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

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 p...

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Main Authors: Refahi, Yassin, Brunoud, Geraldine, Farcot, Etienne, Jean-Marie, Alain, Pulkkinen, Minna, Vernoux, Teva, Godin, Christophe
Format: Article
Published: eLife Sciences Publications 2016
Online Access:https://eprints.nottingham.ac.uk/35141/
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author Refahi, Yassin
Brunoud, Geraldine
Farcot, Etienne
Jean-Marie, Alain
Pulkkinen, Minna
Vernoux, Teva
Godin, Christophe
author_facet Refahi, Yassin
Brunoud, Geraldine
Farcot, Etienne
Jean-Marie, Alain
Pulkkinen, Minna
Vernoux, Teva
Godin, Christophe
author_sort Refahi, Yassin
building Nottingham Research Data Repository
collection Online Access
description 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.
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spelling nottingham-351412020-05-04T18:03:23Z https://eprints.nottingham.ac.uk/35141/ 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 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. eLife Sciences Publications 2016-07-06 Article PeerReviewed Refahi, Yassin, Brunoud, Geraldine, Farcot, Etienne, Jean-Marie, Alain, Pulkkinen, Minna, Vernoux, Teva and Godin, Christophe (2016) A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis. eLife, 5 . e14093/1-e14093/51. ISSN 2050-084X https://elifesciences.org/content/5/e14093 doi:10.7554/eLife.14093 doi:10.7554/eLife.14093
spellingShingle Refahi, Yassin
Brunoud, Geraldine
Farcot, Etienne
Jean-Marie, Alain
Pulkkinen, Minna
Vernoux, Teva
Godin, Christophe
A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
title A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
title_full A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
title_fullStr A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
title_full_unstemmed A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
title_short A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
title_sort stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis
url https://eprints.nottingham.ac.uk/35141/
https://eprints.nottingham.ac.uk/35141/
https://eprints.nottingham.ac.uk/35141/