Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 6 (2), e16747

Swedish Population Substructure Revealed by Genome-Wide Single Nucleotide Polymorphism Data


Swedish Population Substructure Revealed by Genome-Wide Single Nucleotide Polymorphism Data

Elina Salmela et al. PLoS One.


The use of genome-wide single nucleotide polymorphism (SNP) data has recently proven useful in the study of human population structure. We have studied the internal genetic structure of the Swedish population using more than 350,000 SNPs from 1525 Swedes from all over the country genotyped on the Illumina HumanHap550 array. We have also compared them to 3212 worldwide reference samples, including Finns, northern Germans, British and Russians, based on the more than 29,000 SNPs that overlap between the Illumina and Affymetrix 250K Sty arrays. The Swedes--especially southern Swedes--were genetically close to the Germans and British, while their genetic distance to Finns was substantially longer. The overall structure within Sweden appeared clinal, and the substructure in the southern and middle parts was subtle. In contrast, the northern part of Sweden, Norrland, exhibited pronounced genetic differences both within the area and relative to the rest of the country. These distinctive genetic features of Norrland probably result mainly from isolation by distance and genetic drift caused by low population density. The internal structure within Sweden (F(ST) = 0.0005 between provinces) was stronger than that in many Central European populations, although smaller than what has been observed for instance in Finland; importantly, it is of the magnitude that may hamper association studies with a moderate number of markers if cases and controls are not properly matched geographically. Overall, our results underline the potential of genome-wide data in analyzing substructure in populations that might otherwise appear relatively homogeneous, such as the Swedes.

Conflict of interest statement

Competing Interests: The authors have read the journal's policy and have the following conflicts: Prof. Schreiber has been a member of Applied Biosystems scientific advisory board. No Applied Biosystems product or services were used in this study. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.


Figure 1
Figure 1. A map of the studied provinces and regions of Sweden and Finland.
Full population names and their sample sizes are given in Table 1 and Table S1.
Figure 2
Figure 2. Multidimensional scaling plots of genetic distances between individuals.
Identity by state (IBS) distances in Northern Europe (a), Sweden and Finland (b), Sweden (c) and Norrland (d), with the legend for panels (b) and (c) in (e). The axis labels show the proportion of variance explained by the axis. Abbreviations as in Table 1 and Table S1. In (d), the colouring of individuals represents one of the ten major river valleys of Norrland, from north to south. See also Figure S1 for animated three-dimensional versions of (a) and (b).
Figure 3
Figure 3. Clustering of North European individuals by the Structure software.
Each individual is represented by a thin vertical line, and their proportions of ancestry in each of the K inferred clusters (from 2 to 5) are denoted by colors. Abbreviations as in Table 1.
Figure 4
Figure 4. Distributions of pairwise identities by state between North European populations and four HapMap populations.
Each curve represents the IBS similarities of all pairs of individuals where one individual is from the HapMap population in question and one from the population indicated by the color of the curve. The location of distribution medians is denoted by triangles of corresponding color. All distributions with CEU differed significantly (p<0.015) except Eastern Finland vs. Russia, Götaland vs. Germany, and Svealand vs. Germany. All distributions with CHB+JPT differed significantly (p<0.002) except Eastern Finland vs. Russia, Götaland vs. Germany, and Svealand vs. Norrland. In the comparison with YRI, Germany and Russia differed significantly from all populations except each other, and Eastern Finland from Götaland (p<0.027 for each). These p values have been Bonferroni-corrected. Abbreviations: Yoruba from Ibadan, Nigeria (YRI, n = 105); Han Chinese from Beijing, China (CHB, n = 78); and Japanese from Tokyo, Japan (JPT, n = 84); other abbreviations as in Table 1.
Figure 5
Figure 5. Local genetic variation within Sweden.
The colour of each area corresponds to the local value of median ancestry proportion in one of two Structure-inferred clusters (a), median inbreeding coefficient (b) and correlation of genetic and geographic distances (c), calculated in circles with a radius of 150 km and depicted only for those circles that had at least 20 samples (at least 40 in (c)).

Similar articles

See all similar articles

Cited by 12 articles

See all "Cited by" articles


    1. Lao O, Lu TT, Nothnagel M, Junge O, Freitag-Wolf S, et al. Correlation between genetic and geographic structure in Europe. Curr Biol. 2008;18:1241–1248. - PubMed
    1. Novembre J, Johnson T, Bryc K, Kutalik Z, Boyko AR, et al. Genes mirror geography within Europe. Nature. 2008;456:274. - PMC - PubMed
    1. Heath SC, Gut IG, Brennan P, McKay JD, Bencko V, et al. Investigation of the fine structure of European populations with applications to disease association studies. Eur J Hum Genet. 2008;16:1413–1429. - PubMed
    1. Salmela E, Lappalainen T, Fransson I, Andersen PM, Dahlman-Wright K, et al. Genome-wide analysis of single nucleotide polymorphisms uncovers population structure in Northern Europe. PLoS ONE. 2008;3:e3519. - PMC - PubMed
    1. Jakkula E, Rehnstrom K, Varilo T, Pietilainen OP, Paunio T, et al. The genome-wide patterns of variation expose significant substructure in a founder population. Am J Hum Genet. 2008;83:787–794. - PMC - PubMed

Publication types