Large-Scale Comparative Analysis of Codon Models Accounting for Protein and Nucleotide Selection

Area of Science:

• Evolutionary biology
• Molecular evolution
• Genomics

Background:

• Positive selection scans typically assume constant synonymous substitution rates within genes.
• This assumption can lead to inaccurate inferences of selection.
• Sources of variation include direct selection and mutation rate heterogeneity.

Purpose of the Study:

• To compare methods incorporating codon substitution rate variation.
• To develop a novel, computationally tractable model for positive selection inference.
• To investigate the impact of rate variation on detecting selection in Drosophila.

Main Methods:

• Large-scale comparison of existing codon models.
• Development and implementation of a modified codon model.
• Analysis of positive selection in Drosophila melanogaster genomes.
• Investigation of factors influencing nucleotide substitution rate variation.

Main Results:

• Codon substitution rate variation significantly impacts positive selection inference.
• Over 70% of genes detected by the classical branch-site model may be false positives.
• The new model is favored by data, reduces false positives, and detects nucleotide-level selection.
• Recombination and mutation rate variation (e.g., CpG mutation rate) drive nucleotide rate variation.
• The new model identified stronger adaptation signals in Drosophila, potentially linked to dynein and Wolbachia.

Conclusions:

• Accounting for synonymous substitution rate variation is crucial for accurate positive selection detection.
• The proposed model offers improved accuracy and captures selection at regulatory sites within coding regions.
• Recombination and mutation rates are key drivers of nucleotide rate variation.
• The findings provide a more refined understanding of adaptive evolution in Drosophila.