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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2016
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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 |
format | Online Article Text |
id | pubmed-4947393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
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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