Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution
6 affiliations
- 1Tahoe Therapeutics, South San Francisco, CA, USA
- 2Arc Institute, Palo Alto, CA, USA
- 3Tahoe Therapeutics, South San Francisco, CA, USA; Arc Institute, Palo Alto, CA, USA
- 4Parse Biosciences, Seattle, WA, USA
- 5Tahoe Therapeutics, South San Francisco, CA, USA; Arc Institute, Palo Alto, CA, USA; Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA. Electronic address: [email protected]
- 6Tahoe Therapeutics, South San Francisco, CA, USA. Electronic address: [email protected]
Abstract
We present Tahoe-100M, a giga-scale single-cell perturbation atlas comprising 100 million transcriptomes from 50 diverse cancer cell lines treated with 1,100 drug-dose conditions. This parallel profiling of thousands of perturbations at single-cell resolution with minimal batch effects is enabled by the Mosaic platform, which multiplexes genetically distinct cell models into balanced "cell villages." Beyond cataloging transcriptomic shifts, Tahoe-100M systematically quantifies cellular phenotypes, including proliferation, cytotoxicity, lineage-specific vulnerabilities, and cell-cycle changes. It captures population-level transcriptomic heterogeneity, characterizing whether drug responses drive cells toward divergent fates or convergent states. Pathway-based signatures define drug-induced expression programs, classify mechanisms of action, reveal off-target activities, and expose adaptive stress responses associated with resistance. By unifying cellular and molecular readouts, this broadly applicable perturbation atlas advances our ability to model gene regulation, drug response, and network dynamics. Its public release enables the training of AI frameworks to advance predictive models of cell behavior.
Related
- Super-resolution mapping of nuclear stress signaling by probiotic-derived extracellular vesicles in UV-induced skin photodamage
- Mapping fibroblast plasticity across non-cancer lung diseases at single-cell resolution.
- High-resolution mapping of RNA structural maturation during Cas9 assembly with ABEL-FRET
- Alzheimer’s disease research must connect vascular molecular phenotypes with physiology
- Molecular phenotypes and spatial archetypes: A new framework for cancer-associated fibroblasts
BibTeX
@article{zhang2026tahoe100m,
title = {{Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution}},
author = {Jesse M. Zhang and Airol A. Ubas and Valentine Svensson and Nicole Thomas and Vishvak Subramanyam and Christopher Carpenter and Aidan F. Winters and Richard de Borja and Noam Teyssier and Neha Thakar and Umair Khan and Pooja V. Akella and Harper J. Green and John Thompson and Vuong Tran and Joseph Pangallo and Efthymia Papalexi and Ajay A. Sapre and Hoai Nguyen and Oliver Sanderson and Maria Nigos and Olivia Kaplan and Sarah Schroeder and Bryan Hariadi and Simone R Marrujo and Crina Curca and Alec Salvino and Guillermo Gallareta-Olivares and Ryan T. Koehler and Alexander Rosenberg and Charles M. Roco and Chiara Ricci-Tam and Matthew G. Jones and Alexander Dobin and Brian S. Plosky and Danielle E. Lyons and Daniele Merico and Nima Alidoust and Hani Goodarzi and Johnny Yu},
journal = {Cell},
year = {2026},
month = sep,
doi = {10.1016/j.cell.2026.08.035},
url = {https://doi.org/10.1016/j.cell.2026.08.035},
note = {CC BY},
}
RIS
TY - JOUR
TI - Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution
AU - Jesse M. Zhang
AU - Airol A. Ubas
AU - Valentine Svensson
AU - Nicole Thomas
AU - Vishvak Subramanyam
AU - Christopher Carpenter
AU - Aidan F. Winters
AU - Richard de Borja
AU - Noam Teyssier
AU - Neha Thakar
AU - Umair Khan
AU - Pooja V. Akella
AU - Harper J. Green
AU - John Thompson
AU - Vuong Tran
AU - Joseph Pangallo
AU - Efthymia Papalexi
AU - Ajay A. Sapre
AU - Hoai Nguyen
AU - Oliver Sanderson
AU - Maria Nigos
AU - Olivia Kaplan
AU - Sarah Schroeder
AU - Bryan Hariadi
AU - Simone R Marrujo
AU - Crina Curca
AU - Alec Salvino
AU - Guillermo Gallareta-Olivares
AU - Ryan T. Koehler
AU - Alexander Rosenberg
AU - Charles M. Roco
AU - Chiara Ricci-Tam
AU - Matthew G. Jones
AU - Alexander Dobin
AU - Brian S. Plosky
AU - Danielle E. Lyons
AU - Daniele Merico
AU - Nima Alidoust
AU - Hani Goodarzi
AU - Johnny Yu
PY - 2026
DA - 2026/09/01
JO - Cell
DO - 10.1016/j.cell.2026.08.035
UR - https://doi.org/10.1016/j.cell.2026.08.035
AB - We present Tahoe-100M, a giga-scale single-cell perturbation atlas comprising 100 million transcriptomes from 50 diverse cancer cell lines treated with 1,100 drug-dose conditions. This parallel profiling of thousands of perturbations at single-cell resolution with minimal batch effects is enabled by the Mosaic platform, which multiplexes genetically distinct cell models into balanced "cell villages." Beyond cataloging transcriptomic shifts, Tahoe-100M systematically quantifies cellular phenotypes, including proliferation, cytotoxicity, lineage-specific vulnerabilities, and cell-cycle changes. It captures population-level transcriptomic heterogeneity, characterizing whether drug responses drive cells toward divergent fates or convergent states. Pathway-based signatures define drug-induced expression programs, classify mechanisms of action, reveal off-target activities, and expose adaptive stress responses associated with resistance. By unifying cellular and molecular readouts, this broadly applicable perturbation atlas advances our ability to model gene regulation, drug response, and network dynamics. Its public release enables the training of AI frameworks to advance predictive models of cell behavior.
SN - 0092-8674
SN - 1097-4172
ER -