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Integrated loss- and gain-of-function screens define a core network governing human embryonic stem cell behavior

Understanding the genetic control of human embryonic stem cell function is foundational for developmental biology and regenerative medicine. Here we describe an integrated genome-scale loss- and gain-of-function screening approach to identify genetic networks governing embryonic stem cell proliferat...

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Detalles Bibliográficos
Autores principales: Naxerova, Kamila, Di Stefano, Bruno, Makofske, Jessica L., Watson, Emma V., de Kort, Marit A., Martin, Timothy D., Dezfulian, Mohammed, Ricken, Dominik, Wooten, Eric C., Kuroda, Mitzi I., Hochedlinger, Konrad, Elledge, Stephen J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8559676/
https://www.ncbi.nlm.nih.gov/pubmed/34711655
http://dx.doi.org/10.1101/gad.349048.121
Descripción
Sumario:Understanding the genetic control of human embryonic stem cell function is foundational for developmental biology and regenerative medicine. Here we describe an integrated genome-scale loss- and gain-of-function screening approach to identify genetic networks governing embryonic stem cell proliferation and differentiation into the three germ layers. We identified a deep link between pluripotency maintenance and survival by showing that genetic alterations that cause pluripotency dissolution simultaneously increase apoptosis resistance. We discovered that the chromatin-modifying complex SAGA and in particular its subunit TADA2B are central regulators of pluripotency, survival, growth, and lineage specification. Joint analysis of all screens revealed that genetic alterations that broadly inhibit differentiation across multiple germ layers drive proliferation and survival under pluripotency-maintaining conditions and coincide with known cancer drivers. Our results show the power of integrated multilayer genetic screening for the robust mapping of complex genetic networks.