Pallantides
12-09-2010, 03:31 PM
A genome-wide analysis of population structure in the Finnish Saami with implications for genetic association studies
http://www.nature.com/ejhg/journal/vaop/ncurrent/full/ejhg2010179a.html
http://img690.imageshack.us/img690/9759/admixture.jpg
http://img98.imageshack.us/img98/526/ibsq.jpg
http://img193.imageshack.us/img193/5016/joiningtree.jpg
The understanding of patterns of genetic variation within and among human populations is a prerequisite for successful genetic association mapping studies of complex diseases and traits. Some populations are more favorable for association mapping studies than others. The Saami from northern Scandinavia and the Kola Peninsula represent a population isolate that, among European populations, has been less extensively sampled, despite some early interest for association mapping studies. In this paper, we report the results of a first genome-wide SNP-based study of genetic population structure in the Finnish Saami. Using data from the HapMap and the human genome diversity project (HGDP-CEPH) and recently developed statistical methods, we studied individual genetic ancestry. We quantified genetic differentiation between the Saami population and the HGDP-CEPH populations by calculating pair-wise FST statistics and by characterizing identity-by-state sharing for pair-wise population comparisons. This study affirms an east Asian contribution to the predominantly European-derived Saami gene pool. Using model-based individual ancestry analysis, the median estimated percentage of the genome with east Asian ancestry was 6% (first and third quartiles: 5 and 8%, respectively). We found that genetic similarity between population pairs roughly correlated with geographic distance. Among the European HGDP-CEPH populations, FST was smallest for the comparison with the Russians (FST=0.0098), and estimates for the other population comparisons ranged from 0.0129 to 0.0263. Our analysis also revealed fine-scale substructure within the Finnish Saami and warns against the confounding effects of both hidden population structure and undocumented relatedness in genetic association studies of isolated populations.
http://www.nature.com/ejhg/journal/vaop/ncurrent/full/ejhg2010179a.html
http://img690.imageshack.us/img690/9759/admixture.jpg
http://img98.imageshack.us/img98/526/ibsq.jpg
http://img193.imageshack.us/img193/5016/joiningtree.jpg
The understanding of patterns of genetic variation within and among human populations is a prerequisite for successful genetic association mapping studies of complex diseases and traits. Some populations are more favorable for association mapping studies than others. The Saami from northern Scandinavia and the Kola Peninsula represent a population isolate that, among European populations, has been less extensively sampled, despite some early interest for association mapping studies. In this paper, we report the results of a first genome-wide SNP-based study of genetic population structure in the Finnish Saami. Using data from the HapMap and the human genome diversity project (HGDP-CEPH) and recently developed statistical methods, we studied individual genetic ancestry. We quantified genetic differentiation between the Saami population and the HGDP-CEPH populations by calculating pair-wise FST statistics and by characterizing identity-by-state sharing for pair-wise population comparisons. This study affirms an east Asian contribution to the predominantly European-derived Saami gene pool. Using model-based individual ancestry analysis, the median estimated percentage of the genome with east Asian ancestry was 6% (first and third quartiles: 5 and 8%, respectively). We found that genetic similarity between population pairs roughly correlated with geographic distance. Among the European HGDP-CEPH populations, FST was smallest for the comparison with the Russians (FST=0.0098), and estimates for the other population comparisons ranged from 0.0129 to 0.0263. Our analysis also revealed fine-scale substructure within the Finnish Saami and warns against the confounding effects of both hidden population structure and undocumented relatedness in genetic association studies of isolated populations.