Targeted long-read sequencing enables comprehensive analysis of the genetic and epigenetic landscape of inherited myopathies
Yeow, D.; Reis, A. L.; Stevanovski, I.; Njo, N.; Rudaks, L. I.; Grosz, B. R.; Sy, J. S.; Kemp, L.; Chintalaphani, S. R.; Chin, M.; Stoll, M.; Zhu, D.; Liang, C.; Morris, K.; Hannaford, A.; Shandiz, E.; Ahmad, K. E.; El-Wahsh, S.; Reddel, S. W.; Boland-Freitas, R.; Ghaoui, R.; Barnes, S.; Sturm, J.; Willard, A.; Jasinarachchi, M.; Hawke, S.; Simon, N. G.; Worgan, L.; Manser, D.; Tchan, M.; Griffith, N. C.; Davis, R. L.; Fahey, M. C.; Sue, C. M.; McCombe, P. A.; Ng, K.; Kennerson, M. L.; Cheong, P. L.; Kumar, K. R.; Deveson, I. W.
Show abstract
Inherited myopathies are a group of disorders with diverse and complex genetic aetiologies. The causative genetic variants vary widely in type, size and sequence context, encompassing small sequence variants and large structural variants in protein-coding genes, mitochondrial variants, repeat expansions, and more complex events, such as the chromosome 4 D4Z4 macrosatellite contraction and hypomethylation that causes facioscapulohumeral muscular dystrophy (FSHD). This poses a challenge for analysis with next generation sequencing and other molecular methods. This is further compounded by phenotypic variability between patients and phenotypic overlap of different forms of genetic myopathy. To accelerate myopathy research and improve diagnosis we have developed a targeted long-read sequencing assay and an integrated bioinformatics analysis framework that captures the full suite of genes, variants and epigenetic signatures currently implicated in all forms of inherited myopathy. Applying this to a cohort of 53 myopathy patients with and without previous genetic diagnoses, we demonstrate the analytical validity of our approach, as well as its improved accuracy and resolution compared to existing methods - especially for FSHD. Our LRS assay identified an array of new information about the genetic and epigenetic landscape of inherited myopathies and provided new diagnoses for 29% of patients who had remained undiagnosed following clinical genetic testing. In our cohort, FSHD and oculopharyngodistal myopathies were the most common new diagnoses that were missed or mis-diagnosed by standard clinical genetic testing. Our new method constitutes a single streamlined assay for comprehensive genetic and epigenetic characterisation of inherited myopathies.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Saturation genome editing of DDX3X clarifies pathogenicity of germline and somatic variation 94%
- Rare genetic variants impact muscle strength 94%
- Diagnostic Utility of Genome-wide DNA Methylation Analysis in Genetically Unsolved Developmental and Epileptic Encephalopathies and Refinement of a CHD2 Episignature 94%
Similar papers in this journal
- Genome Sequencing and Comprehensive Rare Variant Analysis of 465 Families with Neurodevelopmental Disorders 95%
- Detecting cryptic clinically-relevant structural variation in exome sequencing data increases diagnostic yield for developmental disorders 95%
- Non-coding variants upstream of MEF2C cause severe developmental disorder through three distinct loss-of-function mechanisms 95%
Similar papers in this journal
- A Myasthenia Gravis genomewide association study of three cohorts identifies Agrin as a novel risk locus 92%
- A comparative medical genomics approach may facilitate the interpretation of rare missense variation 92%
- Disease-specific variant interpretation highlighted the genetic findings in 2325 Japanese patients with retinitis pigmentosa and allied diseases 91%
Similar papers in this journal
Similar papers in this journal
- Genetic association analysis of 269 rare diseases reveals novel aetiologies 94%
- Exome-by-phenome-wide rare variant gene burden association with electronic health record phenotypes 93%
- Human loss-of-function variants suggest that partial LRRK2 inhibition is a safe therapeutic strategy for Parkinsons disease 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.