We undertook the clinical feature examination and dystrophin analysis using multiplex ligation-dependent probe amplification (MLPA) and direct DNA sequencing of selected exons in a cohort of 35 Malaysian Duchenne/Becker muscular dystrophy (DMD/BMD) patients. We found 27 patients with deletions of one or more exons, 2 patients with one exon duplication, 2 patients with nucleotide deletion, and 4 patients with nonsense mutations (including 1 patient with two nonsense mutations in the same exon). Although most cases showed compliance to the reading frame rule, we found two unrelated DMD patients with an in-frame deletion of the gene. Two novel mutations have been detected in the Dystrophin gene and our results were compatible with other studies where the majority of the mutations (62.8%) are located in the distal hotspot. However, the frequency of the mutations in our patient varied as compared with those found in other populations.
Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.