Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Pattern formation along signaling gradients driven by active droplet behavior of cell swarms.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Stochastic processes in development and disease.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2024
Same author

Content-aware frame interpolation (CAFI): deep learning-based temporal super-resolution for fast bioimaging.

Nature methods·2024
Same author

Collective signalling drives rapid jumping between cell states.

Development (Cambridge, England)·2023
Same author

Clearing the slate: RNA turnover to enable cell state switching?

Development (Cambridge, England)·2023
Same author

Controlling periodic long-range signalling to drive a morphogenetic transition.

eLife·2023
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 2025

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria
06:08

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Published on: January 25, 2019

12.9K

Single Cell Transcriptome Analysis During Development in Dictyostelium.

Vlatka Antolović1, Jonathan R Chubb2

  • 1UCL Laboratory for Molecular Cell Biology, University College London, London, UK. v.antolovic@ucl.ac.uk.

Methods in Molecular Biology (Clifton, N.J.)
|July 2, 2024
PubMed
Summary
This summary is machine-generated.

Dictyostelium discoideum, a simple model organism, aids in understanding cell decision-making during development. Single-cell transcriptomics reveals gene expression dynamics driving cell fate determination in this model.

Keywords:
Big dataBioinformaticsDevelopmentRNA sequencingSingle cell transcriptomicsStochastic gene expressionTranscription bursting

More Related Videos

High-throughput Measurement of Dictyostelium discoideum Macropinocytosis by Flow Cytometry
06:47

High-throughput Measurement of Dictyostelium discoideum Macropinocytosis by Flow Cytometry

Published on: September 10, 2018

7.7K
Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

29.8K

Related Experiment Videos

Last Updated: Jun 22, 2025

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria
06:08

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Published on: January 25, 2019

12.9K
High-throughput Measurement of Dictyostelium discoideum Macropinocytosis by Flow Cytometry
06:47

High-throughput Measurement of Dictyostelium discoideum Macropinocytosis by Flow Cytometry

Published on: September 10, 2018

7.7K
Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

29.8K

Area of Science:

  • Developmental Biology
  • Cell Biology
  • Genomics

Background:

  • Dictyostelium serves as a simplified model for studying cellular development and decision-making.
  • Its short life cycle and limited cell types facilitate complex biological process analysis.
  • Single-cell transcriptomics is crucial for dissecting developmental transitions and cell fate divergence.

Purpose of the Study:

  • To outline methods for analyzing Dictyostelium single-cell transcriptomic data.
  • To demonstrate how these analyses enhance understanding of cell decision-making.
  • To highlight the utility of Dictyostelium as a model for developmental studies.

Main Methods:

  • Single-cell isolation and transcriptomic profiling of Dictyostelium.
  • Development and application of analysis tools for large transcriptomic datasets.
  • Investigating gene expression patterns during developmental transitions.

Main Results:

  • Single-cell transcriptomics effectively defines developmental transitions and cell fate separation events.
  • Non-disruptive cell isolation enables physiological transcript level measurements.
  • Simplified cell states in Dictyostelium allow for robust data analysis and confident inferences.

Conclusions:

  • Dictyostelium single-cell transcriptomic data analysis provides causal insights into gene expression and cell fate.
  • The model organism facilitates a deeper understanding of the fundamental mechanisms of cell decision-making.
  • Methodological approaches detailed in this chapter are broadly applicable to developmental transcriptomics.