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Statistically derived geometrical landscapes capture principles of decision-making dynamics during cell fate transitions

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Sáez, Meritxell, Blassberg, Robert, Camacho-Aguilar, Elena, Siggia, Eric D., Rand, David A. and Briscoe, James (2022) Statistically derived geometrical landscapes capture principles of decision-making dynamics during cell fate transitions. Cell Systems, 13 (1). pp. 12-28. doi:10.1016/j.cels.2021.08.013

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Official URL: http://dx.doi.org/10.1016/j.cels.2021.08.013

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Abstract

Fate decisions in developing tissues involve cells transitioning between discrete cell states, each defined by distinct gene expression profiles. The Waddington landscape, in which the development of a cell is viewed as a ball rolling through a valley filled terrain, is an appealing way to describe differentiation. To construct and validate accurate landscapes, quantitative methods based on experimental data are necessary. We combined principled statistical methods with a framework based on catastrophe theory and approximate Bayesian computation to formulate a quantitative dynamical landscape that accurately predicts cell fate outcomes of pluripotent stem cells exposed to different combinations of signaling factors. Analysis of the landscape revealed two distinct ways in which cells make a binary choice between one of two fates. We suggest that these represent archetypal designs for developmental decisions. The approach is broadly applicable for the quantitative analysis of differentiation and for determining the logic of developmental decisions.

Item Type: Journal Article
Subjects: Q Science > QH Natural history
Divisions: Faculty of Science, Engineering and Medicine > Science > Mathematics
Library of Congress Subject Headings (LCSH): Gene expression , Gene expression -- Statistical methods, Cells -- Growth -- Mathematical models
Journal or Publication Title: Cell Systems
Publisher: Cell Press
ISSN: 2405-4712
Official Date: 19 January 2022
Dates:
DateEvent
19 January 2022Published
17 September 2021Available
23 August 2021Accepted
Volume: 13
Number: 1
Page Range: pp. 12-28
DOI: 10.1016/j.cels.2021.08.013
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/P019811/1 [EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
1499350[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
UNSPECIFIEDUniversity of Warwickhttp://dx.doi.org/10.13039/501100000741
UNSPECIFIEDCancer Research UKhttp://dx.doi.org/10.13039/501100000289
FC001051[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
FC001051Wellcome Trusthttp://dx.doi.org/10.13039/100010269
742138Horizon 2020 Framework Programmehttp://dx.doi.org/10.13039/100010661
Phy 2013131National Science Foundationhttp://dx.doi.org/10.13039/501100008982
PHY-1748958National Science Foundationhttp://dx.doi.org/10.13039/501100008982
R25GM067110National Institutes of Healthhttp://dx.doi.org/10.13039/100000002
2919.01Gordon and Betty Moore Foundationhttp://dx.doi.org/10.13039/100000936

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