Genome-Wide Analysis of Single Nucleotide Polymorphisms Uncovers Population Structure in Northern Europe

Abstract

BackgroundGenome-wide data provide a powerful tool for inferring patterns of genetic variation and structure of human populations.Principal FindingsIn 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.SignificanceOur results warn against a priori assumptions of homogeneity among Finns and other seemingly isolated populations. Thus, in association studies in such populations, additional caution for population structure may be necessary. Our results illustrate that population history is often important for patterns of genetic variation, and that the analysis of hundreds of thousands of SNPs provides high resolution also for population genetics.

Genetic markers and population history: Finland revisited

“…11,12 Furthermore, differences in the Y-chromosomal and autosomal variation between western and eastern parts of the country have been revealed. 4,5,7,13 Analyses of linkage disequilibrium are also in line with the expectations based on the demographic history scenario described above. 14,15 Curiously, however, the mtDNA diversity patterns found among Finns appear to be at odds with the Y-chromosomal variation and also with the proposed 'medical genetic' scenario of population history.…”

“…16 No significant structure was detected in the small 9-locus autosomal STR data within Finland, which at first appears to be in contrast with the recent results from genome-wide SNP data. 7 However, even with 250 000 SNP markers, the differentiation between eastern and western Finland remains low in absolute terms (F ST ¼ 0.0032) 7 and not drastically different than the estimates obtained here with a small set of autosomal markers.…”

Genomic landscape of positive natural selection in Northern European populations

“…We analyzed Affymetrix (Santa Clara, CA, USA) 250K Sty array data from Eastern and Western Finland, Sweden, 18 Northern Germany, 21 and Great Britain 22 (hereafter, 250K data), combined with 250K Nsp array data from the Germans and the British (hereafter, 500K data). We also used HapMap 12,23 250K and 500K data provided by Affymetrix for estimating genetic differentiation between continents -selection scans for the HapMap populations have been performed previously.…”

“…However, many are likely to arise from false negatives caused by the low power to detect selection, and differences in power between populations because of different allele frequencies, demography, and sample size. 7,9,18,51 This study is not intended to be an exhaustive analysis of positive selection in Northern Europe. Statistical methods to scan for signs of positive natural selection are plagued by several limitations, and no method is suitable for covering the full spectrum of natural selection.…”

“…Additional large data sets have recently become available through genome-wide SNP scans, providing data of a large numbers of individuals from a variety of populations. These data have also provided a powerful tool for analyzing population differentiation and structure, [14][15][16][17][18] but to date, only a few studies have used similar data sets for analyzing traces of positive natural selection. 5,10,19,20 In this study, we used a genome-wide data set from Eastern and Western Finland, Sweden, Northern Germany, and Great Britain, and a combination of three statistical methods to search for loci that have been affected by recent natural selection.…”