A quantitative model for spatio-temporal dynamics of root gravitropism

Abstract Plant organs adapt their morphology according to environmental signals through growth-driven processes called tropisms. While much effort has been directed towards the development of mathematical models describing the tropic dynamics of aerial organs, these cannot provide a good description...

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Bibliographic Details
Published inJournal of experimental botany Vol. 75; no. 2; pp. 620 - 630
Main Authors Porat, Amir, Rivière, Mathieu, Meroz, Yasmine
Format Journal Article
LanguageEnglish
Published UK Oxford University Press 10.01.2024
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Summary:Abstract Plant organs adapt their morphology according to environmental signals through growth-driven processes called tropisms. While much effort has been directed towards the development of mathematical models describing the tropic dynamics of aerial organs, these cannot provide a good description of roots due to intrinsic physiological differences. Here we present a mathematical model informed by gravitropic experiments on Arabidopsis thaliana roots, assuming a subapical growth profile and apical sensing. The model quantitatively recovers the full spatio-temporal dynamics observed in experiments. An analytical solution of the model enables us to evaluate the gravitropic and proprioceptive sensitivities of roots, while also allowing us to corroborate the requirement for proprioception in describing root dynamics. Lastly, we find that the dynamics are analogous to a damped harmonic oscillator, providing intuition regarding the source of the observed oscillatory behavior and the importance of proprioception for efficient gravitropic control. In all, the model provides not only a quantitative description of root tropic dynamics, but also a mathematical framework for the future investigation of roots in complex media. We develop a mathematical model for spatio-temporal dynamics of root gravitropism informed by experiments, identifying the dynamic contributions of proprioception and passive orientation drift.
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Amir Porat and Mathieu Rivière contributed equally to this work.
ISSN:0022-0957
1460-2431
1460-2431
DOI:10.1093/jxb/erad383