Identification of deep intronic variants in junctional epidermolysis bullosa using genome sequencing and splicing assays.

IF 4.7 2区医学 Q1 GENETICS & HEREDITY NPJ Genomic Medicine Pub Date : 2025-02-06 DOI:10.1038/s41525-025-00466-8

Fuying Chen, Ruoqu Wei, Yumeng Wang, Qiaoyu Cao, Jianbo Wang, Chenfei Wang, Dingjin Yao, Zhirong Yao, Cheng Ni, Ming Li

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Abstract

Junctional epidermolysis bullosa (JEB) is characterized by mucocutaneous fragility. We enrolled 69 cases of recessive JEB, with 13.0% of these cases remained genetically undiagnosed following an initial exome sequencing. Among cases carried COL17A1 variants, this proportion can reach 31.6%. We employed genome sequencing to genetically diagnosis these cases. Four deep intronic variants (c.4156+117 G > A, c.2039-104 G > A and c.1267+237dupC in the COL17A1 gene and c.-38 + 2 T > C in the LAMB3 gene) were identified in six cases. The c.4156+117 G > A variant was found in three of the five cases, suggesting it may be a common deep intronic variant in Chinese JEB. Splicing analysis revealed that these variants caused splicing defect by inducing exon skipping, or pseudoexon insertion into the transcript in HaCaT cells, not in HEK293 cells. Our results emphasize the importance of selecting the right cell line for mRNA analysis.

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来源期刊

NPJ Genomic Medicine Biochemistry, Genetics and Molecular Biology-Molecular Biology

CiteScore

9.40

自引率

1.90%

发文量

审稿时长

17 weeks

期刊介绍： npj Genomic Medicine is an international, peer-reviewed journal dedicated to publishing the most important scientific advances in all aspects of genomics and its application in the practice of medicine. The journal defines genomic medicine as "diagnosis, prognosis, prevention and/or treatment of disease and disorders of the mind and body, using approaches informed or enabled by knowledge of the genome and the molecules it encodes." Relevant and high-impact papers that encompass studies of individuals, families, or populations are considered for publication. An emphasis will include coupling detailed phenotype and genome sequencing information, both enabled by new technologies and informatics, to delineate the underlying aetiology of disease. Clinical recommendations and/or guidelines of how that data should be used in the clinical management of those patients in the study, and others, are also encouraged.