Identifying Selected Regions from Heterozygosity and Divergence in Human Populations
Author Information
Author(s): Taras K. Oleksyk, Kai Zhao, Francisco M. De La Vega, Dennis A. Gilbert, Stephen J. O'Brien, Michael W. Smith
Primary Institution: Laboratory of Genomic Diversity, National Cancer Institute at Frederick
Hypothesis
Can we identify genomic regions under selection by analyzing heterozygosity and divergence in two human populations?
Conclusion
The study identified 180 regions of recent selection in human populations using a novel computational approach.
Supporting Evidence
- The study found strong evidence of selection in both populations.
- Regions identified were cross-validated with findings from nine other studies.
- The method does not require dense genotyping, making it applicable to smaller studies.
Takeaway
Scientists looked at DNA from two groups of people to find parts of their genes that have changed because of evolution.
Methodology
The study used a resampling-based computational approach to analyze SNP variants across the human genome.
Potential Biases
Ascertainment bias may affect the results due to the selection of SNPs for genotyping.
Limitations
The analysis was limited by the sample size and the admixed nature of the African American population.
Participant Demographics
The study included 45 European Americans and 45 African Americans.
Statistical Information
P-Value
0.004
Confidence Interval
95% C.I. = 4–831 Kb for old selection sites; 95% C.I. = 6–1,349 Kb for recent sites.
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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