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Differentiation of developing olfactory neurons analysed in terms of coupled epigenetic landscapes.

Alsing AK, Sneppen K - Nucleic Acids Res. (2013)

Bottom Line: The proposed model combines nucleosomes and associated read-write enzymes as mediators of a cis-acting positive feedback with a trans-acting negative feedback, thereby coupling the local epigenetic landscape of the individual OR genes in a way that allow one and only one gene to be active at any time.The model pinpoint that singular gene selection does not require transient mechanisms, enhancer elements or transcription factors to separate choice from maintenance.Intriguingly, it predicts that OR transgenes placed in close proximity should always be expressed simultaneously, though rarely.

View Article: PubMed Central - PubMed

Affiliation: Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark.

ABSTRACT
The olfactory system integrates signals from receptors expressed in olfactory sensory neurons. Each sensory neuron expresses only one of many similar olfactory receptors (ORs). The choice of receptor is made stochastically early in the differentiation process and is maintained throughout the life of the neuron. The underlying mechanism of this stochastic commitment to one of multiple similar OR genes remains elusive. We present a theoretical analysis of a mechanism that invokes important epigenetic properties of the system. The proposed model combines nucleosomes and associated read-write enzymes as mediators of a cis-acting positive feedback with a trans-acting negative feedback, thereby coupling the local epigenetic landscape of the individual OR genes in a way that allow one and only one gene to be active at any time. The model pinpoint that singular gene selection does not require transient mechanisms, enhancer elements or transcription factors to separate choice from maintenance. In addition, our hypothesis allow us to combine all reported characteristics of singular OR gene selection, in particular that OR genes are silenced from OR transgenes. Intriguingly, it predicts that OR transgenes placed in close proximity should always be expressed simultaneously, though rarely.

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Simulation of N = 100 genes, each covered by L = 50 nucleosomes. Left panels (A, D, G) show time course of the first activated gene (blue), second activated (red) and a few examples of other genes (yellow and green). Inserts show the promoter status of the correspondingly colored genes at the final simulation time. Crossed arrows indicate silent promoters. Middle panels (B, E, H) follow the trajectory of the two most expressed genes, identified by their active nucleosome fraction a and b, in a 2-d plane that illustrates deterministic drift of two individual genes, provided all other genes are assumed to act synchronously (see ‘Materials and Methods’ section and Supplementary Material). In the blue region, , whereas the red region shows where . (C, F, I) show the probability (lighter colour for higher) for the two most active genes in the system, obtained by stochastic simulation over 108 time-units. The negative logarithm of this probability may be interpreted as an epigenetic landscape (62,63), with states that to varying degree prefer to be in the corners, see also Supplementary Figure S1. Parameters are (A–C) , r = 1, h = 2 and . (D–F) , r = 1, h = 2 and . (G–I) , r = 1, h = 2 and .
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gkt181-F3: Simulation of N = 100 genes, each covered by L = 50 nucleosomes. Left panels (A, D, G) show time course of the first activated gene (blue), second activated (red) and a few examples of other genes (yellow and green). Inserts show the promoter status of the correspondingly colored genes at the final simulation time. Crossed arrows indicate silent promoters. Middle panels (B, E, H) follow the trajectory of the two most expressed genes, identified by their active nucleosome fraction a and b, in a 2-d plane that illustrates deterministic drift of two individual genes, provided all other genes are assumed to act synchronously (see ‘Materials and Methods’ section and Supplementary Material). In the blue region, , whereas the red region shows where . (C, F, I) show the probability (lighter colour for higher) for the two most active genes in the system, obtained by stochastic simulation over 108 time-units. The negative logarithm of this probability may be interpreted as an epigenetic landscape (62,63), with states that to varying degree prefer to be in the corners, see also Supplementary Figure S1. Parameters are (A–C) , r = 1, h = 2 and . (D–F) , r = 1, h = 2 and . (G–I) , r = 1, h = 2 and .

Mentions: Success of a simulation may be accessed on three criteria. First, the system needs to selectively activate a single OR gene within a given time window. Second, the chosen gene should remain active for a considerable time. Third, no other OR genes may be activated while the initial OR gene is active. Figure 3A, D and G compactly show time courses like those of Figure 2 for a system of 100 genes at three different values of the local activation bias parameter μ. It is clear that increasing μ takes the system from defying the first criteria by switching on more than one gene, to fulfilling all criteria with a single active gene, and to failure owing to lack of turn on of any genes.Figure 3.


Differentiation of developing olfactory neurons analysed in terms of coupled epigenetic landscapes.

Alsing AK, Sneppen K - Nucleic Acids Res. (2013)

Simulation of N = 100 genes, each covered by L = 50 nucleosomes. Left panels (A, D, G) show time course of the first activated gene (blue), second activated (red) and a few examples of other genes (yellow and green). Inserts show the promoter status of the correspondingly colored genes at the final simulation time. Crossed arrows indicate silent promoters. Middle panels (B, E, H) follow the trajectory of the two most expressed genes, identified by their active nucleosome fraction a and b, in a 2-d plane that illustrates deterministic drift of two individual genes, provided all other genes are assumed to act synchronously (see ‘Materials and Methods’ section and Supplementary Material). In the blue region, , whereas the red region shows where . (C, F, I) show the probability (lighter colour for higher) for the two most active genes in the system, obtained by stochastic simulation over 108 time-units. The negative logarithm of this probability may be interpreted as an epigenetic landscape (62,63), with states that to varying degree prefer to be in the corners, see also Supplementary Figure S1. Parameters are (A–C) , r = 1, h = 2 and . (D–F) , r = 1, h = 2 and . (G–I) , r = 1, h = 2 and .
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3643594&req=5

gkt181-F3: Simulation of N = 100 genes, each covered by L = 50 nucleosomes. Left panels (A, D, G) show time course of the first activated gene (blue), second activated (red) and a few examples of other genes (yellow and green). Inserts show the promoter status of the correspondingly colored genes at the final simulation time. Crossed arrows indicate silent promoters. Middle panels (B, E, H) follow the trajectory of the two most expressed genes, identified by their active nucleosome fraction a and b, in a 2-d plane that illustrates deterministic drift of two individual genes, provided all other genes are assumed to act synchronously (see ‘Materials and Methods’ section and Supplementary Material). In the blue region, , whereas the red region shows where . (C, F, I) show the probability (lighter colour for higher) for the two most active genes in the system, obtained by stochastic simulation over 108 time-units. The negative logarithm of this probability may be interpreted as an epigenetic landscape (62,63), with states that to varying degree prefer to be in the corners, see also Supplementary Figure S1. Parameters are (A–C) , r = 1, h = 2 and . (D–F) , r = 1, h = 2 and . (G–I) , r = 1, h = 2 and .
Mentions: Success of a simulation may be accessed on three criteria. First, the system needs to selectively activate a single OR gene within a given time window. Second, the chosen gene should remain active for a considerable time. Third, no other OR genes may be activated while the initial OR gene is active. Figure 3A, D and G compactly show time courses like those of Figure 2 for a system of 100 genes at three different values of the local activation bias parameter μ. It is clear that increasing μ takes the system from defying the first criteria by switching on more than one gene, to fulfilling all criteria with a single active gene, and to failure owing to lack of turn on of any genes.Figure 3.

Bottom Line: The proposed model combines nucleosomes and associated read-write enzymes as mediators of a cis-acting positive feedback with a trans-acting negative feedback, thereby coupling the local epigenetic landscape of the individual OR genes in a way that allow one and only one gene to be active at any time.The model pinpoint that singular gene selection does not require transient mechanisms, enhancer elements or transcription factors to separate choice from maintenance.Intriguingly, it predicts that OR transgenes placed in close proximity should always be expressed simultaneously, though rarely.

View Article: PubMed Central - PubMed

Affiliation: Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark.

ABSTRACT
The olfactory system integrates signals from receptors expressed in olfactory sensory neurons. Each sensory neuron expresses only one of many similar olfactory receptors (ORs). The choice of receptor is made stochastically early in the differentiation process and is maintained throughout the life of the neuron. The underlying mechanism of this stochastic commitment to one of multiple similar OR genes remains elusive. We present a theoretical analysis of a mechanism that invokes important epigenetic properties of the system. The proposed model combines nucleosomes and associated read-write enzymes as mediators of a cis-acting positive feedback with a trans-acting negative feedback, thereby coupling the local epigenetic landscape of the individual OR genes in a way that allow one and only one gene to be active at any time. The model pinpoint that singular gene selection does not require transient mechanisms, enhancer elements or transcription factors to separate choice from maintenance. In addition, our hypothesis allow us to combine all reported characteristics of singular OR gene selection, in particular that OR genes are silenced from OR transgenes. Intriguingly, it predicts that OR transgenes placed in close proximity should always be expressed simultaneously, though rarely.

Show MeSH