TY - JOUR T1 - Unifying the known and unknown microbial coding sequence space JF - bioRxiv DO - 10.1101/2020.06.30.180448 SP - 2020.06.30.180448 AU - Chiara Vanni AU - Matthew S. Schechter AU - Silvia G. Acinas AU - Albert Barberán AU - Pier Luigi Buttigieg AU - Emilio O. Casamayor AU - Tom O. Delmont AU - Carlos M. Duarte AU - A. Murat Eren AU - Robert D. Finn AU - Renzo Kottmann AU - Alex Mitchell AU - Pablo Sanchez AU - Kimmo Siren AU - Martin Steinegger AU - Frank Oliver Glöckner AU - Antonio Fernandez-Guerra Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/11/09/2020.06.30.180448.abstract N2 - Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40%-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we propose a conceptual framework and a computational workflow that bridge the known-unknown gap in genomes and metagenomes. We showcase our approach by exploring 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes. We quantify the extent of the unknown fraction, its diversity, and its relevance across multiple biomes. Furthermore, we provide a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria, being a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.Competing Interest StatementThe authors have declared no competing interest. ER -