## 4 Discussion
However, short reads also possess multiple limitations and are unable to detect complex rearrangements and heteroplasmic levels [27]. They also have limitations in resolving low-frequency variants and homopolymeric regions, which are often included within the mt genome as stretches of the same base, like AAAAA and as repetitive sequences. This can lead to errors in variant calling and gaps in the coverage [28]. For these reasons, there is a diagnostic need for appropriate methods to investigate mtDNA. Long-read sequencing techniques are particularly suitable for applications where a more complete and detailed understanding of the genome is needed, because of some features like the ability to sequence through repetitive and homopolymeric regions, the improved accuracy in detecting structural variants, the better assembly of complex genomes, and the accurate detection of heteroplasmy [20; 29]. Furthermore, they sequence native molecules, which allows them to detect epigenetic modifications [19; 30; 31] that are likely to play a crucial role in the future diagnosis of mitochondrial diseases, thus enhancing its clinical utility. Progress in flow cells and chemistry has further improved sequencing accuracy, offering better detection of low-level heteroplasmy. Precise quantification of the heteroplasmy level is extremely important because it classifies certain variants as the likely cause of the disease or as a benign polymorphism. Despite the high copy number mitochondria per cell, mtDNA contributes only with 0.1-0.2% of the total DNA amount. This is why previous sequencing methods rely on PCR amplification [32; 33]. PCR, however, can introduce biases, especially if there are regions with varying GC content, leading to uneven coverage across the mtDNA genome. This can also complicate the detection and quantification of mtDNA variants, especially in samples with heteroplasmy. Adaptive sampling is a method of software-controlled enrichment unique to nanopore sequencing platforms [34]. It allows for simple enrichment by loading a BED file of a target region. By sequencing the first 400-500 bp of a DNA library, adaptive sampling software can identify reads containing target region or not and pass only these fragments that contain the target region. Adaptive sampling is a relatively new bioinformatic tool [35] but is being more and more explored for mitochondrial DNA analysis, because all published data clearly show that it consistently enriches reference sequences. Moreover, long-read sequencing of mtDNA can be considered a consistently accurate approach for the identification of subjects based on their mtDNA haplogroup/haplotype (for forensic purposes or population genetics). We are aware of other studies that used adaptive sampling of ONT to analyze mitochondrial DNA; however, none of them performed the analysis with mesenchymal stem cells (MSC). Mesenchymal stem cells are non-hematopoietic progenitors that are found in various tissues, most commonly in bone marrow, but also in adipose tissue, umbilical cord tissue, dental pulp, and other sites. They can differentiate into multiple lineages, which makes them very promising tool for therapeutic applications. Unfortunately, their regenerative potential decreases during ageing [18; 36]. Therefore, therapeutic approaches have been investigated and already proposed to either eliminate, revitalize, or substitute senescent MSCs. Decline in mitochondrial function and biogenesis and the accumulation of mtDNA mutations are the primary reasons for ageing [37]. MtDNA mutations are known to accumulate in stem cell populations [38], accompanied by an increase in the somatic mutations [39]. However, the isolation of good quality and a good amount of MSC remains a challenge. AdMSC are a relatively abundant source, with high proliferative capacity and easy harvesting, making them extremely suitable for different applications in regenerative medicine. Another thing is that obesity and obesity-related complications have become more serious issues, affecting people all over the world [40].