September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Retinal transcriptome signatures associated with age-related macular degeneration
Author Affiliations & Notes
  • Rinki Ratnapriya
    Neurobiology Neurodegeneration & Repair Laboratory, National Eye Institute, Bethesda, Maryland, United States
  • Ashley Walton
    Neurobiology Neurodegeneration & Repair Laboratory, National Eye Institute, Bethesda, Maryland, United States
  • Margaret Starostik
    Neurobiology Neurodegeneration & Repair Laboratory, National Eye Institute, Bethesda, Maryland, United States
  • Sandra Rocio Montezuma
    Department of Ophthalmology & Visual Neurosciences, University of Minnesota, Minneapolis, Minnesota, United States
  • Deborah A Ferrington
    Department of Ophthalmology & Visual Neurosciences, University of Minnesota, Minneapolis, Minnesota, United States
  • Anand Swaroop
    Neurobiology Neurodegeneration & Repair Laboratory, National Eye Institute, Bethesda, Maryland, United States
  • Footnotes
    Commercial Relationships   Rinki Ratnapriya, None; Ashley Walton, None; Margaret Starostik, None; Sandra Montezuma, None; Deborah Ferrington, None; Anand Swaroop, None
  • Footnotes
    Support  NIH intramural research program
Investigative Ophthalmology & Visual Science September 2016, Vol.57, No Pagination Specified. doi:
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      Rinki Ratnapriya, Ashley Walton, Margaret Starostik, Sandra Rocio Montezuma, Deborah A Ferrington, Anand Swaroop; Retinal transcriptome signatures associated with age-related macular degeneration. Invest. Ophthalmol. Vis. Sci. 201657(12):.

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

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Abstract

Purpose : Genome-wide association analyses have identified 52 variants at 34 susceptibility loci for age-related macular degeneration (AMD). Yet, genes and mechanisms underlying disease biology remain poorly understood. We hypothesize that a comparative analysis of the retinal transcriptome between healthy and AMD donor eyes will facilitate identification of causative genes and pathways for AMD pathogenesis. Next generation sequencing method (RNAseq) allows comprehensive and quantitative transcriptome profiling with even small amounts of RNA. The goal of this study was to perform a large -scale transcriptome analysis of retina from 398 human donors (105 controls, 160 early AMD, 133 advanced AMD) to elucidate expression signatures associated with AMD and correlate these to genetic susceptibility.

Methods : We acquired inferior donor retinae samples, evaluated for the absence/presence and severity of AMD using the Minnesota Grading Systems using criteria and definitions from Age-Related Eye Disease Study (AREDS). RNA and DNA were extracted using TRIzol protocol (Thermo Fisher). Strand specific RNAseq libraries were prepared from 500 ng of total RNA using Total RNA with Ribo-Zero (Illumina, Inc.). The prepared libraries were clustered and then sequenced on HiSeq 2000 sequencer (Illumina, Inc.). Reads were aligned with TopHat2 to the Gencode (v23), and eXpress was used to assemble transcripts and estimate abundances. Genotypes of CFH and ARMS2 risk variants were obtained using TaqMan assays (Applied Biosystems).

Results : We generated 2.5 billion reads with an average of 50 million paired-end reads per sample. Initial analysis of 96 samples (34 controls, 11 early AMD, 51 advanced AMD) reveals the expression of almost 70% of the transcriptome in the retina (FPKM>1). Over 800 genes exhibit differential expression between healthy and AMD retina. We have also identified numerous novel coding and non-coding transcripts in our analysis. Impact of ARMS2 and CFH risk variants on the transcriptome is under investigation.

Conclusions : Our data represent the first large transcriptome analyses of human control and AMD retina. RNAseq profiling is permitting us to identify gene and pathways that may play critical role in AMD, providing novel insights into disease pathobiology.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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