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Dynamics of gene circuits shapes evolvability.

ABSTRACT: To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for gene circuits that use each of these six mechanisms to evolve novel phenotypes such as multiple stripes, inverted stripes, and gradients of gene expression. Through a comprehensive and systematic analysis, we find that circuits that use alternative mechanisms differ in the likelihood of reaching novel phenotypes through mutation. We characterize the phenotypic transitions and identify key ingredients of the evolutionary potential, such as sensitive interactions and phenotypic hubs. Finally, we provide an intuitive understanding on how the modular design of a particular mechanism favors the access to novel phenotypes. Our work illustrates how the dynamical mechanism by which an organism develops constrains how it can evolve. It is striking that these dynamical mechanisms and their impact on evolvability can be observed even for such an apparently simple patterning task, performed by just three-node circuits.

SUBMITTER: Jimenez A

PROVIDER: S-EPMC4343095 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Dynamics of gene circuits shapes evolvability.

Jiménez Alba A Cotterell James J Munteanu Andreea A Sharpe James J

Proceedings of the National Academy of Sciences of the United States of America 20150202 7

To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for ...[more]

PMID: 25646408

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Project description:Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.

Project description:Short-term plasticity is a fundamental synaptic property thought to underlie memory and neural processing. The glomerular microcircuit comprises complex excitatory and inhibitory interactions and transmits olfactory nerve signals to the excitatory output neurons, mitral/tufted cells (M/TCs). The major glomerular inhibitory interneurons, short axon cells (SACs) and periglomerular cells (PGCs), both provide feedforward and feedback inhibition to M/TCs and have reciprocal inhibitory synapses between each other. Olfactory input is episodically driven by sniffing. We hypothesized that frequency-dependent short-term plasticity within these inhibitory circuits could influence signals sent to higher-order olfactory networks. To assess short-term plasticity in glomerular circuits and MC outputs, we virally delivered channelrhodopsin-2 (ChR2) in glutamic acid decarboxylase-65 promotor (GAD2-cre) or tyrosine hydroxylase promoter (TH-cre) mice and selectively activated one of these two populations while recording from cells of the other population or from MCs. Selective activation of TH-ChR2-expressing SACs inhibited all recorded GAD2-green fluorescent protein(GFP)-expressing presumptive PGC cells, and activation of GAD2-ChR2 cells inhibited TH-GFP-expressing SACs, indicating reciprocal inhibitory connections. SAC synaptic inhibition of GAD2-expressing cells was significantly facilitated at 5-10 Hz activation frequencies. In contrast, GAD2-ChR2 cell inhibition of TH-expressing cells was activation-frequency independent. Both SAC and PGC inhibition of MCs also exhibited short-term plasticity, pronounced in the 5-20 Hz range corresponding to investigative sniffing frequency ranges. In paired SAC and olfactory nerve electrical stimulations, the SAC to MC synapse was able to markedly suppress MC spiking. These data suggest that short-term plasticity across investigative sniffing ranges may differentially regulate intra- and interglomerular inhibitory circuits to dynamically shape glomerular output signals to downstream targets.NEW & NOTEWORTHY Short-term plasticity is a fundamental synaptic property that modulates synaptic strength based on preceding activity of the synapse. In rodent olfaction, sensory input arrives episodically driven by sniffing rates ranging from quiescent respiration (1-2 Hz) through to investigative sniffing (5-10 Hz). Here we show that glomerular inhibitory networks are exquisitely sensitive to input frequencies and exhibit plasticity proportional to investigative sniffing frequencies. This indicates that olfactory glomerular circuits are dynamically modulated by episodic sniffing input.

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Dynamics of gene circuits shapes evolvability.

Publications

Dynamics of gene circuits shapes evolvability.

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