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|Title:||Genetic Structure of the Han Chinese Population Revealed by Genome-wide SNP Variation|
|Source:||Chen, J., Seielstad, M., Liu, J., Zheng, H., Sun, L., Zhang, X., Bei, J.-X., Jia, W.-h., Zeng, Y.-X., Li, T., Zhang, F. (2009). Genetic Structure of the Han Chinese Population Revealed by Genome-wide SNP Variation. American Journal of Human Genetics 85 (6) : 775-785. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ajhg.2009.10.016|
|Abstract:||Population stratification is a potential problem for genome-wide association studies (GWAS), confounding results and causing spurious associations. Hence, understanding how allele frequencies vary across geographic regions or among subpopulations is an important prelude to analyzing GWAS data. Using over 350,000 genome-wide autosomal SNPs in over 6000 Han Chinese samples from ten provinces of China, our study revealed a one-dimensional "north-south" population structure and a close correlation between geography and the genetic structure of the Han Chinese. The north-south population structure is consistent with the historical migration pattern of the Han Chinese population. Metropolitan cities in China were, however, more diffused "outliers," probably because of the impact of modern migration of peoples. At a very local scale within the Guangdong province, we observed evidence of population structure among dialect groups, probably on account of endogamy within these dialects. Via simulation, we show that empirical levels of population structure observed across modern China can cause spurious associations in GWAS if not properly handled. In the Han Chinese, geographic matching is a good proxy for genetic matching, particularly in validation and candidate-gene studies in which population stratification cannot be directly accessed and accounted for because of the lack of genome-wide data, with the exception of the metropolitan cities, where geographical location is no longer a good indicator of ancestral origin. Our findings are important for designing GWAS in the Chinese population, an activity that is expected to intensify greatly in the near future. © 2009 The American Society of Human Genetics.|
|Source Title:||American Journal of Human Genetics|
|Appears in Collections:||Staff Publications|
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