FishCodonKit: A Python-based toolkit for automated codon usage bias analysis and visualization of aquatic organism CDS sequences

Codon usage bias (CUB) arises from mutational pressure and natural selection, and it is associated with gene expression regulation and molecular evolution. Existing tools such as CodonW, BCAWT, and CodonU either lack integrated visualization or require programming expertise, which limits their use by aquaculture researchers. FishCodonKit (version 1.0) is a Python toolkit for CUB analysis of coding sequences (CDS) from aquatic organisms. It integrates nucleotide composition statistics with calculations of relative synonymous codon usage (RSCU), effective number of codons (ENC), codon adaptation index (CAI), and codon bias index (CBI). All analyses are performed with a single command. No programming knowledge is required, and figures and data files are generated automatically. Validation using 39 mitochondrial CDS sequences from three teleost species ( Danio rerio , Oreochromis niloticus , and Takifugu rubripes ) showed an AT-enriched composition (mean GC content of 43.94% ± 3.85%) and moderate codon bias (mean ENC of 44.73 ± 5.22), indicating that both mutational pressure and natural selection contribute to codon usage patterns. The source code of FishCodonKit is publicly available on Zenodo ( https://doi.org/10.5281/zenodo.22008053) .