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Updated: Jan 21, 2026

Lineage Tracing of Inducible Fluorescently-Labeled Stem Cells in the Adult Mouse Brain
Published on: May 20, 2022
Strategies for resolving cellular phylogenies from sequential lineage tracing data
Nicola Mulberry1, Tanja Stadler1
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
New CRISPR-based lineage recorders capture cell history through heritable mutations. This study identifies conditions for accurately reconstructing cellular family trees using these dynamic recording systems.
Area of Science:
- Molecular Biology
- Genetics
- Bioinformatics
Background:
- Advancements in molecular recording devices and sequencing enable lineage tracing in thousands of cells.
- Dynamic lineage recorders utilize heritable mutations from CRISPR-based systems for continuous genetic recording.
- Sequential mutation acquisition is now possible, offering richer phylogenetic information than traditional methods.
Purpose of the Study:
- To model sequentially-edited recording systems.
- To analyze experimental conditions for accurate phylogenetic reconstruction.
- To understand the information content of dynamic lineage recorders.
Main Methods:
- Modeling of a sequentially-edited recording system.
- Theoretical analysis and simulation of mutation accumulation and phylogenetic reconstruction.
- Identification of parameter regimes for accurate lineage tracing.
Main Results:
- Explicit parameter regimes were identified where distance-based methods accurately resolve cellular phylogeny.
- The study found conditions enabling high-probability exact phylogenetic reconstruction.
- Theoretical results can guide experimental design for lineage tracing studies.
Conclusions:
- Simple, efficient reconstruction methods can accurately resolve cellular phylogeny under specific conditions.
- Understanding recorder information content is crucial for advancing lineage tracing.
- This work provides a framework for optimizing experimental design in CRISPR-based lineage tracing.
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