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Single-molecule imaging of transcription dynamics in somatic stem cells

Author

Listed:
  • Justin C. Wheat

    (Albert Einstein College of Medicine
    Albert Einstein College of Medicine)

  • Yehonatan Sella

    (Albert Einstein College of Medicine)

  • Michael Willcockson

    (Albert Einstein College of Medicine)

  • Arthur I. Skoultchi

    (Albert Einstein College of Medicine)

  • Aviv Bergman

    (Albert Einstein College of Medicine
    Albert Einstein College of Medicine
    Albert Einstein College of Medicine
    Santa Fe Institute)

  • Robert H. Singer

    (Albert Einstein College of Medicine
    Albert Einstein College of Medicine
    Albert Einstein College of Medicine
    Albert Einstein College of Medicine)

  • Ulrich Steidl

    (Albert Einstein College of Medicine
    Albert Einstein College of Medicine
    Albert Einstein College of Medicine-Montefiore Medical Center
    Albert Einstein College of Medicine)

Abstract

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.

Suggested Citation

  • Justin C. Wheat & Yehonatan Sella & Michael Willcockson & Arthur I. Skoultchi & Aviv Bergman & Robert H. Singer & Ulrich Steidl, 2020. "Single-molecule imaging of transcription dynamics in somatic stem cells," Nature, Nature, vol. 583(7816), pages 431-436, July.
  • Handle: RePEc:nat:nature:v:583:y:2020:i:7816:d:10.1038_s41586-020-2432-4
    DOI: 10.1038/s41586-020-2432-4
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    Cited by:

    1. A. S. Eisele & M. Tarbier & A. A. Dormann & V. Pelechano & D. M. Suter, 2024. "Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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