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| Verfasst von: | Heigwer, Florian [VerfasserIn]  |
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| | Scheeder, Christian [VerfasserIn] |
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| | Bageritz, Josephine [VerfasserIn] |
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| | Yousefian, Schayan [VerfasserIn] |
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| | Rauscher, Benedikt [VerfasserIn] |
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| | Laufer, Christina [VerfasserIn] |
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| | Beneyto-Calabuig, Sergi [VerfasserIn] |
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| | Funk, Maja C. [VerfasserIn] |
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| | Peters, Vera [VerfasserIn] |
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| | Boulougouri, Maria [VerfasserIn] |
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| | Bilanovic, Jana [VerfasserIn] |
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| | Miersch, Thilo [VerfasserIn] |
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| | Schmitt, Barbara [VerfasserIn] |
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| | Blass, Claudia [VerfasserIn] |
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| | Port, Fillip [VerfasserIn] |
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| | Boutros, Michael [VerfasserIn] |
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| Titel: | A global genetic interaction network by single-cell imaging and machine learning |
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| Verf.angabe: | Florian Heigwer, Christian Scheeder, Josephine Bageritz, Schayan Yousefian, Benedikt Rauscher, Christina Laufer, Sergi Beneyto-Calabuig, Maja Christina Funk, Vera Peters, Maria Boulougouri, Jana Bilanovic, Thilo Miersch, Barbara Schmitt, Claudia Blass, Fillip Port, and Michael Boutros |
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| E-Jahr: | 2023 |
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| Jahr: | April 27, 2023 |
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| Umfang: | 23 S. |
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| Fussnoten: | Gesehen am 14.07.2023 |
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| Titel Quelle: | Enthalten in: Cell systems |
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| Ort Quelle: | Maryland Heights, MO : Elsevier, 2015 |
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| Jahr Quelle: | 2023 |
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| Band/Heft Quelle: | 14(2023,5) Seite 346-362, e1-e6, 23 Seiten |
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| ISSN Quelle: | 2405-4720 |
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| Abstract: | 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. |
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| DOI: | doi:10.1016/j.cels.2023.03.003 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.1016/j.cels.2023.03.003 |
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| | Volltext: https://www.sciencedirect.com/science/article/pii/S2405471223000790 |
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| | DOI: https://doi.org/10.1016/j.cels.2023.03.003 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | gene-function relationship |
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| | genetic epistasis |
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| | genome |
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| | machine learning |
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| | phenotypic profiling |
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| | single-cell phenotyping |
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| | synthetic genetic interaction |
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| K10plus-PPN: | 1852678011 |
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| Verknüpfungen: | → Zeitschrift |
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¬A¬ global genetic interaction network by single-cell imaging and machine learning / Heigwer, Florian [VerfasserIn]; April 27, 2023 (Online-Ressource)
