Gene regulatory network models for plant development.

Abstract

Accumulated genetic data are stimulating the use of mathematical and computational tools for studying the concerted action of genes during cell differentiation and morphogenetic processes. At the same time, network theory has flourished, enabling analyses of complex systems that have multiple elements and interactions. Reverse engineering methods that use genomic data or detailed experiments on gene interactions have been used to propose gene network architectures. Experiments on gene interactions incorporate enough detail for relatively small developmental modules and thus allow dynamical analyses that have direct functional interpretations. Generalities are beginning to emerge. For example, biological genetic networks are robust to environmental and genetic perturbations. Such dynamical studies also enable novel predictions that can lead to further experimental tests, which might then feedback to the theoretical analyses. This interplay is proving productive for understanding plant development. Finally, both experiments on gene interactions and theoretical analyses allow the identification of frequent or fixed evolutionary solutions to developmental problems, and thus are contributing to an understanding of the genetic basis of the evolution of development and body plan.