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Improving the diagnostic yield of exome- sequencing by predicting gene-phenotype associations using large-scale gene expression analysis

Deelen, Patrick ; van Dam, Sipko ; Herkert, Johanna C ; Karjalainen, Juha M ; Brugge, Harm ; Abbott, Kristin M ; van Diemen, Cleo C ; van der Zwaag, Paul A ; Gerkes, Erica H ; Zonneveld-Huijssoon, Evelien ; Boer-Bergsma, Jelkje J ; Folkertsma, Pytrik ; Gillett, Tessa ; van der Velde, K Joeri ; Kanninga, Roan ; van den Akker, Peter C ; Jan, Sabrina Z ; Hoorntje, Edgar T ; Te Rijdt, Wouter P ; Vos, Yvonne J ; Jongbloed, Jan D H ; van Ravenswaaij-Arts, Conny M A ; Sinke, Richard ; Sikkema-Raddatz, Birgit ; Kerstjens-Frederikse, Wilhelmina S ; Swertz, Morris A ; Franke, Lude

Nature communications, 2019-06, Vol.10 (1), p.2837-13, Article 2837 [Periódico revisado por pares]

England: Nature Publishing Group

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Título:
Improving the diagnostic yield of exome- sequencing by predicting gene-phenotype associations using large-scale gene expression analysis
Autor: Deelen, Patrick ; van Dam, Sipko ; Herkert, Johanna C ; Karjalainen, Juha M ; Brugge, Harm ; Abbott, Kristin M ; van Diemen, Cleo C ; van der Zwaag, Paul A ; Gerkes, Erica H ; Zonneveld-Huijssoon, Evelien ; Boer-Bergsma, Jelkje J ; Folkertsma, Pytrik ; Gillett, Tessa ; van der Velde, K Joeri ; Kanninga, Roan ; van den Akker, Peter C ; Jan, Sabrina Z ; Hoorntje, Edgar T ; Te Rijdt, Wouter P ; Vos, Yvonne J ; Jongbloed, Jan D H ; van Ravenswaaij-Arts, Conny M A ; Sinke, Richard ; Sikkema-Raddatz, Birgit ; Kerstjens-Frederikse, Wilhelmina S ; Swertz, Morris A ; Franke, Lude
Assuntos: Databases, Nucleic Acid ; Diagnostic systems ; Gene expression ; Gene Expression Regulation - physiology ; Gene sequencing ; Genes ; Genetic Predisposition to Disease ; Genetic screening ; Genomes ; Humans ; Models, Genetic ; Optimization ; Phenotypes ; Principal Component Analysis ; Ribonucleic acid ; RNA ; Sequence Analysis, RNA - methods ; Software ; Transcriptome ; User-Computer Interface
É parte de: Nature communications, 2019-06, Vol.10 (1), p.2837-13, Article 2837
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Descrição: The diagnostic yield of exome and genome sequencing remains low (8-70%), due to incomplete knowledge on the genes that cause disease. To improve this, we use RNA-seq data from 31,499 samples to predict which genes cause specific disease phenotypes, and develop GeneNetwork Assisted Diagnostic Optimization (GADO). We show that this unbiased method, which does not rely upon specific knowledge on individual genes, is effective in both identifying previously unknown disease gene associations, and flagging genes that have previously been incorrectly implicated in disease. GADO can be run on www.genenetwork.nl by supplying HPO-terms and a list of genes that contain candidate variants. Finally, applying GADO to a cohort of 61 patients for whom exome-sequencing analysis had not resulted in a genetic diagnosis, yields likely causative genes for ten cases.
Editor: England: Nature Publishing Group
Idioma: Inglês

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Improving the diagnostic yield of exome- sequencing by predicting gene-phenotype associations using large-scale gene expression analysis

England: Nature Publishing Group

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