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.
Coulombe-Huntington et al. (Thu,) studied this question.