S. Moore
Modelling plant hormone gradients
Moore, S.; Zhang, X.; Liu, J.; Lindsey, K.
Authors
X. Zhang
Dr Junli Liu junli.liu@durham.ac.uk
Associate Professor
Professor Keith Lindsey keith.lindsey@durham.ac.uk
Professor
Abstract
Cellular patterning in the Arabidopsis root is coordinated via a localised auxin concentration maximum in the root tip, requiring the regulated expression of specific genes. The activities of plant hormones such as auxin, ethylene and cytokinin depend on cellular context and exhibit either synergistic or antagonistic interactions. Due to the complexity and nonlinearity of spatiotemporal interactions between both hormones and gene expression in root development, modelling plant hormone gradients requires a systems approach in which experimental data and modelling analysis are closely combined. Modelling therefore allows a predictive interrogation of highly complex and nonintuitive interactions between components in the system. Important factors to be considered when modelling hormone gradients include the construction of a hormonal crosstalk network, the formulation of kinetic equations and the construction of an in silico root map. A modelling approach enables the analysis of relationships between multiple hormone gradients, predictions on how hormone gradients emerge under the action of hormonal crosstalk, and the prediction and elucidation of experimental results from mutant roots.
Citation
Moore, S., Zhang, X., Liu, J., & Lindsey, K. (online). Modelling plant hormone gradients. https://doi.org/10.1002/9780470015902.a0023733
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 15, 2015 |
Online Publication Date | Oct 15, 2015 |
Deposit Date | Oct 20, 2015 |
Publicly Available Date | Nov 30, 2015 |
Journal | eLS |
Peer Reviewed | Peer Reviewed |
Pages | 1-10 |
DOI | https://doi.org/10.1002/9780470015902.a0023733 |
Keywords | Arabidopsis, Root development, Hormone gradients, Hormonal crosstalk, Mathematical modelling, Kinetics, in silico root map, Gene expression, Metabolic regulation, Systems biology. |
Public URL | https://durham-repository.worktribe.com/output/1397287 |
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Copyright Statement
This is the accepted version of the following article: Moore, S., Zhang, X., Liu, J. and Lindsey, K. 2015. Modelling Plant Hormone Gradients. eLS. 1–10, which has been published in final form at https://doi.org/10.1002/9780470015902.a0023733. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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