1. Computational and Systems Biology
  2. Developmental Biology
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Universality of clonal dynamics poses fundamental limits to identify stem cell self-renewal strategies

  1. Cristina Parigini
  2. Philip Greulich  Is a corresponding author
  1. University of Southampton, United Kingdom
Research Article
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Cite this article as: eLife 2020;9:e56532 doi: 10.7554/eLife.56532

Abstract

How adult stem cells maintain self-renewing tissues is in vivo commonly assessed by analysing clonal data from cell lineage tracing assays. To identify strategies of stem cell self-renewal requires that different models of stem cell fate choice predict sufficiently different clonal statistics. Here we show that models of cell fate choice can, in homeostatic tissues, be categorized by exactly two 'universality classes', whereby models of the same class predict, under asymptotic conditions, the same clonal statistics. Those classes relate to generalizations of the canonical asymmetric vs. symmetric stem cell self-renewal strategies and are distinguished by a conservation law. This poses both challenges and opportunities to identify stem cell self-renewal strategies: while under asymptotic conditions, self-renewal models of the same universality class cannot be distinguished by clonal data only, models of different classes can be distinguished by simple means.

Data availability

All numerical data used for figures is produced by programme code, which can be found on Github, under https://github.com/cp4u17/simCellState

The following data sets were generated

Article and author information

Author details

  1. Cristina Parigini

    Mathematical Sciences, University of Southampton, Southampton, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Philip Greulich

    Mathematical Sciences, University of Southampton, Southampton, United Kingdom
    For correspondence
    P.S.Greulich@soton.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5247-6738

Funding

Medical Research Council (MR/R026610/1)

  • Philip Greulich

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Yukiko M Yamashita, University of Michigan, United States

Publication history

  1. Received: March 2, 2020
  2. Accepted: July 3, 2020
  3. Accepted Manuscript published: July 20, 2020 (version 1)
  4. Version of Record published: August 24, 2020 (version 2)

Copyright

© 2020, Parigini & Greulich

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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