A method for detecting recent selection in the human genome from allele age estimates

Area of Science:

• Population Genetics
• Human Evolutionary Genetics
• Genomic Analysis

Background:

• Naturally occurring genetic variations, particularly those influenced by positive natural selection, significantly impact organismal fitness.
• Identifying recent mutations that have rapidly increased in frequency is crucial for understanding adaptive evolution and disease.
• Existing methods may not fully capture the dynamics of recent selection events.

Purpose of the Study:

• To develop and validate a novel computational method for detecting recent positive selection acting on genetic variants.
• To estimate the age of an allele based on the degree of haplotype sharing at linked genomic sites.
• To apply this method to identify human disease alleles that have undergone recent positive selection.

Main Methods:

• Developed a method to estimate allele age by analyzing haplotype sharing patterns at sites linked to the allele.
• Utilized neutral coalescent simulations to assess the statistical likelihood of the estimated allele age given its observed frequency.
• Applied the method to the hemochromatosis-associated HFE C282Y mutation and another young, common allele.

Main Results:

• The developed method successfully rejected neutral evolutionary models for the HFE C282Y mutation, even when considering complex human demographic histories.
• Evidence suggests that the HFE C282Y allele, and at least one other young, common allele, are under positive selection.
• The findings indicate selection acting directly at the HFE locus or a closely linked genomic region.

Conclusions:

• The novel method provides a powerful tool for identifying recent positive selection in the human genome.
• The hemochromatosis HFE C282Y mutation is a strong candidate for having been driven by positive selection.
• This approach is well-suited for large-scale genomic scans, such as those utilizing the human haplotype map.