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Immunostaining for DNA Modifications: Computational Analysis of Confocal Images
Published on: September 7, 2017
Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal
Alayne L Brunner1, David S Johnson, Si Wan Kim
1Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA.
Genome Research
|March 11, 2009
Summary
Human embryonic stem cell (hESC) differentiation shows unique DNA methylation patterns, differing from in vivo development. Methyl-seq reveals minimal DNA methylation changes but distinct regulatory region involvement during hESC differentiation.
Area of Science:
- Epigenetics
- Developmental Biology
- Genomics
Background:
- DNA methylation is crucial for cellular differentiation and development.
- Understanding epigenetic regulation in human development is essential.
Purpose of the Study:
- To investigate DNA methylation dynamics during human development using a novel method.
- To compare DNA methylation changes during in vitro human embryonic stem cell (hESC) differentiation and in vivo fetal liver development.
Main Methods:
- Development and application of Methyl-seq, a genome-wide DNA methylation assay covering over 90,000 regions.
- Analysis of DNA methylation patterns in hESCs, their derivatives, and human tissues.
Main Results:
- Differentiation involves DNA methylation changes in a small fraction of assayed regions (2%-11%).
- In vitro hESC differentiation exhibits both de novo methylation and demethylation.
- In vivo fetal liver development is primarily characterized by demethylation.
- hESC differentiation uniquely affects H3K27me3-occupied regions, bivalent domains, and low CpG promoters (LCPs).
- These specific regions become highly unmethylated during in vivo liver development, contrasting with hESC trends.
Conclusions:
- hESC differentiation possesses a distinct DNA methylation signature.
- This signature may not accurately reflect in vivo differentiation processes.
- Specific epigenetic marks and regions are key to understanding differentiation trajectories.
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