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Updated: Jun 26, 2025

Loss- and Gain-of-function Approach to Investigate Early Cell Fate Determinants in Preimplantation Mouse Embryos

Loss- and Gain-of-function Approach to Investigate Early Cell Fate Determinants in Preimplantation Mouse Embryos

Published on: June 6, 2016

Automated profiling of gene function during embryonic development.

Rebecca A Green¹, Renat N Khaliullin², Zhiling Zhao²

¹Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA; Department of Cell and Developmental Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.

|May 17, 2024

Summary

This summary is machine-generated.

Researchers developed an automated 4D imaging method to analyze gene functions during C. elegans embryonic development. This approach generates phenotypic signatures to identify genes with similar functions, aiding the study of multicellular organism development.

Keywords:

FACT complex Integrator complex automated analysis cell fate specification computer vision de novo serine synthesis embryonic development energy generation phenotypic profiling tissue morphogenesis

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Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos

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Published on: February 22, 2016

Area of Science:

Developmental Biology
Genomics
Computational Biology

Background:

Understanding gene function in embryonic development is crucial but challenging.
Systematic functional profiling requires advanced imaging and analysis techniques.

Purpose of the Study:

To develop an automated approach for profiling gene function during C. elegans embryogenesis.
To create a resource for identifying genes with similar roles in development.

Main Methods:

Utilized 4D imaging of C. elegans embryogenesis.
Applied automated quantification of developmental phenotypes (cell numbers, tissue position, shape).
Developed numerical phenotypic signatures and a similarity metric for gene comparison.

Main Results:

Generated temporal phenotypic curves and signatures for ~25% of essential developmental genes.
Created ranked lists of genes with predicted similar functions, available via the PhenoBank web portal.
Identified novel gene/pathway relationships in cell fate specification, morphogenesis, and energy metabolism during embryogenesis.

Conclusions:

The automated phenotyping approach provides a foundation for comprehensive analysis of developmental genes.
This method enables discovery of new gene and pathway interactions.
Highlights the importance of energy pathways in embryonic development.