Analysis of East Asia Genetic Substructure Using Genome-Wide SNP Arrays:
In this study, population differentiation (Fst) and Principal Components Analyses (PCA) are examined using >200 K genotypes from multiple populations of East Asian ancestry. The population groups included those from the Human Genome Diversity Panel [Cambodian, Yi, Daur, Mongolian, Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, Xibo, and Yakut], HapMap [ Han Chinese (CHB) and Japanese (JPT)], and East Asian or East Asian American subjects of Vietnamese, Korean, Filipino and Chinese ancestry. Paired Fst (Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups (CHB/Korean, 0.0019; CHB/JPT, 00651; CHB/Vietnamese, 0.0065) with larger separation with Filipino (CHB/Filipino, 0.014). Low levels of differentiation were also observed between Dai and Vietnamese (0.0045) and between Vietnamese and Cambodian (0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan (Fst's These studies have also identified a subset of East Asian substructure ancestry informative markers (EASTASAIMS) that may be useful for future complex genetic disease association studies in reducing type 1 errors and in identifying homogeneous groups that may increase the power of such studies.
No great surprises, and recapitulating what you saw with Europeans earlier. Below the fold is one of the figures reedited for clarity.
The chart illustrates the first two principal components of genetic variation. Note that in the paper they emphasize that there's information in a lot of the subsequent components which is informative for smoking out population substructure.
Related: Genetic map of Europe; genes vary as a function of distance, More genetic maps of Europe, More genetic maps of Europe, Population substructure in Japan and Finns as European outliers.
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When I first saw this, the first thing that popped in my head was "big fucking surprise."
Has someone done a PC analysis on people from all over the United States? That would probably be pretty interesting, given that it almost certainly wouldn't reflect geography as strongly. I wonder what kind of clustering you would get...