Arabidopsis 2010: Regulatory Networks Controlling Root Growth and Differentiation

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PI: Philip N. BenfeyCo-PI: Uwe OhlerIOS-1021619Arabidopsis 2010: Regulatory Networks Controlling Root Growth and DifferentiationThe long-term scientific goal of this project is to determine the dynamics of the gene regulatory networks that control root growth and differentiation in Arabidopsis. The simplifying aspects of root growth and anatomy will be exploited to identify networks involved in development, which will then be perturbed with environmental stimuli. Current work on determining the mRNA expression profile in every cell type of the root and along the developmental axis will be greatly enhanced through the use of a new set of markers that are specific for both cell type and developmental stage and through use of next-generation sequencing to profile expression. In a second aim, the expression data will be combined and extended by chromatin immunoprecipitation followed by sequencing and by yeast one-hybrid analysis to infer regulatory networks controlling biological processes central to agriculture and bioenergy production. In the third aim the response at cellular resolution will be determined for abiotic stresses such as temperature and drought as well as biotic stresses such as bacteria. To obtain parameters for the modeling of the dynamics of network responses to environmental stimuli, the RootArray platform will be used. This technology allows the simultaneous in vivo observation of expression responses of more than 60 seedlings. The fourth aim will be to identify how the tissue-specific response to an abiotic stress changes among natural isolates of Arabidopsis. All of these efforts will be informed by and analyzed in concert with a theory and modeling team, which will lead the effort on network identification, modeling dynamical responses and image analysis. This project also has several broader impacts. To achieve continued improvement in plant traits for food security and bioenergy production will require a sophisticated understanding of the networks that control plant growth and differentiation. This research will generate high-resolution datasets from which regulatory networks controlling biological processes central to real-world agricultural and bioenergy productivity can be identified and characterized. Another important part of the project will be to train the next generation of plant scientists in systems biology, which integrates quantitative and experimental approaches. The experience of all trainees will be enhanced by cross-training opportunities between computational and experimental biology within the Duke Center for Systems Biology as well as participation in outreach efforts such as helping to teach a course on Complex Genetic Traits at North Carolina Central University, a historically black university in Durham, NC and participating in summer undergraduate research programs for students from groups underrepresented in science.