immgenT: A Comprehensive Reference of Convergent T-cell States in the Mouse

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Authors: Ian Magill, Odhran Casey, Dania Mallah, Siba Smarak Panigrahi, Leon Lee Zhou, Olga Barreiro del Río, Derek J. Bangs, Gavyn Chern Wei Bee, Samantha M. Borys, Josh Choi, Can Ergen, Enxhi Ferraj
+51 more Maurizio Fiusco, Antoine Freuchet, Giovanni Galletti, Anna-Maria Globig, Taylor Heim, Charlotte J. Imianowski, Rocky Lai, Zhitao Liang, Andrea Lebron Figueroa, Erin D. Lucas, Julia Merkenschlager, Kevin C. Osum, Shannelle Reilly, Tomoyo Shinkawa, Claire E. Thefaine, Eric S. Weiss, Liang Yang, Shanshan Zhang, Andre L. Zorzetto-Fernandes, Josh D Croteau, Maria‐Luisa Alegre, Samuel M. Behar, Remy Bosselut, Laurent Brossay, Ken Cadwell, Alexander Chervonsky, L. Gapin, Sara E. Hamilton, Jun Ryul Huh, Iliyan Iliev, Bana Jabrì, Steve Jameson, Marc K. Jenkins, Susan M. Kaech, Daniel H. Kaplan, Vijay Kuchroo, Michel Nussenzweig, Marion B. Pepper, David A. Sinclair, Stefani Spranger, Michael N. Starnbach, Matthew Stephens, Ulrich H. von Andrian, Nir Yosef, Joonsoo Kang, M. Kronenberg, Ananda W. Goldrath, Maria Brbic, Christophe Benoist, David Zemmour, the immgenT project
Cited by: 2
References: 88

Abstract

Abstract The immgenT collaborative project generated a comprehensive molecular atlas of T cells spanning virtually all mouse organs and disease states, profiling ∼800,000 cells from 750 samples with RNA, 128-plex surface protein, and αβTCR sequence. Applying a deep generative model to joint RNA and protein data defined the landscape of T-cell states organized into eight lineages and 107 robust clusters, integrating similar cells from different contexts, and resolving prior nomenclatures. Analysis of effector molecules, transcription factors and modules showed that both immunological functions and regulatory programs are shared across cell states. This framework provides a stable, reusable reference, demonstrated by computationally integrating 16 external datasets from diverse biological contexts. A set of public web tools supports browsing of these data and mapping of any dataset onto the immgenT framework. These results propose a molecular classification of T cells organized around a set of shared states reused across immunological contexts.

Fields of Study & Subjects

Single-cell and spatial transcriptomics T-cell and B-cell Immunology vaccines and immunoinformatics approaches

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
2 February 2026
Document type
Preprint