Gene free methodology for cell fate dynamics during development

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Abstract

Models of cell function that assign a variable to each gene frequently lead to systems of equations with many parameters whose behavior is obscure. Geometric models reduce dynamics to intuitive pictorial elements that provide compact representations for sparse in-vivo data and transparent descriptions of developmental transitions. To illustrate, a geometric model fit to vulval development in C. elegans, implies a phase diagram where cell-fate choices are displayed in a plane defined by EGF and Notch signaling levels. This diagram defines allowable and forbidden cell-fate transitions as EGF or Notch levels change, and explains surprising observations previously attributed to context-dependent action of these signals. The diagram also reveals the existence of special points at which minor changes in signal levels lead to strong epistatic interactions between EGF and Notch. Our model correctly predicts experiments near these points, and suggests specific timed perturbations in signals that can lead to additional unexpected outcomes.

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Francis Corson

Laboratoire de Physique Statistique, Ecole Normale Supérieure, Paris, France

For correspondence
corson@lps.ens.fr

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-7230-137X
Eric D Siggia

Center for Studies in Physics and Biology, Rockefeller University, New York, United States

For correspondence
siggiae@mail.rockefeller.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-7482-1854

Funding

National Science Foundation (PHY-1502151)

Eric D Siggia

National Science Foundation (PHY-1125915)

Francis Corson

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

Copyright

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.