An understanding of retinal regulatory networks can help elucidate the molecular basis of retinal development and retinal diseases. Although gains in knowledge about retinal regulatory factors and elements have been made and several transcription factor (TF) mutations associated with retinal disease have been identified, overall understanding of retinal regulatory networks is still rather limited. Our long-term goal is to attain understanding of the structure and dynamics of retinal regulatory networks. To that end, we here propose a computational approach to predict protein-DNA and protein-protein interactions related to the retinal regulation by integrating current knowledge and a variety of data sets from high-throughput experiments. We also propose to verify the prediction experimentally. We are interested not only in the prediction of static interactions, but also in the condition-dependent transcriptional activity of interactions. To achieve our objective, we have four Specific Aims: (1) identification of retina-related cis-regulatory elements and their regulatory targets, (2) determination of interacting transcription factors that co-regulate retina-related genes, (3) characterization of the dynamics of the retinal regulatory networks, and (4) experimental verification of bioinformatics predictions. Beyond investigation of retinal disease, the computational programs developed in this proposal should also be generally useful for a broad community.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
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Biology and Diseases of the Posterior Eye Study Section (BDPE)
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Greenwell, Thomas
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Johns Hopkins University
Schools of Medicine
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