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Dynamic network modelling to understanding flowering transition and floral patterning.

Research paper by J J Davila-Velderrain, J C JC Martinez-Garcia, E R ER Alvarez-Buylla

Indexed on: 31 Mar '16Published on: 31 Mar '16Published in: Journal of experimental botany



Abstract

Differentiation and morphogenetic processes during plant development are particularly robust. At the cellular level, however, plants also show great plasticity in response to environmental conditions, and can even reverse apparently terminal differentiated states with remarkable ease. Can we understand and predict both robust and plastic systemic responses as a general consequence of the non-trivial interplay between intracellular regulatory networks, extrinsic environmental signalling, and tissue-level mechanical constraints? Flower development has become an ideal model system to study these general questions of developmental biology, which are especially relevant to understanding stem cell patterning in plants, animals, and human disease. Decades of detailed study of molecular developmental genetics, as well as novel experimental techniques forin vivoassays in both wild-type and mutant plants, enable the postulation and testing of experimentally grounded mathematical and computational network dynamical models. Research in our group aims to explain the emergence of robust transitions that occur at the shoot apical meristem, as well as flower development, as the result of the collective action of key molecular components in regulatory networks subjected to intra-organismal signalling and extracellular constraints. Here we present a brief overview of recent work from our group, and that of others, focusing on the use of simple dynamical models to address cell-fate specification and cell-state stochastic dynamics during flowering transition and cell-state transitions at the shoot apical meristem ofArabidopsis thaliana.We also focus on how our work fits within the general field of plant developmental modelling, which is being developed by many others.