bioRxivSystems BiologyPreprint
A Chemical-Genetic Interaction Matrix Reveals Drug Mechanism and Genetic Architecture
Jasmin Coulombe‐HuntingtoniD, Thierry BertomeuiD, Caroline HuardiD, Andrew Chatr‐aryamontriiD, Daniel J. St‐CyriD, María Sánchez‐OsunaiD, David J. PapadopoliiD, Karine Normandin, Mohammadjavad PaydariD, Shannon McLaughlaniD, Corinne St‐DenisiD, Li ZhangiD, Henry SayiD, Roger PalouiD, Chris StarkiD, Bobby‐Joe BreitkreutziD, Almer M. van der SlootiD, Sandhya ManohariD, Hugo LavoieiD, Katherine L. B. BordeniD, Brian RaughtiD, Damien D’AmoursiD, Frank SicheriiD, Alain VerreaultiD, Sylvie MaderiD, , Mike TyersiD
Abstract
To probe drug mechanism of action (MOA) and interrogate the genetic architecture of human cells, we carried out isogenic genome-wide CRISPR/Cas9 knockout screens against 310 diverse drugs, bioactive compounds, and stress conditions. Stringent statistical correction for gene knockout fitness defects yielded a large-scale matrix of >12,000 high confidence chemical-genetic interactions (CGIs). This dataset revealed many previously unappreciated off-target effects for well-characterized compounds and novel MOAs for uncharacterized compounds. The CGI matrix uncovered dense genetic modules that yielded new biological insights into phospholipidosis, mitotic regulation, metabolism, the DNA damage response, and mTOR signaling. The dataset allowed identification of multi-drug sensitization and resistance mechanisms, inference of gene function, elaboration of cross-process connectivity, evaluation of the cell type specificity of CGIs, prediction of chemical synergism, and extensive annotation of understudied genes. This resource provides a map of the genetic landscape in human cells and a framework to help guide drug discovery.
- organism: human
- assay: CRISPR screen
- research focus: drug response / drug discovery
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds
Kevin C. Lin, Ya‐Chu Chang, … Chad L. Myers·Scientific ReportsPeer-reviewed·Jan 30, 2024
- MOSAIC: a chemical-genetic interaction data repository and web resource for exploring chemical modes of action
Justin Nelson, Scott W. Simpkins, … Chad L. Myers·BioinformaticsPeer-reviewed·Nov 29, 2017
- Identifying chemogenetic interactions from CRISPR knockout screens with drugZ
Medina Colic, Gang Wang, … Traver Hart·bioRxiv·Mar 11, 2019
- Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens
Emanuel Gonçalves, Aldo Segura‐Cabrera, … Mathew J. Garnett·Molecular Systems BiologyPeer-reviewed·Jul 1, 2020
- A platform for the systematic interrogation of genetic interactions in human cells: 26 gene by genome-wide double knockout screens as a proof of concept
Andrew Chatr‐aryamontri, Li Zhang, … Thierry Bertomeu·bioRxiv·Aug 4, 2025
- Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interaction networks
Scott W. Simpkins, Justin Nelson, … Chad L. Myers·PLoS Computational BiologyPeer-reviewed·Oct 30, 2018