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Copy-number variants in clinical genome sequencing: deployment and interpretation for rare and undiagnosed disease.
Genetics in Medicine ( IF 6.6 ) Pub Date : 2018-10-08 , DOI: 10.1038/s41436-018-0295-y
Andrew M Gross 1 , Subramanian S Ajay 1 , Vani Rajan 1 , Carolyn Brown 1 , Krista Bluske 1 , Nicole J Burns 1 , Aditi Chawla 1 , Alison J Coffey 1 , Alka Malhotra 1 , Alicia Scocchia 1 , Erin Thorpe 1 , Natasa Dzidic 2 , Karine Hovanes 2 , Trilochan Sahoo 2 , Egor Dolzhenko 1 , Bryan Lajoie 1 , Amirah Khouzam 3 , Shimul Chowdhury 4 , John Belmont 1 , Eric Roller 1 , Sergii Ivakhno 5 , Stephen Tanner 1 , Julia McEachern 1 , Tina Hambuch 3 , Michael Eberle 1 , R Tanner Hagelstrom 1 , David R Bentley 5 , Denise L Perry 1 , Ryan J Taft 1
Affiliation  

PURPOSE Current diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, genome sequencing (GS) can detect all genomic pathogenic variant types on a single platform. Here we evaluate copy-number variant (CNV) calling as part of a clinically accredited GS test. METHODS We performed analytical validation of CNV calling on 17 reference samples, compared the sensitivity of GS-based variants with those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis of GS-based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases. RESULTS We found that CNV calls from GS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed, all of which were confirmed by an orthogonal approach. The pipeline also enabled discovery of a uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of select CNVs enabled breakpoint level resolution of genomic rearrangements and phasing of de novo CNVs. CONCLUSION Robust identification of CNVs by GS is possible within a clinical testing environment.

中文翻译:

临床基因组测序中的拷贝数变异:罕见和未确诊疾病的部署和解释。

目的 目前对遗传疾病的诊断测试涉及连续使用跨越多种技术的专业化验。原则上,基因组测序 (GS) 可以在一个平台上检测所有基因组致病变异类型。在这里,我们评估拷贝数变异 (CNV) 调用作为临床认可的 GS 测试的一部分。方法 我们对 17 个参考样本进行了 CNV 调用的分析验证,比较了基于 GS 的变体与临床微阵列的敏感性,并使用正交技术设定了精确度的界限。我们开发了一种基于家族的基于 GS 的 CNV 调用分析的协议,并将其部署在 79 例罕见和未确诊病例的临床队列中。结果 我们发现来自 GS 的 CNV 调用至少与来自微阵列的 CNV 一样敏感,而仅适度增加解释的变体数量(每个案例约 10 个 CNV)。我们在分析的前 79 例病例中发现了 15% 的具有临床意义的 CNV,所有这些都通过正交方法得到证实。该管道还能够发现单亲二体性 (UPD) 和 50% 镶嵌三体性 14。对选定 CNV 的定向分析能够实现基因组重排的断点水平分辨率和从头 CNV 的定相。结论 在临床测试环境中,GS 对 CNV 的可靠鉴定是可能的。对选定 CNV 的定向分析能够实现基因组重排的断点水平分辨率和从头 CNV 的定相。结论 在临床测试环境中,GS 对 CNV 的可靠鉴定是可能的。对选定 CNV 的定向分析能够实现基因组重排的断点水平分辨率和从头 CNV 的定相。结论 在临床测试环境中,GS 对 CNV 的可靠鉴定是可能的。
更新日期:2018-10-08
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