September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Identification of the ARMS2 Biological Pathway using CRISPR and the identification of genes involved in AMD
Author Affiliations & Notes
  • Malela M. Werner
    Ophthalmology, University of Pensylvania, Philadelphia, Pennsylvania, United States
  • Mijin Kim
    Ophthalmology, University of Pensylvania, Philadelphia, Pennsylvania, United States
  • Mingyao Li
    Biostatistics, University of Pensylvania, Philadelphia, Pennsylvania, United States
  • Dwight Stambolian
    Ophthalmology, University of Pensylvania, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Malela M. Werner, None; Mijin Kim, None; Mingyao Li, None; Dwight Stambolian, None
  • Footnotes
    Support  NONE
Investigative Ophthalmology & Visual Science September 2016, Vol.57, No Pagination Specified. doi:
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      Malela M. Werner, Mijin Kim, Mingyao Li, Dwight Stambolian; Identification of the ARMS2 Biological Pathway using CRISPR and the identification of genes involved in AMD. 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 studies (GWAS) have shown a strong association between age-related macular degeneration (AMD) and gene variants in the chromosome region 10q26. Because of strong linkage disequilibrium (LD) in the region these variants have not discriminated between 2 nearby genes, ARMS2 and HTRA1. We hypothesize that mutating ARMS2 and studying its effect on global gene expression will provide a list of differential expression (DE) genes that influence AMD.

Methods : We identified a cell line, JEG3 that has high expression of ARMS2. CRISPR cas9 knockout of the ARMS2 gene was done on 3 separate JEG3 lines. cDNA libraries were made from each line and sequenced on an Illumina HiSeq. Analysis of the RNA-Seq data was performed using GSNAP for read alignment and Cufflinks for differential gene expression (DE). We calculated the expression levels of 23,569 RefSeq protein-coding genes using the Fragments Per Kilobase of gene per Million mapped fragment (FPKM) metric and considered a gene DE if the false discovery rate (FDR) p-value is <0.05.

Results : Sequencing depth for each sample was greater than 140 million paired-end reads. When comparing wild type and mutated ARMS2 cell lines, we found 60 DE genes. The most significantly down regulated genes in the mutated ARMS2 cell lines included HLTF (p = 0.0001, fold change = 213), TNFRSF10D (p < 0.00005, fold change = 47), HIST1H1D (p < 0.00005, fold change = 45). The most significantly upregulated genes included SEMA3C (p = 0.0002, fold change = 16), Septin3 (p < 0.00005, fold change = 11), EGR1 (p < 0.00005, fold change = 10), MXRA5 (p < 0.00005, fold change = 9). There was an overlap of 4 DE genes - DDIT4, DPP7, FN1 and GBP3- in our cell model with DE genes identified between normal and AMD postmortem eyes. These genes are activated under reactive oxidative stress conditions (DDIT4), promote cell adhesion and migration (FN1), are involved in cytokine signaling in immune system (GBP3), and play a role in promoting apoptosis as a serine protease (DPP7).

Conclusions : Our results support our hypothesis that utilizing DE analysis between normal and AMD eyes will assist in identifying causative genes. The knockout of the ARMS2 gene in JEG3 cells resulted in four DE genes that are in common with DE genes detected with RNA-Seq of normal and AMD eyes.

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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