## 4 Discussion
Similar integrative methods have already been applied in the nuclear genome: Using nanopore reads, researchers have phased methylation patterns with SNP haplotypes to reveal allele-specific methylation in human chromosomes [48]. Yet, applying these techniques to mtDNA remains challenging. Mitochondrial methylation levels are very low and sometimes controversial [22; 49; 50], making true signals hard to distinguish from noise. Most controversy stems from CpG specifically targeted detection by most methods, including early DNA methylation detection algorithms, like Nanopolish and Megalodon, as shown by the higher DNA methylation within Guppy basecalling reads [50]. Novel Dorado modes are better suited to detect 5 meC, but perhaps other non-CpG modifications (like 6 mA) should be specifically trained to enable proper and verifiable detection. Substantial evidence argues against widespread, functional CpG methylation in mammalian mtDNA. This scarcity might be linked to the potential gene silencing effects such methylation could exert within the extremely compact mitochondrial genome, combined with the lack of known canonical CpG methyltransferases targeted to mitochondria [51]. This is in stark contrast to the nuclear genome where CpG methylation is a fundamental epigenetic mark. Consequently, earlier studies or methods focusing primarily or solely on CpG methylation might have provided an incomplete picture or underestimated other forms of modification [50]. Additionally, specialized bioinformatics tools are needed to handle the circular mtDNA and to jointly analyze heteroplasmy with methylation. Our approach addresses these gaps by using algorithms tailored to mtDNA's unique characteristics, allowing us to simultaneously assess sequence heteroplasmy and methylation on single molecules. This represents a methodological advance in the emerging field of mitochondrial epigenomics, laying the groundwork for deeper insights into mtDNA regulation in aging and disease. Building on our findings that nanopore adaptive sampling effectively decouples base modification detection from sequencing coverage artifacts (as suggested by the analysis in Figure 10C,D), our data support the detection of genuine, albeit low-level, non-CpG methylation signals directly from native mtDNA molecules. Our analysis pipeline, utilizing Dorado basecalling with MM and ML tags to identify cytosine modifications (Figure 10), revealed globally low levels of methylation, predominantly appearing independent of CpG context. This finding aligns with studies such as [PERSON] et al. [22] which used orthogonal methods and also concluded that non-CpG (CpH) methylation is the more prevalent, though still potentially sparse, form in human mtDNA. While our study lacks independent validation (a limitation discussed previously), the observation of consistent low-level patterns irrespective of coverage depth (Figure 10A vs. Figure 10B) or sequencing strategy (AS vs WGS, Figure 10C vs. Figure 10D) lends support to these signals reflecting features of the sequenced molecules rather than mere technical noise. Furthermore, the potential functional relevance of _maintaining low_ mtDNA methylation levels is underscored by studies indicating that artificial or pathological _hypermethylation_ can perturb mitochondrial gene expression and function [31]. For instance, hypermethylation of genes like ND6 observed under specific pathological conditions associated with obesity models appeared detrimental [52], suggesting that significant increases above baseline methylation might be functionally disruptive. [PERSON] et al. [PERSON] considers mtDNA methylation as technical artifact of low sequencing coverage [49]. Interestingly, AS application produces specific co-occurrence patterns between genetic variants and methylation marks, particularly in functionally significant regions like the D-loop.