Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/135007
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Type: Journal article
Title: Low guanine content and biased nucleotide distribution in vertebrate mtDNA can cause overestimation of non-CpG methylation
Author: Okada, T.
Sun, X.
McIlfatrick, S.
St. John, J.C.
Citation: NAR Genomics and Bioinformatics, 2022; 4(1):1-17
Publisher: Oxford University Press (OUP)
Issue Date: 2022
ISSN: 2631-9268
2631-9268
Statement of
Responsibility: 
Takashi Okada, Xin Sun, Stephen McIlfatrick, and Justin C. St. John
Abstract: Mitochondrial DNA (mtDNA) methylation in vertebrates has been hotly debated for over 40 years. Most contrasting results have been reported following bisulfite sequencing (BS-seq) analyses. We addressed whether BS-seq experimental and analysis conditions influenced the estimation of the levels of methylation in specific mtDNA sequences. We found false positive non-CpG methylation in the CHH context (fpCHH) using unmethylated Sus scrofa mtDNA BS-seq data. fpCHH methylation was detected on the top/plus strand of mtDNA within low guanine content regions. These top/plus strand sequences of fpCHH regions would become extremely AT-rich sequences after BS-conversion, whilst bottom/minus strand sequences remained almost unchanged. These unique sequences caused BS-seq aligners to falsely assign the origin of each strand in fpCHH regions, resulting in false methylation calls. fpCHH methylation detection was enhanced by short sequence reads, short library inserts, skewed top/bottom read ratios and non-directional read mapping modes. We confirmed no detectable CHH methylation in fpCHH regions by BS-amplicon sequencing. The fpCHH peaks were located in the D-loop, ATP6, ND2, ND4L, ND5 and ND6 regions and identified in our S. scrofa ovary and oocyte data and human BS-seq data sets. We conclude that non-CpG methylation could potentially be overestimated in specific sequence regions by BSseq analysis.
Rights: © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
DOI: 10.1093/nargab/lqab119
Grant ID: http://purl.org/au-research/grants/nhmrc/1160106
Published version: http://dx.doi.org/10.1093/nargab/lqab119
Appears in Collections:Molecular and Biomedical Science publications

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