Understanding the forces that direct cell fate is a central goal of biology. Many fundamental questions remain unanswered and vast tracts of vertebrate development are almost completely unexplored. What are the developmental origins and lineage relationships of cell types? What, where, and when are the key molecular events that underlie cell fate transitions? These questions remain unanswered as we lack the technology to map cell fate in both high-throughput and high-resolution. The overall objective of the proposed work is to develop and apply novel technologies that track and translate the cell fate forces into human-decipherable recordings. Our proposal combines innovative use of new CRISPR systems, molecular recording technologies, and improvements to our established lineage tracing technology to reconstruct high accuracy, annotated lineage trees. We will apply these cell fate technologies in mouse embryonic stem cells (mESCs), where we will track differentiation into various progeny cells, generating both transcriptional and lineage maps describing the probabilistic relationship between intestinal cell types at high-resolution. We will then expand these systems into recording mouse lines, where both molecular and lineage recordings can be captured from terminally differentiated cells. In aggregate, the resulting high-resolution lineage maps and tools will provide new insight into the plasticity of cell fate, and these recording mouse lines will be a valuable resource to the biomedical community. We believe these trailblazing technologies will ultimately spur the development of novel fate modulators with application to human disease.

Development starts from a single transformed cell, which ultimately divides into a mix of cells with many unique roles in the body. It’s hard to fully understand this process as we currently do not have a global cell fate map that describes this process. Here we propose inroads towards such a map, using improved versions of our CRISPR lineage tracing approach with molecular recording technologies to track cell fate. We will create these maps in generated mouse lines, providing new insight into how cellular roles are chosen and how overlapping cellular programs shape diverse tissues and organs.