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Lineage Commitment

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During embryogenesis, cells become progressively committed to different fates through a two-step process: specification followed by determination. Specification is demonstrated by removing a segment of an early embryo, “neutrally” culturing the tissue in vitro—for example, in a petri dish with simple medium—and then observing the derivatives. If the cultured region gives rise to cell types that it would normally generate in the embryo, this means that it is specified. In...

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Related Experiment Video

Updated: Jan 9, 2026

Lineage Tracing of Inducible Fluorescently-Labeled Stem Cells in the Adult Mouse Brain

Lineage Tracing of Inducible Fluorescently-Labeled Stem Cells in the Adult Mouse Brain

Published on: May 20, 2022

Inferring cell differentiation maps from lineage tracing data.

Palash Sashittal^1,2, Richard Y Zhang³, Benjamin K Law^3,4

¹Department of Computer Science, Princeton University, Princeton, NJ, USA.

|December 8, 2025

Summary

This summary is machine-generated.

Carta infers optimal cell differentiation maps from lineage tracing data. This new algorithm reveals key developmental features like convergent differentiation and intermediate progenitors, improving our understanding of cell development.

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Last Updated: Jan 9, 2026

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Area of Science:

Developmental Biology
Computational Biology
Genomics

Background:

Cell differentiation follows a hierarchy, visualized by cell differentiation maps.
Current methods for inferring these maps from large-scale data use heuristic models with limitations.
These existing models often make restrictive assumptions about developmental processes.

Purpose of the Study:

Introduce a quantitative framework to evaluate cell differentiation maps.
Develop an algorithm, Carta, to infer an optimal differentiation map from single-cell lineage tracing data.
Address limitations of existing heuristic models in developmental biology.

Main Methods:

Developed Carta, an algorithm inferring optimal differentiation maps.
Employed a quantitative framework for evaluating cell differentiation maps.
Utilized single-cell lineage tracing data for algorithm training and validation.

Main Results:

Carta balances map complexity with unobserved cell type transitions.
Identified convergent differentiation of cell types in mammalian trunk development.
Revealed progenitor differentiation dynamics and new intermediate progenitors in mouse hematopoiesis.

Conclusions:

Carta provides a novel approach to inferring cell differentiation maps.
The algorithm uncovers crucial developmental features missed by other methods.
This work advances the understanding of cell differentiation dynamics and progenitor identification.