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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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Autores principales: Refahi, Yassin, Brunoud, Géraldine, Farcot, Etienne, Jean-Marie, Alain, Pulkkinen, Minna, Vernoux, Teva, Godin, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4947393/
https://www.ncbi.nlm.nih.gov/pubmed/27380805
http://dx.doi.org/10.7554/eLife.14093
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author Refahi, Yassin
Brunoud, Géraldine
Farcot, Etienne
Jean-Marie, Alain
Pulkkinen, Minna
Vernoux, Teva
Godin, Christophe
author_facet Refahi, Yassin
Brunoud, Géraldine
Farcot, Etienne
Jean-Marie, Alain
Pulkkinen, Minna
Vernoux, Teva
Godin, Christophe
author_sort Refahi, Yassin
collection PubMed
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. DOI: http://dx.doi.org/10.7554/eLife.14093.001
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spelling pubmed-49473932016-07-18 A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis Refahi, Yassin Brunoud, Géraldine Farcot, Etienne Jean-Marie, Alain Pulkkinen, Minna Vernoux, Teva Godin, Christophe eLife Developmental Biology and Stem Cells 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. DOI: http://dx.doi.org/10.7554/eLife.14093.001 eLife Sciences Publications, Ltd 2016-07-06 /pmc/articles/PMC4947393/ /pubmed/27380805 http://dx.doi.org/10.7554/eLife.14093 Text en © 2016, Refahi et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Developmental Biology and Stem Cells
Refahi, Yassin
Brunoud, Géraldine
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
topic Developmental Biology and Stem Cells
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4947393/
https://www.ncbi.nlm.nih.gov/pubmed/27380805
http://dx.doi.org/10.7554/eLife.14093
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