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dc.contributor.authorGardner, Eugene
dc.contributor.authorSifrim, Alejandro
dc.contributor.authorLindsay, Sarah J
dc.contributor.authorPrigmore, Elena
dc.contributor.authorRajan, Diana
dc.contributor.authorDanecek, Petr
dc.contributor.authorGallone, Giuseppe
dc.contributor.authorEberhardt, Ruth Y
dc.contributor.authorMartin, Hilary C
dc.contributor.authorWright, Caroline F
dc.contributor.authorFitzPatrick, David R
dc.contributor.authorFirth, Helen V
dc.contributor.authorHurles, Matthew E
dc.date.accessioned2021-12-11T00:30:50Z
dc.date.available2021-12-11T00:30:50Z
dc.date.issued2021-11-04
dc.identifier.issn0002-9297
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/331338
dc.description.abstractStructural variation (SV) describes a broad class of genetic variation greater than 50 bp in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DDs). Individuals presenting with DDs are often referred for diagnostic testing with chromosomal microarrays (CMAs) to identify large copy-number variants (CNVs) and/or with single-gene, gene-panel, or exome sequencing (ES) to identify single-nucleotide variants, small insertions/deletions, and CNVs. However, individuals with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the tool InDelible, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DDs recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 63 rare, damaging variants in genes previously associated with DDs missed by standard SNV, indel, or CNV discovery approaches. Clinical review of these 63 variants determined that about half (30/63) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21 and 500 bp in size and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.9%. Of particular interest were seven confirmed de novo variants in MECP2, which represent 35.0% of all de novo protein-truncating variants in MECP2 among DDD study participants. InDelible provides a framework for the discovery of pathogenic SVs that are most likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.
dc.format.mediumPrint-Electronic
dc.publisherElsevier BV
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectbioinformatics
dc.subjectdevelopmental disorders
dc.subjectdiagnostics
dc.subjectinsertions/deletions
dc.subjectstructural variation
dc.subjectChild
dc.subjectDevelopmental Disabilities
dc.subjectFemale
dc.subjectHumans
dc.subjectMale
dc.subjectMethyl-CpG-Binding Protein 2
dc.subjectWhole Exome Sequencing
dc.titleDetecting cryptic clinically relevant structural variation in exome-sequencing data increases diagnostic yield for developmental disorders.
dc.typeArticle
dc.publisher.departmentMrc Epidemiology Unit
dc.date.updated2021-12-09T14:57:16Z
prism.endingPage2194
prism.issueIdentifier11
prism.publicationDate2021
prism.publicationNameAm J Hum Genet
prism.startingPage2186
prism.volume108
dc.identifier.doi10.17863/CAM.78786
dcterms.dateAccepted2021-09-15
rioxxterms.versionofrecord10.1016/j.ajhg.2021.09.010
rioxxterms.versionVoR
dc.contributor.orcidGardner, Eugene [0000-0001-9671-1533]
dc.identifier.eissn1537-6605
rioxxterms.typeJournal Article/Review
cam.depositDate2021-12-09
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International