Abstract：
OBJECTIVE: Whole-exome sequencing (WES) technology has become an essential tool in the clinical diagnostic for rare genetic disorders, however, the issues that reduce testing precision, sensitivity, and concordance are not clear under routine testing conditions. The study is to systematically evaluate the comparability of clinical WES testing results in laboratories under routine conditions.
METHODS: We designed a multi-laboratory study across 24 participating laboratories in China. We assessed sequencing quality across capture methods and sequencing platforms, benchmarked the impact of coverage and callable regions on detecting single nucleotide variants (SNVs), small insertions and deletions (Indels) under the same computational approaches, and compared the sensitivity, precision and reproducibility on detecting mutations across laboratories.
RESULTS: High inter-laboratory variability on variants detection were found across participating laboratories. Sample DNA concentration and sequencing evenness are two major variables that lead to the coverage variation. The difference in bioinformatics tools and computational settings affect the sensitivity and precision of the final output. Besides, copy-number variants (CNVs) identification is less reproducible than SNVs and Indels in the WES testing. We also compiled a list of 4441 low coverage ClinVar variants of 1176 genes from this study, which can be used as a source for creating in silico and synthetic DNA reference materials for clinical genetic disorder detection.
CONCLUSIONS: The considerable inter-laboratory variability seen in both sequencing coverage evenness and variants detection highlights the urgent need to improve the precision, sensitivity and comparability of the results generated across different laboratories. The list of low coverage variants can have important implications for the development and validation of clinical genetic disorder tests by laboratories. This study also serves to best practice inform guidelines for detecting clinical genetic disorders by exome sequencing.
METHODS: We designed a multi-laboratory study across 24 participating laboratories in China. We assessed sequencing quality across capture methods and sequencing platforms, benchmarked the impact of coverage and callable regions on detecting single nucleotide variants (SNVs), small insertions and deletions (Indels) under the same computational approaches, and compared the sensitivity, precision and reproducibility on detecting mutations across laboratories.
RESULTS: High inter-laboratory variability on variants detection were found across participating laboratories. Sample DNA concentration and sequencing evenness are two major variables that lead to the coverage variation. The difference in bioinformatics tools and computational settings affect the sensitivity and precision of the final output. Besides, copy-number variants (CNVs) identification is less reproducible than SNVs and Indels in the WES testing. We also compiled a list of 4441 low coverage ClinVar variants of 1176 genes from this study, which can be used as a source for creating in silico and synthetic DNA reference materials for clinical genetic disorder detection.
CONCLUSIONS: The considerable inter-laboratory variability seen in both sequencing coverage evenness and variants detection highlights the urgent need to improve the precision, sensitivity and comparability of the results generated across different laboratories. The list of low coverage variants can have important implications for the development and validation of clinical genetic disorder tests by laboratories. This study also serves to best practice inform guidelines for detecting clinical genetic disorders by exome sequencing.
摘要：
目的：全外显子组测序（WES）技术已成为临床诊断罕见遗传病的重要工具，然而,降低测试精度的问题，灵敏度,在常规测试条件下，一致性不明确。该研究旨在系统评估常规条件下实验室临床WES检测结果的可比性。
方法：我们设计了一项跨中国24个参与实验室的多实验室研究。我们评估了捕获方法和测序平台的测序质量，基准测试了覆盖和可调用区域对检测单核苷酸变体（SNV）的影响，在相同的计算方法下的小插入和删除(Indel)，并比较了灵敏度，在实验室中检测突变的精度和可重复性。
结果：在参与的实验室中发现变异检测的实验室间差异很大。样品DNA浓度和测序均匀度是导致覆盖度变化的两个主要变量。生物信息学工具和计算设置的差异影响最终输出的灵敏度和精度。此外,在WES测试中,拷贝数变体(CNV)鉴定的可重复性低于SNV和Indels。我们还编制了一份来自本研究的1176个基因的4441个低覆盖率ClinVar变体的列表，可用作创建用于临床遗传病检测的计算机和合成DNA参考材料的来源。
结论：在测序覆盖均匀性和变异体检测中看到的相当大的实验室间差异突出了迫切需要提高精密度，不同实验室产生的结果的敏感性和可比性。低覆盖率变体的列表对于实验室开发和验证临床遗传疾病测试具有重要意义。这项研究也为通过外显子组测序检测临床遗传疾病的最佳实践提供了指导。
方法：我们设计了一项跨中国24个参与实验室的多实验室研究。我们评估了捕获方法和测序平台的测序质量，基准测试了覆盖和可调用区域对检测单核苷酸变体（SNV）的影响，在相同的计算方法下的小插入和删除(Indel)，并比较了灵敏度，在实验室中检测突变的精度和可重复性。
结果：在参与的实验室中发现变异检测的实验室间差异很大。样品DNA浓度和测序均匀度是导致覆盖度变化的两个主要变量。生物信息学工具和计算设置的差异影响最终输出的灵敏度和精度。此外,在WES测试中,拷贝数变体(CNV)鉴定的可重复性低于SNV和Indels。我们还编制了一份来自本研究的1176个基因的4441个低覆盖率ClinVar变体的列表，可用作创建用于临床遗传病检测的计算机和合成DNA参考材料的来源。
结论：在测序覆盖均匀性和变异体检测中看到的相当大的实验室间差异突出了迫切需要提高精密度，不同实验室产生的结果的敏感性和可比性。低覆盖率变体的列表对于实验室开发和验证临床遗传疾病测试具有重要意义。这项研究也为通过外显子组测序检测临床遗传疾病的最佳实践提供了指导。
