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A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

Refahi, Yassin; Brunoud, Geraldine; Farcot, Etienne; Jean-Marie, Alain; Pulkkinen, Minna; Vernoux, Teva; Godin, Christophe

Authors

Yassin Refahi

Geraldine Brunoud

Alain Jean-Marie

Minna Pulkkinen

Teva Vernoux

Christophe Godin



Abstract

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems.

Citation

Refahi, Y., Brunoud, G., Farcot, E., Jean-Marie, A., Pulkkinen, M., Vernoux, T., & Godin, C. (2016). A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis. eLife, 5, Article e14093. https://doi.org/10.7554/eLife.14093

Journal Article Type Article
Acceptance Date May 4, 2016
Publication Date Jul 6, 2016
Deposit Date Jul 20, 2016
Publicly Available Date Mar 28, 2024
Journal eLife
Electronic ISSN 2050-084X
Publisher eLife Sciences Publications
Peer Reviewed Peer Reviewed
Volume 5
Article Number e14093
DOI https://doi.org/10.7554/eLife.14093
Public URL https://nottingham-repository.worktribe.com/output/802094
Publisher URL https://elifesciences.org/content/5/e14093

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