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Thread: Signature of recent historical events in the European Y-chr. STR haplotype distr.

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    Post Signature of recent historical events in the European Y-chr. STR haplotype distr.

    Originally posted by Dalonord.

    Signature of recent historical events in the European Y-chromosomal STR haplotype distribution


    Lutz Roewer1, Peter J. P. Croucher2, 3, Sascha Willuweit1, Tim T. Lu3, Manfred Kayser4, 5, Rüdiger Lessig6, Peter de Knijff7, Mark A. Jobling8, Chris Tyler-Smith9 and Michael Krawczak3
    (1) Institute of Legal Medicine, Humboldt-University, Berlin, Germany
    (2) First Department of Medicine, Christian-Albrechts-University, Kiel, Germany
    (3) Institute of Medical Informatics and Statistics, Christian-Albrechts-University, Brunswiker Strasse 10, Kiel, Germany
    (4) Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany
    (5) Department of Forensic Molecular Biology, Erasmus University, Rotterdam, The Netherlands
    (6) Institute of Legal Medicine, University of Leipzig, Germany
    (7) Forensic Laboratory for DNA Research, Leiden University, The Netherlands
    (8) Department of Genetics, University of Leicester, UK
    (9) The Wellcome Trust Sanger Institute, Hinxton, UK

    Michael Krawczak
    Email: krawczak@medinfo.uni-kiel.de
    Phone: +49-431-5973200
    Fax: +49-431-5973193
    Received: 13 May 2004 Accepted: 13 September 2004 Published online: 20 January 2005


    Abstract

    Previous studies of human Y-chromosomal single-nucleotide polymorphisms (Y-SNPs) established a link between the extant Y-SNP haplogroup distribution and the prehistoric demography of Europe. By contrast, our analysis of seven rapidly evolving Y-chromosomal short tandem repeat loci (Y-STRs) in over 12,700 samples from 91 different locations in Europe reveals a signature of more recent historic events, not previously detected by other genetic markers. Cluster analysis based upon molecular variance yields two clearly identifiable sub-clusters of Western and Eastern European Y-STR haplotypes, and a diverse transition zone in central Europe, where haplotype spectra change more rapidly with longitude than with latitude. This and other observed patterns of Y-STR similarity may plausibly be related to particular historical incidents, including, for example, the expansion of the Franconian and Ottoman Empires. We conclude that Y-STRs may be capable of resolving male genealogies to an unparalleled degree and could therefore provide a useful means to study local population structure and recent demographic history.
    L. Roewer and P.J.P. Croucher contributed equally to this paper.
    ________________________________________
    Introduction
    The population dynamic processes that created the subtle gradation pattern of European culture, and eventually shaped the continent s genetic structure, are unparalleled in world history. It is widely accepted that extant Europeans have their earliest roots in the scattered Palaeolithic hunter-gatherer communities of around 40,000–43,000 years ago (Boyd and Silk 1997). Some 10,000 years before present (YBP), the rise of agriculture in the Near East led to the migration into Europe of a rapidly expanding farming population, although the extent of concomitant genetic change has been a matter of some dispute (Ammerman and Cavalli-Sforza 1984; Chikhi et al. 2002). Archaeological evidence suggests that the oldest rural villages in Europe developed on the western coast of the Aegean Sea and in Crete around 7,000 YBP. From there, agriculture spread to most of the Balkan Peninsula and unfolded westwards via the Vardar-Danube-Rhine corridor and along the northern coast of the Mediterranean.
    For thousands of years the South-East of Europe was the most developed part of the continent, whilst north of the Alps non-imperial and rather autonomous communities predominated. With the decline of the Roman Empire, around 2,000 YBP, the Teutons started to expand westwards, and the amalgamation of the Roman and Germanic civilisations marked the origin of the extant occidental European populations (Banniard 1989). By contrast, the eastern part of Europe always provided a gateway for migration and invasion by nomadic populations, from the Kurgan expansion around 7,000 YBP to the east-west movements of the Scythians, Mongols, Huns, Avars, Alanes and Magyars in historical times. Originating from the upper Dnjepr, the Slavs had settled on the southern shores of the Baltic Sea and replaced the Germanic speakers in Hungary and the Balkans during the sixth century AD (Gimbutas 1971). Their expansion was only halted by the new European powerhouse, the Franconian Empire. The political divide between these two cultures was marked by the rivers Elbe, Danube and Save, a split that has influenced Europe ever since and is still obvious today.
    The population genetic consequences of the European colonisation and re-colonisation during Palaeolithic and Neolithic times have been addressed by a number of studies that utilised slowly evolving single-nucleotide polymorphisms (SNPs) on the Y chromosome (Rosser et al. 2000; Semino et al. 2000). Owing to its large number of polymorphic sites and its particular sensitivity to genetic drift (Seielstad et al. 1998; Kayser et al. 2001), the non-recombining part of the Y chromosome is especially useful for the investigation of population movements. Biallelic polymorphisms have proven useful for the analysis of prehistoric events, since the ancestral and derived sequence variants have had enough time to evolve independently. However, in order to investigate the impact of political, religious and cultural incidents in historical times, such as the so-called Making of Europe between 950 and 1350 AC (Bartlett 1994), greater resolution is required to distinguish the relevant patrilineal genealogies. The ability of hypervariable Y-chromosomal short tandem repeat (Y-STR) haplotypes to discriminate between even closely related or co-localised male populations has been demonstrated before for Germans and Dutch (Roewer et al. 1996), for the Baltic populations (Lessig et al. 2001), for Central England and North Wales (Weale et al. 2002) and for Poland and Germany (Ploski et al. 2002). In the present study, we genotyped over 12,700 Europeans at seven Y-STR loci and assessed whether the geographical haplotype distribution of these fast-evolving, male-specific markers indeed reflects recent history. Samples were derived from 91 different populations, spread across the culturally most diverse regions of the continent and representing the most extensive survey of human Y-chromosomal diversity undertaken in any population or group of populations to date.
    ________________________________________
    Material and methods
    DNA samples

    DNA samples were obtained from 12727 white European males through 91 local recruitment units (Fig. 1). Nearly all individuals were ascertained via a judicial or private paternity case, and care was taken within the confines of general forensic practice that no closely related males or males of non-local origin were included in the study. The samples therefore represent an unbiased cross-section of that part of the respective male population that would have been liable to a paternity dispute. All samples were logged in the Y-STR haplotype reference database (YHRD), maintained at the Institute of Legal Medicine, Humboldt-University of Berlin, Germany, and made publicly available via the Internet. The names of the samples and meta-samples (see legend to Fig. 1) were chosen pragmatically without any prior causal or explanatory (e.g. linguistic) relationship in mind.



    Y-STR and Y-SNP genotyping
    All samples were genotyped for six tetranucleotide Y-STRs (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS393) and one trinucleotide Y-STR (DYS392), following published protocols (Kayser et al. 1997). In accordance with recommendations by the International Society of Forensic Genetics (Gill et al. 2001), Y-STR alleles were designated according to the number of variable repeats included. Consistent allele designation was assured by the use of allelic ladders in all participating laboratories. Note that, in contrast to the common practice in forensic databases, our allele designation at DYS389I and DYS389II refers to the repeat number at individual loci, and not the repeat numbers revealed by the multiplex genotyping method employed (Rolf et al. 1998). Prior to inclusion in the study, all laboratories had to pass a quality test that involved blind genotyping of five control samples. Additional information about markers, laboratories and sampling procedures is available at the YRHD web site and from the Forensic Laboratory for DNA Research in Leiden, The Netherlands.
    Genotyping of Y-chromosomal SNPs in the Baltic and Dutch samples allowed the assignment of each individual chromosome to one of the most common European Y-SNP haplogroups. Multiplex PCR and SNaPshot minisequencing reactions were carried out as described (Lessig et al. 2004). All products were analyzed on ABI Prism 310 or 3100 Avant Genetic Analyzers.


    Spatial autocorrelation analysis

    Spatial autocorrelation analysis of haplotypes was performed using Moran s I index (Sokal and Oden 1978). Parameter I measures the correlation between observations of the same type, made at locations of a given geographical distance. Here, we used the repeat number of each Y-STR locus as the primary observation. The pair-wise great circle distances (GCD) between haplotype origins (i.e. recruitment units) were determined using Cartesian coordinates obtained from the 2004 version of the CIA World Factbook and other sources in the public domain. We chose not to employ II, an allele frequency-based adaptation of Moran s I to genetic analyses suggested by Barbujani (1987), since STR repeat numbers evolving through single-step mutation represent suitable quantities for analysis on their own. Autocorrelation was evaluated over 11 distance classes, including one class for haplotypes found in the same location (i.e. GCD equal to zero) and ten additional, equally frequent distance classes. Moran s I values were assessed for statistical significance using a randomisation test that permuted samples over locations in 100 replications.

    Analysis of molecular variance
    The genetic relationship between different populations was assessed by means of ST, an analogue of Wright s FST that takes the evolutionary distance between individual haplotypes into account (Excoffier et al. 1992; Excoffier and Smouse 1994). Estimates of ST were obtained using the Arlequin software (Schneider et al. 2000) and tested for statistical significance by means of randomisation (1,000 replicates per comparison). Several local population comparisons yielded exceptionally low ST values, suggesting that the respective samples were genetically indistinguishable. Population samples were, therefore, recursively clustered into meta-samples, based upon ST. In each clustering step, that pair of populations or clusters that yielded the minimum ST value was grouped together. Clustering was performed in a two-tiered fashion, in that groupings were first confined to within one and the same country, and grouping continued until no further insignificant clustering (i.e. P>0.05 for the respective ST) was possible within any country. This procedure led to the definition of regional meta-samples (Fig. 1) which were more comparable to samples from countries with only one recruitment unit. Meta-samples and the remaining individual samples formed the basis of a second, exhaustive round of ST-based clustering.


    Multidimensional scaling analysis
    In order to graphically visualise the Y-STR genetic landscape of Europe, principle coordinates were identified by subjecting the pair-wise ST estimates between all 91 samples to a multidimensional scaling analysis (MDS) using SPSS (SPSS, Chicago Ill., USA). Individual solutions for one through six dimensions were iterated until the improvement in stress was less than 0.0001. The optimum dimensionality was then determined from a scree test (Table 1). A clear elbow was observed for the three-dimensional solution, with higher-dimensional solutions not providing a substantial decrease in Kruskal s stress value, S. The R2 values (Table 1) indicate that 96.4% of the variance in the data can be accounted for by the three-dimensional solution. The resulting coordinates were then used to generate three independent maps, one for each dimension, in which MDS coordinates were interpolated across Cartesian coordinates by inverse distance squared weighting with the 12 nearest neighbour samples, using the GRASS (Geographical Resources Analysis Support System) software. The European land mass was masked from oceans and seas using the GTOPO30 (30-arc seconds topographical) dataset, publicly available at the US Land Processes Distributed Active Archive Center. For better resolution, some sample locations were moved to the centre of the respective country of origin, especially when only one location was included for that country (e.g. Great Britain, Finland, Hungary etc.).


    Table 1 Multidimensional scaling and scree test of pair-wise ST values (S Kruskal s stress value, R2 coefficient of determination)

    No. of dimensions S R2
    1 0.211 0.887
    2 0.136 0.944
    3 0.106 0.964
    4 0.094 0.968
    5 0.084 0.972
    6 0.076 0.975
    The first dimension of the MDS revealed a strong east-west gradient for the Y-STR genetic structure. In order to corroborate this finding more systematically, Spearman rank correlation coefficients were calculated for each of the 91 original samples between pair-wise ST and the longitudinal and latitudinal geographical distance, respectively, to all other samples. Singletons and meta-samples were also subjected to a pseudo-admixture analysis relative to the Western Europe and Eastern Europe sub-clusters that become clearly identifiable in the ST-based cluster analysis (boxed in Fig. 2). Each haplotype that occurred in at least one of the two fringe sub-clusters was labelled either Western or Eastern , depending upon where it was relatively more frequent. All haplotypes that were one-step neighbours of an Eastern or a Western haplotype of at least 1% frequency in the respective sub-cluster were assigned the same origin. All other European samples and meta-samples were then characterised in terms of the relative proportion of the fringe haplotypes.


    Assessment of local haplotype diversity variation

    Under an infinite sites model (ISM) of mutation, the number of different haplotypes, Sn, expected in a population sample of size n is related to the mutation rate and the effective population size N via Ewen s sampling formula (Ewens 1972)

    (1)
    where =N for haploid genomes. When the mutational process generating Y-STR haplotypes is approximated by an ISM (Helgason et al. 2000), adoption of =2×10–2 for of all seven loci combined (Kayser et al. 2000) allows the estimation of effective population sizes from n and Sn, solving Ewen s sampling formula for . Furthermore, for any two populations with constant population sizes N1 and N2, respectively, and a constant number M of migrants per generation between them, assuming that each migrant introduces a new haplotype into the other population leads to expected values, E(Sn, k), that correspond to

    (2)
    For the combined population, E(Sn,c) is such that

    (3)
    if the two populations are completely panmictic. If not, then c as obtained from Sn,c using formula 1 an unbiased estimate of the right-hand side of formula 3 only if n1/n2=N1/N2, i.e. if the two sample sizes are proportional to the population sizes. However, even under complete population separation (i.e. M=0), simulation has shown that the respective bias is not very serious for a wide range of ni values since the curve that relates c to n1 and n2 is usually flat around n1/n2=N1/N2 (data not shown).
    ________________________________________
    Results
    Populations, haplotypes and genetic diversity

    The Y-chromosomal STRs DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392 and DYS393 were analysed in 12,727 males from 91 European populations (Fig. 1). In the total sample, the markers showed between eight (DYS391, DYS393) and 11 (DYS390, DYS392) different alleles. However, of the seven million different theoretically possible haplotypes, only 2,489 were actually observed. More than half of these (1,397/2,489=56.1%) were unique to an individual male. Fifteen haplotypes, comprising 3,088 males (24.3%), occurred in 40 or more populations; another 160 haplotypes, representing 4,692 individuals (36.9%), were found in 10–39 populations. The most frequent haplotype ( 14-13-16-24-11-13-13 , in the above marker order) accounted for 661 males (5.2%) and was observed in 80 populations. Its 14 one-step neighbours comprised another 1,368 individuals (10.7%), with observed haplotype counts ranging from 24 to 303. Whilst the highest haplotype diversity h (Nei 1987) was observed in Vienna, where all 66 haplotypes were different (h=1.00), particularly low values of h (i.e. h<0.95) were noted in Albania and Finland.
    When population samples were iteratively collapsed within countries, a total of 12 meta-samples emerged before all ST values became significant at the 5% level (Fig. 1). This regrouping involved 58 original samples; the remaining 33 data sets were henceforth treated as singletons. The second, exhaustive round of clustering by minimum ST clearly reflected the geographical actuality of Europe (Fig. 2). All Western populations, with the exception of metropolitan Paris, formed a clearly identifiable sub-cluster ( Western Europe ). This sub-cluster also included Emilia Romagna from Italy, which in turn strongly resembled the French sample from the Alsace ( ST=–0.0010, P=0.507). Most notably, the Spanish and Portuguese samples were not found to be significantly different ( ST=0.0014, P=0.078). At the other extreme, all Slavs except Bulgaria formed one cluster ( Eastern Europe ), where only Croatia ( ST=0.0061) and the two Baltic samples ( ST=0.0157) differed from the rest at the 0.1% significance level. Bulgaria belonged to a different sub-cluster, which also incorporated Romania ( ST=0.0001, P=0.417), and which extended to Greece and Hungary at the 1% significance level ( ST=0.0055, P=0.013 for all four samples combined). Sicily and West-Italy together with the two Turkish samples clearly complemented this Balkan-Danube grouping to form a coherent Southern European sub-cluster. Whilst the two southern Dutch populations ( South Holland ) were included in Western Europe , the three northern samples ( North Holland ) formed a Friesian sub-cluster together with Denmark ( ST=–0.0044, P=0.795). The Friesians were part of a more comprehensive sub-cluster, including all francophone populations, West Germany, Vienna and Sweden, which may be loosely called West-Central Europe . By contrast, the other German and Austrian samples as well as Northern-Italian Veneto link in with Norway and eventually Albania and Estonia to group as a East-Central Europe . Finally, Finland can be regarded as a sub-cluster on its own which associated with the non-Slavic populations ( ST=0.0460, P<0.001) before both connected with the Eastern European sub-cluster ( ST=0.0744, P<0.001).

    Genetic and geographic distances
    Spatial autocorrelation analysis yielded results that were consistent with an isolation by distance model of haplotype divergence (Fig. 3). Thus, Y-STR repeat numbers were most similar for haplotypes sampled in the same location (I=0.0929). At less than 1,000 km, the autocorrelation index decreased sharply with distance, reaching a plateau of negative I values thereafter and decreasing only slightly beyond 2,000 km. All indices were significantly different from zero (randomisation P<0.01), including I=–0.0018 for the distance class centred at 940 km.


    Inspection of Fig. 1 suggests that the similarity of Y-STR haplotypes decays much more rapidly along an east-west than a north-south gradient, at least in central Europe. This notion was formally corroborated by a MDS analysis of all pair-wise ST values. The first dimension, accounting for almost 89% of the variance (Table 1), clearly shows a decomposition of the European Y-STR genetic structure into three major components (Fig. 4a), closely corresponding to the Western , Central and Eastern sub-clusters of Fig. 2. The first dimension also highlights the genetic peculiarity of metropolitan Paris and Vienna, Finland, and the two Balkan-Slavic samples of Slovenia and Croatia in relation to their respective surroundings. The degree of east-west stratification of the European Y-STR haplotype spectrum was quantified by Spearman rank correlation analysis between the latitudinal and longitudinal distances, respectively, and pair-wise ST (Fig. 5). For 81 samples, the correlation was stronger with longitude than with latitude, and the few populations showing a notably reversed effect were from the fringe of the continent (Fig. 5). Furthermore, whilst only five samples showed a negative correlation with longitude, namely Emilia Romagna (I), Vaesterbotten (S), Finland, Estonia and Northern Norway, the same was true for 12 samples with latitude. The second dimension of the MDS analysis revealed more subtle structural features, such as, for example, the distinction between the Turkish and non-Turkish samples in Southern Europe and the divide between the two Dutch meta-samples. The third dimension eventually depicted an underlying north-south gradient that is usually seen in Y-SNP studies of European populations (Rosser et al. 2000; Semino et al. 2000). However, since the second and third dimensions of the Y-STR MDS accounted for less than 10% of the variance (Table 1), the major geographic structuring associated with the two types of markers must be substantially different.

    Pseudo-admixture analysis
    When compared with the peripheral Western Europe and Eastern Europe sub-clusters, the other 28 samples/meta-samples exhibited prominent geographical gradients in terms of their Y-STR haplotype spectra (Table 2). The proportion of Western European haplotypes was naturally highest in Western Europe itself (91%), with a cline-like decrease as one moves east and north from Belgium (66%) and North Holland (61%) to Romania (25.0%), Estonia (14%), Eastern Europe (11%) and Finland (10%). The proportion of Eastern European haplotypes showed a similar trend in the reverse direction. Some samples were characterised by a relatively high proportion of haplotypes (>30%) that were not classifiable as either Eastern or Western , including Vienna (50%), Sicily (47%), Styria (46%), Paris (38%), Turkey (37%) and Veneto (33%).

    Table 2 Pseudo-admixture analysis of Y-STR haplotypes in European populations (n total number of haplotypes, NA not applicable)
    Sample/meta-sample n Frequency of haplotype group (%)
    Western Eastern None
    Western Europe 2,529 2300 (91) 229 (9) NA
    Finland 399 39 (10) 266 (67) 94 (23)
    Estonia 133 19(14) 85 (64) 29(22)
    Albania 101 34 (34) 54 (53) 13 (13)
    Styria (A) 65 19 (29) 16 (25) 30 (46)
    Norway 300 93 (31) 151 (50) 56 (19)
    North-East Germany 752 268 (35) 321 (43) 163 (22)
    Veneto (I) 120 62 (52) 18 (15) 40 (33)
    South-East Germany 1,404 613 (44) 551 (39) 240 (17)
    Tyrol (A) 229 100 (44) 88 (38) 41 (18)
    Sweden 667 233 (35) 304 (46) 130 (19)
    Vaesterbotten (S) 41 13 (32) 20 (48) 8 (20)
    West Germany 1,287 631 (49) 418 (32) 238 (19)
    Vienna (A) 66 19 (29) 14 (21) 33 (50)
    North Holland 179 110 (61) 43 (24) 26 (15)
    Denmark 63 35 (56) 17 (27) 11 (17)
    Paris (F) 109 51 (46) 17 (16) 41 (38)
    Central Italy 559 316 (57) 80 (14) 163 (29)
    Berne (CH) 91 47 (52) 24 (26) 20 (22)
    Belgium 125 83 (66) 22 (18) 20 (16)
    Lausanne (CH) 108 64 (60) 22 (20) 22 (20)
    West Italy 373 193 (52) 75 (20) 105 (28)
    Sicily (I) 199 70 (35) 36 (18) 93 (47)
    Hungary 118 35 (30) 62 (52) 21 (18)
    Greece 101 45 (44) 27 (27) 29 (29)
    Bulgaria 122 34 (28) 65 (53) 23 (19)
    Romania 102 25 (24) 58 (57) 19 (19)
    Bulgarian Turks 61 15 (25) 30 (49) 16 (26)
    Turkey 158 54 (34) 46 (29) 58 (37)
    Eastern Europe 2,166 228 (11) 1938 (89) NA
    Total 12,727 5,848 (46) 5,097 (40) 1,782 (14)

    Local variation in the Dutch and Baltic Y-STR haplotype spectra
    Since the effective population size estimates for the North and South Holland meta-samples were neither additive nor identical (Table 3), the two sub-populations cannot have been completely separated or panmictic. Instead, they must have experienced some level of recent migration, and solving formulae 2 and 3 with the respective values included yielded N1=3,918, N2=1,298 and M=22. These estimates were verified by 10,000 simulations of an ISM with migration, using the very same N1, N2 and M values. The mean Sn obtained in simulated samples of the original sizes (i.e. n1=179, n2=96, and n3=n1+n2=275) were 100.3±6.1, 52.3±4.2 and 136.5±7.8, and were therefore very close to the actually values (Table 3). As a consequence, it may be concluded that the Dutch Y-STR data are best explained by a threefold higher effective population size in North than in South Holland and by migration rates of m1=22/3918=0.56% (in and out of the North), and m2=22/1298=1.69% (in and out of the South). On the other hand, over the last, say, 100 generations, the Dutch population can be assumed to have been large enough for genetic drift to have had a minor effect upon its genetic structure. Under this assumption, the change in frequency of a given allele or haplotype can be modelled in the two sub-populations as

    (4)
    Table 3 Patterns of Y-STR haplotype diversity in the Dutch and Baltic populations (n total number of haplotypes, Sn number of different haplotypes, population parameter, N effective population size)
    Sample n Sn
    N
    North Holland 179 103 100.2 5,010
    South Holland 96 53 47.8 2,390
    Combined 275 135 104.3 5,215
    Estonia 133 93 136.0 6,800
    Latvia/Lithuania 296 171 168.0 8,400
    Combined 429 229 198.9 9,945
    For the Dutch population, this implies that any difference in allele or haplotype frequency would have decreased by 0.56+1.69=2.25% in one generation, and by 100•[1–(1–0.0225)100]=89.7% in 100 generations.
    Under the same migration/ISM, we obtained N1=4,172, N2=5,772, and M=53 for the two Baltic samples/meta-samples from Estonia ( 1 ) and Lithuania/Latvia ( 2 ), respectively (Table 3). This implies that the migration rates between the two Baltic sub-regions must have been of a similar order (m1=0.0127, m2=0.0092) as those between the Dutch sub-populations.
    ________________________________________

    Discussion
    The genealogy of European Y chromosomes is characterised by substantial differentiation (Rosser et al. 2000; Semino et al. 2000) and, as expounded upon in more detail below, our study suggests that the observed pattern of cline-like similarity between Y-chromosomal STR haplotypes may partly reflect demographic events that occurred in historical time. Recent male demography would indeed be best assessed by the analysis of Y-chromosomal polymorphisms since the fourfold smaller effective population size of male-to-male transmission renders Y-chromosomal markers much more sensitive to genetic drift and population bottlenecks than their autosomal counterparts. In principle, similar arguments should also apply to mitochondrial (mtDNA) markers, but little geographical structuring has been detected in Europe by means of mtDNA analysis (Richards et al. 2002). This has led to the suggestion that mtDNA is either exceptionally selection-sensitive or that female gene flow has been particularly high in Europe (Barbujani and Chikhi 2000).

    Y-chromosomal short tandem repeats, in particular, are capable of resolving population strata into individual genealogies that would otherwise be inseparable (Roewer et al. 1996; Lessig et al. 2001; Ploski et al. 2002; Weale et al. 2001, 2002). The power of the Y-STR approach is, however, critically dependent upon careful sample collection, especially in regions with neighbouring populations that have undergone mutual transitions. Our analysis has made opportunistic use of the Y-STR haplotype reference database (YHRD), a survey of male genetic variation in Europe that was initiated in 1997 by the Forensic Y Chromosome Research Group. The major purpose of the database was to serve as reference material for the presentation of male DNA profiles in court (Roewer et al. 2000). Since then, the repository has been growing continuously and expanded beyond its original scope. As of August 2004, YHRD contained over 24,000 Y-STR haplotypes from over 230 populations world-wide. The history of the database and its originally intended use in forensic practice imply that sampling has been neither systematic nor comprehensive. However, it is questionable whether a merely academic study of neutral population genetic variation on the present scale would have ever been possible to implement. Furthermore, the use of validated genotyping procedures in quality-controlled forensic laboratories has served to ensure the highest credibility for each and every haplotype that entered into YHRD (Roewer et al. 2001).

    In contrast to previous, SNP-based, studies of European male genetics (Rosser et al. 2000; Semino et al. 2000), our analysis has utilised a much higher level of inter-individual variability, and the identification of previously unrecognised male strata in Europe confirms the utility of this approach. However, the high variability of Y-STR profiles is a direct consequence of the 105 to 106-fold higher likelihood of meiotic repeat length change than single base-pair substitution (Kayser et al. 2000). High mutation rates may homogenise haplotypes of different descent (de Knijff 2000), an inherent drawback of STR haplotypes that could only be compensated for in our study by extensive sampling. The large size of most regional samples and meta-samples ensured that all locally common patrilines were represented by haplotype classes that contain profiles separated by one or only a few single-step mutations.

    Our study provides clear evidence for a major genetic division of European males into Slavic-speaking eastern and Romance language-speaking western populations, separated by a central European block of Germanic- and Italian-speaking populations. The Western and Eastern European geographical clusters are reminiscent of the well-established distribution of Y-SNP haplogroups P(xR1a) and R1a (Rosser et al. 2000). Indeed, preliminary data by Kittler et al. (2003) indicate that the ancestral Y-STR haplotypes were 14-13-16-24-11-13-13 for P(xR1a) and 16(?)-13-17-25-10-11-13 for R1a. Since the respective frequencies of these two haplotypes and their one-step neighbours were 30.6 and 0.6% in Western Europe , as opposed to 4.4 and 20.5% in Eastern Europe , the Y-STR-based and Y-SNP-based power of discrimination between the two sub-clusters would have been equivalent. Furthermore, the significantly negative autocorrelation in Y-STR repeat number observed for haplotypes located more than 1,000 km apart (Fig. 3) is suggestive of a continent-wide cline between at least two different ancient lineages, possibly corresponding to P(xR1a) and R1a. It is important to stress, however, that the autocorrelation was based on allele length, and not frequencies, so that we prefer to interpret Fig. 3 in broader terms as simply representing isolation-by-distance .

    Our data revealed a rapid change in haplotype spectra along east-west gradients, but a relative constancy over more than 1,000 km in a north-south direction in central parts of the continent. This may be indicative of the fact that, when the expanding Slavic and Franconian spheres of influence met in medieval central Europe, the only way for male lineages to expand further may have been in a northerly or southerly direction. Interestingly, in our pseudo-admixture analysis, even the male lineages within contemporary Germany turned out to be notably different in the North-East (n=752; 43% Eastern vs 35% Western), the South East (n=752; 39% Eastern vs 44% Western) and the West (n=1,287; 32% Eastern vs 49% Western). When samples are stratified in this way, the difference between the three Y-STR haplotype spectra is highly significant ( 2=3.945, 2 df, P<0.001). The area covered by the former German Democratic Republic significantly overlaps with the homeland of Slavic (i.e. Wendish) people from the Middle Ages, including the Sorbes, Pomeranes, Wagriens, Obodrites, and Ranes. This geographical coincidence would explain the obvious preservation of Slavic haplotypes in eastern Germany far better than, for example, the settlement of eastern European World War II refugees, since the latter were mostly Germans anyway.

    In the Netherlands, a remarkable subdivision became apparent in that the two southern samples (n=96) were included in the Western Europe sub-cluster whereas the three northern samples (n=179) formed part of a Friesian sub-cluster, together with Denmark. The significant difference between the two Dutch regions was exclusively due to haplotypes 14-13-16-24-10-13-13 and 14-13-16-24-11-13-13 . Their combined frequency was 16/179=0.089 in the North and 23/96=0.240 in the South ( 2=1.583, 1 df, P<0.001). If the two haplotypes, which are also the most frequent ones in Spanish males, are excluded from both meta-samples, pair-wise ST drops from a highly significant 0.0183 (P=0.003) to an insignificant 0.0069 (P=0.086). In the light of the 1–2% background migration implied by the general overlap in Y-STR haplotype spectra, however, such an isolated and focused frequency difference must have had a fairly recent origin for it not to have been eradicated. One possible explanation for this coincidence would be a war-related instance from the 15th and 16th centuries when the south of the Netherlands came under Burgundian and Spanish control much earlier than the northern provinces. The latter formed the Union of Utrecht in 1579 and gained independence from Spain earlier than the southern Union of Arras (Merriman 1996).

    Our considerations about the origin of Dutch Y-STR differences have been based upon various simplifying assumptions, the validity of which is not, however, critical for our main conclusion. First, we have adopted an ISM which is known to overestimate the number of STR alleles (or haplotypes) generated by step-wise mutation (Shriver et al. 1993). In part, this can be corrected for by adopting smaller values in the ISM; i.e. smaller population sizes and/or a smaller mutation rate. However, even if we assume =1×10–2 for the seven Y-STRs combined, this leads to N1=7,836, N2=2,596, M=22, and m1=0.0028, m2=0.0085. Such a level of background mutation is still incompatible with the persistence over more than 100 generations of a 8.9 vs 24.0% allele frequency difference for a Y-SNP, and even more so for a Y-STR. Second, we have neglected migration from outside the Netherlands. Since this can be allowed for by increasing the mutation rate, the effective population sizes would have to be even smaller and the relative background migration even higher than before. Similarly, we have assumed that every migrant introduces a new haplotype. Since this is clearly untrue, even under an ISM, the actual level of migration must have been even higher than estimated in order to achieve the observed effects upon ; i.e. an apparent increase in size over that expected if the two regions had been completely separated. Third, we assumed constant migration and a constant population size, whereas in reality the two populations would have undergone exponential expansion. This simplifying assumption would have biased the interpretation of the haplotype pattern in favour of our hypothesis only if the two regions had experienced a lot of migration occurring between them when populations were small, and became completely separated only more recently. If anything, European history suggests the opposite to be true. Finally, it can be shown that the difference between the two Dutch sub-regions is not detectable with Y-SNPs. SNP haplotype data were available for 171 (North) and 87 (South) of the males included in the Y-STR study, respectively, and the pair-wise ST value obtained with the discriminating Y-SNPs resolving the relevant European haplogroups was 0.0041 (P=0.209).

    In western Europe, Y-STRs identified a large coherent population pool, covering the Iberian Peninsula, parts of Italy, France (Alsace) and the British Isles, which coincides with the Frankonian Empire. Being the heiress of multiethnic Rome, Latin Europe (i.e. the part of Europe that was originally Roman Catholic rather than Greek orthodox or non-Christian) formed a zone where strong shared cultural features were as important as geographical contrasts (Bartlett 1994). Italian- and Germanic-speaking populations were integrated by adopting a common culture that was further consolidated by a strong political system. The eastern part of Europe, also identified by Y-STRs as being homogeneous in terms of its male genetic make-up, has a completely different history. This part of the continent was significantly influenced by various waves of immigration by nomadic Asian populations (Rosser 2000; Wells et al. 2001). Nevertheless, in the vast and hardly structured territory covered by our analysis, with no borders to the east, the Slavic language was clearly a strong uniting element for diverse cultures. The colonisation attempts of western civilisations appear to have left no significant genetic traces in eastern Europe and, during the 20th century, genocide and resettlement have both served to homogenise the (formerly more varied) genetic landscape even further (Ploski et al. 2002).

    In the Baltics, our analysis confirmed that Estonian male lineages are comparatively close to both the Central Europeans and Finnish, but differ strikingly from the Lithuanian and Latvian Y-STR haplotype spectra (Lessig et al. 2001). The difference between the two samples/meta-samples is partly attributable to haplotypes 14-14-16-23-11-14-14 and 14-14-16-24-11-14-14 which occurred with frequencies of 14/129=0.109 in Estonia and 4/296=0.014 in the other two countries (Fisher s exact two-sided P=3.1•10–5). These two haplotypes are also the most frequent ones among Finish males. With one exception ( R1a1 on a Latvian chromosome), they were found to be associated with Y-SNP haplogroup N3 in the Baltic samples. Haplogroup N3 is indeed more frequent in Estonia (49/129=0.380) than in Latvia and Lithuania (80/296=0.270; 2=5.103, 1 df, P=0.024) but not when the above haplotypes are excluded (35/115=0.304 vs 77/292=0.264; 2=0.648, 1 df, P>0.4). Interestingly, the most frequent Estonian haplotype is 14-12-16-22-10-11-13 , with a frequency of 9/129 = 0.070 versus 1/296 = 0.003 in Latvia and Lithuania (Fisher s exact two-sided P=1.3•10–4). This haplotype is the third most frequent one in Germany, and all but one copy in the Baltic samples were found to reside on SNP haplogroup I . Nevertheless, the Y-STR haplotype frequency difference is not explicable in terms of a generally higher frequency of haplogroup I in Estonians. Excluding the ten Germanic Y-STR haplotypes in question, the frequencies of haplogroup I are virtually identical (15/120=0.125 in Estonia and 33/295=0.112 in Latvia/Lithuania). The most likely explanation for the substantial division exhibited by the Baltic male lineages is the linguistic barrier that separates the Lithuanians and Latvians, who speak two of the three Baltic languages, and the Estonians, whose language is part of the Finno-Ugric group. The similarity of the Lithuanian and Latvian Y-chromosomal gene pool, in turn, is potentially explicable by the fact that a large proportion of present-day Latvia came under Lithuanian-Polish control in 1561 and remained so until the second division of Poland in 1772 (Gieysztor et al.1979).

    The sub-cluster broadly described as Balkan-Danube comprises Greek, Romanian, Bulgarian and Hungarian males, i.e. members of populations who speak languages from very different families. The Balkan-Danube sub-cluster is also a relatively short distance away from the Turks (Fig. 2) and relatively distant to the eastern (Slavic) samples. This pattern of genetic similarity may seem counterintuitive at first glance since the geographical region of origin of the Balkan-Danube meta-sample overlaps considerably with the territory occupied by the southern Slavs after their separation from the eastern and western Slavic populations in the fifth and sixth centuries (Gimbutas 1971). In the 16th century, however, the same territory was ruled by the Turks during the Ottoman expansion and, 1,000 years earlier, Finno-Ugric-speaking (Magyars) and Turkic-speaking people (e.g. the Proto-Bulgarians) from western Asia had already invaded and settled in the Danube basin and the Balkans, and had consequently amalgamated with the southern Slavic populations present. Another important factor that divides the Slavic world has been religious orientation, and even today one of the sharpest cultural divisions in the Slavic world is that between people converted to Christianity by the Franks and the Greeks, respectively (Bartlett 1994). More than anywhere else, the genetic record of the Balkan-Danube region can thus be read as a palimpsest of repeatedly overwritten historical processes (Jobling et al. 2004).

    The appearance of singletons which are clearly genetically different from the surrounding populations is a result of sampling either from highly admixed and heterogeneous Metropolitan populations (Paris, Vienna), or sampling populations from the fringes of Europe that have a very distinct history (Finns, Estonians, Irish, Albanians). For the latter category, the most important force creating genetic individuality would have been patrilocality, a socially instituted practice whereby a newly-married couple live with or near the family of the husband. The importance of social (family) structure in influencing the population genetic diversity of patrilocal societies has been described in tribal populations (Oota et al. 2001), but can also be observed in Europe (Seielstad et al. 1998).

    Many of the population structures revealed in the present study could potentially be related to recent historical events. Irrespective of whether these links are true, they would have been less likely to be discernible by Y-SNP analyses, which usually mark much earlier waves of population movement (see the Dutch and Baltic examples above). Single-nucleotide substitutions are known to occur at a rate of approximately 2–5×10–9 per generation (Cooper and Krawczak 1993) implying that common selectively neutral SNPs are likely to have arisen before the major expansion of the human population. With their demic diffusion throughout the world, Y-SNPs could therefore only create local genetic structures in populations that had become particularly isolated. With Y-STRs, by contrast, the rapid mutation process constantly generates new genetic variation that allows genetic structures to change more easily. Furthermore, even with their substantial variation in marker-specific mutation rates, Y-STRs usually manifest so many meiotic mutations in evolutionarily related haplotypes that the actual choice of markers is fairly inconsequential to the inferred nature of the genealogical process. In this respect, Y-STRs represent a much more robust population genetic tool than Y-SNPs, which may have substantially different time-depths and can thus create layers of incongruent maps (Jobling and Tyler-Smith 2003).

    In summary, we have shown that Y-STRs are capable of resolving male genealogies in Europe to an unparalleled degree. Although it is inherently difficult to prove by Y-STR analysis alone whether a particular genetic division is of recent or prehistoric origin, or whether it would have been detectable by Y-SNPs as well, it suggests that Y-STRs should be considered as the markers of choice for studies of local population structure and recent demographic history. Therefore, sampling in YHRD is currently concentrating upon an expansion of the database to Eurasia as well as to the Americas in order to facilitate investigation of migration processes both to and from Europe that occurred during the past millennium.


    Fig. 1 Geographical origin of 91 European male DNA samples. The colour coding of meta-samples, formed by clustering samples within a country according to minimum ST, is given in the inset. Black circles mark singleton samples which were not included in any meta-sample. Meta-samples include Spain (Andalucia, Aragon, Asturias, Caceres, Cantabria, Catalonia, Galicia, Madrid, Valencia), Portugal (North, Central and South Portugal, Madeira), South Holland (Limburg, Zeeland), North Holland (Friesland, Groningen, Leiden), Sweden (Blekinge, Gotland, Ostergoetland, Skaraborg, Stockholm, Uppsala, Vaermland), Norway (North, Central, East, West and South Norway, Oslo), West Germany (Cologne, Düsseldorf, Freiburg, Hamburg, Mainz, Münster, Stuttgart), North-East Germany (Berlin, Rostock), South-East Germany (Chemnitz, Greifswald, Leipzig, Magdeburg, Munich), Central Italy (Lombardy, Marche, Tuscany, Umbria), West Italy (Latium, Liguria, Puglia), and Poland (Bydgoszcz, Gdansk, Krakow, Lublin, Warsaw, Wroclaw).



    Fig. 2 Clustering by minimum Y-STR-based ST of 45 male European samples and meta-samples. The significance of individual groupings is indicated by vertical bars below the dendrogram (top line randomisation P<0.05, bottom line P<0.001).



    Fig. 3 Spatial autocorrelation analysis of European Y-STR haplotypes. Moran s I index was calculated from the repeat number at each Y-STR locus, using the Great Circle Distance between the respective recruitment units as a measure of pair-wise geographical distance between haplotypes.


    Fig. 4a–c Multidimensional scaling analysis of pair-wise Y-STR-based ST between 91 male European samples. Displayed are the first three dimensions (a–c) which together account for 96.4% of the variance. Sample locations are marked in black; colour coding is on an arbitrary rainbow scale that allocates yellow and magenta to the opposite extremes, via green and blue.



    Fig. 5 Longitudinal and latitudinal extent of relatedness among European Y-STR haplotypes. Each dot represents one of 91 recruitment units and depicts the Spearman correlation coefficient of the pair-wise ST values between that unit and all other samples with the respective geographical distances. Horizontal axis correlation with latitudinal distances (north–south), vertical axis correlation with longitudinal distances (east–west).

    Last edited by Triglav; Friday, January 28th, 2005 at 05:02 AM.
    "slavic" languages are absolutely arteficial (Read "slawenlegende"). The "glagolica", invented by a bunch of monks, is nothing but an ancient esperanto, creating new words, definitions and alphabet out of regional slangs.

    The craddle of European Civilization comes from the North. All blond people originate from the north. So if you see a blond-blue eyed Slovene, Russian, Czech, Polak ect., you can be 100% sure that his ancient ancestors originated from "Germanics" (Germanic = Nordic).
    "slovenja" was the settelment of the Langobards = Germanics/Teutons. "Poland" of the Goths and East-Vandals ect. ect. What do "slavs" tell us about their origin?
    Some silly story that they originate from some swamps in the east and popped out of no where into history.

    So you see my dear "Gorostan" [=Triglav], you are in reality a "Germanic" indoctrinated with panslav propaganda and historic fantasy stories. ~Dr. Brandt, former TNP and Skadi member

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    Post Re: Signature of recent historical events in the European Y-chr. STR haplotype distr.

    Nicely put together, my friend.

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    Post Re: Signature of recent historical events in the European Y-chr. STR haplotype distr.

    Quote Originally Posted by Triglav
    [color=#444444][font=Arial][size=2]Originally posted by Dalonord.

    Signature of recent historical events in the European Y-chromosomal STR haplotype distribution[color=Black]


    Lutz Roewer1, Peter J. P. Croucher2, 3, Sascha Willuweit1, Tim T. Lu3, Manfred Kayser4, 5, Rüdiger Lessig6, Peter de Knijff7, Mark A. Jobling8, Chris Tyler-Smith9 and Michael Krawczak3
    (1) Institute of Legal Medicine, Humboldt-University, Berlin, Germany
    (2) First Department of Medicine, Christian-Albrechts-University, Kiel, Germany
    (3) Institute of Medical Informatics and Statistics, Christian-Albrechts-University, Brunswiker Strasse 10, Kiel, Germany
    (4) Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany
    (5) Department of Forensic Molecular Biology, Erasmus University, Rotterdam, The Netherlands
    (6) Institute of Legal Medicine, University of Leipzig, Germany
    (7) Forensic Laboratory for DNA Research, Leiden University, The Netherlands
    (8) Department of Genetics, University of Leicester, UK
    (9) The Wellcome Trust Sanger Institute, Hinxton, UK

    Michael Krawczak
    Email: krawczak@medinfo.uni-kiel.de
    Phone: +49-431-5973200
    Fax: +49-431-5973193
    Received: 13 May 2004 Accepted: 13 September 2004 Published online: 20 January 2005


    Abstract

    Previous studies of human Y-chromosomal single-nucleotide polymorphisms (Y-SNPs) established a link between the extant Y-SNP haplogroup distribution and the prehistoric demography of Europe. By contrast, our analysis of seven rapidly evolving Y-chromosomal short tandem repeat loci (Y-STRs) in over 12,700 samples from 91 different locations in Europe reveals a signature of more recent historic events, not previously detected by other genetic markers. Cluster analysis based upon molecular variance yields two clearly identifiable sub-clusters of Western and Eastern European Y-STR haplotypes, and a diverse transition zone in central Europe, where haplotype spectra change more rapidly with longitude than with latitude. This and other observed patterns of Y-STR similarity may plausibly be related to particular historical incidents, including, for example, the expansion of the Franconian and Ottoman Empires. We conclude that Y-STRs may be capable of resolving male genealogies to an unparalleled degree and could therefore provide a useful means to study local population structure and recent demographic history.
    L. Roewer and P.J.P. Croucher contributed equally to this paper.
    Would anyone have access to the PDF file for this research paper?
    Jesus loves Jews and Muslims just the way they are. Cthulhu thinks they need ketchup.

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    Post AW: Re: Signature of recent historical events in the European Y-chr. STR haplotype distr.

    Quote Originally Posted by Allenson
    Nicely put together, my friend.
    In which format was the study published? PDF or HTML?
    "slavic" languages are absolutely arteficial (Read "slawenlegende"). The "glagolica", invented by a bunch of monks, is nothing but an ancient esperanto, creating new words, definitions and alphabet out of regional slangs.

    The craddle of European Civilization comes from the North. All blond people originate from the north. So if you see a blond-blue eyed Slovene, Russian, Czech, Polak ect., you can be 100% sure that his ancient ancestors originated from "Germanics" (Germanic = Nordic).
    "slovenja" was the settelment of the Langobards = Germanics/Teutons. "Poland" of the Goths and East-Vandals ect. ect. What do "slavs" tell us about their origin?
    Some silly story that they originate from some swamps in the east and popped out of no where into history.

    So you see my dear "Gorostan" [=Triglav], you are in reality a "Germanic" indoctrinated with panslav propaganda and historic fantasy stories. ~Dr. Brandt, former TNP and Skadi member

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    Post Re: AW: Re: Signature of recent historical events in the European Y-chr. STR haplotype distr.

    Quote Originally Posted by Triglav
    In which format was the study published? PDF or HTML?

    HTML. That's why I posted it at Stirpes the way I did. PDF would have been so much easier.

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