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Single-molecule imaging of transcription dynamics in somatic stem cells.
Wheat, Justin C; Sella, Yehonatan; Willcockson, Michael; Skoultchi, Arthur I; Bergman, Aviv; Singer, Robert H; Steidl, Ulrich.
Afiliação
  • Wheat JC; Department of Cell Biology, Albert Einstein College of Medicine, New York, NY, USA.
  • Sella Y; Ruth L. and David S. Gottesman Institute for Stem Cell Research and Regenerative Medicine, Albert Einstein College of Medicine, New York, NY, USA.
  • Willcockson M; Department of Systems and Computational Biology, Albert Einstein College of Medicine, New York, NY, USA.
  • Skoultchi AI; Department of Cell Biology, Albert Einstein College of Medicine, New York, NY, USA.
  • Bergman A; Department of Cell Biology, Albert Einstein College of Medicine, New York, NY, USA.
  • Singer RH; Department of Systems and Computational Biology, Albert Einstein College of Medicine, New York, NY, USA.
  • Steidl U; Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, NY, USA.
Nature ; 583(7816): 431-436, 2020 07.
Article em En | MEDLINE | ID: mdl-32581360
Molecular noise is a natural phenomenon that is inherent to all biological systems1,2. How stochastic processes give rise to the robust outcomes that support tissue homeostasis remains unclear. Here we use single-molecule RNA fluorescent in situ hybridization (smFISH) on mouse stem cells derived from haematopoietic tissue to measure the transcription dynamics of three key genes that encode transcription factors: PU.1 (also known as Spi1), Gata1 and Gata2. We find that infrequent, stochastic bursts of transcription result in the co-expression of these antagonistic transcription factors in the majority of haematopoietic stem and progenitor cells. Moreover, by pairing smFISH with time-lapse microscopy and the analysis of pedigrees, we find that although individual stem-cell clones produce descendants that are in transcriptionally related states-akin to a transcriptional priming phenomenon-the underlying transition dynamics between states are best captured by stochastic and reversible models. As such, a stochastic process can produce cellular behaviours that may be incorrectly inferred to have arisen from deterministic dynamics. We propose a model whereby the intrinsic stochasticity of gene expression facilitates, rather than impedes, the concomitant maintenance of transcriptional plasticity and stem cell robustness.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transcrição Gênica / Regulação da Expressão Gênica / Células-Tronco Adultas / Imagem Individual de Molécula Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transcrição Gênica / Regulação da Expressão Gênica / Células-Tronco Adultas / Imagem Individual de Molécula Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article