1. Population Structure Analyses Provide Insight into the Source Populations Underlying Rural Isolated Communities in Illinois.
- Author
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Owings AC, Fernandes SB, Olatoye MO, Fogleman AJ, Zahnd WE, Jenkins WD, Malhi RS, and Lipka AE
- Subjects
- Founder Effect, Genome-Wide Association Study, Humans, Illinois epidemiology, Principal Component Analysis, Rural Population, Genetic Variation genetics, Genetics, Population statistics & numerical data, White People genetics
- Abstract
We have previously hypothesized that relatively small and isolated rural communities may experience founder effects, defined as the genetic ramifications of small population sizes at the time of a community's establishment. To explore this, we used an Illumina Infinium Omni2.5Exome-8 chip to collect data from 157 individuals from four Illinois communities, three rural and one urban. Genetic diversity estimates of 999,259 autosomal markers suggested that the reduction in heterozygosity due to shared ancestry was approximately 0, indicating a randomly mating population. An eigenanalysis, which is similar to a principal component analysis but run on a genetic coancestry matrix, conducted in the SNPRelate R package revealed that most of these individuals formed one cluster, with a few putative outliers obscuring population variation. An additional eigenanalysis on the same markers in a combined data set including the 2,504 individuals in the 1000 Genomes database found that most of the 157 Illinois individuals clustered into one group in close proximity to individuals of European descent. A final eigenanalysis of the Illinois individuals with the 503 individuals of European descent (within the 1000 Genomes Project) revealed two clusters of individuals and likely two source populations; one British and one consisting of multiple European subpopulations. We therefore demonstrate the feasibility of examining genetic relatedness across Illinois populations and assessing the number of source populations using publicly available databases. When assessed, population structure information can contribute to the understanding of genetic history in rural populations.
- Published
- 2019
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