Whole genome and transcriptome sequencing for gene discovery in dystonia

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Dystonias are hyperkinetic movement disorders, often imposing severe limitations on patients’ health and quality of life. They are rare diseases and show extensive heterogeneity in their etiology and phenotypic presentation. Their molecular etiology is poorly understood, limiting the availability of effective therapies. Many forms of dystonia have a genetic basis; therefore identification of the causal genes is an excellent starting point for the urgently needed progress in diagnostics and treatment options. At present, whole exome sequencing (WES) is the main driving force for gene discovery in monogenic disorders. We have sequenced more than 700 index cases and have compiled one of the largest WES cohorts for dystonia in Europe. These efforts have led to the discovery of novel disease genes and have suggested new pathophysiological concepts for dystonia. However, WES has a limited detection scope, leaving the majority of cases unsolved at present.Therefore, we want to combine whole genome sequencing (WGS) and transcriptome sequencing (RNA-seq) to identify the genetic causes of dystonia in WES-negative individuals.WGS has uniform coverage of all genes, detects structural variants, and enables the analysis of non-coding regulatory variants, which also contribute to monogenic disorders, but are challenging to annotate. We address this by combining WGS with RNA-seq to aid interpretation of the consequences of variation detected by WGS. Using WGS and/or RNA-seq has already proven successful for disease gene discovery in other types of monogenic disorders.We will apply WGS and RNA-seq in a total of 300 individuals selected from our cohort: 76 trios, 25 families with an autosomal-dominant, and 11 families with an autosomal-recessive mode of inheritance. Samples are selected using a prioritization score which we have developed based on our WES results. It integrates several phenotype-based clinical predictors and was shown to identify individuals with a high likelihood of a genetic cause of their dystonia. We will call genetic variants from WGS and filter these based on frequency, function, and mode of inheritance. Function refers to both coding variants (e.g. LoF) and non-coding variants (e.g. regulatory variant in an enhancer). For trios, variants have to be consistent with a de novo model (sequencing parents and affected offspring), whereas in families they have to be consistent with the observed mode of inheritance and between two sequenced family members. We will integrate these variants with genes prioritized by three different readouts from RNA-seq (gene expression, monoallelic expression, splicing patterns) to prioritize genes as candidate causal genes for dystonia. We expect to identify at least four novel disease genes with compelling evidence in our cohort. These genes will then be taken forward to validation in functional follow-up studies. In addition, we will seek additional confirmation in independent dystonia cohorts.