Measuring and detecting molecular adaptation in codon usage against nonsense errors during protein translation

Area of Science:

• Genomics
• Molecular Biology
• Evolutionary Biology

Background:

• Codon usage bias (CUB) is a widespread phenomenon, often attributed to natural selection.
• Existing measures of CUB adaptation are largely heuristic and lack mechanistic grounding.

Purpose of the Study:

• To develop a novel, mechanistic method for defining and quantifying CUB adaptation.
• To reduce the cost of nonsense errors during protein translation as a primary driver of CUB.

Main Methods:

• Developed a protein translation model to calculate the cost of nonsense errors for alleles.
• Defined the nonsense error adaptation index (NAI) based on the cost and its variance across synonymous codons.
• Applied NAI calculations to genes in the Saccharomyces cerevisiae genome.

Main Results:

• Demonstrated clear evidence of adaptation to reduce nonsense error costs in yeast.
• Observed increasing adaptation with codon position and gene expression levels.
• Results align with simulations where nonsense errors are the main selective force driving CUB.

Conclusions:

• The NAI provides a mechanistically derived, interpretable measure of CUB adaptation.
• This approach offers a foundation for developing other adaptation measures, like those for translational accuracy.