Identification of selective sweeps using a dynamically adjusted number of linked microsatellites

Area of Science:

• Population Genetics
• Evolutionary Biology
• Genomics

Background:

• Differentiating genetic variation due to demographic events versus natural selection is crucial.
• Selective sweeps leave distinct genetic signatures that are challenging to identify accurately.

Purpose of the Study:

• To develop and evaluate a powerful multilocus statistical test for identifying candidate sites of selective sweeps.
• To assess the impact of population bottlenecks on the accuracy of detecting selective sweeps.

Main Methods:

• A novel multilocus statistical test utilizing the variability profile of linked microsatellites.
• Analysis of flanking markers to reduce false positives in genome-wide scans.
• Simulation studies exploring various population bottleneck scenarios.

Main Results:

• The proposed test demonstrates high power in detecting selective sweeps.
• Flanking marker analysis significantly reduces false positives, even under many bottleneck conditions.
• Intermediately severe population bottlenecks can mimic selective sweep signatures, increasing false positives up to 50% in worst-case scenarios.

Conclusions:

• The multilocus statistical test is a powerful tool for identifying selective sweeps.
• While population bottlenecks can complicate detection, integrating linked loci information consistently reduces false positives.
• The test shows promise for application in experimental data, such as in Drosophila melanogaster.