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Research Article| Volume 25, ISSUE 6, P502-510, June 2015

Targeted next-generation sequencing for the genetic diagnosis of dysferlinopathy

  • Author Footnotes
    1 These authors contributed equally to this work.
    Ha Young Shin
    Footnotes
    1 These authors contributed equally to this work.
    Affiliations
    Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • Author Footnotes
    1 These authors contributed equally to this work.
    Hoon Jang
    Footnotes
    1 These authors contributed equally to this work.
    Affiliations
    Department of Chemistry, Yonsei University, Seoul, Republic of Korea
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  • Joo Hyung Han
    Affiliations
    Department of Pharmacology, Pharmacogenomic Research Center for Membrane Transporters, Brain Korea 21 PLUS Project for Medical Sciences, Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • Hyung Jun Park
    Affiliations
    Department of Neurology, Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea
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  • Jung Hwan Lee
    Affiliations
    Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • So Won Kim
    Affiliations
    Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea

    Department of Clinical Pharmacology, Inje University, Busan Paik Hospital, Busan, Republic of Korea
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  • Seung Min Kim
    Affiliations
    Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • Young-Eun Park
    Affiliations
    Department of Neurology, Pusan National University School of Medicine, Busan, Republic of Korea
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  • Dae-Seong Kim
    Affiliations
    Department of Neurology, Pusan National University School of Medicine, Busan, Republic of Korea
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  • Duhee Bang
    Affiliations
    Department of Chemistry, Yonsei University, Seoul, Republic of Korea
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  • Min Goo Lee
    Affiliations
    Department of Pharmacology, Pharmacogenomic Research Center for Membrane Transporters, Brain Korea 21 PLUS Project for Medical Sciences, Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • Ji Hyun Lee
    Correspondence
    Corresponding author. Department of Oral Biology, Yonsei University College of Dentistry, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-752, Korea. Tel.: +82 2 2228 3046; fax: +82 2 313 1864.
    Affiliations
    Department of Oral Biology, Yonsei University College of Dentistry, Seoul, Republic of Korea
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  • Young-Chul Choi
    Correspondence
    Corresponding author. Department of Neurology, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul 135-720, Korea. Tel.: +82 2 2019 3323; fax: +82 2 3462 5904.
    Affiliations
    Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
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  • Author Footnotes
    1 These authors contributed equally to this work.
Published:March 17, 2015DOI:https://doi.org/10.1016/j.nmd.2015.03.006

      Highlights

      • DYSF gene analysis is time-consuming and laborious by conventional sequencing method.
      • We set up a next-generation sequencing-based screening method for dysferlinopathy.
      • This method is accurate and efficient for genetic diagnosis of dysferlinopathy.

      Abstract

      Dysferlinopathy comprises a group of autosomal recessive muscular dystrophies caused by mutations in the DYSF gene. Due to the large size of the gene and its lack of mutational hot spots, analysis of the DYSF gene is time-consuming and laborious using conventional sequencing methods. By next-generation sequencing (NGS), DYSF gene analysis has previously been validated through its incorporation in multi-gene panels or exome analyses. However, individual validation of NGS approaches for DYSF gene has not been performed. Here, we established and validated a hybridization capture-based target-enrichment followed by next-generation sequencing to detect mutations in patients with dysferlinopathy. With this approach, mean depth of coverage was approximately 450 fold and almost all (99.3%) of the targeted region had sequence coverage greater than 20 fold. When this approach was tested on samples from patients with known DYSF mutations, all known mutations were correctly retrieved. Using this method on 32 consecutive patient samples with dysferlinopathy, at least two pathogenic variants were detected in 28 (87.5%) samples and at least one pathogenic variant was identified in all samples. Our results suggested that the NGS-based screening method could facilitate efficient and accurate genetic diagnosis of dysferlinopathy.

      Keywords

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