Dopamine is an important neurotransmitter in CNS and contributes profoundly to a variety of motor and emotional behaviors. Dopaminergic dysfunction has been associated with several major neuropsychiatric disorders, ranging from drug addiction to schizophrenia to Parkinson's disease. Molecular studies of dopamine function have revealed a set of Dopamine-Regulated Genes (DRGs), which contribute critically to the unique neurochemical and behavioral properties of the striatum. The central hypothesis of this proposal is that these DRGs are co-regulated by a common but complex set of cis-elements and transcription factors. Our primary goal is to identify and validate the clusters of cis-elements for DRG expression (CEDRG) using integrated molecular and bioinformatics approaches.
Specific Aim 1 : We will employ a set of bioinformatics and molecular analysis tools to characterize as fully as possible the genomic organization of the DRGs, with particular effort to determine the TSSs of DRG. We will integrate all genomic information for DRGs into a Web-accessible database, DopamineDB, which will provide a unique resource for investigation of dopamine neurobiology.
Specific Aim 2 : Following phylogenetic analysis of human and mouse DRGs to reveal evolutionally conserved regions within their promoters, we will employ a range of statistical model-based algorithms (Clover [1]) and Glam [2]) to identify statistically over-represented cis-Elements for Dopamine-Regulated Gene expression (CEDRG). We will systematically evaluate the predicted known and novel cis-element binding activity by ChIP-chip analysis and gel shift assay, respectively, in the putative proximal DRG promoters.
Specific Aim 3 : We will determine functional interactions of CEDRGs by detecting statistically significant CEDRG clusters, and by assaying transcription activity of CEDRG clusters in a striatal cloned cell line (ST14A). Furthermore, we will employ a """"""""safe-haven"""""""" transgenic strategy to evaluate in vivo function of identified CEDRG in transgenic mice. Finally, we will examine DRG expression in mice deficient in transcription factors corresponding to the CEDRG to conclusively determine their involvement in DRG expression. The molecular and bioinformatics analyses are integrated throughout the project to overcome major limitations of each individual technique. The information derived from systematic analyses of DRGs will provide critical insights into dopamine functions and identify novel dopamine-regulated transcription factors and thus greatly facilitate the development of novel treatment strategies for dopamine-associated neuropsychiatric disorders such as drug addiction.
