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C. Bowes Rickman, J.N. Ebright, Z.J. Zavodni, L. Yu, T. Wang, S.P. Daiger, G. Wistow, K. Boon, M.A. Hauser; Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes Using EyeSage . Invest. Ophthalmol. Vis. Sci. 2006;47(13):5414.
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© ARVO (1962-2015); The Authors (2016-present)
To develop large–scale, high–throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies based on eye expression profiles using Serial Analysis of Gene Expression (SAGE).
Two human retina and 2 retinal pigment epithelium (RPE)/choroid SAGE libraries made from macula or mid–peripheral retina and adjacent RPE/choroid of morphologically normal 28–66 year–old donors and a human central retina longSAGE library made from 41–66 year–old donors were generated. Their transcription profiles were entered into a relational database, "EyeSAGE", including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina– and RPE–specific and –associated genes, and candidate genes for retina and RPE disease loci. Differential and or cell–type specific expression was validated using quantitative and single–cell RT–PCR.
Comparison of SAGE libraries synthesized from tissue from 2 separate regions of the same individuals (i.e. macular and peripheral retina) minimizes impact of individual donor variations on the resulting gene expression profiles. Cone photoreceptor–associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag–to–gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet–Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidate genes for retina diseases that have been mapped but the disease gene not yet isolated were identified.
The EyeSAGE database, combining three different gene profiling platforms including our multi–donor–derived retina/RPE SAGE libraries and existing single–donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. EyeSAGE can be used to identify retina–specific genes, including alternatively spliced transcripts, and to prioritize candidate genes within mapped retinal disease regions and is publicly web accessible through the National Eye Institute's (NEI), NEIBank.
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