, Bantu-speakers, etc). African Americans have predominantly West African Bantu (~80%) and European (~17%) ancestry, although individual admixture levels vary considerably. These results justify the need to include a broad range of geographically and ethnically diverse African populations in studies of human genetic variation. 1Pritchard JK, et al. Genetics 155:945-59 (2000) 2Rosenberg NA, et al. Science 298:2381- 5 (2002).

Patterns of admixture in Latino populations

We examined the diversity of 13 Latino populations from seven countries (Mexico, Guatemala, Costa Rica, Colombia, Chile, Argentina and Brazil) typing 745 autosomal microsatellite markers in 250 individuals. Estimates of genetic ancestry for these populations varied substantially. Native American ancestry varied between 19.6% and 70.3%, European ancestry between 26.9% and 70.6%, and African ancestry between 1.1% and 9.8%. Genetic structure analysis provides evidence of a genetic continuity between pre- and post-Columbian populations for specific geographic regions. For instance, a Chibchan-Paezan ancestry is detectable in Latinos from lower Central America and northwest South America. Individual admixture estimates vary considerably between populations. Some Latinos (e.g. Mexico City) show marked variation in individual admixture, whereas others (e.g. Antioquia and Costa Rica) show little variation. This variation is likely to reflect the history of admixture of each geographic region examined: some Latino populations are still undergoing substantial admixture whereas others underwent admixture mostly in early colonial times. These results have important implications for admixture mapping and association mapping studies in Latino populations.

Genomic diversity and population structure of Native Americans

We examined 745 autosomal microsatellite markers in 432 individuals sampled from 24 indigenous populations in the Americas. These data were analyzed jointly with similar data available in 54 other indigenous populations from across the world (including an additional 5 Native American groups). The populations from the Americas show lower diversity and more differentiation than populations from other continental regions (global Fst=0.08). Signals of long-range linkage disequilibrium are detectable to a greater extent in Native Americans than in other populations, as are signals of recent bottlenecks followed by population growth. A negative correlation is observed between population diversity and geographic distance from the Bering Strait, an observation consistent with the north-to-south dispersal of humans upon initial entry into the continent. A higher diversity is observed in western vs. eastern South American populations, potentially reflecting differences in long-term effective population size or in colonization routes within South America. Phylogenetic trees relating Native American populations show a marked differentiation between Canadian and other Native populations. Canadian natives also show a detectable shared ancestry with contemporary Siberian populations, which is less visible for more southerly Americans. A substantial agreement is observed between phylogenetic relatedness and population affiliation according to the linguistic classification of Greenberg.

The rare nonsynonymous SCN5A-S1103Y variant in Caucasians is due to recent African Admixture as revealed by 100k SNP genotyping.

The SCN5A-S1103Y variant is an established and confirmed risk factor conferring an odds ratio up to 8.5 for cardiac ventricular arrhythmias and sudden cardiac death (Splawski et al, Science, 2002, Burke et al., Circulation, 2005, Plant et al., J. Clin. Invest. 2006). In Africans it is a common nonsynonymous SNP (MAF=8%), but it is rarely observed in Caucasians (Chen et al, J. Med. Genet. 2002). In a Bavarian family appearing of entirely Caucasian descent and affected with long QT Syndrome we have detected this variant in heterozygote state as the only causal nonsynonymous variation upon diagnostic ion channel resequencing. To resolve the question, whether in the family the variant was (a) of ancient African descent, (b) due to recent African admixture or (c) a de novo mutation, we analyzed the genetic segment it resided on. Dense SNP genotyping in admixed individuals allows to infer the ethnicity of chromosomal regions if allele frequencies are known in the original populations. Ethnicity inference for any given locus can be carried out by applying the product rule to a sliding window of neighboring SNPs or via modeling ancestry by hidden Markov Chain Monte Carlo Methods (Tang et al. Am. J. Hum. Genet, 2006). By 100k SNP genotyping of the Bavarian family, we demonstate that the S1103 variant is due to recent African admixture (b) and could rule out possibilities (a) and (c). This application demonstrates that inferring ethnicity of chromosomal regions by high density SNP genotyping is a powerful approach with prospects also to admixture mapping of disease loci and population stratification correction of genomewide association mapping of complex disease loci.

Allele frequency estimates from DNA pools for 317,000 SNPs for multiple European and worldwide populations and discovery of Ancestry Informative Markers for Europe.

The identification of Ancestry Informative Markers (AIMs) and inference of individual genetic history is useful in many applications, including studies of geography and evolution of human populations, forensic sciences, pharmacogenomics, admixture mapping and association studies of complex diseases. While many AIMs have been reported that define strong genetic differences between major continents, it is more difficult to identify markers that reflect subtle, within-continent diversity, such as the heterogeneous ancestry of European Americans contributed by different populations within Europe. We have analyzed DNA pools, each for a different population, on Illumina HumanHap300 BeadArrays to estimate allele frequencies for ~317,000 Single Nucleotide Polymorphisms for 9 European, 6 African, and 2 Amerindian populations in the Human Genome Diversity Project collection. We have also evaluated the performance of this method by analyzing three HapMap pools (YRI, CHB, and JPT), for which the true allele frequencies are already known from the International HapMap Project. We found that the allele frequency estimates differed between replicate chips by less than +/-5% for 95% of the SNPs, and that the estimated frequencies and the true frequencies differed by +/-5-10% for 90% of the SNPs. The data for nine European populations, from western Caucasus, Scotland, Tuscany, Sardinia, France, Iberia, Russia, Northern Italy, and a Basque region, showed a clear excess of SNPs having large allele frequency differences (e.g. >30%) between most pairs of populations, compared to what would be expected given the sample sizes. These results provide a valuable resource of European AIMs for monitoring within-continent stratification in association studies. We are currently validating the most informative SNPs by individually genotyping samples that formed the pools as well as those from additional European populations.

Mitochondrial haplogroups are associated with asthma and total serum IgE levels

Maternal history of asthma and/or atopy is a major risk factor for the subsequent development of asthma and allergy in childhood. Although mitochondrial mutations have been implicated in several maternally inherited monogenic disorders, no studies of mitochondrial polymorphisms and asthma have been reported.Weevaluated whether common mitochondrial haplogroups are associated with asthma and total serum IgE levels. 8 common mitochondrial single nucleotide polymorphisms (mtSNP) were genotyped in two cohorts of European ancestry: 512 adult women with incident asthma and 517 matching controls participating in the Nurses’ Health Study (NHS) and 654 children ages 5-12 years with mild to moderate asthma participating in the Childhood Asthma Management Program (CAMP). Genotyping was performed using TaqMan® probe hybridization assays. 93 random NHS samples were run in duplicate for all assays and demonstrated 100% concordance. In the CAMP Study, genotype data from probands’ mothers was also 100% concordant across all assays. Completion rates in both cohorts were > 95% for all markers. mtSNP 9055 was seen at higher frequency in NHS asthma cases (frequency 11.1%) than controls (8.0%, p = 0.02). Association analysis using haplo.score identified two haplogroups associated with asthma: one haplogroup at a frequency of 3.83% among cases compared to 1.27% among controls (p=0.0002) and another at a frequency of 9.97% among cases and 11.3% among controls (p=0.04). The CAMP Study is a case-only (family-based) cohort, thus precluding evaluation of mitochondrial SNP associations with asthma status. However, quantitative analysis of mitochondrial haplogroups identified two haplogroups of 11.0% and 1.87% frequency that were associated with log-transformed total serum IgE levels, an important intermediate phenotype in asthma and atopy (p=0.006 and 0.01, respectively). These data suggest that common mitochondrial haplogroups influence asthma diathesis.

Dumb theory of the day: Odyssey and Iliad were written by a woman

... according to a British "scholar". Never mind that there is no single mention of a female author of these poems, or any epic poetry at all. Never mind that the authorship of the Iliad and the Odyssey was universally attributed to Homer in historical times by all Greeks who ever bothered to mention what was common knowledge. Never mind that the poems universally assign the role of story teller to men, and confine women to domestic pursuits. What is the "scholar"'s evidence?

Dalby explained that women throughout the ancient world were "often the last and most skillful exponents of an oral tradition."

For example, the world’s first named poet was a Sumerian woman named Enheduanna, who lived from around 2285-2250 B.C. Dalby said women also saved the ancient oral poetry of the northern Japanese, many Irish traditions, and numerous English folk ballads.

Another recent book, Clever Maids: The Secret History of the Grimm Fairy Tales, claims the Brothers Grimm gathered most of their famous stories from women. Author Valerie Paradiz told Discovery News that the brothers "only gave credit to one woman by name," but then linked most other tales to male editors who also gathered stories from women.

Yep, the Sumerians, Japanese, Irish, English and the Brothers Grimm did it, ergo the Iliad was written by a woman. QED. Mr. Darby gives us his own scholarly "guesses" too:

If the poet was a woman, Dalby believes her name is probably lost to history.

"I would guess that Sappho (a female Greek poet) and her contemporary, the male poet Alkaios, probably knew the name, but they did not mention it in their own poetry," Dalby said.

Well, too bad they never said anything about it. How convenient for Mr. Dalby's speculations! If anyone is still wondering Who Killed Homer? now we have an answer: Mr. Dalby, and "scholars" like him.

PS: I don't mind people writing what they want. We should not however award any respect to crackpots. Mr. Dalby's theory belongs in the same category as the "Merovingians were descended from Jesus Christ" or "Homer in the Baltic".

Anthropological types of Corded Ware and Yamna cultures

Some useful descriptions from the paper (pp. 351-353):

The Corded Ware culture includes about twenty variants (Sveshnikov 1974) and occupies predominantly Central Europe, Scandinavia, Sub-Carpathia and also the Upper Volga (Fig. 1). It was formed in Central Europe, in an area of special concentration of qute distinct cultures of different origins, including those from Mediterranean and North-Baltic regions of Europe. Bearers of the southern LBK (Roessen, Tisza, Lengyel, etc) were engaged in cattle-breeding, had developed ceramic production, and were familiar with plastic arts. They buried their dead in the flexed position on the right or left side. Generally it was a comparatively gracile short people of the Mediterranean (South Europoid) anthropological type.

Peoples of the Baltic circle of cultures (Ertebo/lle) were hunters and fishermen, and produced only one or two pottery forms. This was a rather tall, broad-faced population of the North Europoid type, who buried their dead in the extended position on the back.

Certain cultures of syncretic appearance involving Northern and Southern features were formed in Central Europe and the Baltic during the 4th-3rd millennium BC, e.g. Comb Ware, TRB, and Globular Amphora cultures. During the Early Bronze Age these cultures were displaced by the Corded Ware (Battle Axe) culture characterized by flexed inhumation on the back or side under a barrow. Specifically, this culture embraces both bottle-like vessels and bowls with funnel-like neck of the Northern circle of cultures, and also vessels of the Danubian type. In an anthropological sense this population combines traits of southern gracile and northern massive types, in particular bearers of TRB culture (Schwidetzky 1978).

...

The Yamna culture of the Pontic-Caspian steppe is recorded for an enormous territory between the North-Western Pontic area and Trans-Uralia. Its sites are known here in the basin of the Emba and Tobol rivers, the Karaganda region and further eastward (Merpert 1974). The Yamna population generally belongs to the European race. It was tall (175.5cm), dolichocephalic, with broad faces of medium height. Among them there were, however, more robust elements with high and wide faces of the proto-Europoid type, and also more gracile individuals with narrow and high faces, probably reflecting contacts with the East Mediterranean type (Kurts 1984: 90).

See also a previous related post on the Anthropology of Sredny Stog and Novodanylovka.

Journal of Indo-European Studies Vol. 33: 3-4, p. 339

The Yamna Culture and the Indo-European Homeland Problem

D. Ya. Telegin

Excavations between the rivers Orel' and Samara have uncovered burials of a syncretic nature that attest contacts between the spheres of the Corded Ware and Yamna cultures. It is suggested that these may indicate early contacts between proto-Indo-Iranians and the prehistoric ancestors of the Balts and Slavs.

The Slavs in Russia

I believe that this is related to my recent post on Y chromosomes and mtDNA of Russians.

How the Slavs conquered Russia (Informnauka (Informscience) Agency):

Geneticist specialists from the Institute of Biological Problems of the North, Far-East Branch of Russian Academy of Sciences, are reconstructing the picture of Eurasia colonization by the Slavs. According to the researchers’ opinion, the Slavonic men and women jointly developed the territory of the south of contemporary Russia. However, after the 9th century, women used to stay at home, and colonization of the east and north was mainly performed by men.

This conclusion was made by geneticists through analyzing variable consecutions of DNA of mitochondria and of some sections of Y-chromosome with representatives of 10 Russian populations from the Stavropol Territory in the south through the Pskov Region in the north and from the Orel Region in the west through the Nizhni Novgorod Region in the east. The mitochondrial DNA is inherited from generation to generation along a female line, DNA of Y- chromosome – along a male line. Analysis of variability of these consecutions allows to judge about migrations of our forefathers and foremothers.

Along the maternal line, Russian populations are rather close to each other. They can be conditionally split into two zones. Inhabitants of the south-eastern zone (including the Orel, Rostov, Kursk, Kaluga and Saratov Regions and the Stavropol Territory) have the roots among western Slavs, Baltic and some Finno-Ugric nations (Poles, Lithuanians and Estonians). Ancestors of Russians in the north-eastern zone took wives from the Finno-Ugric and other nations of Eastern Europe (Finns, Karelians, Maris, Tatars and Adygeis).

Comparison of Y-chromosomes of Russian populations provides different results. Only the Pskov and coast-dweller populations are close along the paternal line to the Finno-Ugric and Baltic nations of the Northern and Eastern Europe, the overwhelming majority of Russians are relatives to the Poles, Ukrainians and Byelorussians. Judging by consecution variations of the “male” chromosome, the Slavs, arriving in various locations of Eastern Europe, contacted in different ways with residential population: in some places - closely and in some others – otherwise.

Genetic analysis results agree with the anthropological data, according to which Russian populations can be divided into three zones. In the western part of the ethnic territory, Russians descend from the Slavs who had come from Central Europe. Russian population of the central part appeared as a result of mixture of the Slavs with the Finno-Ugric nations, Eastern European mothers dominating in these populations, and the population of the North evidently has in its genealogy Finno-Ugric ancestors of both sexes. According to the geneticists, the reasons for these differences are caused by different participation of men and women in Slavonic migrations. Women apparently participated only in early phases of the Slavs’ migration into Eastern Europe. Starting from the 9th century, colonization of the east and the north of Eastern Europe was mainly performed by men who chose wives from residential population. The obtained picture needs more precise definition, therefore the researchers are planning to further investigate variability of specific “maternal” and “ paternal” DNAs in different Russian populations.

Y chromosome variation of Finns

An interesting comprehensive new article on Finnish Y-chromosome variation. The main finding is that the arrival of Finno-Ugric speakers (possessing haplogroup N3) was later followed by Scandinavian migrations mainly into western Finland, which reduced the frequency of N3 there, bringing especially haplogroup I1a. Thus, within Finland, western Finns are close to Swedes, and eastern Finns are close to their Finno-Ugric brethren. Interestingly, Finns seem to lack haplogroup R1b which is found among Germanic-speaking Scandinavians. Thus, the most probable sequence of events is the following:

1. Movement of N3 into Finland
2. Movement of I1a into western Finland
3. Movement of R1b into Germanic Scandinavia

This seems to support a picture in which early Germanics had a high frequency of I1a, early Finns had a high frequency of N3, and R1b in Scandinavia is the result of foreign settlers, probably continental Germans, Britons etc.

Gene. 2006 Mar 18; [Epub ahead of print]

Regional differences among the Finns: A Y-chromosomal perspective.

Lappalainen T, Koivumaki S, Salmela E, Huoponen K, Sistonen P, Savontaus ML, Lahermo P.

Twenty-two Y-chromosomal markers, consisting of fourteen biallelic markers (YAP/DYS287, M170, M253, P37, M223, 12f2, M9, P43, Tat, 92R7, P36, SRY-1532, M17, P25) and eight STRs (DYS19, DYS385a/b, DYS388, DYS389I/II, DYS390, DYS391, DYS392, DYS393), were analyzed in 536 unrelated Finnish males from eastern and western subpopulations of Finland. The aim of the study was to analyze regional differences in genetic variation within the country, and to analyze the population history of the Finns. Our results gave further support to the existence of a sharp genetic border between eastern and western Finns so far observed exclusively in Y-chromosomal variation. Both biallelic haplogroup and STR haplotype networks showed bifurcated structures, and similar clustering was evident in haplogroup and haplotype frequencies and genetic distances. These results suggest that the western and eastern parts of the country have been subject to partly different population histories, which is also supported by earlier archaeological, historical and genetic data. It seems probable that early migrations from Finno-Ugric sources affected the whole country, whereas subsequent migrations from Scandinavia had an impact mainly on the western parts of the country. The contacts between Finland and neighboring Finno-Ugric, Scandinavian and Baltic regions are evident. However, there is no support for recent migrations from Siberia and Central Europe. Our results emphasize the importance of incorporating Y-chromosomal data to reveal the population substructure which is often left undetected in mitochondrial DNA variation. Early assumptions of the homogeneity of the isolated Finnish population have now proven to be false, which may also have implications for future association studies.

Link

mtDNA distribution in European Russian populations

Very interesting article:

Russians, who occupy an immense area comparable by its size with the whole Western Europe, are characterized by substantial anthropological and dialectic diversity. Development of the independent Russian nation began in the 9th century A.D., as a result of the integration of Eastern Slavic tribes within the frames of the Old Russian State, and assimilation of Finno-Ugric, Baltic, and Turkic ethnic groups [1]. Subsequent integration and migration processes, as well as an enlargement of the territory of residence, introduced new ethnic elements into the Ancient Russian ethnic group. Numerous investigations of anthropological traits and classical genetic markers provided the idea on the complex genetic structure of Russians, and described the regional differences between different groups, caused by the interaction of newly arrived Slavic tribes with aboriginal populations. Until recently, mitochondrial DNA (mtDNA) diversity of Russians was studied only in some individual populations. At present, this problem attracts growing attention.

...

Most part of these mitotypes (from 80 to 85%) mark the main European haplogroups, H, I, J, K, T, U, V, W, and X (Table 2). Five of these haplogroups, H, U, J, T, and K, which are most prevalent among the European populations, account for 70 to 78% of the total diversity. In general, haplogroup frequency distribution patterns described in Russian populations were similar to those in European populations [5, 10–14, 16]. However, it should be noted that rather high frequencies (14 to 19.5%) of the mitotypes, not attributed to the haplogoups mentioned, were observed in the Russian populations examined (in Table 2, these mitotypes are defined as “others”). This mitotype group may contain Asian and some minor European haplogroups, the members of macrohaplogroup N.

...

Finally, the most “specific” Tambov oblast is located at the border between the Eastern European and the steppe complex, the anthropological specificity of which was repeatedly mentioned in a number of studies [1, 20].


...

Thus, our results point to closeness of the populations from three oblasts (Ivanovo, Ryazan’, and Vologda) to the average regional type, as well as to a substantial difference of the representatives of the two southern oblasts, Orel and Tambov, from this average type. It seems likely that this pattern reflects subdivision of the Russian ethnic area into zones determined by the patterns of the relationships between the Slavs and the local ethnic groups. This subdivision was first described by Rychkov et al. in their study of anthropological and classical genetic markers [8, 21]. According to the view of these authors, this subdivision reflected the movements of the annalistic Slavs from the west eastward. Ivanovo, Ryzan, and Vologda oblasts, defined in the present study as “middle Russian,” are located within the most typical of Russian population “zone of panmixia,” i.e., the region where the forward movement of ancient Slavs proper was replaced by intensive assimilation of the local (in this case, probably, Finno-Ugric) population [8, 21]. At the same time, “genetically specific” populations (Orlov and Tambov) are territorially close to the “cores” of the greatest anthropological specificity of the Russian population, which, according to Rychkov et al., traces back to the annalistic Slavic tribes [8]. Inclusion of more Russian populations in further analysis will probably enable more precise characterization of the observed patterns.

Characteristics of the eastern European complex:

Characteristics: Darkening of the color of the hair and eyes distinguishes this from the White Sea-Baltic group. In the territory of the eastern European plain have been isolated several local combinations, that are differentiated, in essence, by variations in the cephalic index, and by the width and proportions of the face.

Description of the steppe complex:

Steppe Complex. Unfortunately, the population of the Steppe zone has been rather poorly studied by anthropologists. Therefore, the description of the Steppe complex is based only on scanty data regarding some Russian groups inhabiting the midflows of the Dona and Khoper rivers, and a few Turkic-speaking groups dwelling on the right banks of the Volga, most importantly the Mishars. The populations which form this complex are distinguished by mesocephaly, relatively small absolute dimensions of the head and face, partial depigmentation, intermediate development of tretiarry hair cover, intermediate horizontal facial profile and relatively strong nasal protrusion.

See also Hair-color of the Proto-Slavs, Hair-color of the Proto-Slavs (revisited).

Russian Journal of Genetics Volume 41, Number 9

Mitochondrial DNA Polymorphism in Russian Population form Five Oblasts of the European Part of Russia

I. Yu. Morozova et al.

Abstract New data on mitochondrial DNA polymorphism among Russian population from five oblasts, located within the main ethnic area of Russians, specifically, Ryazan' oblast, Ivanovo oblast, Vologda oblast, Orel oblast, and Tambov oblast (N = 177) are presented. RFLP analysis of the mtDNA coding region showed that most of the mtDNA diversity in the populations examined could be described by main European haplogroups H, U, T, J, K, I, V, W, and X. Haplogroup frequency distribution patterns in the populations of interest were analyzed in comparison with the European and Uralic populations. Based on the haplogroup frequencies, the indices of intraethnic population diversity, Wright's F _st statistics, and the values of squared deviation from the mean, as well as genetic distances between Russians and European and Uralic populations were estimated. Analysis of these indices along with the anthropological data provided identification of a number of regional groups within the populations examined, which could either result from the interaction of ancient Slavs with different non-Slavic tribes, or could be caused by the ethnic heterogeneity of the ancient Slavs themselves.

Link

Mesolithic of Baltic Sea basin

Journal of Anthropological Archaeology (Article in Press)

Mobility, contact, and exchange in the Baltic Sea basin 6000–2000 BC

Marek Zvelebil

My intention in this paper is to outline the main features and principal aspects of contact and exchange among the later prehistoric hunter–gatherers (late Mesolithic and post-Mesolithic) in the Baltic Sea basin, which covers the southern and eastern reaches of Northern Europe, and to summarise the main advances in current research. The area broadly covered includes the Baltic Sea basin that has provided effective routes for communication between the coastal regions surrounding the Baltic Sea, central Baltic islands, and regions further away in the north European Plain, inland regions of Fennoscandia and Russia that could be reached by an extensive network of major rivers and lakes. Effective transport for negotiating these routes both in the summer and winter existed already from the early Mesolithic. Goods moved along these routes included a wide range of artefacts discussed in the paper. Geographically, exchange was organised at three levels: regionally, inter-regionally, and over long distances. Each mode of exchange was probably organised along different lines socially, and each served to implement wide-ranging social strategies for the general purposes of social reproduction, mate exchange and biological reproduction, as well as the spread of innovations. In the concluding section, I discuss the nature of contacts and consequences of exchanges between the early farming communities and the hunter–gathering groups within the framework of the core-periphery relations.

Link

Y-chromosome diversity in East Asia and Oceania

This chapter is a comprehensive review of Y-chromosomal diversity in East Asia and Oceania. It should come in useful to those (like me) who don't have a deep knowledge of the diverse populations of that part of the world.

Peter A. Underhill, A Synopsis of Extant Y chromosome Diversity in East Asia and Oceania (pdf).

An interesting excerpt:

Conversely, the LLY22g and TAT frequency and distribution data from Karafet et al. (2001) and unpublished data regarding M214* indicate that these chromosomes are informative in East Asian and Siberian populations. The low microsatellite diversity reported for TAT defined chromosomes indicates the occurrence of a bottleneck and subsequent demographic and range expansion (Zerjal et al. 1997). The presence of M214* lineages in East Asia suggest that they may have originated here and then dispersed northward on trajectories reaching the Baltic region. An East Asian origin of M214 is reinforced by the fact that it is a sister clade of the M175 clade that comprises the majority of East Asian lineages.

The link between haplogroup N and M175 is further reinforced by the discovery that M214 is also found in O-M175 chromosomes.

PS: You might want to read Inferring Human History: Clues from Y-chromosome haplotypes first to get an overview of human Y chromosome phylogeny.