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J.C. Corbo, T. Hsiau, C.L. Cepko; The Architecture Of Mammalian Photoreceptor Transcriptional Networks . Invest. Ophthalmol. Vis. Sci. 2006;47(13):4185.
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© ARVO (1962-2015); The Authors (2016-present)
The photoreceptor cells of the retina are the nexus point of our visual system and as such are subject to a greater number of genetic diseases than any other single cell type in the human body. There are currently 163 mapped disease loci which cause blindness in humans. In order to create an integrated framework with which to understand this remarkable genetic heterogeneity we are developing a comprehensive model of the transcriptional networks that underlie the development, function, and diseases of photoreceptors.
We have undertaken a detailed microarray and in situ hybridization analysis of the transcriptional network controlled by the key photoreceptor transcription factors, Crx, Nrl, and Nr2e3. In addition, we have conducted an extensive computational analysis of the cis–regulatory elements controlling expression of the target genes discovered in these analyses.
We have developed a global model of the photoreceptor transcriptional network which presently contains hundreds of genes including several dozen mouse orthologs of human retinal disease genes. A detailed computational analysis of the target genes derived from our microarray studies has permitted us to formulate a model of the canonical photoreceptor cis–regulatory element. In addition, we have begun to elucidate the batteries of genes that are differentially expressed between the two principal photoreceptor cell types, rods and cones. We have found striking metabolic differences between rods and cones which may underlie their differential susceptibility to disease. Lastly, our analysis of the Nr2e3 (rd7) mutant retina has demonstrated the presence of a molecularly and ultrastructurally hybrid photoreceptor cell type which expresses both rod and cone genes.
This study lays the groundwork for a systematic understanding of gene expression control in mammalian photoreceptors. We are currently extending our network analysis by analyzing the retinal expression pattern of nearly 1,000 mouse transcription factors. In this way we hope to exhaustively identify the transcription factor nodes in this network. The connectivity of these new nodes will be determined by both experimental and computational approaches including quantitative analysis of their cis–regulatory elements in single photoreceptor cells. Our ultimate goal is to create a complete, quantitative model of photoreceptor transcriptional regulation which will serve as a template for translating between disease–causing mutations and the complex cellular phenotypes of photoreceptors that result in blindness.
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