Background and Objective

Mitochondrial diseases are a frequent cause of inherited genetic disorders caused by mutations in both the mitochondrial and nuclear human genome. The new technique of high-throughput sequencing, which is used more and more frequently around the world, is most often focused on nuclear DNA. In some cases, such data after proper IT processing could also allow to determine alterations in mtDNA genome. In our work, we want to verify that off-target reads from targeted gene panels are sufficient data to determine pathogenic variants in the mitochondrial genome.

Methods

We analyzed 50 patients who underwent routine diagnostics with the Illumina's TruSight One Sequencing Panel. In the entire bioinformatic analysis process, we have used only free, user-friendly and generally available online tools that do not require specialized IT knowledge.

Results

Most of the data obtained were suitable for determining the presence of homoplasmic variants in mtDNA; 84% of the data met the minimum 20-fold coverage requirement as defined in the scientific literature for clinical data. We managed to identify 16 pathogenic variants in the examined genetic material (mtDNA) according to the ClinVar database.

Conclusions

In conclusion, we have outlined that off-target reads from targeted gene panel (TruSight One Sequencing Panel) may also be suitable for determining potentially pathogenic homoplasmic variants in mtDNA. We also described a simple pipeline based only on free tools available online. Introducing such a pipeline into a standard procedure of clinical units which carry out such research undoubtedly can extend the diagnostic potential by information about mtDNA, especially when it is based on purely free tools that do not require specialized bioinformatic knowledge.

中文翻译：

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来自靶向基因组的NGS数据在线粒体疾病筛查中的临床应用。

背景与目的

线粒体疾病是线粒体和核人类基因组突变引起的遗传遗传病的常见原因。高通量测序的新技术在世界范围内越来越广泛地使用，并且最常集中在核DNA上。在某些情况下，经过适当的IT处理后，此类数据也可以确定mtDNA基因组的变化。在我们的工作中，我们要验证从目标基因组中脱靶的读数是否足以确定线粒体基因组中的致病变异。

方法

我们使用Illumina的TruSight One测序小组分析了50位接受常规诊断的患者。在整个生物信息学分析过程中，我们仅使用了不需要专门的IT知识的免费，用户友好型且普遍可用的在线工具。

结果

获得的大多数数据都适合确定mtDNA中是否存在同质变异体。84％的数据满足临床文献中科学文献中定义的最低20倍覆盖率要求。根据ClinVar数据库，我们设法在所检查的遗传物质（mtDNA）中鉴定出16种致病变体。

结论

总之，我们概述了从目标基因组（TruSight One测序组）中脱靶的读段也可能适用于确定mtDNA中潜在的致病同质变异。我们还描述了一个仅基于在线免费工具的简单管道。毫无疑问，将这样的管道引入执行此类研究的临床单位的标准程序中，无疑可以通过有关mtDNA的信息来扩大诊断潜力，尤其是当它基于不需要专门的生物信息学知识的纯免费工具时。