Over the past decades, lineage tracing has been fundamental to unraveling how diverse cell types arise during development and how tumors evolve through clonal expansion. Traditional approaches largely depend on exogenous DNA barcodes, fluorescent proteins, or CRISPR-based recorders engineered into model organisms. However, these synthetic strategies require genetic manipulation, making them difficult to apply to native human clinical samples. Thus, developing versatile, non-invasive methods that can reconstruct the genealogical history of individual cells directly from patient tissues is crucial. The ideal approach should leverage endogenous, heritable markers that accumulate naturally within cells.

Recently, a team led by Dr. Zheng Hu from the Shenzhen Institute of Synthetic Biology, Chinese Academy of Sciences, published an article “Single-cell mitochondrial lineage tracing: Opportunities and challenges” in Quantitative Biology. They systematically examined how naturally occurring mitochondrial DNA (mtDNA) mutations can serve as intrinsic barcodes for high-resolution lineage tracing without any genetic engineering.

The review establishes that mtDNA is particularly well-suited for this purpose because it mutates 10- to 100-fold faster than the nuclear genome, is compact (16,569 bp), and is present in multiple copies per cell. The authors catalog current experimental platforms spanning two major categories: direct mtDNA-based methods (including scMito-seq, scSTAMP, mtscATAC-seq, and ReDeem) and mitochondrial cDNA-based approaches (such as Smart-Seq2, MutaSeq, and MAESTER), evaluating each for throughput, coverage, and multi-omics integration. They further dissect critical biological confounders—genetic drift, bottleneck effects, and horizontal mitochondrial transfer—and showcase next-generation computational tools (MQuad, MitoTracer, and LINEAGE) that move beyond simple frequency cutoffs to identify truly informative mutations. Their original simulations reveal that low-frequency variants, often discarded as noise, carry essential topological information for fine-scale phylogenetic reconstruction.

Figure 1 illustrates the principle of single-cell lineage tracing using endogenous mtDNA variants. Pre-existing mtDNA mutations reside in cells, while de novo mutations naturally arise and accumulate over successive cell divisions, creating heritable markers that define clonal populations and enable phylogenetic inference. When coupled with single-cell transcriptomics, this lineage information can be integrated with phenotypic readouts to reconstruct cellular trajectories. These findings highlight the transformative potential of endogenous mtDNA variants for minimally invasive lineage tracing in human tissues, and provide a practical roadmap for selecting appropriate experimental and computational frameworks across diverse biological scenarios.
DOI
10.1002/qub2.70018