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Stephanie Halford, Richard Holt, Rachel Butler, Joel Beevers, Aarti Jagannath, Stuart Peirson, Susan Downes; Utilisation of Mouse Expression Data to Investigate the Molecular Genetic Basis of Human Retinal Disease. Invest. Ophthalmol. Vis. Sci. 2012;53(14):1616.
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Inherited retinal dystrophies affect approximately 1 in 2500 people, currently RetNet lists 204 retinal disease loci with the underlying gene identified in 161 of them. In the case of autosomal recessive retinitis pigmentosa (arRP) 39 susceptibility loci have been reported with the causal gene identified in 36 of these. However, this only accounts for ~40% of arRP cases diagnosed in clinics. Comparable situations exist for other forms of retinal dystrophy and hence there remains a considerable proportion of disease genes to be identified. Dysfunction or death of rod and cone photoreceptors is the primary cause of blindness in most retinal degenerative diseases. Therefore, a catalogue of the specific gene expression profiles of rods and cones will provide a comprehensive database of candidates for retinal degenerations and provide a mechanistic basis for understanding photoreceptor development, function and maintenance. It will also lead to an investigation of cellular pathways and events that are currently undefined.
We have utilized our unique access to a mouse model lacking rod and/or cone photoreceptors (rd/rd, cl/cl and rd/rd cl) coupled with our expertise in whole genome expression profiling to identify genes expressed in photoreceptors. By comparing RNA from the retinae of degenerate mice and congenic wildtype controls, using Affymetrix Exon Arrays, we have identified genes that are markedly down-regulated in mice lacking rod and/or cone photoreceptors.
We have established a database of genes that are expressed in rods and/or cones; and as well as identifying genes with a known role in the retina we have identified a subset of novel genes with no previously known retinal function. We are in the process of characterising these novel genes. We have also shown in the case of arRP that alteration of expression of known causal genes differs significantly from other genes within the same regions (P< 0.001). We are currently utilising these data to select high priority candidate genes in regions showing linkage to retinal dystrophy for mutation screening.
Using this entirely innovative strategy we have been able to identify novel and known genes expressed in photoreceptors, which now need further characterization. Understanding the role of photoreceptor-specific genes will enable us to determine if mutations in these genes give rise to retinal disease, improving patient screening and guiding future development of therapeutics for these conditions.
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