Genetic variation in the Sorbs of eastern Germany in the context of broader European genetic diversity

Abstract

Population isolates have long been of interest to genetic epidemiologists because of their potential to increase power to detect disease-causing genetic variants. The Sorbs of Germany are considered as cultural and linguistic isolates and have recently been the focus of disease association mapping efforts. They are thought to have settled in their present location in eastern Germany after a westward migration from a largely Slavic-speaking territory during the Middle Ages. To examine Sorbian genetic diversity within the context of other European populations, we analyzed genotype data for over 30 000 autosomal single-nucleotide polymorphisms from over 200 Sorbs individuals. We compare the Sorbs with other European individuals, including samples from population isolates. Despite their geographical proximity to German speakers, the Sorbs showed greatest genetic similarity to Polish and Czech individuals, consistent with the linguistic proximity of Sorbian to other West Slavic languages. The Sorbs also showed evidence of subtle levels of genetic isolation in comparison with samples from non-isolated European populations. The level of genetic isolation was less than that observed for the Sardinians and French Basque, who were clear outliers on multiple measures of isolation. The finding of the Sorbs as only a minor genetic isolate demonstrates the need to genetically characterize putative population isolates, as they possess a wide range of levels of isolation because of their different demographic histories.

Extensive genome-wide autozygosity in the population isolates of Daghestan

“…To minimize bias from high withingroup covariance for larger samples sizes, we used a 'drop one in' procedure described by Veeramah et al 10 Genetic differentiation was estimated by the ARLEQUIN 3.5 software 50 and SMARTPCA program in the EIGENSOFT software package. 48 To assess the extent of inbreeding in Daghestan, we used three different measures of genome-wide homozygosity: (1) the coefficient of inbreeding F as obtained from PLINK, 13 (2) a population-based estimate of the distribution of ROH as measured by a logarithm of the odds (LOD) score 19,22 with the same parameters as those used by Pemberton et al 19 and (3) an individual-based estimate of the distribution of ROH using PLINK 13 with the parameters identical to McQuillan et al 20 Estimates of F as obtained from PLINK (which assumes independence among SNPs) were performed on the merged data set of 104 519 SNPs in 56 populations, whereas the LOD and PLINK-ROH analyses were performed on our Axiom data set in 480 individuals from 33 populations (549 008 SNPs).…”

“…In addition, population isolates are hypothesized to possess lower levels of allelic heterogeneity underlying disease traits and higher levels of linkage disequilibrium (LD), which suggests, when coupled with a relatively homogeneous background, that they may also be useful for the identification of susceptibility genes for complex diseases and quantitative traits. [7][8][9][10] However, it is important to characterize the level of inbreeding in a population isolate to determine its usefulness for examining particular diseases. Whereas the study of population isolates that were recently founded from a small number of individuals and that have undergone population expansions are useful for identifying loci associated with rare recessive diseases (for example, Finns), older population isolates with constant small N e may be more helpful for finding loci contributing to complex disease (for example, the Saami).…”

“…13 Importantly, this method can also distinguish between recent and more ancient consanguinity based on homozygous tract lengths. 10,12,[14][15][16][17][18][19][20] Recently, a model-based approach for detecting ROH was described that better accounts for missing data because of potential sequencing error, is potentially more sensitive to detecting true autozygous segments and does not require a priori size boundaries for different size classes that may introduce bias when comparing populations with different histories. 19,21,22 In this study we examine the level of inbreeding and population structure using genome-wide autosomal single-nucleotide polymorphisms (SNPs) genotyped in 20 Daghestanian populations belonging to 19 ethnic groups from the Caucasus Mountains.…”

Coevolution of genes and languages and high levels of population structure among the highland populations of Daghestan

“…To We applied PCA on the merged autosomal data set using a 'drop one in' procedure for incorporating populations 52 ( Supplementary Figure 2). Specifically, PCA analysis was performed for each individual from a Daghestani population isolate along with all other samples.…”

“…Daghestani isolated populations and uneven sample sizes 52 . In general, the resulting PCA plot separates regional populations according to their geographical location.…”