Generation of diverse biological forms through combinatorial interactions between tissue polarity and growth

Kennaway, Richard, Coen, Enrico, Green, Amelia and Bangham, Andrew (2011) Generation of diverse biological forms through combinatorial interactions between tissue polarity and growth. PLoS Computational Biology, 7 (6). ISSN 1553-7358

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Abstract

A major problem in biology is to understand how complex tissue shapes may arise through growth. In many cases this process involves preferential growth along particular orientations raising the question of how these orientations are specified. One view is that orientations are specified through stresses in the tissue (axiality-based system). Another possibility is that orientations can be specified independently of stresses through molecular signalling (polarity-based system). The axiality-based system has recently been explored through computational modelling. Here we develop and apply a polarity-based system which we call the Growing Polarised Tissue (GPT) framework. Tissue is treated as a continuous material within which regionally expressed factors under genetic control may interact and propagate. Polarity is established by signals that propagate through the tissue and is anchored in regions termed tissue polarity organisers that are also under genetic control. Rates of growth parallel or perpendicular to the local polarity may then be specified through a regulatory network. The resulting growth depends on how specified growth patterns interact within the constraints of mechanically connected tissue. This constraint leads to the emergence of features such as curvature that were not directly specified by the regulatory networks. Resultant growth feeds back to influence spatial arrangements and local orientations of tissue, allowing complex shapes to emerge from simple rules. Moreover, asymmetries may emerge through interactions between polarity fields. We illustrate the value of the GPT-framework for understanding morphogenesis by applying it to a growing Snapdragon flower and indicate how the underlying hypotheses may be tested by computational simulation. We propose that combinatorial intractions between orientations and rates of growth, which are a key feature of polarity-based systems, have been exploited during evolution to generate a range of observed biological shapes.

Item Type: Article
Additional Information: © 2011 Kennaway et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Uncontrolled Keywords: computer simulation,anisotropy,cell polarity,morphogenesis,gene expression regulation, plant,computational biology,antirrhinum,models, biological
Faculty \ School: Faculty of Science > School of Computing Sciences
Faculty of Science > School of Biological Sciences
Depositing User: Users 2731 not found.
Date Deposited: 31 Jan 2012 09:55
Last Modified: 21 Apr 2020 16:48
URI: https://ueaeprints.uea.ac.uk/id/eprint/36588
DOI: 10.1371/journal.pcbi.1002071

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