The CAI Analyser Package: inferring gene expressivity from raw genomic data

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• The Codon Adaptation Index (CAI) quantifies codon usage bias.
• Gene expression levels are influenced by codon bias, tRNA abundance, and thermodynamics.
• Previous computational methods exist for deriving gene expressivity measures from genomes.

Purpose of the Study:

• To present the CAI Analyser Package (CAIAP), a platform-independent software package.
• To enable easy-to-use, automatic analysis of gene expressivity and inter-species genome comparisons.
• To provide tools for deep study of gene expressivity from raw gene sequences.

Main Methods:

• Implementation and optimization of a procedure to derive reference sequences from whole genomes.
• Calculation of CAI using codon usage from derived reference sequences.
• Integration of functional gene annotations into the analysis output.
• Development of statistical analysis tools for result robustness.

Main Results:

• CAIAP allows for the calculation of CAI and in-depth gene expressivity studies.
• The package optimizes reference sequence derivation from whole genomes.
• Provided analysis tools enhance the statistical robustness of results.
• A web server offers analyses for hundreds of genomes with intergenomic comparison capabilities.

Conclusions:

• CAIAP offers a comprehensive solution for gene expressivity analysis and inter-species comparisons.
• The package simplifies complex bioinformatics tasks for researchers.
• CAIAP facilitates robust and statistically sound investigations into gene expression patterns across diverse genomes.