Generation of Diverse Biological Forms through Combinatorial Interactions between Tissue Polarity and Growth

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.

Discovery of the surface polarity gradient on iridescent Morpho butterfly scales reveals a mechanism of their selective vapor response

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Mechanical constraints imposed by 3D cellular geometry and arrangement modulate growth patterns in the Arabidopsis embryo

“…it is possible to understand the often unintuitive relationships between gene expression patterns and the resulting organ shapes (1,(20)(21)(22)(23). Using computational models, we demonstrate that the 3D shape of cells and their arrangement within multicellular plant organs can profoundly affect their growth response to gradients of expansion-promoting gene expression.…”

“…computational modeling | quantification | biomechanics | plant development | seed germination C entral to developmental biology is the question of how gene expression leads to morphogenesis and the creation of form (1,2). However, there are few studies that link genes directly with shape change in a mechanistic way (3)(4)(5).…”

Computational Method for Quantifying Growth Patterns at the Adaxial Leaf Surface in Three Dimensions

“…A Polarizing Substance May Control Growth Directionality Kennaway et al (2011) recently outlined three possibilities regarding the control of growth directionality in developing tissues. The first possibility is that directions of growth are defined in the leaf tissue early in development and remain fixed locally, in which case any change in the pattern of growth directions at the whole organ level would reflect rotation of the tissue within the organ.…”