Affordable Access

deepdyve-link
Publisher Website

Application of whole-exome sequencing for detecting copy number variants in CMT1A/HNPP.

Authors
  • Jo, H-Y1
  • Park, M-H1
  • Woo, H-M1
  • Han, M H1
  • Kim, B-Y1
  • Choi, B-O2
  • Chung, K W3
  • Koo, S K1
  • 1 Division of Intractable Diseases, Center for Biomedical Sciences, Korea National Institute of Health, Cheongju, South Korea. , (North Korea)
  • 2 Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. , (North Korea)
  • 3 Department of Biological Sciences, Kongju National University, Gongju, South Korea. , (North Korea)
Type
Published Article
Journal
Clinical Genetics
Publisher
Wiley (Blackwell Publishing)
Publication Date
Aug 01, 2016
Volume
90
Issue
2
Pages
177–181
Identifiers
DOI: 10.1111/cge.12714
PMID: 26662885
Source
Medline
Keywords
License
Unknown

Abstract

Large insertions and deletions (indels), including copy number variations (CNVs), are commonly seen in many diseases. Standard approaches for indel detection rely on well-established methods such as qPCR or short tandem repeat (STR) markers. Recently, a number of tools for CNV detection based on next-generation sequencing (NGS) data have also been developed; however, use of these methods is limited. Here, we used whole-exome sequencing (WES) in patients previously diagnosed with CMT1A or HNPP using STR markers to evaluate the ability of WES to improve the clinical diagnosis. Patients were evaluated utilizing three CNV detection tools including CONIFER, ExomeCNV and CEQer, and array comparative genomic hybridization (aCGH). We identified a breakpoint region at 17p11.2-p12 in patients with CMT1A and HNPP. CNV detection levels were similar in both 6 Gb (mean read depth = 80×) and 17 Gb (mean read depth = 190×) data. Taken together, these data suggest that 6 Gb WES data are sufficient to reveal the genetic causes of various diseases and can be used to estimate single mutations, indels, and CNVs simultaneously. Furthermore, our data strongly indicate that CNV detection by NGS is a rapid and cost-effective method for clinical diagnosis of genetically heterogeneous disorders such as CMT neuropathy.

Report this publication

Statistics

Seen <100 times