September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
RNA-seq analysis of the developing chicken retina
Author Affiliations & Notes
  • Christophe J Langouet-Astrie
    Biology, James Madison University, HARRISONBURG, Virginia, United States
  • Annamarie Meinsen
    Biology, James Madison University, HARRISONBURG, Virginia, United States
  • Stephen Turner
    PBHS Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States
  • Ray Enke
    Biology, James Madison University, HARRISONBURG, Virginia, United States
    Center for Genome & Metagenome Studies, James Madison University, Harrisonburg, Virginia, United States
  • Footnotes
    Commercial Relationships   Christophe Langouet-Astrie, None; Annamarie Meinsen , None; Stephen Turner, None; Ray Enke, None
  • Footnotes
    Support  Commonwealth Health Research Board Grant #216-05-15, James Madison University 4-VA Grant
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 6568. doi:
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    • Get Citation

      Christophe J Langouet-Astrie, Annamarie Meinsen, Stephen Turner, Ray Enke; RNA-seq analysis of the developing chicken retina. Invest. Ophthalmol. Vis. Sci. 2016;57(12):6568.

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

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Abstract

Purpose : Developmental patterning of the vertebrate retina requires complex temporal orchestration of transcriptional activation and repression. Chicken embryos are a useful model for studying developmentally-regulated gene expression during retinogenesis. Here we used Illumina RNA-sequencing (RNA-seq) analysis to characterize the mRNA transcriptome of the developing chicken retina in an effort to identify genes critical for retinal development.

Methods : Animal experiments were carried out in accordance with the ARVO statement on the use of animals in ophthalmic and visual research. Whole retinas were harvested from chick embryonic day 8 (E8), and E18 embryos. Whole corneas were also collected from E18 embryos as a reference tissue. Duplicates were obtained for sample and total RNA was extracted using a Qiagen AllPrep Mini Kit. Illumina TrueSeq mRNA-seq libraries were prepared from total RNA and sequencing reads were generated using the Illumina NextSeq 500 sequencing platform. QC analysis and filtering were applied to raw sequences and the Spliced Transcripts Alignment to a Reference (STAR) aligner was used for ultrafast transcript assembly. Differential gene expression between samples was quantified at the gene level using the read summarization program featureCounts.

Results : Sequencing yielded between 26-72 million 125 bp paired end reads/run. Principal Component Analysis demonstrated tight clustering of sample duplicates. Distance Matrix Analysis indicated most significant gene expression variation between E8 retina v E18 retina and E18 retina v E18 cornea. 6905 genes were found to have significant (q-value<0.05 and fold change>1 or <-1) variation in expression between E8 and E18 retina. 7514 genes were found with significant variation in expression between E18 retina and E18 cornea. Candidate genes were selected for validation and further analysis based on gene ontology (GO).

Conclusions : RNA-seq coupled with GO analysis of candidate genes has shifted our focus to regulation of the Notch and phototransduction pathways during retinogenesis. Current studies are underway investigating transcriptional and epigenetic regulation of these pathways during retinal development.

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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