September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
RNA-Seq profiling of RNA splicing factor RP mouse models identify global changes in splicing
Author Affiliations & Notes
  • Michael H Farkas
    Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, United States
  • Elizabeth Au
    Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, United States
  • Maria Sousa
    Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, United States
  • Eric A Pierce
    Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Michael Farkas, None; Elizabeth Au, None; Maria Sousa, None; Eric Pierce, None
  • Footnotes
    Support  NEI Grant EY020902
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 4790. doi:
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    • Get Citation

      Michael H Farkas, Elizabeth Au, Maria Sousa, Eric A Pierce; RNA-Seq profiling of RNA splicing factor RP mouse models identify global changes in splicing
      . Invest. Ophthalmol. Vis. Sci. 2016;57(12):4790.

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

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Abstract

Purpose : The spliceosome, which is a ubiquitously expressed macromolecule, is required for producing mature mRNAs. Mutations in components of the spliceosome result in non-syndromic retinitis pigmentosa (RP). The mechanism behind RNA splicing factor-associated RP is currently unknown. Using RNA-Seq based transcriptome studies, we tested the hypothesis that aberrant splicing underlies the disease in Prpf3, 8, and 31 mouse models.

Methods : We collected brain, skeletal muscle, retinal pigment epithelium (RPE), and neural retina from 5 biological replicates each of Prpf3, 8, and 31 mutant mice and littermate wild type controls. Total RNA was isolated from each sample, and RNA-Seq libraries were prepared. Each sample was 101 bp paired-end sequenced with a minimum of 100 million reads. The data were aligned using the RNA-Seq Unified Mapper, and differential expression of transcripts, introns, exons, and splice junctions was determined. We then determined differentially expressed features with p-value < 0.05 and fold change > 1.5. Using a combination of the differential expression data and custom scripts, putative aberrant transcripts were identified.

Results : We first characterized the wild type transcriptome for each tissue to identify splicing events that are not contained in the current annotation databases. We observed considerable variability amongst the tissues where we identified as few as 4,500 novel splicing events in the muscle and RPE and as many as approximately 20,000 novel events in the retina and brain. We next determined differential expression of all features between the mutant models and their corresponding controls. We identified as few as 396 transcripts that were differentially expressed in muscle from Prpf31 mutant mice to as many as 8,387 in the RPE of Prpf3 mutant mice. Using these data, between 24 and 189 aberrant transcripts were identified in all of the tissues and models.

Conclusions : While splicing is a ubiquitous process, it is unknown how mutations in splicing factors cause non-syndromic RP. We have shown that splicing is affected in all of the tissues studied, suggesting aberrant splicing occurs globally. Since aberrant splicing occurs in all tissues studied, and we have previously identified the RPE as the site of disease onset, these data suggest that specific, rather than global, alterations in splicing affect the RPE.

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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