TaxaGO: a novel, phylogenetically informed gene ontology enrichment analysis tool.

Abstract

The functional interpretation of genes and their protein products across diverse species remains a central challenge in genomics, particularly as datasets grow in scale and complexity. The Gene Ontology (GO) knowledgebase offers a detailed resource of accessing a gene's function. While GO enrichment analysis tools are widely used to uncover biological insights, they are designed for single-species analyses and are not able to integrate phylogenetic relationships into the enrichment analyses. To address this, we created TaxaGO, a high-performance, multi-taxonomic GO enrichment analysis tool that incorporates evolutionary distances with species-level enrichment results to unravel GO enrichment profiles at a taxonomic level. Implemented in Rust for speed and scalability, TaxaGO enables robust cross-species GO enrichment analyses by combining species-specific results through phylogeny-aware statistical frameworks. It supports FASTA and CSV inputs, provides curated background populations for 12 131 species across Archaea, Bacteria, and Eukaryota, and offers advanced features such as count propagation, common ancestor analysis, semantic similarity calculation, and interactive visualizations. When benchmarking against established tools, TaxaGO demonstrates a maximum of 70.33× faster performance and 3.79× reduced memory usage. With an intuitive command-line interface and a user-friendly graphical interface, TaxaGO provides a powerful and accessible platform for functional genomics, evolutionary biology, and systems-level studies across the tree of life.