The University of Southampton
University of Southampton Institutional Repository

Universality of clonal dynamics poses fundamental limits to identify stem cell self-renewal strategies

Universality of clonal dynamics poses fundamental limits to identify stem cell self-renewal strategies
Universality of clonal dynamics poses fundamental limits to identify stem cell self-renewal strategies

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.

2050-084X
Parigini, Cristina
e703096b-49c9-43e6-af7c-62a3a85e9a9b
Greulich, Philip
65da32ad-a73a-435a-86e0-e171437430a9
Parigini, Cristina
e703096b-49c9-43e6-af7c-62a3a85e9a9b
Greulich, Philip
65da32ad-a73a-435a-86e0-e171437430a9

Parigini, Cristina and Greulich, Philip (2020) Universality of clonal dynamics poses fundamental limits to identify stem cell self-renewal strategies. eLife, 9, [e56532]. (doi:10.7554/eLife.56532).

Record type: Article

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.

Text
Universal-clonal-dynamics Parigini+Greulich 2020 - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)
Text
Universal-clonal-dynamics Parigini+Greulich 2020 Supplement - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: 3 July 2020
e-pub ahead of print date: 20 July 2020
Published date: 20 July 2020
Additional Information: © 2020, Parigini and Greulich.

Identifiers

Local EPrints ID: 442625
URI: http://eprints.soton.ac.uk/id/eprint/442625
ISSN: 2050-084X
PURE UUID: abf7e763-a520-43e2-bdb8-b927586f1e00
ORCID for Philip Greulich: ORCID iD orcid.org/0000-0001-5247-6738

Catalogue record

Date deposited: 21 Jul 2020 16:34
Last modified: 17 Mar 2024 03:33

Export record

Altmetrics

Contributors

Author: Cristina Parigini
Author: Philip Greulich ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×