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B. Chang, S. Madden, P. Doran, R. Kane, C. O'Brien; In Silico Gene Identification of Eye Specific Genes . Invest. Ophthalmol. Vis. Sci. 2003;44(13):409.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: The human eye has a large number of different cell types with highly specialised functions, which are unique in the human body. The functioning of highly specialised tissues, such as the retina, lens and cornea in health and disease is believed to be governed by cohorts of tissue specific genes. Digital Differential Display (DDD) is an Internet based resource for the identification of genes whose expression is altered between different tissue types (the eye and the rest of the body). This resource exploits the large number of publicly available cDNA libraries corresponding to different tissue, available as part of the UNIGENE facility at the National Centre for Biotechnology Information. Methods: In order to elucidate those genes whose expression is specific to the eye, EST libraries, corresponding to the eye were compared with the rest of the body using DDD. The results were analysed by Digital Extractor, a software developed in-house specifically for this purpose. Digital Extractor integrates and utilizes a number of tools including, (a) CAP3, for assembly of EST clusters, (b) RepeatMasker to mask repetitive elements and (c) BLAST, for gene identification. Results: Using this approach, we identified 74 cDNAs specifically expressed in ocular versus non-ocular tissue. These cDNAs encode 11 previously characterised genes (including crystallins, keratin 12 and MP19). The remaining transcripts identified were cDNA without homology to any known sequences. Digital Extractor enabled further characterisation and identification of these unknown genes. This transcriptome profiling experiment has identified a host of putative mediators of ocular integrity and function, and provide exciting new avenues for exploration in ocular disease research. Conclusion: In silico transcriptomics represents an efficient, user-friendly platform for the identification of tissue specific genes. Using publicly available sequence libraries and an integrated computational pipeline we have identified a cohort of eye specific genes. This will have implications in developing new gene therapies in visually blinding diseases.
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