A global genetic interaction network by single-cell imaging and machine learning.

Autor:	Heigwer F; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany; Department of Life Sciences and Engineering, University of Applied Sciences Bingen, Bingen am Rhein, Germany., Scheeder C; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Bageritz J; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany; Center of Organismal Studies, Heidelberg University, Heidelberg, Germany., Yousefian S; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Rauscher B; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Laufer C; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Beneyto-Calabuig S; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Funk MC; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Peters V; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Boulougouri M; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Bilanovic J; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Miersch T; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Schmitt B; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Blass C; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Port F; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany., Boutros M; German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany. Electronic address: m.boutros@dkfz.de.
Jazyk:	angličtina
Zdroj:	Cell systems [Cell Syst] 2023 May 17; Vol. 14 (5), pp. 346-362.e6. Date of Electronic Publication: 2023 Apr 27.
DOI:	10.1016/j.cels.2023.03.003
Abstrakt:	Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different organisms. Here, we generated synthetic genetic interaction and cell morphology profiles of more than 6,800 genes in cultured Drosophila cells. The resulting map of genetic interactions was used for machine learning-based gene function discovery, assigning functions to genes in 47 modules. Furthermore, we devised Cytoclass as a method to dissect genetic interactions for discrete cell states at the single-cell resolution. This approach identified an interaction of Cdk2 and the Cop9 signalosome complex, triggering senescence-associated secretory phenotypes and immunogenic conversion in hemocytic cells. Together, our data constitute a genome-scale resource of functional gene profiles to uncover the mechanisms underlying genetic interactions and their plasticity at the single-cell level. Competing Interests: Declaration of interests The authors declare no competing interests. (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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