A method for the simultaneous estimation of selection intensities in overlapping genes

Area of Science:

• Evolutionary biology
• Molecular evolution
• Genomics

Background:

• Inferring positive selection in protein-coding genes is crucial for understanding adaptation.
• Overlapping genes, common across all life forms, have been recently suggested to exhibit high levels of positive selection.

Purpose of the Study:

• To develop a novel method for simultaneously estimating selection intensities in overlapping genes.
• To investigate the cause of the apparent positive selection in overlapping genes.

Main Methods:

• Developed an exact evolutionary model for simultaneous estimation of selection in overlapping genes.
• Avoided approximations and intensive computations.
• Tested the method using simulations of overlapping gene evolution under various scenarios.

Main Results:

• The assumption of independent selection in overlapping genes creates a false appearance of positive selection.
• This independent estimation approach can incorrectly indicate positive selection when genes are under negative selection.
• Re-analysis of two influenza A genes previously reported to show positive selection found no evidence for it.

Conclusions:

• The apparent positive selection in overlapping genes is an artifact of analytical methods that ignore co-evolutionary constraints.
• The new method provides accurate estimation of selection intensities in overlapping genes.
• This work corrects previous findings and emphasizes the importance of using appropriate evolutionary models for overlapping genes.