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Deconstructing transcriptional heterogeneity in pluripotent stem cells

Author

Listed:
  • Roshan M. Kumar

    (Wyss Institute for Biologically Inspired Engineering, Harvard University
    Howard Hughes Medical Institute, Center of Synthetic Biology, Boston University)

  • Patrick Cahan

    (Stem Cell Transplantation Program, Manton Center for Orphan Disease Research, Howard Hughes Medical Institute, Boston Children’s Hospital and Dana Farber Cancer Institute, Harvard Medical School, Harvard Stem Cell Institute)

  • Alex K. Shalek

    (Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA)

  • Rahul Satija

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • A. Jay DaleyKeyser

    (Wyss Institute for Biologically Inspired Engineering, Harvard University)

  • Hu Li

    (Center for Individualized Medicine, Mayo Clinic College of Medicine)

  • Jin Zhang

    (Stem Cell Transplantation Program, Manton Center for Orphan Disease Research, Howard Hughes Medical Institute, Boston Children’s Hospital and Dana Farber Cancer Institute, Harvard Medical School, Harvard Stem Cell Institute)

  • Keith Pardee

    (Wyss Institute for Biologically Inspired Engineering, Harvard University
    Howard Hughes Medical Institute, Center of Synthetic Biology, Boston University)

  • David Gennert

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • John J. Trombetta

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Thomas C. Ferrante

    (Wyss Institute for Biologically Inspired Engineering, Harvard University)

  • Aviv Regev

    (Broad Institute of MIT and Harvard, 7 Cambridge Center
    Howard Hughes Medical Institute, Massachusetts Institute of Technology)

  • George Q. Daley

    (Stem Cell Transplantation Program, Manton Center for Orphan Disease Research, Howard Hughes Medical Institute, Boston Children’s Hospital and Dana Farber Cancer Institute, Harvard Medical School, Harvard Stem Cell Institute)

  • James J. Collins

    (Wyss Institute for Biologically Inspired Engineering, Harvard University
    Howard Hughes Medical Institute, Center of Synthetic Biology, Boston University)

Abstract

Pluripotent stem cells (PSCs) are capable of dynamic interconversion between distinct substates; however, the regulatory circuits specifying these states and enabling transitions between them are not well understood. Here we set out to characterize transcriptional heterogeneity in mouse PSCs by single-cell expression profiling under different chemical and genetic perturbations. Signalling factors and developmental regulators show highly variable expression, with expression states for some variable genes heritable through multiple cell divisions. Expression variability and population heterogeneity can be influenced by perturbation of signalling pathways and chromatin regulators. Notably, either removal of mature microRNAs or pharmacological blockage of signalling pathways drives PSCs into a low-noise ground state characterized by a reconfigured pluripotency network, enhanced self-renewal and a distinct chromatin state, an effect mediated by opposing microRNA families acting on the Myc/Lin28/let-7 axis. These data provide insight into the nature of transcriptional heterogeneity in PSCs.

Suggested Citation

  • Roshan M. Kumar & Patrick Cahan & Alex K. Shalek & Rahul Satija & A. Jay DaleyKeyser & Hu Li & Jin Zhang & Keith Pardee & David Gennert & John J. Trombetta & Thomas C. Ferrante & Aviv Regev & George Q, 2014. "Deconstructing transcriptional heterogeneity in pluripotent stem cells," Nature, Nature, vol. 516(7529), pages 56-61, December.
    • Handle: RePEc:nat:nature:v:516:y:2014:i:7529:d:10.1038_nature13920
    DOI: 10.1038/nature13920
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    Cited by:

    1. Kentaro Mochizuki & Jafar Sharif & Kenjiro Shirane & Kousuke Uranishi & Aaron B. Bogutz & Sanne M. Janssen & Ayumu Suzuki & Akihiko Okuda & Haruhiko Koseki & Matthew C. Lorincz, 2021. "Repression of germline genes by PRC1.6 and SETDB1 in the early embryo precedes DNA methylation-mediated silencing," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    2. Hyun Kim & Won Chang & Seok Joo Chae & Jong-Eun Park & Minseok Seo & Jae Kyoung Kim, 2024. "scLENS: data-driven signal detection for unbiased scRNA-seq data analysis," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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