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In Silico Biology 10, 0008 (2010); ©2009, Bioinformation Systems e.V.  

Modelling the molecular interactions in the flower developmental network of Arabidopsis thaliana

Kerstin Kaufmann1, Masao Nagasaki2 and Ruy Jáuregui3*

1 Business Unit Bioscience, Plant Research International, Wageningen, The Netherlands
2 Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan
3 BIOBASE GmbH, Wolfenbüttel, Germany

* Corresponding author

Edited by E. Wingender; received September 24, 2009; revised December 08, 2009; accepted December 20, 2009; published January 02, 2010


We present a dynamical model of the gene network controlling flower development in Arabidopsis thaliana. The network is centered at the regulation of the floral organ identity genes (AP1, AP2, AP3, PI and AG) and ends with the transcription factor complexes responsible for differentiation of floral organs. We built and simulated the regulatory interactions that determine organ specificity using an extension of hybrid Petri nets as implemented in Cell Illustrator. The network topology is characterized by two main features: (1) the presence of multiple autoregulatory feedback loops requiring the formation of protein complexes, and (2) the role of spatial regulators determining floral patterning. The resulting network shows biologically coherent expression patterns for the involved genes, and simulated mutants produce experimentally validated changes in organ expression patterns. The requirement of heteromeric higher-order protein complex formation for positive autoregulatory feedback loops attenuates stochastic fluctuations in gene expression, enabling robust organ-specific gene expression patterns. If autoregulation is mediated by monomers or homodimers of proteins, small variations in initial protein levels can lead to biased production of homeotic proteins, ultimately resulting in homeosis. We also suggest regulatory feedback loops involving miRNA loci by which homeotic genes control the activity of their spatial regulators.

Keywords: dynamical model, flower development, gene network