OpenAlea: a visual programming and component-based software platform for plant modelling

Pradal, Christophe; Dufour-Kowalski, Samuel; Boudon, Frédéric; Fournier, Christian; Godin, Christophe

doi:10.1071/fp08084

Cited by 270 publications

(181 citation statements)

References 29 publications

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“…All postacquisition image processing was performed using Fiji, AMIRA, and OpenAlea (27). More details on statistical shape analysis and measurements of LRP radialization can be found in SI Materials and Methods.…”

Section: Methodsmentioning

confidence: 99%

Lateral root morphogenesis is dependent on the mechanical properties of the overlaying tissues

Lucas

Kenobi

Wangenheim

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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208

186

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In Arabidopsis, lateral root primordia (LRPs) originate from pericycle cells located deep within the parental root and have to emerge through endodermal, cortical, and epidermal tissues. These overlaying tissues place biomechanical constraints on the LRPs that are likely to impact their morphogenesis. This study probes the interplay between the patterns of cell division, organ shape, and overlaying tissues on LRP morphogenesis by exploiting recent advances in live plant cell imaging and image analysis. Our 3D/4D image analysis revealed that early stage LRPs exhibit tangential divisions that create a ring of cells corralling a population of rapidly dividing cells at its center. The patterns of division in the latter population of cells during LRP morphogenesis are not stereotypical. In contrast, statistical analysis demonstrated that the shape of new LRPs is highly conserved. We tested the relative importance of cell division pattern versus overlaying tissues on LRP morphogenesis using mutant and transgenic approaches. The double mutant aurora1 (aur1) aur2 disrupts the pattern of LRP cell divisions and impacts its growth dynamics, yet the new organ's dome shape remains normal. In contrast, manipulating the properties of overlaying tissues disrupted LRP morphogenesis. We conclude that the interaction with overlaying tissues, rather than the precise pattern of divisions, is most important for LRP morphogenesis and optimizes the process of lateral root emergence.lateral root development | plant morphogenesis | biomechanical regulation | statistical shape analysis | Arabidopsis thaliana I n contrast to animals, only the basic blueprint of the plant body plan is laid out during embryogenesis. Instead, the majority of plant organs are formed postembryonically. In some instances, organ formation can occur deep within another organ, as is the case for lateral roots (1, 2). In addition, plant cells are constrained by rigid walls; hence, cell migration cannot occur. Instead, plant morphogenesis relies on two mechanisms: oriented cell division and anisotropic growth (3, 4). For example, during embryogenesis, cells exhibit a highly synchronized program of expansion and division (5). How cell division, cell shape, and overlaying tissues interact during plant organ morphogenesis is currently unclear.Lateral roots are derived from cell division events deep within the primary root (1, 2). Pairs of pericycle cells in several adjacent files undergo a series of asymmetric formative divisions (reviewed in ref. 6). These periclinal (parallel) and anticlinal (perpendicular) divisions give birth to a lateral root primordium (LRP) that will develop further into a lateral root comprising a new root meristem. LRP formation in Arabidopsis was first described in a pioneering study 14 years ago (7) that proposed a seven-stage taxonomy of LRP development on the basis of 2D observations of cell layer numbers that still forms the basis of all studies describing LRP development in Arabidopsis.Recent advances in live biological imaging and image ...

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Section: Methodsmentioning

confidence: 99%

Lateral root morphogenesis is dependent on the mechanical properties of the overlaying tissues

Lucas

Kenobi

Wangenheim

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

208

186

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“…It is well-known by our first generation users, and has very specific features, making it possible to perform both data analysis and simulation (retro-action loops, modeling) while allowing visualization of complex data. As shown previously in [10,6], OpenAlea belongs to the family of functional workflow systems (such as [9,34,35,36]). It provides a unique solution, which is able to extend the dataflow model of computation by introducing higher-order language constructs in a visual programming environment, thus allowing to design highly expressive workflows in a fully uniform way.…”

Section: Discussionmentioning

confidence: 99%

“…The OpenAlea scientific workflow system is a component-based architecture implemented as a set of pure Python packages [6]. The visual programming environment and graphical user interface (GUI) is implemented using the PyQt toolkit, a Python binding to the Qt application framework.…”

Section: Scientific Workflow Management System: Openaleamentioning

confidence: 99%

InfraPhenoGrid: A scientific workflow infrastructure for plant phenomics on the Grid

Pradal

Artzet

Chopard

et al. 2017

Future Generation Computer Systems

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Plant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges, in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data.In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middleware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users.

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“…The three models used different modeling platforms: the Minimal Framework model was built using OpenAlea (Pradal et al, 2008), the Growing Root model used VirtualLeaf (Merks et al, 2011), and the Auxin Flux model was a Cellular Potts model. The first two approaches are the most similar, as they are both vertex based.…”

Section: Model Constructionmentioning

confidence: 99%

Theoretical approaches to understanding root vascular patterning: a consensus between recent models

Mellor

Adibi

El‐Showk

et al. 2016

EXBOTJ

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. AbstractThe root vascular tissues provide an excellent system for studying organ patterning, as the specification of these tissues signals a transition from radial symmetry to bisymmetric patterns. The patterning process is controlled by the combined action of hormonal signaling/transport pathways, transcription factors, and miRNA that operate through a series of non-linear pathways to drive pattern formation collectively. With the discovery of multiple components and feedback loops controlling patterning, it has become increasingly difficult to understand how these interactions act in unison to determine pattern formation in multicellular tissues. Three independent mathematical models of root vascular patterning have been formulated in the last few years, providing an excellent example of how theoretical approaches can complement experimental studies to provide new insights into complex systems. In many aspects these models support each other; however, each study also provides its own novel findings and unique viewpoints. Here we reconcile these models by identifying the commonalities and exploring the differences between them by testing how transferable findings are between models. New simulations herein support the hypothesis that an asymmetry in auxin input can direct the formation of vascular pattern. We show that the xylem axis can act as a sole source of cytokinin and specify the correct pattern, but also that broader patterns of cytokinin production are also able to pattern the root. By comparing the three modeling approaches, we gain further insight into vascular patterning and identify several key areas for experimental investigation.

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OpenAlea: a visual programming and component-based software platform for plant modelling

Cited by 270 publications

References 29 publications

Lateral root morphogenesis is dependent on the mechanical properties of the overlaying tissues

Lateral root morphogenesis is dependent on the mechanical properties of the overlaying tissues

InfraPhenoGrid: A scientific workflow infrastructure for plant phenomics on the Grid

Theoretical approaches to understanding root vascular patterning: a consensus between recent models

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