RNA Sequencing in Disease Diagnosis

Abstract

RNA sequencing (RNA-seq) enables the accurate measurement of multiple transcriptomic phenotypes for modeling the impacts of disease variants. Advances in technologies, experimental protocols, and analysis strategies are rapidly expanding the application of RNA-seq to identify disease biomarkers, tissue- and cell-type-specific impacts, and the spatial localization of disease-associated mechanisms. Ongoing international efforts to construct biobank-scale transcriptomic repositories with matched genomic data across diverse population groups are further increasing the utility of RNA-seq approaches by providing large-scale normative reference resources. The availability of these resources, combined with improved computational analysis pipelines, has enabled the detection of aberrant transcriptomic phenotypes underlying rare diseases. Further expansion of these resources, across both somatic and developmental tissues, is expected to soon provide unprecedented insights to resolve disease origin, mechanism of action, and causal gene contributions, suggesting the continued high utility of RNA-seq in disease diagnosis.

Keywords: RNA sequencing; genetic disease; transcriptomics.

Figure 1

RNA-seq in disease diagnosis and treatment. A patient’s biospecimen is subject to RNA-seq and subsequently deposited in or compared with rare-disease and population-based RNA-seq datasets. Outlier gene expression or alternative splicing can inform an underlying pathogenic effect to assist with diagnosis, and comparison with drug signatures that may restore normal molecular function provides an opportunity to identify treatment strategies. Abbreviations: GREGoR, Genomics Research to Elucidate the Genetics of Rare Diseases; GTEx, Genotype–Tissue Expression; RNA-seq, RNA sequencing. Figure adapted from images created with BioRender.com.