Nature MethodsBioinformaticsPeer-reviewed journal article
Morphological map of under- and over-expression of genes in human cells
Srinivas Niranj ChandrasekaraniD, Eric Alix, John ArévaloiD, Adriana BorowaiD, Patrick J. ByrneiD, William G CharlesiD, Zitong CheniD, Beth A. CiminiiD, Boxiong Deng, John G. DoenchiD, Jessica EwaldiD, Briana Fritchman, Colin J. FulleriD, Jedidiah GaetziD, Amy B. GoodaleiD, Marzieh HaghighiiD, Yu HaniD, Zahra HanifehlouiD, Holger HennigiD, Desiree Hernandez, Christina B. JacobiD, Tim JamesiD, Tomasz JetkaiD, Alexandr A. KalininiD, Ben Komalo, , Anne Elizabeth CarpenteriD
Abstract
Cell Painting images offer valuable insights into a cells state 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 datasets robustness and biological relevance. 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.
- organism: human
- assay: imaging
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 17
- FWCI
- 6.00
- Field percentile
- top 3%
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