Strategies for resolving cellular phylogenies from sequential lineage tracing data.

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.