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Peer-reviewedCC BY-NCNucleic Acids Research

BASELINE: a CRISPR base editing platform for mammalian-scale single-cell lineage tracing

  • Evan Winter1,2,3
  • Francesco E. Emiliani1,2,3
  • Aidan Cook2,4,5
  • Asma Abderrahim6,7
  • Aaron McKenna8,2,9
9 affiliations
  1. 1Molecular and Cellular Biology Program, Dartmouth College , Hanover, NH, 03756 ,
  2. 2Molecular and Systems Biology, Dartmouth College , Hanover, NH, 03755 ,
  3. 3Molecular and Cellular Biology Program, Dartmouth College
  4. 4Quantitative Biomedical Science Program, Dartmouth College , Lebanon, NH, 03756 ,
  5. 5Quantititaive Biomedical Science Program
  6. 6POWERED Program, Dartmouth Cancer Center, Dartmouth College , Lebanon, NH, 03756 ,
  7. 7POWERED Program, Dartmouth College
  8. 8Dartmouth Cancer Center, Dartmouth College , Lebanon, NH, 03755 ,
  9. 9Molecular and Systems Biology, Dartmouth College
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Abstract

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.

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Cite

BibTeXRIS
BibTeX
@article{winter2026baseline,
  title = {{BASELINE: a CRISPR base editing platform for mammalian-scale single-cell lineage tracing}},
  author = {Evan Winter and Francesco E. Emiliani and Aidan Cook and Asma Abderrahim and Aaron McKenna},
  journal = {Nucleic Acids Research},
  year = {2026},
  month = jul,
  doi = {10.1093/nar/gkag769},
  url = {https://doi.org/10.1093/nar/gkag769},
  note = {CC BY-NC},
}
RIS
TY  - JOUR
TI  - BASELINE: a CRISPR base editing platform for mammalian-scale single-cell lineage tracing
AU  - Evan Winter
AU  - Francesco E. Emiliani
AU  - Aidan Cook
AU  - Asma Abderrahim
AU  - Aaron McKenna
PY  - 2026
DA  - 2026/07/17
JO  - Nucleic Acids Research
DO  - 10.1093/nar/gkag769
UR  - https://doi.org/10.1093/nar/gkag769
AB  - 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.
SN  - 0305-1048
SN  - 1362-4954
SN  - 1362-4962
ER  -