May 2005
Volume 46, Issue 13
ARVO Annual Meeting Abstract  |   May 2005
Profiling Rnr KO and rd7 Mice to Identify Direct Targets of RNR (Nr2e3)
Author Affiliations & Notes
  • A.L. Webber
    Merck Research Laboratories, West Point, PA
  • P. Hodor
    Molecular Profiling,
    Merck Research Laboratories, West Point, PA
  • T. Zhang
    Target Validation, Merck Research Laboratories, Boston, MA
  • D. Holder
    Biometrics Research,
    Merck Research Laboratories, West Point, PA
  • K. Petrukhin
    Merck Research Laboratories, West Point, PA
  • Footnotes
    Commercial Relationships  A.L. Webber, Merck E; P. Hodor, Merck E; T. Zhang, Merck E; D. Holder, Merck E; K. Petrukhin, Merck E.
  • Footnotes
    Support  None.
Investigative Ophthalmology & Visual Science May 2005, Vol.46, 3068. doi:
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      A.L. Webber, P. Hodor, T. Zhang, D. Holder, K. Petrukhin; Profiling Rnr KO and rd7 Mice to Identify Direct Targets of RNR (Nr2e3) . Invest. Ophthalmol. Vis. Sci. 2005;46(13):3068.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract: : Purpose: RNR (Retina–specific Nuclear Receptor, Nr2e3) represents an orphan nuclear receptor expressed exclusively in photoreceptor cells. The specificity of RNR expression in photoreceptor cells and the analysis of retinal degeneration found in both Rnr KO mice and in human patients with mutations in the RNR gene provide evidence to support RNR as a therapeutic target for retinal degeneration. We have used expression profiling of retinas from Rnr KO and rd7 mice in order to identify direct target genes of RNR. Methods: RNA was isolated from retinas of postnatal day (p)6, p10, p14, p30, and p180 RNR KO, rd7, and wild–type C57BL/6 mice. Following amplification and labeling, samples were hybridized to 60–mer oligonucleotide microarrays (Agilent). Results: We have used molecular profiling of Rnr KO and rd7 retinas from p6, p10, p14, p30, and p180 to identify 422 putative RNR–dependent genes. Ingenuity Pathways Analysis indicates that the putative RNR target genes are involved in canonical pathways and/or functional categories such as lipid metabolism, fatty acid metabolism, cell–to–cell signaling, molecular transport, small molecule biochemistry, cell death, immunological disease, and inflammatory disease. In order to identify direct targets of RNR, the promoters of differentially expressed genes were analyzed with respect to known nuclear receptor binding sites and hexamer configurations. The promoters of a subset of genes are enriched for the hexamer pairs DR1, DR4, ER3, and IR3. Conclusions: Using microarray technology, we have identified 422 putative RNR–dependent genes. Results from the transcription factor binding site analysis will be used to prioritize genes for future gel shift and chromatin immunoprecipitation (ChIP) experiments in order to show direct interaction with RNR. Downstream target genes regulated by RNR will be useful for mechanism of action, refinement of structure–activity relationship (SAR), efficacy studies, and identification of potential new targets in the pathway.

Keywords: photoreceptors • gene microarray • transgenics/knock-outs 

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