The E3-ome gene-centric compendium reveals the human E3 ligase landscape
Ngee Kiat Chua, Tania J. González-Robles, Cameron J. Reddington, Jane Dudley-Fraser, Richard W. Birkinshaw, Jiru Han, Ashleigh Solano, Soon Wei Wong, Tomasz Kochańczyk, Joshua Peter, Mark A. Nakasone, Florian Aust, Jacob E. Munro, Yeh Huei Tong, Julie Iskander, Waruni Abeysekera, Alex Garnham, Hannah Huckstep, Matthew E. Ritchie, Ingrid E. Wertz, Sarah Hymowitz, Sharad Kumar, R CONAWAY, Gilbert G. Privé, Alex N. Bullock, Jeffrey J. Babon, Rachel E. Klevit, Sonja Lorenz, Alessio Ciulli, Eric S. Fischer, Nicolas H. Thomä, Radosław P. Nowak, Brenda A. Schulman, Michael Rapé, Katrin Rittinger, Julia K. Pagan, Melanie Bahlo, Joel P. Mackay, Peter D. Mace, Christopher D. Lima, Ronald T. Hay, David Komander, Bernhard C. Lechtenberg, Claudio A.P. Joazeiro, Michele Pagano, Kay Hofmann, Rebecca Feltham
Abstract
To define and systematically characterize the human E3 ubiquitin ligase (E3) landscape, we generated the E3-ome, a compendium of E3s encoded by the human genome. The E3-ome integrates experimental data, bioinformatics, and published research, revealing 672 high-confidence E3s. We standardized E3 classifications to create a unified framework for annotation and comparative analysis. The E3-ome identified several previously unrecognized domains, motifs, E3 candidates, and relationships, expanding the diversity of E3s. Furthermore, the E3-ome mapped the spatial and physiological organization of E3s across human tissues and cell types, revealing context-dependent E3s. Genetic analyses identified disease-associated variants across the E3-ome, linking E3s to diverse human pathologies. Together, these analyses define the human E3 landscape at high resolution and deliver a foundational resource to drive mechanistic and therapeutic discovery.