The overall goal of this proposal is to use a bioinformatics approach to help decipher the transcriptional regulatory networks associated with retinal gene expression. To this end, we will develop two algorithms: one for discovering cis-regulatory motifs and another for predicting transcription factor targets.
Specific Aim 1 is to find novel regulatory motifs associated with retinal expression. For this aim, we will develop a new algorithm for motif discovery, one that takes into account motif complexity and motif location relative to the transcription start site. By applying this program to the upstream sequences of genes that are preferentially expressed in the retina, we expect to detect novel retina-related motifs.
Specific Aim 2 is to identify the regulatory targets of retinal transcription factors. We propose to develop a regulatory target-prediction program that will search the binding sites of multiple transcription factors and that requires the specific relative location of these binding sites. With this program we hope to increase the specificity of the prediction. We will apply the program to retina-related transcription factors and the motifs detected in Aim 1.
Specific Aim 3 is to integrate microarray data with the regulatory networks. We will explore the relationship between gene expression and the regulatory network, and we will integrate microarray data into the program for prediction of transcription factor targets. Results obtained from this proposed study should be useful for guiding wet-lab experiments, and the increased knowledge about the retinal regulatory network will likely have implications for better understanding of retinal development, function, and disease.
