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A symmetric toggle switch explains the onset of random X inactivation in different mammals.

ABSTRACT: Gene-regulatory networks control the establishment and maintenance of alternative gene-expression states during development. A particular challenge is the acquisition of opposing states by two copies of the same gene, as in the case of the long non-coding RNA Xist in mammals at the onset of random X-chromosome inactivation (XCI). The regulatory principles that lead to stable mono-allelic expression of Xist remain unknown. Here, we uncover the minimal regulatory network that can ensure female-specific and mono-alleleic upregulation of Xist, by combining mathematical modeling and experimental validation of central model predictions. We identify a symmetric toggle switch as the basis for random mono-allelic upregulation of Xist, which reproduces data from several mutant, aneuploid and polyploid mouse cell lines with various Xist expression patterns. Moreover, this toggle switch explains the diversity of strategies employed by different species at the onset of XCI. In addition to providing a unifying conceptual framework with which to explore XCI across mammals, our study sets the stage for identifying the molecular mechanisms needed to initiate random XCI.

SUBMITTER: Mutzel V

PROVIDER: S-EPMC6558282 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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A symmetric toggle switch explains the onset of random X inactivation in different mammals.

Mutzel Verena V Okamoto Ikuhiro I Dunkel Ilona I Saitou Mitinori M Giorgetti Luca L Heard Edith E Schulz Edda G EG

Nature structural & molecular biology 20190408 5

Gene-regulatory networks control the establishment and maintenance of alternative gene-expression states during development. A particular challenge is the acquisition of opposing states by two copies of the same gene, as in the case of the long non-coding RNA Xist in mammals at the onset of random X-chromosome inactivation (XCI). The regulatory principles that lead to stable mono-allelic expression of Xist remain unknown. Here, we uncover the minimal regulatory network that can ensure female-spe ...[more]

PMID: 30962582

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Project description:The circadian clock controls many physiological processes in higher plants and causes a large fraction of the genome to be expressed with a 24h rhythm. The transcripts encoding the RNA-binding proteins AtGRP7 (Arabidopsis thaliana Glycine Rich Protein 7) and AtGRP8 oscillate with evening peaks. The circadian clock components CCA1 and LHY negatively affect AtGRP7 expression at the level of transcription. AtGRP7 and AtGRP8, in turn, negatively auto-regulate and reciprocally cross-regulate post-transcriptionally: high protein levels promote the generation of an alternative splice form that is rapidly degraded. This clock-regulated feedback loop has been proposed to act as a molecular slave oscillator in clock output. While mathematical models describing the circadian core oscillator in Arabidopsis thaliana were introduced recently, we propose here the first model of a circadian slave oscillator. We define the slave oscillator in terms of ordinary differential equations and identify the model's parameters by an optimization procedure based on experimental results. The model successfully reproduces the pertinent experimental findings such as waveforms, phases, and half-lives of the time-dependent concentrations. Furthermore, we obtain insights into possible mechanisms underlying the observed experimental dynamics: the negative auto-regulation and reciprocal cross-regulation via alternative splicing could be responsible for the sharply peaking waveforms of the AtGRP7 and AtGRP8 mRNA. Moreover, our results suggest that the AtGRP8 transcript oscillations are subordinated to those of AtGRP7 due to a higher impact of AtGRP7 protein on alternative splicing of its own and of the AtGRP8 pre-mRNA compared to the impact of AtGRP8 protein. Importantly, a bifurcation analysis provides theoretical evidence that the slave oscillator could be a toggle switch, arising from the reciprocal cross-regulation at the post-transcriptional level. In view of this, transcriptional repression of AtGRP7 and AtGRP8 by LHY and CCA1 induces oscillations of the toggle switch, leading to the observed high-amplitude oscillations of AtGRP7 mRNA.

Project description:BACKGROUND:Waddington's epigenetic landscape is an intuitive metaphor for the developmental and evolutionary potential of biological regulatory processes. It emphasises time-dependence and transient behaviour. Nowadays, we can derive this landscape by modelling a specific regulatory network as a dynamical system and calculating its so-called potential surface. In this sense, potential surfaces are the mathematical equivalent of the Waddingtonian landscape metaphor. In order to fully capture the time-dependent (non-autonomous) transient behaviour of biological processes, we must be able to characterise potential landscapes and how they change over time. However, currently available mathematical tools focus on the asymptotic (steady-state) behaviour of autonomous dynamical systems, which restricts how biological systems are studied. RESULTS:We present a pragmatic first step towards a methodology for dealing with transient behaviours in non-autonomous systems. We propose a classification scheme for different kinds of such dynamics based on the simulation of a simple genetic toggle-switch model with time-variable parameters. For this low-dimensional system, we can calculate and explicitly visualise numerical approximations to the potential landscape. Focussing on transient dynamics in non-autonomous systems reveals a range of interesting and biologically relevant behaviours that would be missed in steady-state analyses of autonomous systems. Our simulation-based approach allows us to identify four qualitatively different kinds of dynamics: transitions, pursuits, and two kinds of captures. We describe these in detail, and illustrate the usefulness of our classification scheme by providing a number of examples that demonstrate how it can be employed to gain specific mechanistic insights into the dynamics of gene regulation. CONCLUSIONS:The practical aim of our proposed classification scheme is to make the analysis of explicitly time-dependent transient behaviour tractable, and to encourage the wider use of non-autonomous models in systems biology. Our method is applicable to a large class of biological processes.

Dataset Information

A symmetric toggle switch explains the onset of random X inactivation in different mammals.

Publications

A symmetric toggle switch explains the onset of random X inactivation in different mammals.

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