Andrew Bangham

Generation of Leaf Shape Through Early Patterns of Growth and Tissue Polarity

Shape-Shifting Signals Although orthogonal signaling systems seem to direct various developmental processes, few tissues remain in the same shape as they are at initiation to that of the final form. Arabidopsis leaves are free of the cell migrations that complicate animal development, and thus allowed Kuchen et al. (p. 1092) to track and model the trajectory of leaf growth under a variety of perturbations. Varying the values of parameters in their model produced outputs of different leaf shapes ranging from obcordate, ovate, and oval to elliptic, and offered predictions for genes that regulate the developmental process. The meristem at the growing tip of plants is home to stem cells and is the source of newly differentiating shoots and leaves. New leaves make their first appearance as bulges at the side of the dome-shaped meristem. Although these developmental events are under hormonal control, they also seem to be constrained by the physical properties of the meristem. Kierzkowski et al. (p. 1096) tested physical effects acting on the shoot apical meristem of growing tomato shoots that alter turgor pressure. Again, mathematical modeling combined with observations of plant tissue helped to define the different zones in the meristem that respond to diverse mechanical stimuli. A model for the development of leaf shape describes how it arises through oriented growth and tissue deformation. A major challenge in biology is to understand how buds comprising a few cells can give rise to complex plant and animal appendages like leaves or limbs. We address this problem through a combination of time-lapse imaging, clonal analysis, and computational modeling. We arrive at a model that shows how leaf shape can arise through feedback between early patterns of oriented growth and tissue deformation. Experimental tests through partial leaf ablation support this model and allow reevaluation of previous experimental studies. Our model allows a range of observed leaf shapes to be generated and predicts observed clone patterns in different species. Thus, our experimentally validated model may underlie the development and evolution of diverse organ shapes.

Visualizing Plant Development and Gene Expression in Three Dimensions Using Optical Projection Tomography

A deeper understanding of the mechanisms that underlie plant growth and development requires quantitative data on three-dimensional (3D) morphology and gene activity at a variety of stages and scales. To address this, we have explored the use of optical projection tomography (OPT) as a method for capturing 3D data from plant specimens. We show that OPT can be conveniently applied to a wide variety of plant material at a range of scales, including seedlings, leaves, flowers, roots, seeds, embryos, and meristems. At the highest resolution, large individual cells can be seen in the context of the surrounding plant structure. For naturally semitransparent structures, such as roots, live 3D imaging using OPT is also possible. 3D domains of gene expression can be visualized using either marker genes, such as β-glucuronidase, or more directly by whole-mount in situ hybridization. We also describe tools and software that allow the 3D data to be readily quantified and visualized interactively in different ways.

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

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.

JAGGED Controls Arabidopsis Petal Growth and Shape by Interacting with a Divergent Polarity Field

Computational modeling and experimentation show how Arabidopsis petals develop their size and shape through a growth pattern that is distinct to, but operates within, the developmental framework that also controls leaf shape.

An intracellular partitioning-based framework for tissue cell polarity in plants and animals

Tissue cell polarity plays a major role in plant and animal development. We propose that a fundamental building block for tissue cell polarity is the process of intracellular partitioning, which can establish individual cell polarity in the absence of asymmetric cues. Coordination of polarities may then arise through cell-cell coupling, which can operate directly, through membrane-spanning complexes, or indirectly, through diffusible molecules. Polarity is anchored to tissues through organisers located at boundaries. We show how this intracellular partitioning-based framework can be applied to both plant and animal systems, allowing different processes to be placed in a common evolutionary and mechanistic context.

Evolution of Allometry in Antirrhinum

Correlated variation in shape and size (allometry) is a major component of natural diversity. We examined the evolutionary and genetic basis for allometry using leaves and flower petals of snapdragon species (Antirrhinum). A computational method was developed to capture shape and size variation in both types of organ within the Antirrhinum species group. The results show that the major component of variation between species involves positively correlated changes in leaf and petal size. The correlation was maintained in an F2 population derived from crossing two species with organs of different sizes, suggesting that developmental constraints were involved. Identification of the underlying genes as quantitative trait loci revealed that the larger species carried alleles that increased organ size at all loci. Although this was initially taken as evidence that directional selection has driven diversity in both leaf and petal size, simulations revealed that evolution without consistent directional selection, an undirected walk, could also account for the parental distribution of organ size alleles.

Mutational spaces for leaf shape and size

A key approach to understanding how genes control growth and form is to analyze mutants in which shape and size have been perturbed. Although many mutants of this kind have been described in plants and animals, a general quantitative framework for describing them has yet to be established. Here we describe an approach based on Principal Component Analysis of organ landmarks and outlines. Applying this method to a collection of leaf shape mutants in Arabidopsis and Antirrhinum allows low‐dimensional spaces to be constructed that capture the key variations in shape and size. Mutant phenotypes can be represented as vectors in these allometric spaces, allowing additive gene interactions to be readily described. The principal axis of each allometric space reflects size variation and an associated shape change. The shape change is similar to that observed during the later stages of normal development, suggesting that many phenotypic differences involve modulations in the timing of growth arrest. Comparison between allometric mutant spaces from different species reveals a similar range of phenotypic possibilities. The spaces therefore provide a general quantitative framework for exploring and comparing the development and evolution of form.

Shape retrieval by principal components descriptor

Shape information is an important distribution to Content-Base Image Retrieval (CBIR) systems. There are two major types of shape descriptors, namely region-based and contour-based. In this paper we present a shape retrieval method that makes use of a contour-based descriptor, Principal Components Descriptor (PCD). In PCD, shapes are aligned on principal axes and described by a combination of the mean shape and weighted eigenvectors. The retrieval is achieved by comparing the weights of the eigenvectors. The developed approach is applied to Sharvits Silhouettes database and the results are compared with MPEG-7 standard contour-based descriptor, Curvature Scale Space (CSS). The comparison indicates that PCD shows higher accuracy than CSS.

Ufeel: Using haptics and stereo to place landmarks in three-dimensional volumetric images

This paper is concerned with extracting 3D models from volumetric images. Building models of 3D shape relies on placement of landmarks and in many biological and medical applications automatic landmark placement is impractical. We introduce a system, called uFeel, which allows manual placement of landmarks in 3D using a combination of stereo and haptics. This system is used to capture and analyse data on growing Arabidopsis leaves.

03-P090 Visualising plant growth and shape in 3D using optical projection tomography

We have explored the use of optical projection tomography (OPT) as a method for capturing 3D morphology and gene activity at a variety of developmental stages and scales from plant specimens, in collaboration with the Medical Research Council, James Sharpe and Bioptonics. OPT can be conveniently applied to a wide variety of plant material including seedlings, leaves, flowers, roots, seeds, embryos and meristems. At the highest resolution large individual cells can be seen in the context of the surrounding plant structure. 3D domains of gene expression can be visualised using either marker genes such as s-glucuronidase, or more directly by whole-mount in situ hybridization. To interactively analyse and quantify 3D OPT data we are developing software using haptics to accurately place points on volumes in 3D space. These tools will enable us to create 3D statistical shape models to analyse phenotypic variation in Arabidopsis leaves. For naturally semi-transparent structures, such as roots, live 3D imaging using OPT is possible. 3D gene expression patterns in living transgenic plants expressing fluorescent GFP markers can also be visualised by OPT. We are using GFP marked trichomes to track leaf growth in 4D, by obtaining OPT time-course data for Arabidopsis plants growing in the OPT device. Computer vision techniques are being developed to analyse sequential OPT datasets. The combination of 4D time-course data, 3D point-placing, trichome tracking and modelling will allow us to understand mechanisms controlling growth and shape from earliest stages of leaf growth to maturity.