Clinical Validation of Copy Number Variant Detection from Targeted Next-Generation Sequencing Panels
Clinical Validation of Copy Number Variant Detection from Targeted Next-Generation Sequencing Panels
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DOI：
10.1016/j.jmoldx.2017.07.004
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发表时间：
2017-11-01
影响因子：
4.1
通讯作者：
Sadikovic, Bekim
中科院分区：
文献类型：
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作者：
Kerkhof, Jennifer;Schenkel, Laila C.;Sadikovic, Bekim
下一代测序（NGS）技术已迅速取代桑格测序在临床遗传学实验室的序列变异的评估。当前NGS方法的一个主要限制是检测大约>50 bp的拷贝数变异（CNV）的能力。由于这些代表了许多遗传性疾病的主要突变负担，通常需要使用替代补充方法进行平行CNV评估沿着NGS分析，导致劳动力，成本和周转时间增加。本研究的目的是临床验证一种新的CNV检测算法，使用靶向临床NGS基因面板数据。我们在391个样本的回顾性队列和2375个样本的前瞻性队列中应用了这种方法，发现37个独特事件的灵敏度为100%（95%CI，89%-100%），并且在9个不同的靶向NGS基因组中检测CNV的特异性很高。这种NGS CNV管道能够在临床实验室环境中对CNV和序列变体进行独立的第一层评估，无需使用经典技术进行并行CNV分析，例如微阵列，远程PCR或多重连接依赖性探针扩增。这种NGS CNV管道也可以应用于复杂基因组区域的评估，包括假基因DNA序列，如PMS 2CL基因，以及线粒体基因组异质性检测。
Next-generation sequencing (NGS) technology has rapidly replaced Sanger sequencing in the assessment of sequence variations in clinical genetics laboratories. One major limitation of current NGS approaches is the ability to detect copy number variations (CNVs) approximately >50 bp. Because these represent a major mutational burden in many genetic disorders, parallel CNV assessment using alternate supplemental methods, along with the NGS analysis, is normally required, resulting in increased labor, costs, and turnaround times. The objective of this study was to clinically validate a novel CNV detection algorithm using targeted clinical NGS gene panel data. We have applied this approach in a retrospective cohort of 391 samples and a prospective cohort of 2375 samples and found a 100% sensitivity (95% CI, 89% -100%) for 37 unique events and a high degree of specificity to detect CNVs across nine distinct targeted NGS gene panels. This NGS CNV pipeline enables stand-alone first-tier assessment for CNV and sequence variants in a clinical laboratory setting, dispensing with the need for parallel CNV analysis using classic techniques, such as microarray, long-range PCR, or multiplex ligation dependent probe amplification. This NGS CNV pipeline can also be applied to the assessment of complex genomic regions, including pseudogenic DNA sequences, such as the PMS2CL gene, and to mitochondrial genome heteroplasmy detection.