Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation

Gene Ontology (GO) enrichment analysis has been widely adopted for interpretating omics data, including in ecological research. Although valuable for summarizing large gene lists into functional categories, it is often treated as the final interpretive step. In ecological omics, where functional annotations are frequently incomplete and experimental validation is often difficult, this reliance can lead to repetitive, generic conclusions that lack environmental and mechanistic specificity. Although previous literature has addressed the statistical and annotation-related limitations of GO enrichment, its role in shaping the broader interpretive process has received less critical attention. Here, we highlight a conceptual weakness: the treatment of enriched GO terms as definitive biological insight. We focus particularly on ecological studies of non-model organisms in complex, and heterogeneous environments. We discuss complementary strategies, including co-expression network analysis, integration with environmental metadata, phylogenetically informed annotation, and AI-assisted functional inference. To promote more context-sensitive interpretation, we introduce the concept of GO-Deep, which frames GO enrichment as a starting point for integrative, multilayered functional insight. By reframing GO enrichment as an entry point rather than a conclusion, ecological omics can move toward more mechanistically informative and environmentally grounded interpretations of high-throughput data.