Global genetic distances (graph map).
Have been looking for this map for a long time since AF was down, finally found it.
http://i88.photobucket.com/albums/k1...aterearr-1.gif
Enlarged pic of Euro cluster:
http://img132.imageshack.us/img132/6684/60550356.jpg
Notice how the distances between Europeans are many times smaller than even between them and other Caucasoids (Indians, Arabs, Iranians, Caucasus and Volga-Urals people).
Finnland, Spain and Romania are a little removed from the main cluster, but insignificantly so. Rest of Europe, from France to Russian and from Norway to Hungary is indistinguishable on the global plot.
Asians are much more diverse:
http://img195.imageshack.us/img195/9749/66475183.jpg
And Africans ever more so, especially Khoi-San vs SSA (Bantoids). It is interesting that Bushmen form a third cluster in Africa, different from both SSA and Khoi-San, and not between them (as i would expect).
Horners (Tigri, Amhara et cetera) are between Euro/Middle-East and SSA, and appear to be roughly equidistant from them.
Amerindians are very distant from Asians, not much closer to them than to Europeans, ruining the myth about them belonging to Mongoloid race (they clearly form a separate one). Same for Australoids.
Interestingly, Asians proper appear to be between Austroloid and Amerindians, plus a little tilted to the European. So would you get a Chinese by mixing an Australian Aborigine with Sylvid and adding a Euro great-grandparent ;)?
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300 000 SNPS - Heath et al
An investigation into fine-scale European population structure was carried out using high-density genetic variation on nearly 6000 individuals originating from across Europe. The individuals were collected as control samples and were genotyped with more than 300 000 SNPs in genome-wide association studies using the Illumina Infinium platform. A major East–West gradient from Russian (Moscow) samples to Spanish samples was identified as the first principal component (PC) of the genetic diversity. The second PC identified a North–South gradient from Norway and Sweden to Romania and Spain. Variation of frequencies at markers in three separate genomic regions, surrounding LCT, HLA and HERC2, were strongly associated with this gradient. The next 18 PCs also accounted for a significant proportion of genetic diversity observed in the sample. We present a method to predict the ethnic origin of samples by comparing the sample genotypes with those from a reference set of samples of known origin. These predictions can be performed using just summary information on the known samples, and individual genotype data are not required. We discuss issues raised by these data and analyses for association studies including the matching of case-only cohorts to appropriate pre-collected control samples for genome-wide association studies
For more information, method etc click link
http://www.nature.com/ejhg/journal/v...g2008210a.html
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The plot below shows variation internallly in a Country, in this case Germany(Dresden - Munich)
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Lao et al 2008 - 500 000 SNPs
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Salmela et al 2008 - 250 000 SNPs
In this study, we analysed almost 250,000 SNPs from a total of 945 samples from Eastern and Western Finland, Sweden, Northern Germany and Great Britain complemented with HapMap data. Small but statistically significant differences were observed between the European populations (FST = 0.0040, p<10−4), also between Eastern and Western Finland (FST = 0.0032, p<10−3). The latter indicated the existence of a relatively strong autosomal substructure within the country, similar to that observed earlier with smaller numbers of markers. The Germans and British were less differentiated than the Swedes, Western Finns and especially the Eastern Finns who also showed other signs of genetic drift. This is likely caused by the later founding of the northern populations, together with subsequent founder and bottleneck effects, and a smaller population size. Furthermore, our data suggest a small eastern contribution among the Finns, consistent with the historical and linguistic background of the population.
http://www.plosone.org/article/info:...l.pone.0003519
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Nelis et al 2009 - 270000 SNPs
Using principal component (PC) analysis, we studied the genetic constitution of 3,112 individuals from Europe as portrayed by more than 270,000 single nucleotide polymorphisms (SNPs) genotyped with the Illumina Infinium platform. In cohorts where the sample size was >100, one hundred randomly chosen samples were used for analysis to minimize the sample size effect, resulting in a total of 1,564 samples. This analysis revealed that the genetic structure of the European population correlates closely with geography. The first two PCs highlight the genetic diversity corresponding to the northwest to southeast gradient and position the populations according to their approximate geographic origin. The resulting genetic map forms a triangular structure with a) Finland, b) the Baltic region, Poland and Western Russia, and c) Italy as its vertexes, and with d) Central- and Western Europe in its centre. Inter- and intra- population genetic differences were quantified by the inflation factor lambda (λ) (ranging from 1.00 to 4.21), fixation index (Fst) (ranging from 0.000 to 0.023), and by the number of markers exhibiting significant allele frequency differences in pair-wise population comparisons. The estimated lambda was used to assess the real diminishing impact to association statistics when two distinct populations are merged directly in an analysis. When the PC analysis was confined to the 1,019 Estonian individuals (0.1% of the Estonian population), a fine structure emerged that correlated with the geography of individual counties. With at least two cohorts available from several countries, genetic substructures were investigated in Czech, Finnish, German, Estonian and Italian populations. Together with previously published data, our results allow the creation of a comprehensive European genetic map that will greatly facilitate inter-population genetic studies including genome wide association studies (GWAS).
http://www.plosone.org/article/info:...l.pone.0005472
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Tian et al 2009 - 300 000 SNPS
The definition of European population genetic substructure and its application to understanding complex phenotypes is becoming increasingly important. In the current study using over 4,000 subjects genotyped for 300,000 single-nucleotide polymorphisms (SNPs), we provide further insight into relationships among European population groups and identify sets of SNP ancestry informative markers (AIMs) for application in genetic studies. In general, the graphical description of these principal components analyses (PCA) of diverse European subjects showed a strong correspondence to the geographical relationships of specific countries or regions of origin. Clearer separation of different ethnic and regional populations was observed when northern and southern European groups were considered separately and the PCA results were influenced by the inclusion or exclusion of different self-identified population groups including Ashkenazi Jewish, Sardinian, and Orcadian ethnic groups. SNP AIM sets were identified that could distinguish the regional and ethnic population groups. Moreover, the studies demonstrated that most allele frequency differences between different European groups could be controlled effectively in analyses using these AIM sets. The European substructure AIMs should be widely applicable to ongoing studies to confirm and delineate specific disease susceptibility candidate regions without the necessity of performing additional genome-wide SNP studies in additional subject sets.
http://www.ncbi.nlm.nih.gov/pmc/arti...9/?tool=pubmed
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The Impact of Divergence Time on the Nature of Population Structure: An Example from Iceland
The Icelandic population has been sampled in many disease association studies, providing a strong motivation to understand the structure of this population and its ramifications for disease gene mapping. Previous work using 40 microsatellites showed that the Icelandic population is relatively homogeneous, but exhibits subtle population structure that can bias disease association statistics. Here, we show that regional geographic ancestries of individuals from Iceland can be distinguished using 292,289 autosomal single-nucleotide polymorphisms (SNPs). We further show that subpopulation differences are due to genetic drift since the settlement of Iceland 1100 years ago, and not to varying contributions from different ancestral populations. A consequence of the recent origin of Icelandic population structure is that allele frequency differences follow a null distribution devoid of outliers, so that the risk of false positive associations due to stratification is minimal. Our results highlight an important distinction between population differences attributable to recent drift and those arising from more ancient divergence, which has implications both for association studies and for efforts to detect natural selection using population differentiation.
http://www.plosgenetics.org/article/...l.pgen.1000505
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Nordic Database - 45k SNPs
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Quote:
Top axes of genetic variation in the Nordic Control Database (4620 samples) contrasted with the CEU population (108 samples) HapMap and a Finnish reference population (81 samples). The MDS analysis was performed on approximately 45K SNPs that were common between the genotyping platforms. The samples are represented with the color of their country of origin: Finland (red), Sweden (green) and Denmark (yellow). The geographical map is highlighted for comparison.
CAPS is Swedish
SGENE & MS are Finnish (Helsinki)
Aneurysm is Finnish (Helsinki and Kupio)
http://www.nordicdb.org/database/Map.html
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Moskvina et al. 2010 - 40k SNPs
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Genetic Differences between Five European Populations
Abstract:
Quote:
Aims: We sought to examine the magnitude of the differences in SNP allele frequencies between five European populations (Scotland, Ireland, Sweden, Bulgaria and Portugal) and to identify the loci with the greatest differences. Methods: We performed a population-based genome-wide association analysis with Affymetrix 6.0 and 5.0 arrays. We used a 4 degrees of freedom χ2 test to determine the magnitude of stratification for each SNP. We then examined the genes within the most stratified regions, using a highly conservative cutoff of p < 10–45. Results: We found 40,593 SNPs which are genome-wide significantly (p ≤ 10–8) stratified between these populations. The largest differences clustered in gene ontology categories for immunity and pigmentation. Some of the top loci span genes that have already been reported as highly stratified: genes for hair color and pigmentation (HERC2, EXOC2, IRF4), the LCT gene, genes involved in NAD metabolism, and in immunity (HLA and the Toll-like receptor genes TLR10, TLR1, TLR6). However, several genes have not previously been reported as stratified within European populations, indicating that they might also have provided selective advantages: several zinc finger genes, two genes involved in glutathione synthesis or function, and most intriguingly, FOXP2, implicated in speech development. Conclusion: Our analysis demonstrates that many SNPs show genome-wide significant differences within European populations and the magnitude of the differences correlate with the geographical distance. At least some of these differences are due to the selective advantage of polymorphisms within these loci.
http://content.karger.com/ProdukteDB...oduktNr=224250
From Gypsies on a Genetic Island
