Through sophisticated statistical analyses and advanced computer simulations, researchers are learning more about the genomic patterns of human population structure around the world.
Revealing such patterns provides insights into the history of human evolution, the predominant evolutionary forces that shaped local populations, and the relationships among populations.
"Studying genomic patterns of human population structure also has practical applications in disease-gene mapping," noted Dr. Joshua M. Akey, University of Washington (UW) assistant professor of genome sciences. Akey is senior author of new genomic research findings about the fine-scale structure of diverse human populations. The results will be published May 15 in the American Journal of Human Genetics. The lead authors were Shameek Biswas and Dr. Laura B. Scheinfeldt, both of the UW Department of Genome Sciences.
A statistical method called principle component analysis allows researchers to look through a thick, voluminous fog of genetic data and see significant variations. The UW researchers applied this method to a data set of almost 650,000 SNPs (pronounced "snips").
A single nucleotide polymorphism is a genetic variation in which the DNA code differs by only one "letter" in the same DNA sequence from two individuals of the same species. The data set of 650,000 SNPs came from 944 unrelated persons representing 52 broadly classified populations living in several regions on seven continental groups: Africa, America, Central and South East Asia, East Asia, Europe, Middle East, and Oceania. This global sampling came from The Human Genome Diversity Project - Center for the Study of Human Polymorphisms
Most previous genomic studies of this nature have focused on broad-scale patterns of structure among geographically diverse populations, the UW researchers noted. These studies concluded that 85 to 95 percent of human genetic variation can be attri
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University of Washington