<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Yepez VA</submitter><funding>Bundesministerium für Bildung und Forschung</funding><funding>Instituto de Salud Carlos III</funding><funding>Deutsche Forschungsgemeinschaft</funding><funding>Deutsches Zentrum für Herz-Kreislaufforschung</funding><funding>Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)</funding><funding>Medical Research Council</funding><funding>Agency for Medical Research and Development</funding><funding>National Institute for Health Research (NIHR)</funding><funding>Wellcome Trust Centre for Mitochondrial Research</funding><funding>Wellcome Trust</funding><funding>Lundbeck Foundation</funding><pagination>38</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8981716</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>14(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics.&lt;h4>Methods&lt;/h4>We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease</pubmed_abstract><journal>Genome medicine</journal><pubmed_title>Clinical implementation of RNA sequencing for Mendelian disease diagnostics.</pubmed_title><pmcid>PMC8981716</pmcid><funding_grant_id>PI16/01048</funding_grant_id><funding_grant_id>R263-2017-4384</funding_grant_id><funding_grant_id>01KU2016A</funding_grant_id><funding_grant_id>01IS18053F</funding_grant_id><funding_grant_id>MR/S005021/1</funding_grant_id><funding_grant_id>JP20ek0109468</funding_grant_id><funding_grant_id>PDF-2018-11-ST2-021</funding_grant_id><funding_grant_id>203105/Z/16/Z</funding_grant_id><funding_grant_id>01GM1113C</funding_grant_id><pubmed_authors>Terrile C</pubmed_authors><pubmed_authors>Fang F</pubmed_authors><pubmed_authors>Muller MF</pubmed_authors><pubmed_authors>Van Coster R</pubmed_authors><pubmed_authors>Prokisch H</pubmed_authors><pubmed_authors>Hempel M</pubmed_authors><pubmed_authors>Kishita Y</pubmed_authors><pubmed_authors>Beblo S</pubmed_authors><pubmed_authors>Murayama K</pubmed_authors><pubmed_authors>Meitinger T</pubmed_authors><pubmed_authors>Schwarzmayr T</pubmed_authors><pubmed_authors>Ohtake A</pubmed_authors><pubmed_authors>Strom TM</pubmed_authors><pubmed_authors>Xu M</pubmed_authors><pubmed_authors>Hayflick SJ</pubmed_authors><pubmed_authors>Staufner C</pubmed_authors><pubmed_authors>Nadel A</pubmed_authors><pubmed_authors>Freisinger P</pubmed_authors><pubmed_authors>Wagner M</pubmed_authors><pubmed_authors>Tort F</pubmed_authors><pubmed_authors>Piekutowska-Abramczuk D</pubmed_authors><pubmed_authors>Ban R</pubmed_authors><pubmed_authors>Yepez VA</pubmed_authors><pubmed_authors>Ribes A</pubmed_authors><pubmed_authors>Klopstock T</pubmed_authors><pubmed_authors>Haberle J</pubmed_authors><pubmed_authors>Wortmann SB</pubmed_authors><pubmed_authors>Smet J</pubmed_authors><pubmed_authors>Gagneur J</pubmed_authors><pubmed_authors>Blessing H</pubmed_authors><pubmed_authors>Mayr JA</pubmed_authors><pubmed_authors>Rotig A</pubmed_authors><pubmed_authors>Itkis YS</pubmed_authors><pubmed_authors>Vanlander A</pubmed_authors><pubmed_authors>Ghezzi D</pubmed_authors><pubmed_authors>Alston CL</pubmed_authors><pubmed_authors>Okazaki Y</pubmed_authors><pubmed_authors>Ciara E</pubmed_authors><pubmed_authors>Lamperti C</pubmed_authors><pubmed_authors>Smith NH</pubmed_authors><pubmed_authors>Mertes C</pubmed_authors><pubmed_authors>Munoz-Pujol G</pubmed_authors><pubmed_authors>Stenton SL</pubmed_authors><pubmed_authors>Distelmaier F</pubmed_authors><pubmed_authors>Gusic M</pubmed_authors><pubmed_authors>Krylova TD</pubmed_authors><pubmed_authors>Mosegaard S</pubmed_authors><pubmed_authors>Berutti R</pubmed_authors><pubmed_authors>Kopajtich R</pubmed_authors><pubmed_authors>Taylor RW</pubmed_authors><pubmed_authors>Makowski C</pubmed_authors><pubmed_authors>Lenz D</pubmed_authors><pubmed_authors>Procopio E</pubmed_authors></additional><is_claimable>false</is_claimable><name>Clinical implementation of RNA sequencing for Mendelian disease diagnostics.</name><description>&lt;h4>Background&lt;/h4>Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics.&lt;h4>Methods&lt;/h4>We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Apr</publication><modification>2026-05-31T01:05:30.245Z</modification><creation>2025-04-04T11:31:43.318Z</creation></dates><accession>S-EPMC8981716</accession><cross_references><pubmed>35379322</pubmed><doi>10.1186/s13073-022-01019-9</doi></cross_references></HashMap>