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Comparison of two next-generation sequencing kits for diagnosis of epileptic disorders with a user-friendly tool for displaying gene coverage, DeCovA

机译:使用用于显示基因覆盖率的用户友好工具DeCovA对两种用于诊断癫痫病的下一代测序试剂盒进行比较

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In recent years, molecular genetics has been playing an increasing role in the diagnostic process of monogenic epilepsies. Knowing the genetic basis of one patient's epilepsy provides accurate genetic counseling and may guide therapeutic options. Genetic diagnosis of epilepsy syndromes has long been based on Sanger sequencing and search for large rearrangements using MLPA or DNA arrays (array-CGH or SNP-array). Recently, next-generation sequencing (NGS) was demonstrated to be a powerful approach to overcome the wide clinical and genetic heterogeneity of epileptic disorders. Coverage is critical for assessing the quality and accuracy of results from NGS. However, it is often a difficult parameter to display in practice. The aim of the study was to compare two library-building methods (Haloplex, Agilent and SeqCap EZ, Roche) for a targeted panel of 41 genes causing monogenic epileptic disorders. We included 24 patients, 20 of whom had known disease-causing mutations. For each patient both libraries were built in parallel and sequenced on an Ion Torrent Personal Genome Machine (PGM). To compare coverage and depth, we developed a simple homemade tool, named DeCovA (Depth and Coverage Analysis). DeCovA displays the sequencing depth of each base and the coverage of target genes for each genomic position. The fraction of each gene covered at different thresholds could be easily estimated. None of the two methods used, namely NextGene and Ion Reporter, were able to identify all the known mutations/CNVs displayed by the 20 patients. Variant detection rate was globally similar for the two techniques and DeCovA showed that failure to detect a mutation was mainly related to insufficient coverage.
机译:近年来,分子遗传学在单基因癫痫的诊断过程中发挥着越来越重要的作用。了解一名患者癫痫的遗传基础可提供准确的遗传咨询,并可能指导治疗选择。长期以来,癫痫综合征的遗传诊断一直基于Sanger测序,并使用MLPA或DNA阵列(CGH阵列或SNP阵列)来寻找大的重排。最近,新一代测序(NGS)被证明是克服癫痫病广泛的临床和遗传异质性的有效方法。覆盖范围对于评估NGS结果的质量和准确性至关重要。但是,在实践中通常很难显示该参数。该研究的目的是比较两种库构建方法(Haloplex,Agilent和SeqCap EZ,Roche)针对的41种引起单基因癫痫性疾病的基因。我们纳入了24位患者,其中20位具有已知的致病突变。对于每个患者,两个文库都是并行构建的,并在离子激流型个人基因组机(PGM)上进行测序。为了比较覆盖范围和深度,我们开发了一个简单的自制工具,名为DeCovA(深度和覆盖率分析)。 DeCovA显示每个碱基的测序深度以及每个基因组位置的靶基因覆盖率。可以容易地估计每个基因在不同阈值处所占的比例。 NextGene和Ion Reporter这两种方法均无法识别20名患者显示的所有已知突变/ CNV。两种技术的变异检测率总体上相似,DeCovA显示未能检测到突变主要与覆盖范围不足有关。

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