Nucleic acids researchAug 4, 2026

BASELINE: A gene-editing tool to track individual cell development in mammals

CRISPR Gene Editing Weekly Brief ↗PubMed ↗DOI ↗OA ↗

Updated Aug 5, 2026

Abstract

BASELINE can record more than 4300 bits of lineage information in a model of pancreatic cancer.

BASELINE employs a specific base editor to permanently modify nucleotides at 50 synthetic sites in a cell's genome.
The technology captures lineage-specific marks over various biologically relevant timeframes.
On average, 29 cell divisions are recorded per lineage, which aligns with typical mammalian developmental ranges.
BASELINE offers a significant 50-fold improvement in information capture compared to previous lineage-tracing methods.
This method shows potential for diverse applications in studying development and disease, particularly in complex cellular systems.

Simplified

A cell's fate is shaped by its inherited state, or lineage, and the ever-shifting context of its environment. CRISPR-based recording technologies are a promising solution for mapping the lineage of a developing system; however, challenges remain regarding single-cell recovery, engineering complexity, and scale. Here, we introduce BASELINE, which uses base editing to generate high-resolution lineage trees in conjunction with single-cell profiling. BASELINE uses the Cas12a adenine base editor to irreversibly edit nucleotides across target arrays built from 50 synthetic target sites, which are integrated multiple times into a cell's genome. We demonstrate that BASELINE accumulates lineage-specific marks over a wide range of biologically relevant intervals, recording more than 4300 bits of information in a model of pancreatic cancer, a 50-fold increase over existing technologies. Single-cell sequencing reveals high-fidelity capture of these recorders, averaging 29 cell divisions captured per lineage, within the estimated range of mammalian development. We expect BASELINE to apply to a wide range of lineage-tracing projects in development and disease, especially those in which cellular engineering makes small, more distributed systems challenging.