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International Journal of Legal Medicine

Erschienen in:

26.12.2017 | Original Article

Assessment of mitochondrial DNA heteroplasmy detected on commercial panel using MPS system with artificial mixture samples

verfasst von: Sohee Cho, Moon Young Kim, Ji Hyun Lee, Soong Deok Lee

Erschienen in: International Journal of Legal Medicine | Ausgabe 4/2018

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Abstract

Mitochondrial DNA (mtDNA) heteroplasmy is a potential genetic marker for forensic mtDNA analysis as well as phylogenic studies. Frequency of mtDNA heteroplasmy has been investigated in different populations through massively parallel sequencing (MPS) analysis, revealing various levels of frequency based on different MPS systems. For accurate heteroplasmy identification, it is essential to explore reliable detection threshold on various MPS systems. In addition, software solutions and pipelines need to be evaluated to analyze data effectively. In this study, heteroplasmy analysis was conducted on a commercially available mtDNA analysis system developed for forensic caseworks with artificially mixed DNA samples known for ratios and variant positions for assessment. mtDNA heteroplasmy > 10% was detectable with Torrent Variant Caller (TVC) while lower levels were identified using GeneMarker® HTS specialized software for minor variant detection. This study implies that analytical parameters and tools need to be optimized and evaluated for low-level heteroplasmy identification. Automated system with simple and efficient workflow is needed for forensic caseworks.

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Titel: Assessment of mitochondrial DNA heteroplasmy detected on commercial panel using MPS system with artificial mixture samples
verfasst von: Sohee Cho
Moon Young Kim
Ji Hyun Lee
Soong Deok Lee
Publikationsdatum: 26.12.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal of Legal Medicine / Ausgabe 4/2018
Print ISSN: 0937-9827
Elektronische ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-017-1755-7

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Assessment of mitochondrial DNA heteroplasmy detected on commercial panel using MPS system with artificial mixture samples

Abstract

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