Cell lineage inference from mitochondrial mutations

Tissues and organs develop from single founder cells, which give rise to distinct cell lineages that contribute to regeneration and maintenance of homeostasis in the adult. Tracing the genealogical relationships between individual cells and their gene expression signatures is an important step towards understanding how these processes are regulated in human health and disease. Here, we present mt-SCITE, a computational method for inferring the evolutionary history of dividing cells based on mitochondrial mutations detected in single cells. We show that mt-SCITE outperforms existing methods in accurately estimating the correct mitochondrial mutation tree from simulated data. To validate our method, we applied mt-SCITE on in vitro expanded T-cells profiled with bulk ATAC sequencing, where the clonal relationships were determined independently from T cell receptor sequences. We used our method to reconstruct the division histories and transcriptional heterogeneity of clonally related CD8+ T cells from single-cell RNA sequencing data obtained from a healthy human donor. This allowed us to track the in vivo development of CD8+ T cell clones post vaccination and resolve subclonal lineage relationships without the need for genetic barcoding. Our analysis revealed that T cell clones can adopt predominantly memory-like or effector-like states, while some exhibit mixed identities. Taken together, our method represents a novel approach to study cell lineage development in humans.