Plant development is highly plastic, with major variations in form determined by the environment. An excellent example is shoot branching, where the body plan of the shoot system conferred by one genotype can range from a single unbranched stem, to a highly ramified bush, depending on the growth conditions. In recent years we have investigated the hormonal network that allows environmentally sensitive changes in shoot branching in Arabidopsis. Through the analysis of a set of monogenic mutants with clear effects on both the number of shoot branches produced and on its responsiveness to environmental inputs, we have developed a model for shoot branching control involving interactions between three systemically transported plant hormones. In collaboration with Prusinkiewicz (Calgary), we have built a computational implementation of this model, which captures the phenotypes of wild-type plants and, through the manipulation of single biologically plausible model parameters, our mutant phenotypes. While there is still much to learn about individual network components, the mechanistic framework we have established is sufficiently well developed to allow network-level investigation. We therefore propose an ambitious project to use natural allelic variation in shoot branching and its environmental sensitivity as in vivo differently parameterized versions of the shoot branching regulatory network, which can be compared with parameter space exploration in our computational model. By investigating the properties of shoot branching in diverse genotypes and in the computational model parameter space, we will identify trait correlations that will contribute to understanding the architecture of the regulatory network. This approach will simultaneously test the validity of our current model and provide new hypotheses for investigation. Furthermore, the rapidly moving genomics tools available in Arabidopsis will allow us to elucidate the genetic basis for key network properties.
Call for proposal
See other projects for this call