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Updated: Apr 16, 2026

Multi-exon Skipping Using Cocktail Antisense Oligonucleotides in the Canine X-linked Muscular Dystrophy
Published on: May 24, 2016
New splicing mutation in the choline kinase beta (CHKB) gene causing a muscular dystrophy detected by whole-exome
Jorge Oliveira1, Luís Negrão2, Isabel Fineza3
11] Unidade de Genética Molecular, Centro de Genética Médica Dr Jacinto de Magalhães, Centro Hospitalar do Porto E.P.E., Porto, Portugal [2] Departamento de Microscopia, Laboratório de Biologia Celular, Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal [3] Unidade Multidisciplinar de Investigação Biomédica (UMIB), Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal.
Abstract:
Muscular dystrophies (MDs) are a group of hereditary muscle disorders that include two particularly heterogeneous subgroups: limb-girdle MD and congenital MD, linked to 52 different genes (seven common to both subgroups). Massive parallel sequencing technology may avoid the usual stepwise gene-by-gene analysis. We report the whole-exome sequencing (WES) analysis of a patient with childhood-onset progressive MD, also presenting mental retardation and dilated cardiomyopathy. Conventional sequencing had excluded eight candidate genes. WES of the trio (patient and parents) was performed using the ion proton sequencing system. Data analysis resorted to filtering steps using the GEMINI software revealed a novel silent variant in the choline kinase beta (CHKB) gene. Inspection of sequence alignments ultimately identified the causal variant (CHKB:c.1031+3G>C). This splice site mutation was confirmed using Sanger sequencing and its effect was further evaluated with gene expression analysis. On reassessment of the muscle biopsy, typical abnormal mitochondrial oxidative changes were observed. Mutations in CHKB have been shown to cause phosphatidylcholine deficiency in myofibers, causing a rare form of CMD (only 21 patients reported). Notwithstanding interpretative difficulties that need to be overcome before the integration of WES in the diagnostic workflow, this work corroborates its utility in solving cases from highly heterogeneous groups of diseases, in which conventional diagnostic approaches fail to provide a definitive diagnosis.
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