June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Meta-analysis of human retinal transcriptome data: a powerful tool to gain insight into the genomic organization of inherited retinal disease genes
Author Affiliations & Notes
  • Karla Alejandra Ruiz Ceja
    Telethon Institute of Genetics and Medicine, Napoli, Campania, Italy
  • Dalila Capasso
    Telethon Institute of Genetics and Medicine, Napoli, Campania, Italy
    School for Advanced Studies (SSM), Genomics and Experimental Medicine program, Universita degli Studi di Napoli Federico II, Napoli, Campania, Italy
  • Diego di Bernardo
    Telethon Institute of Genetics and Medicine, Napoli, Campania, Italy
    Department of Chemical Engineering and Industrial Engineering, Universita degli Studi di Napoli Federico II, Napoli, Campania, Italy
  • Sandro Banfi
    Telethon Institute of Genetics and Medicine, Napoli, Campania, Italy
    Department of Precision Medicine, Universita degli Studi della Campania Luigi Vanvitelli, Napoli, Campania, Italy
  • Footnotes
    Commercial Relationships   Karla Alejandra Ruiz Ceja None; Dalila Capasso None; Diego di Bernardo None; Sandro Banfi None
  • Footnotes
    Support  European Union, ITN Grant StarT (No. 813490)
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 1171 – A0025. doi:
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      Karla Alejandra Ruiz Ceja, Dalila Capasso, Diego di Bernardo, Sandro Banfi; Meta-analysis of human retinal transcriptome data: a powerful tool to gain insight into the genomic organization of inherited retinal disease genes. Invest. Ophthalmol. Vis. Sci. 2022;63(7):1171 – A0025.

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

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Abstract

Purpose : To gain insight into the genomic organization and transcript composition of inherited retinal disease (IRDs) genes using publicly available RNA-Seq datasets obtained from the human retina.

Methods : We retrieved from publicly available expression databases 177 bulk RNA-Seq human retina data from non-visually impaired post-mortem donors (Pinelli et al., PMID:27235414 and Ratnapriya et al., PMID:30742112). After quality control analysis, we retained only 161 of them. We then re-analyzed the whole datasets using an ad-hoc designed pipeline. RNA-Seq alignments were assembled at a single sample level and merged to generate an Observed Transcriptome that allowed us to create a single set of assembled transcripts. Transcript expression levels were quantified by scaling TPM (Transcript Per Million) abundance estimates per sample (scaled TPM), and transcripts with less than one median TPM were filtered out. We selected a subset of newly identified candidate transcripts for independent validation by Reverse Transcriptase (RT-)PCR. cDNAs were obtained from RNA extracted from human retina and blood samples. Obtained RT-PCR products were sequenced to assess their identity.

Results : We focused our analysis on 219 IRD genes and identified a total of 3367 putative novel transcripts. The latter were the results of a) partial intron retentions, b) exon skipping and extension, and, in fewer cases, c) novel exon additions and d) connections with other transcriptional units. RT-PCR analysis carried out on a selected subset of putative novel transcripts revealed an overall 50% rate of experimental validation.

Conclusions : This is, to the best of our knowledge, the most comprehensive and extended meta-analysis of IRD genes carried out on RNA-Seq data. Our work provides a reliable expression quantification of IRD transcripts in the human retina, including the identification of novel ones, and paves the way towards a better understanding of the organization of their transcriptional units and, possibly, of the molecular mechanisms underlying inherited retinal diseases.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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