Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
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DOI：
10.1371/journal.pone.0153295
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Soyer OS
中科院分区：
文献类型：
--
作者：
Steinacher A;Bates DG;Akman OE;Soyer OS
由调节网络支撑的细胞表型需要对进化压力做出反应，以允许适应，但同时对扰动具有鲁棒性。这就产生了一个冲突，即影响调控网络的突变必须既产生变异，又在表型水平上被容忍。在这里，我们对监管网络进行数学分析和模拟，以更好地理解鲁棒性和可进化性之间的潜在权衡。检查突变的表型效应，我们发现鲁棒性和可进化性之间的逆相关性，打破只有在网络动态的非线性，通过创建区域呈现突变的表型与基因型的小变化。对于基因型嵌入低水平的非线性，鲁棒性和可进化性负相关，几乎完美。相比之下，基因型嵌入非线性动力学允许表达水平对小扰动具有鲁棒性，同时在较大扰动下产生高多样性（可进化性）。因此，非线性通过允许对不同突变的不同反应来打破基因表达水平中的鲁棒性-可进化性权衡。使用分析推导的鲁棒性和系统的灵敏度，我们表明，这些发现扩展到一个大类的基因调控网络架构，也持有实验观察到的参数制度。此外，只要系统的关键参数显示特定的关系，无论其绝对值的鲁棒性-可演化性权衡的非线性的影响是确保。我们发现，在此参数范围内，基因型显示低和嘈杂的表达水平。检查突变的表型效应，我们发现鲁棒性和可进化性之间的逆相关性，只有在网络动态中的非线性才能打破。我们的研究结果提供了一个可能的解决方案的鲁棒性，可进化性的权衡，建议解释基因表达网络中普遍存在的非线性动力学，并产生有用的指导方针，为合成基因电路的设计。
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.