Improving genetic diagnosis in Mendelian disease with transcriptome sequencing

Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. A team led by researchers at Massachusetts General Hospital explored the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. They describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. They demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. The researchers also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. They identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.

Overview of the number of samples that underwent RNA-seq

rna-seq

The researchers performed RNA-seq on 13 previously genetically diagnosed patients, 4 patients in whom previous genetic analysis had identified an extended splice site variant of unknown significance (VUS), 12 patients in whom genetic analysis had identified a strong candidate gene, and 34 patients with no strong candidates from previous analysis. RNA-seq enabled the diagnosis of 35% of patients overall, with the rate, shown above the bar plots, varying depending on previous evidence from genetic analysis. (B) PCA based on gene expression profiles of patient muscle samples passing quality control (n = 61) and GTEx samples of tissues that potentially contaminate muscle biopsies shows that patient samples cluster closely with GTEx skeletal muscle. (C) Overview of experimental setup and RNA-seq analyses performed. Our framework is based on identifying transcriptional aberrations that are present in patients and missing in GTEx controls. Upon ensuring that GTEx and patient RNA-seq data were comparable, we validated the capacity of RNA-seq to resolve transcriptional aberrations in previously diagnosed patients and performed analyses of aberrant splicing, allele imbalance, and variant calling in the remaining cohort of genetically undiagnosed muscle disease patients.

Cummings BB et al. (2017) Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Sci Transl Med 9(386). [abstract]

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