Maximum-likelihood methods for detecting recent positive selection and localizing the selected site in the genome

Area of Science:

• Evolutionary genetics
• Population genetics
• Genomics

Background:

• Detecting positive selection is crucial for understanding adaptation.
• Previous methods often struggle with linked neutral loci and recombination.
• Identifying the precise location of selection remains challenging.

Purpose of the Study:

• To develop and validate novel maximum-likelihood methods for detecting recent positive selection.
• To accurately localize the target of selection along a recombining chromosome.
• To assess the performance of these methods using simulated and empirical data.

Main Methods:

• Utilizing the mutation frequency spectrum at multiple, partially linked neutral loci.
• Employing maximum-likelihood estimation to infer selection.
• Simulating genetic data to evaluate test power and false positive rates.
• Applying the methods to X chromosome data from Drosophila melanogaster.

Main Results:

• The proposed methods demonstrate high statistical power (80-98%) for detecting selection.
• False positive rates are low (approx. 10%) with a sufficient number of marker loci (>= 20).
• The methods provide a reasonably narrow confidence interval for the estimated position of selection.
• Evidence of selection, including a shared selective sweep, was found in both European and African Drosophila melanogaster populations.

Conclusions:

• The developed maximum-likelihood methods are effective for detecting recent positive selection and pinpointing its genomic location.
• These methods offer improved accuracy and power compared to existing approaches.
• The findings provide insights into the evolutionary history and adaptive processes in Drosophila melanogaster populations.