May 2008
Volume 49, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2008
Gene Patterning and Genomic Location Analysis of Late-Born Retinal Cells in the Developing Mouse Retina
Author Affiliations & Notes
  • W. Xiao
    University of Houston, Houston, Texas
  • A. Giddabasappa
    University of Houston, Houston, Texas
  • B. Xu
    University of Houston, Houston, Texas
  • S. Mukherjee
    University of Houston, Houston, Texas
  • M. Brook
    University of Michigan, Ann Arbor, Michigan
  • R. Khanna
    University of Michigan, Ann Arbor, Michigan
  • A. Swaroop
    NEI, Bethesda, Maryland
  • D. A. Fox
    University of Houston, Houston, Texas
  • Footnotes
    Commercial Relationships  W. Xiao, None; A. Giddabasappa, None; B. Xu, None; S. Mukherjee, None; M. Brook, None; R. Khanna, None; A. Swaroop, None; D.A. Fox, None.
  • Footnotes
    Support  NIH Grants ES012482, EY07751, and EY11115 and Sramek Foundation.
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 3089. doi:https://doi.org/
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      W. Xiao, A. Giddabasappa, B. Xu, S. Mukherjee, M. Brook, R. Khanna, A. Swaroop, D. A. Fox; Gene Patterning and Genomic Location Analysis of Late-Born Retinal Cells in the Developing Mouse Retina. Invest. Ophthalmol. Vis. Sci. 2008;49(13):3089. doi: https://doi.org/.

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

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Abstract

Purpose: : Previously we identified 4,899 differentially expressed genes from embryonic day (E) 16.5, E18.5, postnatal day (PN) 2, PN6 and PN10 C57BL/6 mouse retinas. Using K-means clustering analysis these genes were sorted and grouped into five distinct clusters based on their differential pattern and level of expression (ARVO 2007). Genes in clusters 2, 3 and 5 were upregulated and those in clusters 1 and 4 were downregulated. Our current goals were to compare our gene data set with that for FACS-sorted E16-PN10 Nrl-GFP rods in order to identify genes specific for late-born retinal cells (rods, bipolar cells and Müller glial cells) and the relative chromosomal positions of these genes.

Methods: : The Nrl-GFP rod gene array was downloaded from GEO and our stringent threshold and statistical procedures (R, dChip and ANOVA) were used to identify differentially expressed rod genes. These results were compared to our differentially expressed retinal genes. Gene positions were located with the UCSC Mouse Genome Browser.

Results: : We identified a subset of genes differentially expressed in retina and Nrl-GFP rods (rod pool: 1,118 genes) and others only in a non-rod pool (3,781 genes). Retinal clusters 1 to 5 had 39%, 18%, 29%, 7% and 7% of the 4,899 genes, respectively. Rod pool clusters 1 to 5 had 48%, 7%, 14%, 16% and 15% of the 1,118 genes, respectively. Non-rod pool clusters 1 to 5 had 37%, 21%, 34%, 4% and 4% of the 3,781 genes, respectively. Ten of 15 putative Müller glial cell genes were found in the non-rod pool. The genomic positions of 4,312 of the 4,899 differentially expressed genes were identified. Multiple differentially expressed genes with the same expression pattern were in close proximity to each other on their chromosome positions. CpG islands were identified in these genomic regions.

Conclusions: : Two independent gene pools contributed to late-born rods and non-rods (bipolar and Müller glial cells). For each pool, clusters with different and new retinal genes were identified. Genes in clusters 4 and 5 contributed more to rod than non-rod development, whereas genes in clusters 2 and 3 contributed more to non-rod than rod development. The identification of CpG islands near differentially expressed genes from the same pool and cluster should yield important new information about gene co-regulatory mechanisms during normal and abnormal retinal development.

Keywords: retinal development • photoreceptors • gene microarray 
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