Date of Award
Winter 10-30-2025
Document Type
Thesis (Ph.D.)
Department or Program
Molecular and Systems Biology
First Advisor
Aaron McKenna
Second Advisor
Duane Compton
Third Advisor
Margaret Ackerman
Abstract
Lineage tracing technologies enable the reconstruction of developmental and disease trajectories, yet existing approaches face limitations in recorder capture, information loss, and scalability. Here, we present BASELINE, a dynamic lineage tracing system designed to address these challenges. BASELINE recorders can be selectively amplified and recovered alongside transcriptomes during single-cell sequencing, enabling direct linkage of lineage and cell state. By employing a base editor rather than a double-strand break–inducing nuclease, BASELINE minimizes multi-site deletions and preserves recorder integrity, while still generating sufficient diversity for accurate tree reconstruction. The relatively low editing efficiency of base editing combined with our 50-target array further supports extended temporal recording. Importantly, BASELINE is compatible with CRISPR-based perturbation screens through the use of Cas12a, allowing simultaneous functional interrogation and lineage reconstruction. Finally, we establish a workflow for direct Nanopore sequencing of full-length lineage recorders, enabling affordable long-read characterization of recorder diversity. We validate BASELINE using pancreatic cancer cells and pursued recording developmental lineage in iPSC-derived cerebral organoids. This work establishes a framework for scalable, high-fidelity lineage tracing that integrates seamlessly with single-cell genomics.
Recommended Citation
Winter, Evan, "Rewriting the Record: A Base Editing Framework for Scalable Lineage Tracing" (2025). Dartmouth College Ph.D Dissertations. 452.
https://digitalcommons.dartmouth.edu/dissertations/452
