Using computational modelling to reveal mechanisms of epigenetic Polycomb control

Area of Science:

• Epigenetics
• Molecular Biology
• Computational Biology

Background:

• The Polycomb system is crucial for stable gene silencing across organisms.
• Polycomb Repressive Complex 2 (PRC2) mediates silencing via H3K27me2/me3 histone modifications, acting as epigenetic memory.
• PRC2-based memory is a cis-acting system involving self-reinforcing feedback loops.

Purpose of the Study:

• To explore conditions enabling stable epigenetic memory, even during perturbations like DNA replication.
• To investigate the digital nature of Polycomb-mediated switching between active and silenced states.
• To review recent advances in computational models of Polycomb control.

Main Methods:

• Computational modeling to explore epigenetic memory mechanisms.
• Analysis of models predicting digital switching (on/off states) at Polycomb loci.
• Review of models incorporating transcriptional feedback and bivalent chromatin.

Main Results:

• Modeling predicts Polycomb-mediated switching and memory are digital, not graded.
• Self-reinforcing feedback from H3K27me2/me3 is key to stable cis-acting memory.
• Models incorporating transcriptional antagonism and bivalent states offer further insights.

Conclusions:

• Computational modeling is vital for understanding Polycomb control and epigenetic memory.
• Further quantitative data on histone modification kinetics and single-cell resolution will expand modeling's role.
• Interconnected memory mechanisms in Polycomb regulation require sophisticated modeling approaches.