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Transition states and cell fate decisions in epigenetic landscapes

Nature Reviews Genetics volume 17, pages 693703 (2016) | Download Citation

Abstract

Waddington's epigenetic landscape is an abstract metaphor frequently used to represent the relationship between gene activity and cell fates during development. Over the past few years, it has become a useful framework for interpreting results from single-cell transcriptomics experiments. It has led to the proposal that, during fate transitions, cells experience smooth, continuous progressions of global transcriptional activity, which can be captured by (pseudo)temporal dynamics. Here, focusing strictly on the fate decision events, we suggest an alternative view: that fate transitions occur in a discontinuous, stochastic manner whereby signals modulate the probability of the transition events.

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Affiliations

  1. Naomi Moris and Alfonso Martinez Arias are at the Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.

    • Naomi Moris
    •  & Alfonso Martinez Arias
  2. Cristina Pina is at the Department of Haematology, University of Cambridge, Cambridge CB2 0PT, UK.

    • Cristina Pina

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The authors declare no competing financial interests.

Corresponding author

Correspondence to Alfonso Martinez Arias.

Glossary

Bifurcation theory

A branch of mathematics associated with dynamical systems that accounts for the evolution of a physical or biological system according to a control parameter.

Cell fate

The developmental destination of a cell if left undisturbed in its environment. The fate of a cell is more restricted than its potential.

Cell states

The transcriptional output of a gene regulatory network, with a variable degree of stability; development is characterized by sequences of cell states that culminate in specific fates.

Cellular potential

Biologically, potentials represent the range of fates into which a cell can develop. It is reduced during development and is obscured in, for example, lineage-tracing experiments, which only reveal fates. In physics, potential can be described as the ability to do work and represents an amount of energy stored for that purpose. In both biology and physics, it represents an ability to do something.

Dynamical systems

Systems defined by a number of related variables that evolve in time according to certain rules. A gene regulatory network is an example of a dynamical system in which the variables are the transcription factors that represent the nodes.

Epistasis analysis

A genetic technique in which analysis of the phenotype of double mutants allows an ordering of the temporal activity of the wild-type products of the mutated genes. This works best, and often only, in linear processes.

Gene expression heterogeneity

Variability in the expression of a gene or a group of genes across a population at single-cell resolution.

Gene regulatory networks

(GRNs). GRNs represent units of interacting proteins that are functionally constrained by defined regulatory relationships. These interactions provide a structure and determine an output in the form of a pattern of gene expression. GRNs are usually represented by nodes (proteins) and edges (their interactions).

Genetic programmes

Temporally ordered interactions between proteins, usually transcription factors, associated with the emergence of cell types.

Macrostate

A notion derived from statistical mechanics that defines the macroscopic state of a system (for example, a particular volume or temperature) and, in the case of a biological system, a functional state. Importantly, a macrostate can be observed and measured.

Microstate

A notion derived from statistical mechanics that defines a configuration of the elements that are associated with a particular macrostate of the system: for example, a molecular configuration associated with a particular volume or temperature. Any given macrostate may be associated with many different microstates. We surmise that gene expression profiles can be related to microstates in a biological context. These are often inferred.

Phase space

A geometrical representation of the possible states of a dynamical system as a function of the value of its variables. A simple example is the states of water in terms of pressure, temperature and volume. In a cell state, the 'phenotype' is represented by the levels of expression of the genes that are active in that state.

Pseudotime

A notion derived from the analysis of single-cell transcriptomes in a cell population that allows the ordering of individual cells based on minimal differences of their transcriptomes. It has an implicit assumption that the resulting order reflects a smooth and continuous change in the state of the cell and aims to relate this change to changes in gene expression.

Transition state

An intermediate state during cell fate decisions in which a cell exhibits a mixed identity between two or more states, which often represents the state of origin (that is, the initial state the cell is in) and that of destination (that is, the identity that the cell is adopting). It is highly unstable and reversible.

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https://doi.org/10.1038/nrg.2016.98

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