2008 November 6; 456(7218): 98–101. | John Novembre1,2, Toby Johnson4,5,6, Katarzyna Bryc7, Zoltán Kutalik4,6, Adam R. Boyko7, Adam Auton7, Amit Indap7, Karen S. King8, Sven Bergmann4,6, Matthew R. Nelson8, Matthew Stephens2,3, and Carlos D. Bustamante7
The study investigates the genetic structure of European populations using a sample of 3,000 individuals genotyped at over half a million DNA sites. Despite low average genetic differentiation among Europeans, the genetic variation closely mirrors geographic distances, forming a natural two-dimensional map of Europe. This genetic correlation is more pronounced than expected for discrete populations and aligns with theoretical models of genetic similarity decaying with distance in a two-dimensional habitat. The results highlight the importance of accounting for genetic structure when mapping disease phenotypes and suggest that genetic ancestry testing can accurately infer geographic origins, often within a few hundred kilometers. The study also demonstrates that population structure can lead to spurious associations in genome-wide association studies, emphasizing the need for correction methods like principal component analysis (PCA). The findings underscore the potential for subtle population structure detection and the promise of advanced genetic ancestry tests.The study investigates the genetic structure of European populations using a sample of 3,000 individuals genotyped at over half a million DNA sites. Despite low average genetic differentiation among Europeans, the genetic variation closely mirrors geographic distances, forming a natural two-dimensional map of Europe. This genetic correlation is more pronounced than expected for discrete populations and aligns with theoretical models of genetic similarity decaying with distance in a two-dimensional habitat. The results highlight the importance of accounting for genetic structure when mapping disease phenotypes and suggest that genetic ancestry testing can accurately infer geographic origins, often within a few hundred kilometers. The study also demonstrates that population structure can lead to spurious associations in genome-wide association studies, emphasizing the need for correction methods like principal component analysis (PCA). The findings underscore the potential for subtle population structure detection and the promise of advanced genetic ancestry tests.