IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v5y2014i1d10.1038_ncomms4451.html
   My bibliography  Save this article

Discriminating cellular heterogeneity using microwell-based RNA cytometry

Author

Listed:
  • Ivan K. Dimov

    (Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California
    Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine)

  • Rong Lu

    (Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine)

  • Eric P. Lee

    (Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California
    Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine)

  • Jun Seita

    (Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine)

  • Debashis Sahoo

    (Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine)

  • Seung-min Park

    (Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California
    Stanford University School of Medicine)

  • Irving L. Weissman

    (Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine)

  • Luke P. Lee

    (Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California)

Abstract

Discriminating cellular heterogeneity is important for understanding cellular physiology. However, it is limited by the technical difficulties of single-cell measurements. Here we develop a two-stage system to determine cellular heterogeneity. In the first stage, we perform multiplex single-cell RNA cytometry in a microwell array containing over 60,000 reaction chambers. In the second stage, we use the RNA cytometry data to determine cellular heterogeneity by providing a heterogeneity likelihood score (HLS). Moreover, we use Monte-Carlo simulation and RNA cytometry data to calculate the minimum number of cells required for detecting heterogeneity. We apply this system to characterize the RNA distributions of ageing-related genes in a highly purified mouse haematopoietic stem cell population. We identify genes that reveal novel heterogeneity of these cells. We also show that changes in expression of genes such as Birc6 during ageing can be attributed to the shift of relative portions of cells in the high-expressing subgroup versus low-expressing subgroup.

Suggested Citation

  • Ivan K. Dimov & Rong Lu & Eric P. Lee & Jun Seita & Debashis Sahoo & Seung-min Park & Irving L. Weissman & Luke P. Lee, 2014. "Discriminating cellular heterogeneity using microwell-based RNA cytometry," Nature Communications, Nature, vol. 5(1), pages 1-12, May.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4451
    DOI: 10.1038/ncomms4451
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms4451
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms4451?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4451. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.