Expression Atlas in 2026: enabling FAIR and open expression data through community collaboration and integration
Pedro Madrigal, Anil S. Thanki, Silvie Fexová, Iris Diana Uy, Arsenios Chatzigeorgiou, Ida Zucchi, José Carlos Marugán, Liora Haim-Vilmovsky, Amnon Khen, Lingyun Zhao, Karoly Erdos, Sandeep R Kurri, Sandeep Selvakumar, Upendra Kumbham, Ananth Prakash, Shengbo Wang, Andrew Green, Carlos Eduardo Ribas, Blake Sweeney, Tobi Alegbe, Dániel Süveges, Anmol Jaywant Hemrom, David E Gomez Gutierrez, Santiago Insua, Matt Jeffryes, M. B. Y. D. J. Pearce, Prasad Basutkar, Myrsini Kaforou, Aubrey J. Cunnington, Michael Levin, Sunita Kumari, Doreen Ware, Damien Goutte-Gattat, Katja Röper, Nicholas H. Brown, Yanhui Hu, Norbert Perrimon, Irene Papatheodorou, Alvis Brāzma, Henning Hermjakob, Melissa Harrison, David Ocaña, David Ochoa, Ellen M. McDonagh, Alex Bateman, Thomas Keane, Juan Antonio Vizcaíno, Christina Ernst
Abstract
Expression Atlas (https://www.ebi.ac.uk/gxa/home) is EMBL-EBI's comprehensive knowledgebase for gene and protein expression across tissues, cell types, conditions, and multiple species. Since our last update, Expression Atlas has expanded substantially in both content and functionality, now comprising >4500 studies from 67 species, with increased proteomics coverage and updated Genotype-Tissue Expression (GTEx) tissue profiles. The resource also includes hundreds of single-cell RNA-seq experiments spanning 21 species, among them externally analysed community datasets such as Tabula Sapiens and GTEx single-nucleus profiles, allowing exploration of curated atlases while maintaining their original analytical framework. Key methodological advances include a new marker gene analysis module for bulk baseline experiments, alongside workflow updates that improve reproducibility. Expression Atlas data are integrated into EMBL-EBI resources such as Ensembl, UniProt, and Europe PMC and disseminated through collaboration with model organism communities such as FlyBase and Gramene. The resource also supports translational research through the European Diagnostic Transcriptomic Library and integration with the Open Targets platform. Future directions include modernizing analysis pipelines, enhancing programmatic access, and delivering AI-ready data formats, strengthening Expression Atlas as a findable, accessible, interoperable, and reusable (FAIR) community-driven resource for both fundamental and translational discovery.