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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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Model sensitivity to activation bias parameter μ, for  genes, L = 50 nucleosomes system with repression factor r = 1, hill h = 2 and noise  fixed. Data are averaged over 200 simulations. (A) Orange area shows the probability that one and only one gene becomes active within 5000 time units as function of asymmetry μ. Concurrent dark orange area marks success with the additional constraint that one gene becomes active within the first 1000 time units. Grey area marks the cut-off at 50% successful simulations. (B) Orange area marks the largest number of active nucleosomes within one gene during a 5000 time-unit simulation. When no genes reach full activity during the first 5000 time-units, no ORs have turned on. Cyan and dark cyan show maximal activity of the second and third most active genes, respectively. Where the second most active gene has many active nucleosomes, the two genes have shown simultaneous activity. (C) Orange area as in panel A. The two black curves refer to simulations with the sharper threshold function for gene activity described in ‘Materials and Methods’ section, and gene copy numbers as indicated. Only assigning feedback activity to genes where more than two-third of their nucleosomes are marked as active, even N = 1000 genes can differentiate successfully. Data for black curves are averaged over 50 simulations. See also Supplementary Figure S2 for sensitivity to parameters r, h, and β.
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gkt181-F4: Model sensitivity to activation bias parameter μ, for genes, L = 50 nucleosomes system with repression factor r = 1, hill h = 2 and noise fixed. Data are averaged over 200 simulations. (A) Orange area shows the probability that one and only one gene becomes active within 5000 time units as function of asymmetry μ. Concurrent dark orange area marks success with the additional constraint that one gene becomes active within the first 1000 time units. Grey area marks the cut-off at 50% successful simulations. (B) Orange area marks the largest number of active nucleosomes within one gene during a 5000 time-unit simulation. When no genes reach full activity during the first 5000 time-units, no ORs have turned on. Cyan and dark cyan show maximal activity of the second and third most active genes, respectively. Where the second most active gene has many active nucleosomes, the two genes have shown simultaneous activity. (C) Orange area as in panel A. The two black curves refer to simulations with the sharper threshold function for gene activity described in ‘Materials and Methods’ section, and gene copy numbers as indicated. Only assigning feedback activity to genes where more than two-third of their nucleosomes are marked as active, even N = 1000 genes can differentiate successfully. Data for black curves are averaged over 50 simulations. See also Supplementary Figure S2 for sensitivity to parameters r, h, and β.

Mentions: In our standard simulations, we assume that , which in effect implies that a gene that is half covered by silenced nucleosomes, still retain 1/4 of its maximal activity. This rather soft repression limits the functional range of our model considerably. A much more robust differentiation is obtained by using a higher value of h or by simply assuming that there is only activity from genes i where the fraction of active nucleosomes, ai, has reached a finite threshold, say . The latter case is examined in Figure 4C.


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

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

Model sensitivity to activation bias parameter μ, for  genes, L = 50 nucleosomes system with repression factor r = 1, hill h = 2 and noise  fixed. Data are averaged over 200 simulations. (A) Orange area shows the probability that one and only one gene becomes active within 5000 time units as function of asymmetry μ. Concurrent dark orange area marks success with the additional constraint that one gene becomes active within the first 1000 time units. Grey area marks the cut-off at 50% successful simulations. (B) Orange area marks the largest number of active nucleosomes within one gene during a 5000 time-unit simulation. When no genes reach full activity during the first 5000 time-units, no ORs have turned on. Cyan and dark cyan show maximal activity of the second and third most active genes, respectively. Where the second most active gene has many active nucleosomes, the two genes have shown simultaneous activity. (C) Orange area as in panel A. The two black curves refer to simulations with the sharper threshold function for gene activity described in ‘Materials and Methods’ section, and gene copy numbers as indicated. Only assigning feedback activity to genes where more than two-third of their nucleosomes are marked as active, even N = 1000 genes can differentiate successfully. Data for black curves are averaged over 50 simulations. See also Supplementary Figure S2 for sensitivity to parameters r, h, and β.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3643594&req=5

gkt181-F4: Model sensitivity to activation bias parameter μ, for genes, L = 50 nucleosomes system with repression factor r = 1, hill h = 2 and noise fixed. Data are averaged over 200 simulations. (A) Orange area shows the probability that one and only one gene becomes active within 5000 time units as function of asymmetry μ. Concurrent dark orange area marks success with the additional constraint that one gene becomes active within the first 1000 time units. Grey area marks the cut-off at 50% successful simulations. (B) Orange area marks the largest number of active nucleosomes within one gene during a 5000 time-unit simulation. When no genes reach full activity during the first 5000 time-units, no ORs have turned on. Cyan and dark cyan show maximal activity of the second and third most active genes, respectively. Where the second most active gene has many active nucleosomes, the two genes have shown simultaneous activity. (C) Orange area as in panel A. The two black curves refer to simulations with the sharper threshold function for gene activity described in ‘Materials and Methods’ section, and gene copy numbers as indicated. Only assigning feedback activity to genes where more than two-third of their nucleosomes are marked as active, even N = 1000 genes can differentiate successfully. Data for black curves are averaged over 50 simulations. See also Supplementary Figure S2 for sensitivity to parameters r, h, and β.
Mentions: In our standard simulations, we assume that , which in effect implies that a gene that is half covered by silenced nucleosomes, still retain 1/4 of its maximal activity. This rather soft repression limits the functional range of our model considerably. A much more robust differentiation is obtained by using a higher value of h or by simply assuming that there is only activity from genes i where the fraction of active nucleosomes, ai, has reached a finite threshold, say . The latter case is examined in Figure 4C.

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