RNA sequencing in mitochondrial disease resolves hidden mutations
Source PublicationAnnals of Clinical and Translational Neurology
Primary AuthorsLiu, Duan, Peymani et al.

RNA-seq identifies genetic causes for 25% of mitochondrial disorders where standard DNA tests failed. Locating these mutations is difficult because standard exome sequencing ignores non-coding regions and functional consequences of synonymous mutations. While DNA provides the blueprint, it lacks the functional context required to prove how specific variants disrupt cellular energy production.
Mitochondrial diseases are genetically diverse, leaving approximately half of all patients without a molecular explanation. Current DNA-based methods often miss deep intronic variants or fail to predict how a mutation alters protein production. This diagnostic gap leaves families without clear prognoses or reproductive options.
RNA sequencing in mitochondrial disease
Researchers in China applied transcriptomics to skin fibroblasts from 140 undiagnosed children. The study utilised the DROP pipeline to detect expression and splicing outliers, comparing results against Whole Exome Sequencing (WES) data. The findings were categorised into two groups: those with existing variants of uncertain significance and those with no DNA leads.
- 71% of cases with previously suspicious DNA variants were resolved through functional validation.
- 13% of entirely unsolved cases received a definitive diagnosis by pinpointing new candidate genes.
- A specific synonymous mutation in ECHS1 was identified as a recurrent East Asian founder variant.
The data demonstrated that 14% of variants expected to trigger mRNA degradation actually escaped it, contradicting existing computational models. Half of the pathogenic variants identified were non-coding, highlighting the limitations of exome-only approaches. This discrepancy suggests that in silico tools often misjudge the severity of protein-truncating mutations.
This study suggests that transcriptomics is a necessary component of metabolic diagnostics to capture cryptic splicing and regulatory events. This method does not solve cases where the causative gene is silent in skin fibroblasts or requires tissue-specific expression from the brain or heart.