June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Keratoconus transcriptome analysis by RNA-Seq of individual corneas identifies dysregulated cell survival and mesenchymal regulatory programs.
Author Affiliations & Notes
  • Shukti Chakravarti
    Medicine, Johns Hopkins Sch of Medicine, Baltimore, MD
  • Steven Salzberg
    Medicine, Johns Hopkins Sch of Medicine, Baltimore, MD
  • Stacey Gabriel
    Broad Institute, Boston, MA
  • Yassine Daoud
    Ophthalmology, Johns Hopkins Sch of Medicine, Baltimore, MD
  • James W Foster
    Medicine, Johns Hopkins Sch of Medicine, Baltimore, MD
  • Albert S Jun
    Ophthalmology, Johns Hopkins Sch of Medicine, Baltimore, MD
  • Walter J. Stark
    Ophthalmology, Johns Hopkins Sch of Medicine, Baltimore, MD
  • Footnotes
    Commercial Relationships Shukti Chakravarti, None; Steven Salzberg, None; Stacey Gabriel, None; Yassine Daoud, None; James Foster, None; Albert Jun, None; Walter Stark, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 1929. doi:
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      Shukti Chakravarti, Steven Salzberg, Stacey Gabriel, Yassine Daoud, James W Foster, Albert S Jun, Walter J. Stark, ; Keratoconus transcriptome analysis by RNA-Seq of individual corneas identifies dysregulated cell survival and mesenchymal regulatory programs.. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):1929.

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

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Abstract

Purpose: We investigated transcript abundance and variants by next generation sequencing-based RNA sequence (RNA-Seq) analyses of individual donor (DN) and keratoconus (KC) patient corneas for insights into disease pathogenesis.

Methods: Total RNA from 3 KC and 1 DN corneas with RIN scores > 8.0 (Agilent Bioanalyzer) were used to prepare cDNA libraries (TruSeq Stranded library kit). Strand-specific, RNA-Seq was performed on an Illumina HiSeq 2000 instrument to yield > 15 million paired end 100x100 bp reads for each sample. After assessments of read quality and retention of unique reads, mean levels and variances of expression for each gene were calculated for all samples. Quantification of each transcript was performed by Cufflinks and differential expression by Cuffdiff2 (Trapnell, 2013 Nat. Biotechnol 31:46).

Results: RNA-seq detected ~9000 full length transcripts. There were 4652 differentially expressed transcripts; of these 927 transcripts were increased by 2-9 fold and 1361 transcripts were decreased by -2 to -8 fold in KC over the control. Increases included novel apoptosis related transcripts (DAPL1, PERP), known KC candidates (CTSL2, lysosomal protease) and AKAP13 (central corneal thickness) and LYPD3 (also noted in a KC microarray analysis). Decreases included ECM and cytoskeletal transcripts (LUM, DCN, COL12A, VIM), keratocyte markers (KERA, CD34) and those relating to cell survival programs (Jun, IGFBPs).

Conclusions: The RNA-Seq findings suggest dysregulated mesenchymal keratocyte phenotype, cell survival and ECM loss in KC. In addition, it identified several altered gene regulations reported in our previous proteomic study (Chaerkady, 2013. J. Proteomics. 8 7: 1 2 2). We show that high quality RNA-Seq data can be obtained from individual cornea button halves. RNA-Seq from a larger set of DN and KC corneas is underway to identify significant pathways and candidate genes for keratoconus.

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