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FANTASIA leverages language models to decode the functional dark proteome across the animal tree of life

Gemma I. Martínez‐Redondo, Francisco M Pérez-Canales, Belén Carbonetto, José M. Fernández, Israel Barrios-Núñez, Marçal Vázquez-Valls, Ildefonso Cases, Ana M. Rojas, Rosa Fernández

2025Communications Biology13 citationsDOIOpen Access PDF

Abstract

Protein functional annotation is crucial in biology, but many protein-coding genes remain uncharacterized, especially in non-model organisms. FANTASIA (Functional ANnoTAtion based on embedding space SImilArity) integrates protein language models for large-scale functional annotation. Applied to ~1000 animal proteomes, FANTASIA predicts functions to virtually all proteins, including up to 50% that remained unannotated by traditional homology-based methods. This enables the discovery of novel gene functions, enhancing our understanding of molecular evolution and organismal biology. FANTASIA holds particular promise for functional discovery in non-model taxa, offering advantages over homology-based tools in sensitivity and generalizability. FANTASIA is available on GitHub at https://github.com/CBBIO/FANTASIA . FANTASIA, a protein language model-based tool, enables large-scale functional annotation across ~1000 animal proteomes, revealing novel gene functions in both model and non-model organisms beyond homology-based methods.

Topics & Concepts

Tree (set theory)ProteomeTree of life (biology)Computer scienceComputational biologyCommunicationBiologyPsychologyBioinformaticsMathematicsGenePhylogenetic treeCombinatoricsGeneticsMachine Learning in BioinformaticsRNA and protein synthesis mechanismsGenomics and Phylogenetic Studies
FANTASIA leverages language models to decode the functional dark proteome across the animal tree of life | Litcius