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A.C. Ziesel, S.L. Bernstein, P.W. Wong; Further Definition of the Human Foveo–Macular Transcriptome . Invest. Ophthalmol. Vis. Sci. 2005;46(13):3099.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: Whole tissue transcriptome characterization is an accessible method to rapidly establish a profile of gene expression activity for a single state (developmental time point and disease state). For a tissue such as human fovea, whose limited size and availability for study poses specific challenges to expression analysis, pooling of modestly–sized, independent studies provides a more comprehensive picture; additionally, comparative analysis of contributing smaller studies allows for certain inter–dataset comparisons. Methods: Two screens of different banks of ESTs using a human fovea cDNA probe identified ESTs bearing homology to fovea transcripts and by extension foveally expressed genes. A publicly–available foveo–macular expression data set was included in this analysis to expand the breadth of messages analyzed. These three data sets were subjected to in silico analysis using established molecular data resources, collecting genomic location, annotated function and disease data. Results: 10282 ESTs, 3963 ESTs, and 6474 ESTs were identified from the three data sets (Wong set, Bernstein set, and Soares set respectively). 6779 unique UniGene clusters were identified; overlap of genes associated with these identified ESTs is conspicuously minimal, suggesting that these three sets do not fully represent gene expression in the normal adult human fovea. A number of known macular expressed transcripts including visual cascade elements and known disease genes were identified in this screen, providing reassurance as to the validity of this approach. 49% of known retinal disease genes listed in the RetNet resource were re–identified in this analysis, further supporting the notions that this data collection is incomplete . Moreover, different datasets seem to display modest preference for relative abundance of expression and consequently for existing relevant molecular data. Conclusions: Modest, independent studies of gene expression can collectively generate a comprehensive view of a transcriptome. Analysis of multiple identification rates of specific genes between compared data sets can indicate completion of transcriptome characterization. Further accretion of fovea gene expression study data, regardless of methods employed, will continue to enrich the profile of normal foveal expression activity and the pool of candidate genes for inherited foveal degenerative conditions.
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