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


Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
03 Sep 2024
Historique:
received: 08 08 2024
revised: 22 08 2024
accepted: 23 08 2024
medline: 14 9 2024
pubmed: 14 9 2024
entrez: 14 9 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39273516
pii: ijms25179569
doi: 10.3390/ijms25179569
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Velux Stiftung
ID : 1371

Auteurs

Jordi Maggi (J)

Institute of Medical Molecular Genetics, University of Zurich, 8952 Schlieren, Switzerland.

Silke Feil (S)

Institute of Medical Molecular Genetics, University of Zurich, 8952 Schlieren, Switzerland.

Jiradet Gloggnitzer (J)

Institute of Medical Molecular Genetics, University of Zurich, 8952 Schlieren, Switzerland.

Kevin Maggi (K)

Institute of Medical Molecular Genetics, University of Zurich, 8952 Schlieren, Switzerland.

Ruxandra Bachmann-Gagescu (R)

Institute of Medical Genetics, University of Zurich, 8952 Schlieren, Switzerland.
Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland.
Neuroscience Center Zurich (ZNZ), University and ETH Zurich, 8057 Zurich, Switzerland.

Christina Gerth-Kahlert (C)

Department of Ophthalmology, University Hospital Zurich and University of Zurich, 8091 Zurich, Switzerland.

Samuel Koller (S)

Institute of Medical Molecular Genetics, University of Zurich, 8952 Schlieren, Switzerland.

Wolfgang Berger (W)

Institute of Medical Molecular Genetics, University of Zurich, 8952 Schlieren, Switzerland.
Neuroscience Center Zurich (ZNZ), University and ETH Zurich, 8057 Zurich, Switzerland.
Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich, 8057 Zurich, Switzerland.

Articles similaires

Genome, Chloroplast Phylogeny Genetic Markers Base Composition High-Throughput Nucleotide Sequencing

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C

Classifications MeSH