Genome sequencing reveals the impact of pseudoexons in rare genetic disease

Abstract

Purpose: Advancements in sequencing technologies have significantly improved clinical genetic testing, yet the diagnostic yield remains around 30-40%. Emerging sequencing technologies are now being deployed in the clinical setting to address the remaining diagnostic gap.

Methods: We tested whether short-read genome sequencing could increase diagnostic yield in individuals enrolled into the UCI-GREGoR research study, who had suspected Mendelian conditions and prior inconclusive clinical genetic testing. Two other collaborative research cohorts, focused on aortopathy and dilated cardiomyopathy, consisted of individuals who were undiagnosed but had not undergone harmonized prior testing.

Results: We sequenced 353 families (754 participants) and found a molecular diagnosis in 54 (15.3%) of them. Of these diagnoses, 55.5% were previously missed because the causative variants were in regions not interrogated by the original testing. In 5 cases, they were deep intronic variants, all of which led to abnormal splicing and pseudoexons, as directly shown by RNA sequencing. All 5 of these variants had inconclusive spliceAI scores. In 26% of newly diagnosed cases, the causal variant could have been detected by exome sequencing reanalysis.

Conclusion: Genome sequencing overcomes multiple limitations of clinical genetic testing, such as inability to call intronic variants and technical limitations. Our findings highlight pseudoexons as a common mechanism via which deep intronic variants cause Mendelian disease. However, they also reinforce that reanalysis of exome datasets can be a fruitful approach.

Keywords: RNA sequencing; genome sequencing; intronic variants; pseudoexon; rare disease.