Quantitative fate mapping: A general framework for analyzing progenitor state dynamics via retrospective lineage...

Area of Science:

• Developmental Biology
• Genomics
• Computational Biology

Background:

• Somatic mutations in the genome record cellular phylogenetic relationships during development.
• Understanding progenitor cell dynamics and their commitment biases remains a challenge.

Purpose of the Study:

• To develop a quantitative fate mapping approach for reconstructing progenitor cell states and dynamics.
• To introduce Phylotime, a scalable method for reconstructing time-scaled phylogenies from lineage barcodes.

Main Methods:

• Quantitative fate mapping based on time-scaled phylogenies of descendant cells.
• Phylotime: a scalable maximum likelihood clustering approach using a barcoding mutagenesis model.
• Validation using in silico and in vitro barcoding experiments.

Main Results:

• Reconstruction of progenitor cell hierarchy, commitment times, population sizes, and biases.
• Establishment of criteria for robust quantitative fate mapping and progenitor state coverage.
• Demonstration of lineage barcodes for analyzing post-embryonic progenitor fate.

Conclusions:

• Quantitative fate mapping provides a powerful framework for studying developmental dynamics.
• Lineage barcodes, natural or synthetic, are valuable tools for understanding cell fate and dynamics across organisms.
• The Phylotime method enables scalable phylogenetic reconstruction from barcoding data.