Challenges in detecting genomic copy number aberrations using next-generation sequencing data and the eXome Hidden Markov Model: a clinical exome-first diagnostic approach

Toshiyuki Yamamoto; Keiko Shimojima; Yumiko Ondo; Katsumi Imai; Pin Fee Chong; Ryutaro Kira; Mitsuhiro Amemiya; Akira Saito; Nobuhiko Okamoto

doi:10.1038/hgv.2016.25

Challenges in detecting genomic copy number aberrations using next-generation sequencing data and the eXome Hidden Markov Model: a clinical exome-first diagnostic approach

Hum Genome Var. 2016 Aug 18:3:16025. doi: 10.1038/hgv.2016.25. eCollection 2016.

Authors

Toshiyuki Yamamoto¹, Keiko Shimojima¹, Yumiko Ondo¹, Katsumi Imai², Pin Fee Chong³, Ryutaro Kira³, Mitsuhiro Amemiya⁴, Akira Saito⁴, Nobuhiko Okamoto⁵

Affiliations

¹ Tokyo Women's Medical University Institute for Integrated Medical Sciences , Tokyo, Japan.
² National Epilepsy Center, NHO Shizuoka Institute of Epilepsy and Neurological Disorders , Shizuoka, Japan.
³ Department of Pediatric Neurology, Fukuoka Children's Hospital , Fukuoka, Japan.
⁴ Division of Biomedical Informatics, StaGen Co., Ltd. , Tokyo, Japan.
⁵ Department of Medical Genetics, Osaka Medical Center and Research Institute for Maternal and Child Health , Osaka, Japan.

Abstract

Next-generation sequencing (NGS) is widely used for the detection of disease-causing nucleotide variants. The challenges associated with detecting copy number variants (CNVs) using NGS analysis have been reported previously. Disease-related exome panels such as Illumina TruSight One are more cost-effective than whole-exome sequencing (WES) because of their selective target regions (~21% of the WES). In this study, CNVs were analyzed using data extracted through a disease-related exome panel analysis and the eXome Hidden Markov Model (XHMM). Samples from 61 patients with undiagnosed developmental delays and 52 healthy parents were included in this study. In the preliminary study to validate the constructed XHMM system (microarray-first approach), 34 patients who had previously been analyzed by chromosomal microarray testing were used. Among the five CNVs larger than 200 kb that were considered as non-pathogenic CNVs and were used as positive controls, four CNVs was successfully detected. The system was subsequently used to analyze different samples from 27 patients (NGS-first approach); 2 of these patients were successfully diagnosed as having pathogenic CNVs (an unbalanced translocation der(5)t(5;14) and a 16p11.2 duplication). These diagnoses were re-confirmed by chromosomal microarray testing and/or fluorescence in situ hybridization. The NGS-first approach generated no false-negative or false-positive results for pathogenic CNVs, indicating its high sensitivity and specificity in detecting pathogenic CNVs. The results of this study show the possible clinical utility of pathogenic CNV screening using disease-related exome panel analysis and XHMM.