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A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project
A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project
Background
Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data.

Methods
Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon–intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon–intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies.

Results
We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed.

Conclusions
Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases.
1756-994X
79
Blakes, Alexander J.M.
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Wai, Htoo
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Davies, Ian
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Moledina, Hassan E
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Ruiz, April
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Thomas, Tessy
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Bunyan, David
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Thomas, N Simon
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Burren, Christine P
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Greenhalgh, Lynn
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Lees, Melissa
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Pichini, Amanda
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Smithson, Sarah F.
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Tavares, Ana Lisa Taylor
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O'Donovan, Peter
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Douglas, Andrew
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Whiffin, Nicola
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Baralle, Diana
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Lord, Jenny
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Genomics England Research Consortium, Splicing and Disease Working Group
Blakes, Alexander J.M.
dfefed45-fab2-4980-8667-7e46ce0a14f5
Wai, Htoo
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Davies, Ian
c9c5c54a-1dd8-4eda-a080-f0574f79740e
Moledina, Hassan E
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Ruiz, April
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Thomas, Tessy
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Bunyan, David
d57bd2a7-d531-4892-bcce-e096dc95eee7
Thomas, N Simon
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Burren, Christine P
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Greenhalgh, Lynn
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Lees, Melissa
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Pichini, Amanda
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Smithson, Sarah F.
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Tavares, Ana Lisa Taylor
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O'Donovan, Peter
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Douglas, Andrew
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Whiffin, Nicola
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Baralle, Diana
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Lord, Jenny
e1909780-36cd-4705-b21e-4580038d4ec6

Whiffin, Nicola, Baralle, Diana and Lord, Jenny , Genomics England Research Consortium, Splicing and Disease Working Group (2022) A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project. Genome Medicine, 14 (1), 79, [79]. (doi:10.1186/s13073-022-01087-x).

Record type: Article

Abstract

Background
Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data.

Methods
Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon–intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon–intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies.

Results
We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed.

Conclusions
Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases.

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More information

Accepted/In Press date: 13 July 2022
Published date: 26 July 2022

Identifiers

Local EPrints ID: 468545
URI: http://eprints.soton.ac.uk/id/eprint/468545
ISSN: 1756-994X
PURE UUID: efacdf6f-45cf-404a-87e6-1498abe646b8
ORCID for Htoo Wai: ORCID iD orcid.org/0000-0002-3560-6980
ORCID for Andrew Douglas: ORCID iD orcid.org/0000-0001-5154-6714
ORCID for Diana Baralle: ORCID iD orcid.org/0000-0003-3217-4833
ORCID for Jenny Lord: ORCID iD orcid.org/0000-0002-0539-9343

Catalogue record

Date deposited: 17 Aug 2022 17:15
Last modified: 17 Mar 2024 03:54

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Contributors

Author: Alexander J.M. Blakes
Author: Htoo Wai ORCID iD
Author: Ian Davies
Author: Hassan E Moledina
Author: April Ruiz
Author: Tessy Thomas
Author: David Bunyan
Author: N Simon Thomas
Author: Christine P Burren
Author: Lynn Greenhalgh
Author: Melissa Lees
Author: Amanda Pichini
Author: Sarah F. Smithson
Author: Ana Lisa Taylor Tavares
Author: Peter O'Donovan
Author: Andrew Douglas ORCID iD
Author: Nicola Whiffin
Author: Diana Baralle ORCID iD
Author: Jenny Lord ORCID iD
Corporate Author: Genomics England Research Consortium, Splicing and Disease Working Group

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