Strategies for resolving cellular phylogenies from sequential lineage tracing data

A combination of recent advancements in molecular recording devices and sequencing technologies has made it possible to generate lineage tracing data on the order of thousands of cells. Dynamic lineage recorders are able to generate random, heritable mutations which accumulate continuously on the timescale of developmental processes; this genetic information is then recovered using single-cell RNA sequencing. These data have the potential to hold rich phylogenetic information due to the irreversible nature of the editing process, a key feature of the employed CRISPR-based systems that deviates from traditional assumptions about molecular mutation processes. Recent technologies have furthermore made it possible for mutations to be acquired sequentially. Understanding the information content of these recorders remains an open area of investigation. Here, we model a sequentially-edited recording system and analyse the experimental conditions over which exact phylogenetic reconstruction occurs with high probability. We find, using simulation and theory, explicit parameter regimes over which simple and efficient distance-based reconstruction methods can accurately resolve the cellular phylogeny. We furthermore illustrate how our theoretical results could be used to help inform experimental design.