Scanning for genomic regions subject to selective sweeps using SNP-MaP strategy

Area of Science:

• Population genomics
• Molecular evolution
• Human genetics

Background:

• High-throughput genotyping enables population genomic scans for selective sweeps but is costly.
• DNA pooling offers a cost-effective alternative for large-scale genotyping in association studies.
• Evaluating pooling strategies is crucial for efficient genome-wide selection scans.

Purpose of the Study:

• To assess the efficiency of DNA pooling strategies for genome-wide selection scans using SNP-MaP analysis.
• To demonstrate the utility of average heterozygosity (HET) in detecting selective sweeps with pooling.
• To identify regions under positive selection in Eurasian populations, particularly Europeans.

Main Methods:

• SNP-MaP (single nucleotide polymorphism microarrays and pooling) analysis on Eurasian samples.
• Simulations of allelotype data to evaluate pooling error effects on heterozygosity.
• Sliding window analysis of average heterozygosity (HET) to detect large contiguous regions (LCRs).
• Validation using integrated haplotype score (iHS) and known selected genes.

Main Results:

• Average heterozygosity (HET) boxplots effectively detect strong selective sweeps even with moderate pooling error.
• Identified 63 large contiguous regions (LCRs) putatively under selective sweeps in a European population.
• Results corroborated by iHS tests and confirmation of European-specific selection signatures in genes like KEL and TRPV.

Conclusions:

• The SNP-MaP strategy is highly credible for scanning selective sweeps, offering a cost-effective approach.
• The study provides valuable insights into population differentiation and genetic selection in Eurasia.
• This method enhances the feasibility of large-scale population genomic studies.