Search

Background: Up to 7% of patients with Duchenne muscular dystrophy (DMD) or Becker muscular dystrophy (BMD) remain genetically undiagnosed after routine genetic testing. These patients are thought to carry deep intronic variants, structural variants or splicing alterations not detected through multiplex ligation-dependent probe amplification or exome sequencing. Methods: RNA was extracted from seven muscle biopsy samples of patients with genetically undiagnosed DMD/BMD after routine genetic diagnosis. RT-PCR of the DMD gene was performed to detect the presence of alternative transcripts. Droplet digital PCR and whole-genome sequencing were also performed in some patients. Results: We identified an alteration in the mRNA level in all the patients. We detected three pseudoexons in DMD caused by deep intronic variants, two of them not previously reported. We also identified a chromosomal rearrangement between Xp21.2 and 8p22. Furthermore, we detected three exon skipping events with unclear pathogenicity. Conclusion: These findings indicate that mRNA analysis of the DMD gene is a valuable tool to reach a precise genetic diagnosis in patients with a clinical and anatomopathological suspicion of dystrophinopathy that remain genetically undiagnosed after routine genetic testing. [ABSTRACT FROM AUTHOR]

Purpose Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies. Methods 68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test FANCA missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies. Results We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two FANCA variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) Conclusion WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source. [ABSTRACT FROM AUTHOR]