Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop

Gui, Rong; Liu, Quan; Yao, Yuangen; Deng, Haiyou; Ma, Chengzhang; Jia, Ya; Yi, Ming

doi:10.3389/fphys.2016.00600

Cited by 21 publications

(20 citation statements)

References 51 publications

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“…Gene expression is a noisy process [12,26]. There are various studies about Gaussian noise in gene regulation [27][28][29][30][31]. However, the transcription of a gene can be a discontinuous or burstlike event, and mRNA is synthesized in intermittent but intense pulses or bursts [21,22,[32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Most probable dynamics of a genetic regulatory network under stable Lévy noise

Chen

Duan

et al. 2019

Applied Mathematics and Computation

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Numerous studies have demonstrated the important role of noise in the dynamical behaviour of a complex system. The most probable trajectories of nonlinear systems under the influence of Gaussian noise have recently been studied already. However, there has been only a few works that examine how most probable trajectories in the two-dimensional system (MeKS network) are influenced under non-Gaussian stable Lévy noise. Therefore, we discuss the most probable trajectories of a two-dimensional model depicting the competence behaviour in B. subtilis under the influence of stable Lévy noise. On the basis of the Fokker-Planck equation, we describe the noise-induced most probable trajectories of the MeKS network from the low ComK protein concentration (vegetative state) to the high ComK protein concentration (competence state) under stable Lévy noise.We demonstrate choices of the non-Gaussianity index α and the noise intensity ǫ which generate the ComK protein escape from the low concentration to the high concentration. We also reveal the optimal combination of both parameters α and ǫ making the tipping time shortest. Moreover, we find that different initial concentrations around the low ComK protein concentration evolve to a metastable state, and provide the optimal α and ǫ such that the distance between the deterministic competence state and the metastable state is smallest.

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Section: Introductionmentioning

confidence: 99%

Most probable dynamics of a genetic regulatory network under stable Lévy noise

Chen

Duan

et al. 2019

Applied Mathematics and Computation

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“…This is important in order to stay in the state H:OFF/ E:ON. In addition, the FFL may act as a noise filter (Gui et al, 2016). This noise may derive, for example, from fluctuations in biochemical rates or from genetic variation that could affect the regulatory constants that are included in our model.…”

Section: Discussionmentioning

confidence: 99%

A Toggle-Switch and a Feed-Forward Loop Engage in the Control of the Drosophila Retinal Determination Gene Network

et al. 2019

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Dipterans show a striking range of eye sizes, shapes, and functional specializations. Their eye is of the compound type, the most frequent eye architecture in nature. The development of this compound eye has been most studied in Drosophila melanogaster. The early development of the Drosophila eye is under the control of a gene regulatory network of transcription factors and signaling molecules called the retinal determination gene network (RDGN). Nodes in this network have been found to be involved not only in the development of different eye types in invertebrates and vertebrates, but also of other organs. Here we have analyzed the network properties in detail. First, we have generated quantitative expression profiles for a number of the key RDGN transcription factors, at a single-cell resolution. With these profiles, and applying a correlation analysis, we revisited several of the links in the RDGN. Our study uncovers a new link, that we confirm experimentally, between the transcription factors Hth/Meis1 and Optix/Six3 and indicates that, at least during the period of eye differentiation, positive feedback regulation from Eya and Dac on the Pax6 gene Ey is not operating. From this revised RDGN we derive a simplified gene network that we model mathematically. This network integrates three basic motifs: a coherent feedforward loop, a toggle-switch and a positive autoregulation which, together with the input from the Dpp/BMP2 signaling molecule, recapitulate the gene expression profiles obtained experimentally, while ensuring a robust transition from progenitor cells into retinal precursors.

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“…Such a network configuration appears to result in a rapid response to activating signal and a delayed response when the inputs are removed (termed sign-sensitive delay), thereby prolonging the effect of a transient activator (Mangan and Alon, 2003). Additionally, feedforward loops are effective at buffering the system against stochastic noise, ensuring developmental robustness (Chepyala et al, 2016;Gui et al, 2016;Maduro, 2015) This design principal appears to be crucial to ensure timely and robust activation of elt-7 and -2, as we and others have shown (Boeck et al, 2011;Dineen et al, 2018;Maduro et al, 2015). Delayed onset of elt-2 in early embryos has been shown to cause sustained metabolic defects in larvae despite the reattainment of wildtype ELT-2 levels (Maduro et al, 2015).…”

Section: Regulatory Logic Of Developmental Grnmentioning

confidence: 99%

Feedforward regulatory logic underlies robustness of the specification-to-differentiation transition and fidelity of terminal cell fate duringC. elegansendoderm development

Ewe

Sommermann

Kenchel

et al. 2021

Preprint

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Development is driven by gene regulatory networks (GRNs) that progressively dictate specification and differentiation of cell fates. The architecture of GRNs directly determines the specificity and accuracy of developmental outcomes. We report here that the core regulatory circuitry for endoderm development in C. elegans is comprised of a recursive series of interlocked feedforward modules linking a cascade of six sequentially expressed GATA-type transcription factors. This structure results in a reiterated sequential redundancy, in which removal of a single factor or alternate factors in the cascade results in no, or a mild, effect on endoderm development and gut differentiation, while elimination of any two factors that are sequentially deployed in the cascade invariably results in a strong phenotype. The strength of the observed phenotypes is successfully predicted by a computational model based on the timing and levels of transcriptional states. The feedforward regulatory logic in the GRN appears to ensure timely onset of terminal differentiation genes and allow rapid and robust lockdown of cell fate during early embryogenesis. We further found that specification-to-differentiation transition is linked through a common regulator, the END-1 GATA factor that straddles the two processes. Finally, we revealed roles for key GATA factors in establishing spatial regulatory state domains by acting as transcriptional repressors that appear to define the boundaries of the digestive tract. Our findings support a comprehensive model of the core gene network that describes how robust endoderm development is achieved during C. elegans embryogenesis.

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Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop

Cited by 21 publications

References 51 publications

Most probable dynamics of a genetic regulatory network under stable Lévy noise

Most probable dynamics of a genetic regulatory network under stable Lévy noise

A Toggle-Switch and a Feed-Forward Loop Engage in the Control of the Drosophila Retinal Determination Gene Network

Feedforward regulatory logic underlies robustness of the specification-to-differentiation transition and fidelity of terminal cell fate duringC. elegansendoderm development

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