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SUsPECT: a pipeline for variant effect prediction based on custom long-read transcriptomes for improved clinical variant annotation.
Salz, Renee; Saraiva-Agostinho, Nuno; Vorsteveld, Emil; van der Made, Caspar I; Kersten, Simone; Stemerdink, Merel; Allen, Jamie; Volders, Pieter-Jan; Hunt, Sarah E; Hoischen, Alexander; 't Hoen, Peter A C.
Afiliação
  • Salz R; Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands.
  • Saraiva-Agostinho N; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
  • Vorsteveld E; Department of Human Genetics, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands.
  • van der Made CI; Department of Human Genetics, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands.
  • Kersten S; Department of Internal Medicine, Radboud Institute for Molecular Life Sciences, and Radboud Expertise Center for Immunodeficiency and Autoinflammation, Radboud University Medical Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands.
  • Stemerdink M; Department of Human Genetics, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands.
  • Allen J; Department of Otorhinolaryngology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, 6525 GA, The Netherlands.
  • Volders PJ; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
  • Hunt SE; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
  • Hoischen A; Laboratory of Molecular Diagnostics, Department of Clinical Biology, Jessa Hospital, Hasselt, 3500, Belgium.
  • 't Hoen PAC; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
BMC Genomics ; 24(1): 305, 2023 Jun 06.
Article em En | MEDLINE | ID: mdl-37280537
ABSTRACT
Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular if they affect transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are not predicted to be pathogenic using the reference transcript annotation. In further support of SUsPECT's utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Transcriptoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Transcriptoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda