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Translating RNA splicing analysis into diagnosis and therapy

Translating RNA splicing analysis into diagnosis and therapy
Translating RNA splicing analysis into diagnosis and therapy
A large proportion of rare disease patients remain undiagnosed and the vast majority of such conditions remain untreatable whether diagnosed or not. RNA splicing analysis is able to increase the diagnostic rate in rare disease by identifying cryptic splicing mutations and can help in interpreting the pathogenicity of genomic variants. Whilst targeted RT-PCR analysis remains a highly sensitive tool for assessing the splicing effects of known variants, RNA-seq can provide a more comprehensive transcriptome-wide analysis of splicing. Appropriate care should be taken in RNA-seq experimental design since sample quality, processing, choice of library preparation and sequencing parameters all introduce variability. Many bioinformatic tools exist to aid both in the prediction of splicing effects from DNA sequence and in the handling of RNA-seq data for splicing analysis. Once identified, splicing abnormalities may be amenable to correction using antisense oligonucleotide compounds by masking cryptic splice sites or blocking key splice regulatory elements, or by use of alternative corrective technologies such as trans-splicing. A growing number of such drugs have started to enter clinical use, most notably nusinersen for the treatment of spinal muscular atrophy. By bringing together the fields of RNA diagnostics and antisense therapeutics, it is becoming feasible to envisage the development of a truly personalised medicine pipeline. This has already been shown to be possible in the case of milasen, an n=1 bespoke antisense drug, and the growth and convergence of these technologies means that similar therapeutic opportunities should arise in the near future.
Douglas, Andrew
2c789ec4-a222-43bc-a040-522ca64fea42
Baralle, Diana
faac16e5-7928-4801-9811-8b3a9ea4bb91
Douglas, Andrew
2c789ec4-a222-43bc-a040-522ca64fea42
Baralle, Diana
faac16e5-7928-4801-9811-8b3a9ea4bb91

Douglas, Andrew and Baralle, Diana (2021) Translating RNA splicing analysis into diagnosis and therapy. OBM Genetics, 5 (1). (doi:10.21926/obm.genet.2101125).

Record type: Review

Abstract

A large proportion of rare disease patients remain undiagnosed and the vast majority of such conditions remain untreatable whether diagnosed or not. RNA splicing analysis is able to increase the diagnostic rate in rare disease by identifying cryptic splicing mutations and can help in interpreting the pathogenicity of genomic variants. Whilst targeted RT-PCR analysis remains a highly sensitive tool for assessing the splicing effects of known variants, RNA-seq can provide a more comprehensive transcriptome-wide analysis of splicing. Appropriate care should be taken in RNA-seq experimental design since sample quality, processing, choice of library preparation and sequencing parameters all introduce variability. Many bioinformatic tools exist to aid both in the prediction of splicing effects from DNA sequence and in the handling of RNA-seq data for splicing analysis. Once identified, splicing abnormalities may be amenable to correction using antisense oligonucleotide compounds by masking cryptic splice sites or blocking key splice regulatory elements, or by use of alternative corrective technologies such as trans-splicing. A growing number of such drugs have started to enter clinical use, most notably nusinersen for the treatment of spinal muscular atrophy. By bringing together the fields of RNA diagnostics and antisense therapeutics, it is becoming feasible to envisage the development of a truly personalised medicine pipeline. This has already been shown to be possible in the case of milasen, an n=1 bespoke antisense drug, and the growth and convergence of these technologies means that similar therapeutic opportunities should arise in the near future.

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Revised_Translating_RNA_splicing_into_diagnosis_and_therapy - Accepted Manuscript
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More information

Accepted/In Press date: 26 February 2021
Published date: 8 March 2021
Additional Information: Published by LiDSEN publishing Inc.

Identifiers

Local EPrints ID: 447482
URI: http://eprints.soton.ac.uk/id/eprint/447482
PURE UUID: 521f4834-2b67-46ed-b685-c6211e762090
ORCID for Andrew Douglas: ORCID iD orcid.org/0000-0001-5154-6714
ORCID for Diana Baralle: ORCID iD orcid.org/0000-0003-3217-4833

Catalogue record

Date deposited: 12 Mar 2021 17:32
Last modified: 30 Oct 2021 01:43

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