Chandrasekaran, S. N.; Alix, E.; Arevalo, J.; Borowa, A.; Byrne, P. J.; Charles, W. G.; Chen, Z. S.; Cimini, B. A.; Deng, B.; Doench, J. G.; Ewald, J. D.; Fritchman, B.; Fuller, C. J.; Gaetz, J.; Goodale, A.; Haghighi, M.; Han, Y.; Hanifehlou, Z.; Hennig, H.; Hernandez, D.; Jacob, C. B.; James, T.; Jetka, T.; Kalinin, A. A.; Komalo, B.; Kost-Alimova, M.; Krawiec, T.; Marion, B. A.; Martin, G.; McCarthy, N. J.; Miller, L.; Monsees, A.; Moshkov, N.; Munoz, A. F.; Ogier, A.; Otrocka, M.; Rataj, K.; Root, D. E.; Rubbo, F.; Scrace, S. F.; Selinger, D. W.; Senft, R. A.; Sommer, P.; Thibaudeau, A.; T

Cell Painting images offer valuable insights into the state of a cell and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP (Joint Undertaking in Morphological Profiling) Cell Painting Consortium perturbed roughly 75% of the protein-coding genome in human U-2 OS cells, generating a rich resource of single-cell images and extracted features. These profiles capture the phenotypic impacts of perturbing 15,243 human genes, including overexpressing 12,609 genes (using open reading frames, ORFs) and knocking out 7,975 genes (using CRISPR-Cas9). We mitigated technical artifacts by rigorously evaluating data processing options and validated the robustness and biological relevance of the dataset. Analysis of phenotypic profiles revealed novel gene clusters and functional relationships, including those associated with mitochondrial function, cancer, and neural processes. The JUMP Cell Painting genetic dataset is a valuable resource for exploring gene relationships and uncovering novel functions.