Nanopore Deep Sequencing as a Tool to Characterize and Quantify Aberrant Splicing Caused by Variants in Inherited Retinal Dystrophy Genes

The contribution of splicing variants to molecular diagnostics of inherited diseases is reported to be less than 10%. This figure is likely an underestimation due to several factors including difficulty in predicting the effect of such variants, the need for functional assays, and the inability to detect them (depending on their locations and the sequencing technology used). The aim of this study was to assess the utility of Nanopore sequencing in characterizing and quantifying aberrant splicing events. For this purpose, we selected 19 candidate splicing variants that were identified in patients affected by inherited retinal dystrophies. Several in silico tools were deployed to predict the nature and estimate the magnitude of variant-induced aberrant splicing events. Minigene assay or whole blood-derived cDNA was used to functionally characterize the variants. PCR amplification of minigene-specific cDNA or the target gene in blood cDNA, combined with Nanopore sequencing, was used to identify the resulting transcripts. Thirteen out of nineteen variants caused aberrant splicing events, including cryptic splice site activation, exon skipping, pseudoexon inclusion, or a combination of these. Nanopore sequencing allowed for the identification of full-length transcripts and their precise quantification, which were often in accord with in silico predictions. The method detected reliably low-abundant transcripts, which would not be detected by conventional strategies, such as RT-PCR followed by Sanger sequencing.

Publication Details

Journal
Repository for Publications and Research Data (ETH Zurich)
Published
2024-09-01
DOI
https://doi.org/10.3929/ethz-b-000694817
Primary Topic
Outsourcing and Supply Chain Management
Type
article
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article

Nanopore Deep Sequencing as a Tool to Characterize and Quantify Aberrant Splicing Caused by Variants in Inherited Retinal Dystrophy Genes

Repository for Publications and Research Data (ETH Zurich)
Outsourcing and Supply Chain Management
article

Nanopore Deep Sequencing as a Tool to Characterize and Quantify Aberrant Splicing Caused by Variants in Inherited Retinal Dystrophy Genes

article en

Abstract

The contribution of splicing variants to molecular diagnostics of inherited diseases is reported to be less than 10%. This figure is likely an underestimation due to several factors including difficulty in predicting the effect of such variants, the need for functional assays, and the inability to detect them (depending on their locations and the sequencing technology used). The aim of this study was to assess the utility of Nanopore sequencing in characterizing and quantifying aberrant splicing events. For this purpose, we selected 19 candidate splicing variants that were identified in patients affected by inherited retinal dystrophies. Several in silico tools were deployed to predict the nature and estimate the magnitude of variant-induced aberrant splicing events. Minigene assay or whole blood-derived cDNA was used to functionally characterize the variants. PCR amplification of minigene-specific cDNA or the target gene in blood cDNA, combined with Nanopore sequencing, was used to identify the resulting transcripts. Thirteen out of nineteen variants caused aberrant splicing events, including cryptic splice site activation, exon skipping, pseudoexon inclusion, or a combination of these. Nanopore sequencing allowed for the identification of full-length transcripts and their precise quantification, which were often in accord with in silico predictions. The method detected reliably low-abundant transcripts, which would not be detected by conventional strategies, such as RT-PCR followed by Sanger sequencing.

Repository for Publications and Research Data (ETH Zurich)
Openalex Percentile: Top 40%
Outsourcing and Supply Chain Management
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Nanopore Deep Sequencing as a Tool to Characterize and Quantify Aberrant Splicing Caused by Variants in Inherited Retinal Dystrophy Genes · Repository for Publications and Research Data (ETH Zurich) (2024) | TGRS Research Map | TGRS