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Published October 7, 2011 | public
Journal Article

Steady-state invariant genetics: probing the role of morphogen gradient dynamics in developmental patterning

Nahmad, Marcos

Abstract

Morphogen-mediated patterning is the predominant mechanism by which positional information is established during animal development. In the classical view, the interpretation of positional signals depends on the equilibrium distribution of a morphogen, regardless of the dynamics of gradient formation. The problem of whether or not morphogen dynamics contribute to developmental patterning has not been explored in detail, partly because genetic experiments, which selectively affect signalling dynamics while maintaining unchanged the steady-state morphogen profile, are difficult to design and interpret. Here, I present a modelling-based approach to identify genetic mutations in developmental patterning that may affect the transient, but leave invariant the steady-state signalling gradient. As a case study, this approach is used to explore the dynamic properties of Hedgehog (Hh) signalling in the developing wing of the fruitfiy, Drosophila melanogaster. This analysis provides insights into how different properties of the Hh gradient dynamics, such as the duration of exposure to the signal or the maximum width of the transient gradient, can be genetically perturbed without affecting the steady-state distribution of the Hh concentration profile. I propose that this method can be used as an experimental design tool to investigate the role of transient morphogen gradients in developmental patterning and discuss the generality of these ideas in other problems.

Additional Information

© 2011 The Royal Society. Received December 25, 2010. Accepted February 18, 2011. Published online before print March 18, 2011. I thank John Doyle for his advice and insightful discussions about this work. I also thank Angelike Stathopoulos and Arthur Lander for comments on the manuscript. This work was supported by a grant from the National Institutes of Health (R01-G1\I078992) to John Doyle.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023