Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Lineage Commitment

Lineage Commitment

Commitment is the process whereby stem cells:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Longitudinal lineage tracing reveals early clonal attrition during Drosophila midgut aging.

PLoS biology·2026

Same author

Rapid evolution driven by translocation-associated selection during meiosis.

EMBO reports·2026

Same author

DIAG: A Framework for Evaluating Whole-Genome Amplification Quality in Single-Cell SNV Analysis.

Biology·2026

Same author

Computational approaches for multimodal lineage tracing.

Nature reviews. Genetics·2026

Same author

Mapping the zygote-to-adult developmental cell phylogeny in Arabidopsis thaliana reveals a three-cell rule of branching.

Nature plants·2026

Same author

The Trait Coding Rule in Phenotype Space.

Phenomics (Cham, Switzerland)·2026

Same journal

ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.

Nature methods·2026

Same journal

RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.

Nature methods·2026

Same journal

Spatio-DARLIN enables robust and efficient in situ lineage tracing in mice at single-cell resolution.

Nature methods·2026

Same journal

EasyGrid: a versatile platform for automated cryo-EM sample preparation and quality control.

Nature methods·2026

Same journal

Cloud-based microscope enables live neuroimaging for 24 h and beyond with worldwide access.

Nature methods·2026

Same journal

Deep molecular profiling in three dimensions.

Nature methods·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 2, 2025

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Published on: March 24, 2023

A statistical method for quantifying progenitor cells reveals incipient cell fate commitments.

Shanjun Deng¹, Han Gong¹, Di Zhang¹

¹MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China.

|February 21, 2024

Summary

This summary is machine-generated.

This study introduces targeting coalescent analysis (TarCA), a novel statistical method to quantify progenitor cells using cell phylogenetic trees, even without specific markers. TarCA accurately estimates progenitor numbers and identifies lineage-specific gene expression during development.

More Related Videos

Identification and Isolation of Oligopotent and Lineage-committed Myeloid Progenitors from Mouse Bone Marrow

Identification and Isolation of Oligopotent and Lineage-committed Myeloid Progenitors from Mouse Bone Marrow

Published on: July 29, 2018

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

Related Experiment Videos

Last Updated: Jul 2, 2025

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Published on: March 24, 2023

Identification and Isolation of Oligopotent and Lineage-committed Myeloid Progenitors from Mouse Bone Marrow

Identification and Isolation of Oligopotent and Lineage-committed Myeloid Progenitors from Mouse Bone Marrow

Published on: July 29, 2018

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

Area of Science:

Developmental Biology
Computational Biology
Genetics

Background:

Quantifying progenitor cells is crucial for understanding organism development and homeostasis.
Existing methods often rely on specific marker genes, which are not always available.
A general method is needed to estimate progenitor numbers across diverse tissues and cell populations.

Purpose of the Study:

To develop a general statistical method for quantifying progenitor cells without requiring specific markers.
To utilize cell phylogenetic trees to infer progenitor numbers.
To validate the method's accuracy and applicability in various organisms.

Main Methods:

Developed targeting coalescent analysis (TarCA), a statistical method using cell phylogenetic trees.
TarCA calculates the probability of cell coalescence within tissue-specific clades.
The inverse of this probability estimates the progenitor cell number.

Main Results:

Mathematical modeling and computer simulations confirmed TarCA's high accuracy.
TarCA was successfully validated using real data from nematode, fruit fly, and mouse.
The method identified lineage-specific upregulated genes during embryogenesis, revealing early cell fate commitments.

Conclusions:

Targeting coalescent analysis (TarCA) provides a robust and generalizable approach to quantify progenitor cells.
This method overcomes limitations of marker-based approaches in developmental and homeostatic studies.
TarCA has potential applications in identifying developmental gene expression patterns and cell fate decisions.