## 3 Results
While CpG methylation is the most studied form in the nuclear genome, its relevance in mtDNA is debated due to the low CpG content within mtDNA and the lack of a known mitochondrally targeted canonical CpG methyltransferase. However, studies utilizing direct detection methods have reported evidence of mtDNA methylation, predominantly in non-CpG contexts [22]. Therefore, our analysis focused on identifying all potential cytosine methylation events captured by the Dorado bascaller's MM and ML tags, specifically quantifying non-CpG methylation frequencies across the mitochondrial genome obtained from both adaptive sampling (AS) and whole genome sequencing (WGS) datasets. Modified bases were called only when the posterior probability was \(\geq\)0.80, thereby stringently filtering spurious signals that can arise from current drift or base-calling errors. Mean read depth and the corresponding non-CpG (CHH + CHG) methylation percentage were binned in 100 bp windows along the 16.6 kb molecule (Figure 10). Genome-wide profiles revealed that non-CpG methylation levels were consistently low across the vast majority of the mitochondrial genome in both sequencing approaches (Figure 10A,B; red lines). The percentage of non-CpG methylation rarely exceeded 5-10% at most positions, with the overall average being significantly lower. This observation of globally low non-CpG methylation stands in stark contrast to the sequencing coverage depth profiles (Figure 10A,B; light blue lines). The AS data exhibited highly variable coverage depth, characteristic of the targeted enrichment strategy, with sharp peaks in certain regions and lower coverage elsewhere (Figure 10A). Conversely, the WGS data showed much higher and relatively uniform coverage depth across the entire mitochondrial genome (Figure 10B). Despite these dramatic differences in coverage magnitude and distribution between the AS and WGS datasets, the detected levels and overall pattern of low non-CpG methylation remained remarkably similar. To directly assess the relationship between methylation detection and sequencing depth, we plotted the non-CpG methylation percentage against the mean coverage depth for each 1 bp window across the mitochondrial genome (Figure 10C,D). For both the AS dataset (Figure 10C), which spans a wide range of coverage depths, and the WGS dataset (Figure 10D), which primarily represents high coverage depths, the results were consistent. Non-CpG methylation percentages primarily cluster near zero, showing no apparent trend with increasing coverage depth. Quantitative Spearman correlation analysis confirmed this lack of a meaningful relationship, yielding very weak correlation coefficients (AS: \(\rho=-0.025\), \(p=2.0\,\times 10^{-5}\), \(n=16\),569; WGS: \(\rho=-0.028\), \(p=9.6\,\times 10^{-4}\), \(n=16\),569). Although the \(p\)-values are statistically significant due to the large number of data points, the correlation coefficients near zero strongly indicate that the detection of these low-level non-CpG methylation signals is not dependent on sequencing coverage depth. This supports the interpretation that the observed signals reflect characteristics of the underlying DNA rather than technical artifacts related to sequencing depth or the AS enrichment strategy.