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The patterning of the Arabidopsis root epidermis depends on a genetic regulatory network that operates both within and between cells. Genetic studies have identified a number of key components of this network, but a clear picture of the functional logic of the network is lacking. Here, we integrate existing genetic and biochemical data in a mathematical model that allows us to explore both the sufficiency of known network interactions and the extent to which additional assumptions about the model can account for wild-type and mutant data. Our model shows that an existing hypothesis concerning the autoregulation of WEREWOLF does not account fully for the expression patterns of components of the network. We confirm the lack of WEREWOLF autoregulation experimentally in transgenic plants. Rather, our modelling suggests that patterning depends on the movement of the CAPRICE and GLABRA3 transcriptional regulators between epidermal cells. Our combined modelling and experimental studies show that WEREWOLF autoregulation does not contribute to the initial patterning of epidermal cell fates in the Arabidopsis seedling root. In contrast to a patterning mechanism relying on local activation, we propose a mechanism based on lateral inhibition with feedback. The active intercellular movements of proteins that are central to our model underlie a mechanism for pattern formation in planar groups of cells that is centred on the mutual support of two cell fates rather than on local activation and lateral inhibition.

Original publication

DOI

10.1371/journal.pbio.0060235

Type

Journal article

Journal

PLoS Biol

Publication Date

23/09/2008

Volume

6

Keywords

Arabidopsis, Arabidopsis Proteins, Basic Helix-Loop-Helix Transcription Factors, Cell Lineage, DNA-Binding Proteins, Gene Expression Regulation, Developmental, Gene Expression Regulation, Plant, Gene Regulatory Networks, Mathematics, Models, Biological, Morphogenesis, Plant Epidermis, Plant Roots, Plants, Genetically Modified, Proto-Oncogene Proteins c-myb, Recombinant Fusion Proteins, Transcription, Genetic