KozakExplorer: an interactive framework for genome-wide Kozak sequence analysis

Translation initiation signals shape gene expression across all domains of life. In eukaryotes, nu-cleotide constraints surrounding the start codon are commonly described by the Kozak Consensus Sequence (KCS), whereas in bacteria and archaea, initiation frequently involves Shine–Dalgarno ribosome-binding motifs. Although these signals have been extensively characterized in model or-ganisms, their large-scale diversity and evolutionary distribution remain incompletely explored.

We present KozakExplorer, a reproducible framework for quantitative and comparative analysis of translation initiation contexts from genome assemblies and annotations. The software per-forms strand-aware extraction of start codon environments from FASTA and GFF3 files and ap-plies information-theoretic metrics—including Kullback–Leibler (KL) divergence and information content (IC)—to measure positional nucleotide constraints relative to a background model. Derived summary statistics (Kozak Strength Index [KSI], maximum information content, peak position) con-vert motif patterns into interpretable per-genome signatures suitable for cross-species comparison. Our primary analysis covers 2,282 eukaryotic reference genomes, producing a standardized dataset of translation initiation metrics. Dimensionality reduction via t-SNE on per-position KL divergence, information content, and motif nucleotide frequencies reveals a structured eukaryotic KCS land-scape with kingdom-level clustering and continuous variation in signal strength. A dedicated case study of 216 Apicomplexa genomes shows genus-level structure consistent with host range and phylogeny. An extended analysis across 25,344 reference genomes (22,253 bacteria, 809 archaea) places eukaryotic patterns in a global comparative framework, revealing transitions between sharply localized Kozak motifs and distributed Shine–Dalgarno-type signatures.

Implemented within the open-source Sequana ecosystem, KozakExplorer is distributed as a Python module and an interactive web application that accepts local annotated assemblies, GenBank records, or NCBI RefSeq accessions, and exports all computed metrics, embeddings, and coordi-nates for downstream comparative and evolutionary genomics.

Implemented in Python within the Sequana framework. Source code available at https://github.com/sequana/sequana and https://github.com/sequana/webapp_kozak .

Contact

thomas.cokelaer@pasteur.fr