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Improving genetic diagnosis in Mendelian disease with transcriptome sequencing

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dc.contributor.authorCummings, Beryl B.-
dc.contributor.authorMarshall, Jamie L.-
dc.contributor.authorTukiainen, Taru-
dc.contributor.authorLek, Monkol-
dc.contributor.authorDonkervoort, Sandra-
dc.contributor.authorFoley, A. Reghan-
dc.contributor.authorBolduc, Veronique-
dc.contributor.authorWaddell, Leigh B.-
dc.contributor.authorSandaradura, Sarah A.-
dc.contributor.authorO'Grady, Gina L.-
dc.contributor.authorEstrella, Elicia-
dc.contributor.authorReddy, Hemakumar M.-
dc.contributor.authorZhao, Fengmei-
dc.contributor.authorWeisburd, Ben-
dc.contributor.authorKarczewski, Konrad J.-
dc.contributor.authorO'Donnell-Luria, Anne H.-
dc.contributor.authorBirnbaum, Daniel-
dc.contributor.authorSarkozy, Anna-
dc.contributor.authorHu, Ying-
dc.contributor.authorGonorazky, Hernan-
dc.contributor.authorClaeys, Kristl-
dc.contributor.authorJoshi, Himanshu-
dc.contributor.authorBournazos, Adam-
dc.contributor.authorOates, Emily C.-
dc.contributor.authorGhaoui, Roula-
dc.contributor.authorDavis, Mark R.-
dc.contributor.authorLaing, Nigel G.-
dc.contributor.authorTopf, Ana-
dc.contributor.authorKang, Peter B.-
dc.contributor.authorBeggs, Alan H.-
dc.contributor.authorNorth, Kathryn N.-
dc.contributor.authorStraub, Volker-
dc.contributor.authorDowling, James J.-
dc.contributor.authorMuntoni, Francesco-
dc.contributor.authorClarke, Nigel F.-
dc.contributor.authorCooper, Sandra T.-
dc.contributor.authorBonnemann, Carsten G.-
dc.contributor.authorMacArthur, Daniel G.-
dc.contributor.authorGTEx Consortium-
dc.contributor.authorHan, Buhm-
dc.date.accessioned2023-04-25T07:33:05Z-
dc.date.available2023-04-25T07:33:05Z-
dc.date.created2023-04-21-
dc.date.created2023-04-21-
dc.date.issued2017-04-
dc.identifier.citationScience Translational Medicine, Vol.9 No.386, p. eaal5209-
dc.identifier.issn1946-6234-
dc.identifier.urihttps://hdl.handle.net/10371/191533-
dc.description.abstractExome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A 1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.-
dc.language영어-
dc.publisherAmerican Association for the Advancement of Science-
dc.titleImproving genetic diagnosis in Mendelian disease with transcriptome sequencing-
dc.typeArticle-
dc.identifier.doi10.1126/scitranslmed.aal5209-
dc.citation.journaltitleScience Translational Medicine-
dc.identifier.wosid000399454600005-
dc.identifier.scopusid2-s2.0-85018570855-
dc.citation.number386-
dc.citation.startpageeaal5209-
dc.citation.volume9-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorHan, Buhm-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusENHANCERS ESES-
dc.subject.keywordPlusRNA-SEQ-
dc.subject.keywordPlusMUTATIONS-
dc.subject.keywordPlusVARIANTS-
dc.subject.keywordPlusGUIDELINES-
dc.subject.keywordPlusTOOL-
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  • College of Medicine
  • Department of Medicine
Research Area Bioinformatics, Genomics, Statistical Genetics

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