Wood, E. orcid.org/0000-0001-7418-6037, Parker, M.D. orcid.org/0000-0003-2999-3870, Dunning, M.J. orcid.org/0000-0002-8853-9435 et al. (4 more authors) (Submitted: 2019) Clinical long-read sequencing of the human mitochondrial genome for mitochondrial disease diagnostics. bioRxiv. (Submitted)
Abstract
Purpose Long-read, third generation, sequencing technologies have the potential to improve current state of the art diagnostic strategies. In order to determine if long-read sequencing technologies are suitable for the diagnosis of mitochondrial disorders due to mitochondrial DNA (mtDNA) variants, particularly large deletions, we compared the performance of Oxford Nanopore Technologies (ONT) MinION to current diagnostic methods.
Methods We sequenced mtDNA from nine patients with mtDNA deletion disorders and three normal controls with both ONT MinION and Illumina MiSeq. We applied a computational pipeline to estimate the positions of mtDNA deletions in patients, and subsequently validated the breakpoints using Sanger sequencing.
Results We were able to detect mtDNA deletions with a MinION workflow, successfully calling the disease causing event in all cases. Sequencing coverage was in most cases significantly more (p=0.03, Wilcoxon test) uniform with MinION than with MiSeq and subsequent correction of MinION reads improved breakpoint accuracy and reduced false positives. Although heteroplasmic single nucleotide variants are detectable, the high number of false positives and false negatives precludes their use in diagnostics at this time.
Conclusion The MinION is becoming an increasingly attractive diagnostic tool due to the reducing cost, increasing accuracy, and the speed at which data can be obtained.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Author(s). For reuse permissions, please contact the Author(s). |
Keywords: | Mitochondria; Nanopore; Diagnostics; Sequencing |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Neuroscience (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 May 2019 13:21 |
Last Modified: | 15 May 2019 13:21 |
Status: | Submitted |
Publisher: | Cold Spring Harbor Laboratory |
Identification Number: | 10.1101/597187 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146072 |