CodonShuffle: a tool for generating and analyzing synonymously mutated sequences.

Area of Science:

• Virology
• Molecular Biology
• Bioinformatics

Background:

• Synonymous mutations typically do not alter protein sequences and are considered neutral.
• However, empirical evidence indicates synonymous mutations can significantly affect viral fitness.
• Factors influencing synonymous codon usage include translational efficiency, mutational bias, RNA structure, and immune selection against specific dinucleotides.

Purpose of the Study:

• To develop a bioinformatics tool for generating and analyzing viral sequences with large-scale synonymous mutations.
• To address the challenge of defining the mechanistic basis for fitness impacts of synonymous mutations.
• To facilitate experimental studies on the fitness effects of synonymous mutations.

Main Methods:

• Developed a bioinformatics tool to generate synonymously mutated viral sequences using various permutation strategies.
• Analyzed dinucleotide frequency, codon usage, codon pair bias, and RNA folding free energy for permuted genomes.
• Employed z-score normalization and least squares regression to quantify sequence divergence from the wild-type.

Main Results:

• The tool enables the identification of numerous synonymously mutated sequences with controlled similarity to the wild-type genome.
• Quantified sequence divergence across multiple nucleic-acid-based determinants of viral fitness.
• Provided a method to systematically explore the fitness landscape shaped by synonymous mutations.

Conclusions:

• The developed bioinformatics tool aids in designing viral genomes for experimental investigation of synonymous mutation effects.
• Facilitates a deeper understanding of the role of synonymous mutations in viral evolution and fitness.
• Supports the study of pleiotropic effects of synonymous mutations on viral genomes.