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Article

Analyzing Low-Level mtDNA Heteroplasmy—Pitfalls and Challenges from Bench to Benchmarking

1
Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, A-6020 Innsbruck, Austria
2
Carinthia University of Applied Sciences, A-9524 Villach, Austria
*
Author to whom correspondence should be addressed.
These authors contributed equally.
Int. J. Mol. Sci. 2021, 22(2), 935; https://doi.org/10.3390/ijms22020935
Received: 9 December 2020 / Revised: 5 January 2021 / Accepted: 15 January 2021 / Published: 19 January 2021
(This article belongs to the Section Molecular Genetics and Genomics)
Massive parallel sequencing technologies are promising a highly sensitive detection of low-level mutations, especially in mitochondrial DNA (mtDNA) studies. However, processes from DNA extraction and library construction to bioinformatic analysis include several varying tasks. Further, there is no validated recommendation for the comprehensive procedure. In this study, we examined potential pitfalls on the sequencing results based on two-person mtDNA mixtures. Therefore, we compared three DNA polymerases, six different variant callers in five mixtures between 50% and 0.5% variant allele frequencies generated with two different amplification protocols. In total, 48 samples were sequenced on Illumina MiSeq. Low-level variant calling at the 1% variant level and below was performed by comparing trimming and PCR duplicate removal as well as six different variant callers. The results indicate that sensitivity, specificity, and precision highly depend on the investigated polymerase but also vary based on the analysis tools. Our data highlight the advantage of prior standardization and validation of the individual laboratory setup with a DNA mixture model. Finally, we provide an artificial heteroplasmy benchmark dataset that can help improve somatic variant callers or pipelines, which may be of great interest for research related to cancer and aging. View Full-Text
Keywords: mitochondrial DNA (mtDNA); next generation sequencing (NGS); heteroplasmy; variant callers; DNA polymerase mitochondrial DNA (mtDNA); next generation sequencing (NGS); heteroplasmy; variant callers; DNA polymerase
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  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.3991749
    Link: https://zenodo.org/record/3991749
    Description: Heteroplasmy Benchmark Dataset - mitochondrial DNA mixture model - MiSeq - FASTQ files
  • Externally hosted supplementary file 2
    Doi: 10.5281/zenodo.4395665
    Link: https://zenodo.org/record/4395665
    Description: Heteroplasmy Benchmark Dataset - mitochondrial DNA mixture model - MiSeq - BAM files
  • Externally hosted supplementary file 3
    Doi: 10.5281/zenodo.3339078
    Link: https://zenodo.org/record/3339078
    Description: Heteroplasmy Benchmark Dataset - mitochondrial DNA mixture model - HiSeq - BAM files
MDPI and ACS Style

Fazzini, F.; Fendt, L.; Schönherr, S.; Forer, L.; Schöpf, B.; Streiter, G.; Losso, J.L.; Kloss-Brandstätter, A.; Kronenberg, F.; Weissensteiner, H. Analyzing Low-Level mtDNA Heteroplasmy—Pitfalls and Challenges from Bench to Benchmarking. Int. J. Mol. Sci. 2021, 22, 935. https://doi.org/10.3390/ijms22020935

AMA Style

Fazzini F, Fendt L, Schönherr S, Forer L, Schöpf B, Streiter G, Losso JL, Kloss-Brandstätter A, Kronenberg F, Weissensteiner H. Analyzing Low-Level mtDNA Heteroplasmy—Pitfalls and Challenges from Bench to Benchmarking. International Journal of Molecular Sciences. 2021; 22(2):935. https://doi.org/10.3390/ijms22020935

Chicago/Turabian Style

Fazzini, Federica, Liane Fendt, Sebastian Schönherr, Lukas Forer, Bernd Schöpf, Gertraud Streiter, Jamie Lee Losso, Anita Kloss-Brandstätter, Florian Kronenberg, and Hansi Weissensteiner. 2021. "Analyzing Low-Level mtDNA Heteroplasmy—Pitfalls and Challenges from Bench to Benchmarking" International Journal of Molecular Sciences 22, no. 2: 935. https://doi.org/10.3390/ijms22020935

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