Bagheera

Bagheera predicts the translation scheme of the CUG codon in Saccharomycetes and other yeast species to determine whether CUG encodes serine or leucine by analyzing gene sequences and tRNACAG presence.

Key Features:

• Reference dataset: 2,071 manually assembled and annotated sequences from cytoskeletal and motor proteins across 79 yeast species.
• Gene prediction and homology alignment: Predicts and aligns homologous genes against the reference dataset for comparative analysis.
• CUG codon position analysis: Analyzes CUG positions within predicted genes with emphasis on amino-acid similarity and conservation among related species.
• tRNACAG detection and comparison: Predicts tRNACAG genes in genomic data and compares them to known leu-tRNACAG and ser-tRNACAG sequences to refine decoding predictions.
• Sequence-type evaluation: Evaluates mRNA and protein sequence data according to species-specific CUG codon usage patterns.
• External validation: Applied to six genomes not included in the reference dataset to predict most probable CUG decoding schemes.

Scientific Applications:

• Genetic code variation analysis: Detects and characterizes nonstandard CUG decoding (serine versus leucine) in yeasts.
• CUG decoding assignment in new genomes: Assigns probable CUG translation schemes for newly sequenced Saccharomycetes genomes based on sequence and tRNA evidence.
• Evolutionary studies: Supports investigation of evolutionary loss or retention of CUG codons across yeast lineages.
• Functional genomics: Informs interpretation of cytoskeletal and motor protein sequences affected by alternative CUG decoding.

Methodology:

Uses a reference set of 2,071 annotated cytoskeletal and motor protein sequences from 79 yeast species; predicts and aligns homologous genes to this reference; analyzes CUG codon positions for amino-acid similarity and conservation; predicts tRNACAG genes in genomic data and compares them to leu-tRNACAG and ser-tRNACAG sequences to infer the CUG decoding scheme.