Clinical implementation of RNA sequencing for Mendelian disease diagnostics

Abstract

BackgroundLack of functional evidence hampers variant interpretation, leaving a large proportion of cases with a suspected Mendelian disorder without genetic diagnosis after 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. MethodsWe implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease which previously underwent WES. ResultsWe detected on average 12,500 genes per sample including around 60% disease genes - a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than one week from sample preparation to result reporting and provided a median of eight disease-associated genes per patient for inspection. A genetic diagnosis was established for 16% of the 205 WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions. ConclusionTogether, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics. One sentence summaryImplementation of RNA-seq as a complementary tool in standard diagnostics achieves a 16% in diagnosis rate over whole exome sequencing.