We plan to employ a combination of computational and experimental approaches to identify features of the cis-regulatory regions that underlie common patterns of gene expression observed during hippocampal development. Rather than grouping genes on the b asis of the overall similarity of expression profiles, we plan to first decompose the profiles into simpler modes, using the singular value decomposition (SVD), and then to look for the features associated with individual modes. We performed SVD of the p ublished expression data set from gene profiling of the hippocampal development in mouse (Mody et al., 2001, PNAS 98: 8862-7), which revealed that most of the differences in expression patterns can be represented by the first two modes, reflecting variat ion in the amplitude of expression, and the difference between up and down regulation in the course of development, respectively. In further work, we plan to identify features specifically associated with each of these two modes. The computational work will constitute of identification of putative regulatory regions, annotation of these regions with known transcription factor binding sites (motives), and then with putative higher order features built from these motives. Such features will be scored fo r their statistical association with loadings of a particular mode. For a small number of the top scoring features we will also perform in silico hypotheses tests (on another part of the data set). The role of the most promising features, in the regulati on of the genes that contain them (putative target genes), will be verified in the experimental part of the project, performed in the hippocampal neuronal culture. Previous work of the applicant demonstrated that this culture system is a good model for g ene regulation in the developing hippocampus (Dabrowski et al., 2003, J.Neurochem. 85:1279-88).
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