CREATIV Dynamic Regulatory Modeling of the Iron Deficiency Response in Arabidopsis thaliana
Joel J. Ducoste
Project runs from 08/15/2012 to 07/31/2019
In this proposal, we present a novel paradigm for identifying putative cis-regulatory promoter targets that control the regulation of stress responses in plants. This paradigm will also be used to identify critical regulatory components that differentiate the regulatory stress response across different cell types. We first develop the computational and analytical infrastructure needed to build a dynamic model of the gene regulatory network from time-course transcription profile data that quantifies the stress response. Novel analytical model refinement techniques are proposed to reduce the space of feasible solutions, generate specifications for model validation experiments, and test functional redundancy in the response. Parallel computing architectures will be used to scale the implementation of these model refinement approaches to the size and complexity associated with gene regulatory networks. The dynamic model of the gene regulatory network will be used to identify relationships between genes, build corresponding functional modules, and identify putative cis-regulatory promoter targets and regulatory components that can be used to alter responses to biotic and abiotic stresses in plants. Previous cell-specific transcription profiling has indicated that cell types have distinct expression profiles and respond differently to stress. We will generate cell-specific time-course transcription profiles using experiment specifications derived from the dynamic gene regulatory network. These data will be used to create a cell-specific dynamic gene regulatory network for identifying regulators that are key in differentiating the stress response between cell types.