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<p>Cell Painting images offer valuable insights into a cell’s state and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP 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) and knocking out 7,975 genes (using CRISPR–Cas9). Here we mitigated technical artifacts by rigorously evaluating data processing options and validated the dataset’s robustness and biological relevance. Analysis of phenotypic profiles revealed previously undiscovered 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 previously unknown functions.</p>

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Morphological map of under- and overexpression of genes in human cells

  • 期刊论文

  • 发表日期：

    2025年8月7日

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  • Srinivas Niranj Chandrasekaran,
  • Eric Alix,
  • John Arevalo,
  • Adriana Borowa,
  • Patrick J. Byrne,
  • William G. Charles,
  • Zitong S. Chen,
  • Beth A. Cimini,
  • Boxiong Deng,
  • John G. Doench,
  • Jessica D. Ewald,
  • Briana Fritchman,
  • Colin J. Fuller,
  • Jedidiah Gaetz,
  • Amy Goodale,
  • Marzieh Haghighi,
  • Yu Han,
  • Zahra Hanifehlou,
  • Holger Hennig,
  • Desiree Hernandez,
  • Christina B. Jacob,
  • Tim James,
  • Tomasz Jetka,
  • Alexandr A. Kalinin,
  • Ben Komalo,
  • Maria Kost-Alimova,
  • Tomasz Krawiec,
  • Brittany A. Marion,
  • Glynn Martin,
  • Nicola Jane McCarthy,
  • Lisa Miller,
  • Arne Monsees,
  • Nikita Moshkov,
  • Alán F. Muñoz,
  • Arnaud Ogier,
  • Magdalena Otrocka,
  • Krzysztof Rataj,
  • David E. Root,
  • Francesco Rubbo,
  • Simon Scrace,
  • Douglas W. Selinger,
  • Rebecca A. Senft,
  • Peter Sommer,
  • Amandine Thibaudeau,
  • Sarah Trisorus,
  • Rahul Valiya Veettil,
  • William J. Van Trump,
  • Sui Wang,
  • Michał Warchoł,
  • Erin Weisbart,
  • Amélie Weiss,
  • Michael Wiest,
  • Agata Zaremba,
  • Andrei Zinovyev,
  • Shantanu Singh,
  • Anne E. Carpenter

摘要

Cell Painting images offer valuable insights into a cell’s state and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP 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) and knocking out 7,975 genes (using CRISPR–Cas9). Here we mitigated technical artifacts by rigorously evaluating data processing options and validated the dataset’s robustness and biological relevance. Analysis of phenotypic profiles revealed previously undiscovered 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 previously unknown functions.