PURPOSE: To develop gene expression profiles of human sclera to allow for the identification of novel, uncharacterized genes in this tissue-type, and to identify candidate genes for scleral disorders. METHODS: Total RNA was isolated from 6 donor sources of human sclerae, and reverse transcribed into cDNA using a T7-(dT) 24 primer. The resulting cDNA was in vitro transcribed to produce biotin-labeled cRNA, fragmented, and mixed with hybridization controls before a 16 h hybridization step with oligonucleotide probes on 6 Affymetrix U95A chips. The chips were scanned twice at 570 nM and the data collected using GeneChip software. Array analyses were carried out with Microarray Suite, version 5.0 (Affymetrix), using the expression analysis algorithm to run an absolute analysis after cell intensities were computed. All arrays were scaled to the same target intensity using all probe sets. Reverse-transcription polymerase chain reaction (RT-PCR) was performed to validate the microarray results. RESULTS: There were 3,751 genes with "present" calls assigned independently to all six human scleral samples. These genes could be clustered into 4 major categories; transcription (10%), metabolism (8.8%), cell growth and proliferation (5.4%), and extracellular matrix (2%). Many extracellular matrix proteins, such as collagens 6A3 and 10A1, thrombospondins 2 and 4, and dystroglycan have not previously been shown to be expressed in sclera. RT-PCR results confirmed scleral expression in 7 extracellular matrix genes examined. CONCLUSIONS: This study demonstrated the utility of gene microarray technology in identifying global patterns of scleral gene expression, and provides an extended list of genes expressed in human sclera. Identification of genes expressed in sclera contributes to our understanding of scleral biology, and potentially provides positional candidate genes for scleral disorders such as high myopia.
PURPOSE: To develop gene expression profiles of human sclera to allow for the identification of novel, uncharacterized genes in this tissue-type, and to identify candidate genes for scleral disorders. METHODS: Total RNA was isolated from 6 donor sources of human sclerae, and reverse transcribed into cDNA using a T7-(dT) 24 primer. The resulting cDNA was in vitro transcribed to produce biotin-labeled cRNA, fragmented, and mixed with hybridization controls before a 16 h hybridization step with oligonucleotide probes on 6 Affymetrix U95A chips. The chips were scanned twice at 570 nM and the data collected using GeneChip software. Array analyses were carried out with Microarray Suite, version 5.0 (Affymetrix), using the expression analysis algorithm to run an absolute analysis after cell intensities were computed. All arrays were scaled to the same target intensity using all probe sets. Reverse-transcription polymerase chain reaction (RT-PCR) was performed to validate the microarray results. RESULTS: There were 3,751 genes with "present" calls assigned independently to all six human scleral samples. These genes could be clustered into 4 major categories; transcription (10%), metabolism (8.8%), cell growth and proliferation (5.4%), and extracellular matrix (2%). Many extracellular matrix proteins, such as collagens 6A3 and 10A1, thrombospondins 2 and 4, and dystroglycan have not previously been shown to be expressed in sclera. RT-PCR results confirmed scleral expression in 7 extracellular matrix genes examined. CONCLUSIONS: This study demonstrated the utility of gene microarray technology in identifying global patterns of scleral gene expression, and provides an extended list of genes expressed in human sclera. Identification of genes expressed in sclera contributes to our understanding of scleral biology, and potentially provides positional candidate genes for scleral disorders such as high myopia.
Authors: David Troilo; Earl L Smith; Debora L Nickla; Regan Ashby; Andrei V Tkatchenko; Lisa A Ostrin; Timothy J Gawne; Machelle T Pardue; Jody A Summers; Chea-Su Kee; Falk Schroedl; Siegfried Wahl; Lyndon Jones Journal: Invest Ophthalmol Vis Sci Date: 2019-02-28 Impact factor: 4.799
Authors: Ravikanth Metlapally; Yi-Ju Li; Khanh-Nhat Tran-Viet; Diana Abbott; Gregory R Czaja; Francois Malecaze; Patrick Calvas; David Mackey; Thomas Rosenberg; Sandrine Paget; Tetyana Zayats; Michael J Owen; Jeremy A Guggenheim; Terri L Young Journal: Invest Ophthalmol Vis Sci Date: 2009-04-22 Impact factor: 4.799