An algorithm for detecting directional and non-directional positive selection, neutrality and negative selection in...

Area of Science:

• Evolutionary biology
• Molecular evolution
• Genomics

Background:

• Adaptive evolution drives advantageous genetic changes in protein-coding genes.
• Examples include new enzyme functions, reproductive isolation, and pathogen evasion.
• Detecting positive selection is difficult due to sequence saturation, codon bias, and varied selective pressures.

Purpose of the Study:

• To develop an accurate and computationally efficient method for detecting positive selection in protein-coding genes.
• To identify specific lineages undergoing adaptive evolution using a novel character-based approach.

Main Methods:

• A character-based method was developed to analyze internal branches of phylogenetic trees.
• The method assesses the number of replacement substitutions exceeding expectations.
• Substitutions are classified based on whether they became invariable (directional selection) or changed again (non-directional selection).

Main Results:

• The new method accurately identifies lineages experiencing positive selection.
• It is sensitive to short-lived selection events.
• The approach is robust to sampling density and the proportion of sites under selection.

Conclusions:

• The developed method offers a fast, accurate, and implementable solution for detecting positive selection.
• It effectively distinguishes between directional and non-directional selection pressures.
• This advancement aids in understanding the mechanisms of adaptive evolution in protein-coding genes.