Reconstructing an epigenetic landscape using a genetic `pulling' approach

TL;DR

This paper introduces a novel nonequilibrium perturbation method to reconstruct epigenetic landscapes, enabling the study of cell state transitions and regulatory networks with fewer experiments, advancing understanding of developmental dynamics.

Contribution

The paper presents a new theoretical and computational approach to reconstruct epigenetic landscapes from limited perturbation data, providing a general framework for studying cell state stability.

Findings

Accurately reconstructs epigenetic landscapes from simulated perturbation data.

Demonstrates that few experiments suffice for landscape recovery.

Suggests perturbation impulse as a key quantity in developmental switches.

Abstract

Cells use genetic switches to shift between alternate stable gene expression states, e.g., to adapt to new environments or to follow a developmental pathway. Conceptually, these stable phenotypes can be considered as attractive states on an epigenetic landscape with phenotypic changes being transitions between states. Measuring these transitions is challenging because they are both very rare in the absence of appropriate signals and very fast. As such, it has proven difficult to experimentally map the epigenetic landscapes that are widely believed to underly developmental networks. Here, we introduce a new nonequilibrium perturbation method to help reconstruct a regulatory network's epigenetic landscape. We derive the mathematical theory needed and then use the method on simulated data to reconstruct the landscapes. Our results show that with a relatively small number of perturbation experiments it is possible to recover an accurate representation of the true epigenetic landscape. We propose that our theory provides a general method by which epigenetic landscapes can be studied. Finally, our theory suggests that the total perturbation impulse required to induce a switch between metastable states is a fundamental quantity in developmental dynamics.