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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doaj-5ba8bc46b0744bf6ba3305a797ccef1c2021-05-05T00:28:21ZengeLife Sciences Publications LtdeLife2050-084X2016-07-01510.7554/eLife.14093A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxisYassin Refahi0Géraldine Brunoud1Etienne Farcot2Alain Jean-Marie3Minna Pulkkinen4Teva Vernoux5https://orcid.org/0000-0002-8257-4088Christophe Godin6https://orcid.org/0000-0002-1202-8460Laboratoire de Reproduction de développement des plantes, Lyon, France; Sainsbury Laboratory, University of Cambridge, Cambridge, United KingdomLaboratoire de Reproduction de développement des plantes, Lyon, FranceSchool of Mathematical Sciences, The University of Nottingham, Nottingham, United Kingdom; Center for Integrative Plant Biology, The University of Nottingham, Notthingam, United KingdomINRIA Project-Team Maestro, INRIA Sophia-Antipolis Méditerranée Research Center, Montpellier, FranceUMR Lerfob, AgroParisTech, Nancy, FranceLaboratoire de Reproduction de développement des plantes, Lyon, FranceINRIA Project-Team Virtual Plants, CIRAD, INRA and INRIA Sophia-Antipolis Méditerranée Research Center, Montpellier, FranceExploration 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.https://elifesciences.org/articles/14093phyllotaxisemergenceinhibitory fieldsnoisemulti-scale modelingpermutations |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yassin Refahi Géraldine Brunoud Etienne Farcot Alain Jean-Marie Minna Pulkkinen Teva Vernoux Christophe Godin |
spellingShingle |
Yassin Refahi Géraldine Brunoud Etienne Farcot Alain Jean-Marie Minna Pulkkinen Teva Vernoux Christophe Godin A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis eLife phyllotaxis emergence inhibitory fields noise multi-scale modeling permutations |
author_facet |
Yassin Refahi Géraldine Brunoud Etienne Farcot Alain Jean-Marie Minna Pulkkinen Teva Vernoux Christophe Godin |
author_sort |
Yassin Refahi |
title |
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_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_sort |
stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2016-07-01 |
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. |
topic |
phyllotaxis emergence inhibitory fields noise multi-scale modeling permutations |
url |
https://elifesciences.org/articles/14093 |
work_keys_str_mv |
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