PURPOSE: To construct a custom cDNA microarray for comprehensive human retinal gene expression profiling and apply it to the identification of genes that are preferentially expressed in the retina. METHODS: A cDNA microarray was constructed based on the predicted human retina gene expression profile according to expressed sequence tag (EST) databases. Gene expression profiles were obtained from five human retinas, two livers, and the cerebral cortical regions of two brains. Each sample was studied in duplicate, using a reference sample experimental design. Retina-enriched genes were identified by using the significance analysis for microarray (SAM) algorithm. Quantitative real time PCR was used to confirm microarray results. Bioinformatic analysis was performed to compare the array results with expression data available from public databases. RESULTS: The cDNA microarray contains 10,034 sequences: 67% represent known genes and 33% represent ESTs. Differential hybridization with the array identified, in addition to known retinal genes, 186 retina-enriched genes that do not have known retinal function. Of these, 96 represent novel genes. Quantitative real-time PCR of 11 of the identified genes and ESTs confirmed their retina-enriched expression pattern. Bioinformatic analysis of EST databases suggests that of the 186 genes, approximately 40% are predominantly expressed in the retina, whereas the remainder show significant expression in other tissues. Comparison of this study's microarray-based retina-enriched gene set with three published similar sets identified using complementary high-throughput approaches demonstrated only limited overlap of the identified genes. CONCLUSIONS: Because previous studies have demonstrated that many retina-enriched genes are crucial for maintaining normal retinal function, the genes identified here are likely to include ones that have important roles in the retina and ones that when mutated can cause or modulate retinal disease. In addition, the retina custom array should provide a useful resource for comparing expression profiles between normal and diseased human retinas.
PURPOSE: To construct a custom cDNA microarray for comprehensive human retinal gene expression profiling and apply it to the identification of genes that are preferentially expressed in the retina. METHODS: A cDNA microarray was constructed based on the predicted human retina gene expression profile according to expressed sequence tag (EST) databases. Gene expression profiles were obtained from five human retinas, two livers, and the cerebral cortical regions of two brains. Each sample was studied in duplicate, using a reference sample experimental design. Retina-enriched genes were identified by using the significance analysis for microarray (SAM) algorithm. Quantitative real time PCR was used to confirm microarray results. Bioinformatic analysis was performed to compare the array results with expression data available from public databases. RESULTS: The cDNA microarray contains 10,034 sequences: 67% represent known genes and 33% represent ESTs. Differential hybridization with the array identified, in addition to known retinal genes, 186 retina-enriched genes that do not have known retinal function. Of these, 96 represent novel genes. Quantitative real-time PCR of 11 of the identified genes and ESTs confirmed their retina-enriched expression pattern. Bioinformatic analysis of EST databases suggests that of the 186 genes, approximately 40% are predominantly expressed in the retina, whereas the remainder show significant expression in other tissues. Comparison of this study's microarray-based retina-enriched gene set with three published similar sets identified using complementary high-throughput approaches demonstrated only limited overlap of the identified genes. CONCLUSIONS: Because previous studies have demonstrated that many retina-enriched genes are crucial for maintaining normal retinal function, the genes identified here are likely to include ones that have important roles in the retina and ones that when mutated can cause or modulate retinal disease. In addition, the retina custom array should provide a useful resource for comparing expression profiles between normal and diseased human retinas.
Authors: Sem Genini; Barbara Zangerl; Julianna Slavik; Gregory M Acland; William A Beltran; Gustavo D Aguirre Journal: Invest Ophthalmol Vis Sci Date: 2010-06-23 Impact factor: 4.799
Authors: Abrar A Rageh; Deborah A Ferrington; Heidi Roehrich; Ching Yuan; Marcia R Terluk; Elizabeth F Nelson; Sandra R Montezuma Journal: Curr Eye Res Date: 2015-10-02 Impact factor: 2.424
Authors: Darryl Y Nishimura; Lisa M Baye; Rahat Perveen; Charles C Searby; Almudena Avila-Fernandez; Ines Pereiro; Carmen Ayuso; Diana Valverde; Paul N Bishop; Forbes D C Manson; Jill Urquhart; Edwin M Stone; Diane C Slusarski; Graeme C M Black; Val C Sheffield Journal: Am J Hum Genet Date: 2010-04-15 Impact factor: 11.025