CUBAP

CUBAP analyzes codon usage biases across human populations to quantify population-specific differences in codon-related metrics and relate them to potential functional and disease-associated effects.

Key Features:

• 1000 Genomes Project data: Uses variant and sequence data from the 1000 Genomes Project to assess population variation.
• Gene coverage: Evaluates codon-related metrics across 17,634 genes.
• Codon frequencies: Computes codon usage frequencies per gene and population.
• Codon aversion: Quantifies absence or underrepresentation of specific codons across populations.
• Identical codon pairing: Detects and compares occurrences of adjacent identical codons between populations.
• Co-tRNA codon pairing: Assesses pairing of codons decoded by the same tRNA (co-tRNA) across genes and populations.
• Ramp sequences: Analyzes ramp sequence patterns per gene and population.
• Nucleotide composition: Measures nucleotide composition across genes and populations.
• Population variation in codon pairing: Identifies significant codon-pairing variation between populations for 35.8% of genes.
• Ancestry prediction: Predicts individual place of origin with reported accuracies of 98.8% for African individuals and 100% for East Asian individuals.
• IRGM CTG pairing bias: Detects decreased CTG pairing in the IRGM gene in East Asian and African populations and notes correlation with a reduced association of rs10065172 with Crohn's disease.

Scientific Applications:

• Genome-wide association studies: Supports interpretation of synonymous variants and codon-level biases in GWAS contexts.
• Candidate-gene analysis: Enables gene-specific and codon-specific analyses to evaluate candidate genes.
• Functional interpretation of synonymous variants: Aids prediction of population-specific impacts of synonymous variants.
• Population genetics and ancestry inference: Uses codon usage patterns to categorize genetic biases unique to populations and infer place of origin.
• Disease-association analysis: Facilitates investigation of codon usage changes in disease contexts, exemplified by IRGM CTG pairing and rs10065172 in Crohn's disease.

Methodology:

Uses 1000 Genomes Project data to calculate codon frequencies, codon aversion, identical codon pairing, co-tRNA codon pairing, ramp sequences, and nucleotide composition across 17,634 genes and assesses population-specific differences and predictive assignments.