Modeling genetic/metabolic networks for speciation traits in Petunia

One M.Sc. studentship

The three species Petunia integrifolia, Petunia axillaris, and Petunia exserta are adapted for different pollinators. Traits such as flower morphology, nectar volume, scent production, and flower color are thought to influence pollinator preference and contribute to speciation. Each of these traits is the result of complex biochemical pathways, and it is not always clear how individual components of the genetic and metabolic network contribute to its steady-state, resulting in an observed phenotypic trait. Simulation models can help to understand these complexities and aid in the analysis of experiments that isolate specific portions of individual pathways. Since exact values of kinetic parameters for reactions, and concentration of biochemical substances are often unknown, networks must be specified in a qualitative fashion. One such approach is Boolean network modeling. With this formalism interactions are specified simply as inhibitions, or activations, genes are either "on" or "off", and biochemical substances have "low" or "high" concentration (hence the term Boolean network). Since kinetic parameters for the interactions are not required, this approach is especially useful when many genes are involved, or for systems that are not well characterized. However with flower color analysis or odor production "on" or "off" may not be sufficient. To address this type of problem, several extensions to the Boolean network model have been proposed. In this project we will use one such extension to model the genetic and metabolic network responsible for one or more speciation traits in Petunia. The modeling environment to be used creates a standardized dynamic system to represent the Boolean network [4]. It has the advantage in that the network is almost as simple to specify as a Boolean network, while also being able to capture dynamic behavior and continuous values for model output traits.

Methods
• Simulation modeling of genetic and metabolic networks (prior programming experience not required)
• Classical genetics, QTL mapping

Literature

1. Galliot, C., Stuurman, J., and Kuhlemeier, C. (2006) The genetic dissection of floral pollination syndromes. Current Opinion in Plant Biology. 9:78—82.
2. Grotewold, E. (2006) The Genetics and Biochemistry of Floral Pigments. Annul Review of Plant Biology. 57:761—80.
3. Boatright, J., Negre, F., Chen, X., Kish, C.M., Wood, B., Peel, G., Orlova, I., Gang, D., Rhodes, D., and Dudareva, N. (2004)  Understanding in Vivo Benzenoid Metabolism in Petunia Petal Tissue. Plant Physiology. 135: 1993—2011
4. Di Cara, A., Abhishek Garg, A., De Micheli, G., Xenarios. I., and Mendoza, L. (2007) Dynamic simulation of regulatory networks using SQUAD. BMC Bioinformatics. 8:462

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