Theoretical modeling on CRISPR-coded cell lineages: efficient encoding and optimal reconstruction

Abstract

Delineating cell lineages is a prerequisite for understanding the genesis of cell types. Recent studies have demonstrated the feasibility of generating and reconstructing CRISPR/Cas9-coded cell lineages. However, these works have not investigated the limitations or optimality of the encoding or reconstruction processes. Here, we surveyed a multitude of reconstruction algorithms and found hierarchical clustering, with a metric based on the number of shared Cas9 edits, provides the best reconstruction. As to the efficiency, the simple encoding method, with constant Cas9/gRNA edit rate, produces exponential reduction in available coding units and severely limits the trackable depth of lineages. To overcome this, we propose alternative encoding methods, one based on parallel gRNA cascades enabled by CLADES, and another based on variable Cas9 editing rate. Both significantly increase the trackable depth. In summary, we provide a theoretical basis in understanding, designing and analyzing efficient and robust CRISPR-based cell lineage tracking system.