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The function of chromatin modifiers in lineage commitment and cell fate specification.

Signolet J, Hendrich B - FEBS J. (2014)

Bottom Line: Yet functional details of why these proteins are important, i.e. how their action influences a given biological process, are lacking.In this essay we consider the impact of two abundant and highly conserved chromatin modifying complexes, namely the nucleosome remodelling and deacetylation (NuRD) complex and the polycomb repressive complex 2 (PRC2), on the change in GRNs associated with lineage commitment during early mammalian development.We propose that while the NuRD complex limits the stability of cell states and defines the developmental trajectory between two stable states, PRC2 activity is important for stabilizing a new GRN once established.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, UK.

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ES cell differentiation landscape. Model in which the GRN is indicated as a 3D surface, with all possible gene expression combinations existing as discrete coordinates in 2D state space. Some coordinates (meaning combinations of expression patterns) are more likely or more stable than others, and are called ‘attractors’. For example, in (A) positions 1 and 2 indicate stable or highly probable attractor states, whereas position 3 indicates a very unstable/unlikely position. Position 1 in (A) represents self-renewing cells in 2i/LIF conditions and position 2 represents ES cells in serum/LIF conditions. Upon loss of self-renewal signals (B), the resulting GRN no longer favours attractors 1 or 2, which become very unstable. In contrast attractors 4, 5 and 6 have become more stable and can attract cells traversing the landscape. These would represent entry points into different differentiation pathways. During normal development cells can only move from left to right in this model. Moving from right to left would only occur during experimental reprogramming. NuRD activity is predicted to limit the depth of the attractors and/or define the trajectories, displayed here as troughs, between attractors. PRC2 function is proposed to be required to stabilize/maintain the attractors.
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fig01: ES cell differentiation landscape. Model in which the GRN is indicated as a 3D surface, with all possible gene expression combinations existing as discrete coordinates in 2D state space. Some coordinates (meaning combinations of expression patterns) are more likely or more stable than others, and are called ‘attractors’. For example, in (A) positions 1 and 2 indicate stable or highly probable attractor states, whereas position 3 indicates a very unstable/unlikely position. Position 1 in (A) represents self-renewing cells in 2i/LIF conditions and position 2 represents ES cells in serum/LIF conditions. Upon loss of self-renewal signals (B), the resulting GRN no longer favours attractors 1 or 2, which become very unstable. In contrast attractors 4, 5 and 6 have become more stable and can attract cells traversing the landscape. These would represent entry points into different differentiation pathways. During normal development cells can only move from left to right in this model. Moving from right to left would only occur during experimental reprogramming. NuRD activity is predicted to limit the depth of the attractors and/or define the trajectories, displayed here as troughs, between attractors. PRC2 function is proposed to be required to stabilize/maintain the attractors.

Mentions: Development is often described as if it is deterministic: zygote becomes morula becomes blastocyst etc. But, as alluded to above, there is a degree of stochasticity in development which is probably attributable to a combination of the often small numbers of each chemical species and biological noise [25,28,39]. This apparent paradox between developmental predictability and stochasticity can be resolved by considering the behaviour of a cell as a dynamical system [38,40,41]. One way of doing this based purely on gene expression is to categorize a cell's type by measuring its gene expression profile and assigning a cell state, S. The cell state is jointly defined by the expression of all genes in the genome x1, x2, …, xN, and so each state S = [x1, x2, …, xN] represents a coordinate in state space (Fig.1) [38]. Using this dynamical systems conception, different cell types thus occupy different regions in state space, and changes in expression are accompanied by the movement of S along one of a set of trajectories. GRNs include many nodes (genes) which directly influence the expression of other nodes, namely the transcription factors [42–44]. By nature this restricts the scope of potential trajectories.


The function of chromatin modifiers in lineage commitment and cell fate specification.

Signolet J, Hendrich B - FEBS J. (2014)

ES cell differentiation landscape. Model in which the GRN is indicated as a 3D surface, with all possible gene expression combinations existing as discrete coordinates in 2D state space. Some coordinates (meaning combinations of expression patterns) are more likely or more stable than others, and are called ‘attractors’. For example, in (A) positions 1 and 2 indicate stable or highly probable attractor states, whereas position 3 indicates a very unstable/unlikely position. Position 1 in (A) represents self-renewing cells in 2i/LIF conditions and position 2 represents ES cells in serum/LIF conditions. Upon loss of self-renewal signals (B), the resulting GRN no longer favours attractors 1 or 2, which become very unstable. In contrast attractors 4, 5 and 6 have become more stable and can attract cells traversing the landscape. These would represent entry points into different differentiation pathways. During normal development cells can only move from left to right in this model. Moving from right to left would only occur during experimental reprogramming. NuRD activity is predicted to limit the depth of the attractors and/or define the trajectories, displayed here as troughs, between attractors. PRC2 function is proposed to be required to stabilize/maintain the attractors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508967&req=5

fig01: ES cell differentiation landscape. Model in which the GRN is indicated as a 3D surface, with all possible gene expression combinations existing as discrete coordinates in 2D state space. Some coordinates (meaning combinations of expression patterns) are more likely or more stable than others, and are called ‘attractors’. For example, in (A) positions 1 and 2 indicate stable or highly probable attractor states, whereas position 3 indicates a very unstable/unlikely position. Position 1 in (A) represents self-renewing cells in 2i/LIF conditions and position 2 represents ES cells in serum/LIF conditions. Upon loss of self-renewal signals (B), the resulting GRN no longer favours attractors 1 or 2, which become very unstable. In contrast attractors 4, 5 and 6 have become more stable and can attract cells traversing the landscape. These would represent entry points into different differentiation pathways. During normal development cells can only move from left to right in this model. Moving from right to left would only occur during experimental reprogramming. NuRD activity is predicted to limit the depth of the attractors and/or define the trajectories, displayed here as troughs, between attractors. PRC2 function is proposed to be required to stabilize/maintain the attractors.
Mentions: Development is often described as if it is deterministic: zygote becomes morula becomes blastocyst etc. But, as alluded to above, there is a degree of stochasticity in development which is probably attributable to a combination of the often small numbers of each chemical species and biological noise [25,28,39]. This apparent paradox between developmental predictability and stochasticity can be resolved by considering the behaviour of a cell as a dynamical system [38,40,41]. One way of doing this based purely on gene expression is to categorize a cell's type by measuring its gene expression profile and assigning a cell state, S. The cell state is jointly defined by the expression of all genes in the genome x1, x2, …, xN, and so each state S = [x1, x2, …, xN] represents a coordinate in state space (Fig.1) [38]. Using this dynamical systems conception, different cell types thus occupy different regions in state space, and changes in expression are accompanied by the movement of S along one of a set of trajectories. GRNs include many nodes (genes) which directly influence the expression of other nodes, namely the transcription factors [42–44]. By nature this restricts the scope of potential trajectories.

Bottom Line: Yet functional details of why these proteins are important, i.e. how their action influences a given biological process, are lacking.In this essay we consider the impact of two abundant and highly conserved chromatin modifying complexes, namely the nucleosome remodelling and deacetylation (NuRD) complex and the polycomb repressive complex 2 (PRC2), on the change in GRNs associated with lineage commitment during early mammalian development.We propose that while the NuRD complex limits the stability of cell states and defines the developmental trajectory between two stable states, PRC2 activity is important for stabilizing a new GRN once established.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, UK.

Show MeSH