GeneGA

GeneGA optimizes coding sequences by jointly modeling mRNA secondary structure and codon usage bias to improve protein expression.

Key Features:

• Integration with ViennaRNA Package: Uses the ViennaRNA Package to model mRNA secondary structures with dynamic programming and thermodynamic parameters to compute ground states and base pairing probabilities.
• Advanced RNA structure analysis: Leverages ViennaRNA Package 2.0 capabilities including centroid structures, maximum expected accuracy (MEA) structures derived from base pairing probabilities, RNA-RNA interaction analysis, and restricted ensemble analysis.
• Parallel computation: Employs OpenMP-supported concurrent computations within the ViennaRNA components for faster processing of large datasets.
• R-based genetic algorithm: Implements an R-based genetic algorithm to optimize coding sequences considering both structural and translational factors.
• Genomic codon usage data: Integrates codon usage information derived from highly expressed genes across nearly 200 genomes to inform optimization of codon choice.
• Output metrics and formats: Provides z-scores for locally stable secondary structures and accepts input in FASTA format.

Scientific Applications:

• Gene expression optimization: Optimization of coding sequences to enhance protein production by jointly considering mRNA structure and codon usage.
• Synthetic biology: Design and optimization of gene constructs for high expression in synthetic biology applications.
• RNA biology: Analysis of mRNA structural dynamics and their impact on translation through secondary-structure-informed sequence design.
• Evolutionary genomics: Comparative use of codon usage patterns from highly expressed genes across ~200 genomes to study translational selection.
• Molecular modeling: Use of computed secondary-structure properties and thermodynamic metrics to support molecular-level interpretations of sequence effects.

Methodology:

R-based genetic algorithm; ViennaRNA Package and ViennaRNA Package 2.0 using dynamic programming and thermodynamic parameters to compute ground states, base pairing probabilities, centroid and MEA structures, RNA-RNA interactions and restricted ensembles; OpenMP concurrency for parallel computations; calculation of z-scores for locally stable secondary structures; accepts FASTA input; integration of codon usage statistics from highly expressed genes across nearly 200 genomes.