Clinical use of NGS data from the targeted gene panel for mitochondrial diseases screening.

Comput Methods Programs Biomed 2020 Oct 15;194:105529. Epub 2020 May 15.

Department of Clinical Genetics, Medical University of Lodz, Pomorska 251, 92-213 Lodz, Poland.

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.

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Source
http://dx.doi.org/10.1016/j.cmpb.2020.105529DOI Listing
October 2020

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