June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Characterization of a Novel Prolactin Transcript in Photoreceptors of Degenerating Retina
Author Affiliations & Notes
  • Raghavi Sudharsan
    School of Vet Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Leonardo Murgiano
    School of Vet Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Gustavo D Aguirre
    School of Vet Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • William A Beltran
    School of Vet Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Raghavi Sudharsan, None; Leonardo Murgiano, None; Gustavo Aguirre, None; William Beltran, None
  • Footnotes
    Support  NIH grants: EY06855, EY17549, the Foundation Fighting Blindness, University of Pennsylvania unrestricted funds to William A. Beltran, and Van Sloun Fund for Canine Genetic Research.
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 666. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Raghavi Sudharsan, Leonardo Murgiano, Gustavo D Aguirre, William A Beltran; Characterization of a Novel Prolactin Transcript in Photoreceptors of Degenerating Retina. Invest. Ophthalmol. Vis. Sci. 2020;61(7):666.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : Prolactin (PRL) was identified as one of the most highly upregulated mRNA in our retinal transcriptomic analysis comparing normal dogs to mutant rcd1 (PDE6B) and xlpra2 (RPGR) dogs at advanced stages of retinal degeneration. We now report the expression of PRL mRNA in normal and degenerating retinas.

Methods : Retinas from 3 female rcd1 and 3 xlpra2 dogs with ≥ 50% photoreceptor loss and from 3 normal dogs were used. Each of the retinal cell layers (outer nuclear layer with inner segments, ONL/IS; inner nuclear layer, INL; and ganglion cell layer, GCL) were individually isolated by laser capture microdissection (LCM), RNA was extracted and amplified by a linear RNA amplification protocol, and qPCR analysis performed to analyze PRL expression. Retinal PRL expression was further confirmed by RNA in situ hybridization (RNA-ISH, RNAscope, ACDBio) performed on OCT embedded normal and mutant retinal sections. Retinal PRL was amplified by PCR. 5’-RACE was performed on retinal cDNAs to identify the N-terminus sequence, and PRL expression examined in other tissues of a normal female dog by PCR. Western blot and mass spectrometric analyses (LC-MS/MS) were performed to identify the expression of PRL protein in retinal extracts.

Results : Expression of PRL mRNA in photoreceptors correlated with onset of cell death and increased steadily as retinal degeneration progressed. An alternate shorter PRL transcript (PRL2) was identified from the retinal RNA-seq data. The transcript for the PRL2 isoform initiates in intron 1 of the PRL gene and lacks the fifth exon, terminating in the fourth intronic region. Thus, the C-terminal sequence of PRL2 differs from full length PRL. Using PCR primers specific to PRL2, this isoform was shown to express in both normal and degenerating retinas as well as the anterior pituitary gland, mammary tissue and cerebellum. The full length PRL mRNA was expresssed only in the anterior pituitary gland. We did not detect the expression of PRL2 protein in the retinas by western blot and LC-MS/MS analysis.

Conclusions : Our results experimentally confirm the expression of the predicted PRL2 isoform in dog retina. PRL2 protein expression in the retinas is either absent or not detectable by the methods utilized. Additional experiments will address the possible function of PRL2 mRNA and its role in retinal degeneration.

This is a 2020 ARVO Annual Meeting abstract.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×