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Nonequilibrium models of optimal enhancer function [Biophysics and Computational Biology]
Proceedings of the National Academy of Sciences of the United States of America ( IF 9.4 ) Pub Date : 2020-12-15 , DOI: 10.1073/pnas.2006731117
Rok Grah 1 , Benjamin Zoller 2, 3 , Gašper Tkačik 1
Affiliation  

In prokaryotes, thermodynamic models of gene regulation provide a highly quantitative mapping from promoter sequences to gene-expression levels that is compatible with in vivo and in vitro biophysical measurements. Such concordance has not been achieved for models of enhancer function in eukaryotes. In equilibrium models, it is difficult to reconcile the reported short transcription factor (TF) residence times on the DNA with the high specificity of regulation. In nonequilibrium models, progress is difficult due to an explosion in the number of parameters. Here, we navigate this complexity by looking for minimal nonequilibrium enhancer models that yield desired regulatory phenotypes: low TF residence time, high specificity, and tunable cooperativity. We find that a single extra parameter, interpretable as the “linking rate,” by which bound TFs interact with Mediator components, enables our models to escape equilibrium bounds and access optimal regulatory phenotypes, while remaining consistent with the reported phenomenology and simple enough to be inferred from upcoming experiments. We further find that high specificity in nonequilibrium models is in a trade-off with gene-expression noise, predicting bursty dynamics—an experimentally observed hallmark of eukaryotic transcription. By drastically reducing the vast parameter space of nonequilibrium enhancer models to a much smaller subspace that optimally realizes biological function, we deliver a rich class of models that could be tractably inferred from data in the near future.



中文翻译:

最佳增强子功能的非平衡模型[生物物理学与计算生物学]

在原核生物中,基因调控的热力学模型提供了从启动子序列到基因表达水平的高度定量映射,可与体内和体外生物物理测量相兼容。对于真核生物中增强子功能的模型尚未实现这种一致性。在平衡模型中,很难以高度的调节特异性来调节报道的短转录因子(TF)在DNA上的停留时间。在非平衡模型中,由于参数数量激增,因此很难进行。在这里,我们通过寻找产生所需调节表型的最小非平衡增强子模型来解决这种复杂性:低TF停留时间,高特异性和可调协同性。我们发现,有一个额外的参数,可以解释为“链接率”,通过绑定的TF与介体组件的相互作用,使我们的模型能够逃脱平衡界限并获得最佳的调节表型,同时与报道的现象学保持一致,并且可以从即将进行的实验中推断出足够简单。我们进一步发现,在非平衡模型中的高特异性是在与基因表达噪声的权衡中进行的,该噪声预测了突发动力学-这是实验观察到的真核转录的标志。通过将非平衡增强器模型的巨大参数空间大幅度减少到可以最佳实现生物学功能的较小子空间,我们提供了可以在不久的将来从数据中轻松推断出的丰富模型。同时与所报道的现象学保持一致,并且足够简单,可以从即将进行的实验中推断出来。我们进一步发现,在非平衡模型中的高特异性是在与基因表达噪声的权衡中进行的,该噪声预测了突发动力学-这是实验观察到的真核转录的标志。通过将非平衡增强器模型的巨大参数空间大幅度减少到可以最佳实现生物学功能的较小子空间,我们提供了可以在不久的将来从数据中轻松推断出的丰富模型。同时与所报道的现象学保持一致,并且足够简单,可以从即将进行的实验中推断出来。我们进一步发现,在非平衡模型中的高特异性是在与基因表达噪声的权衡中进行的,该噪声预测了突发动力学-这是实验观察到的真核转录的标志。通过将非平衡增强器模型的巨大参数空间大幅度减少到可以最佳实现生物学功能的较小子空间,我们提供了可以在不久的将来从数据中轻松推断出的丰富模型。预测爆发动力学-真核转录的实验观察标志。通过将非平衡增强器模型的巨大参数空间大幅度减少到可以最佳实现生物学功能的较小子空间,我们提供了可以在不久的将来从数据中轻松推断出的丰富模型。预测爆发动力学-真核转录的实验观察标志。通过将非平衡增强器模型的巨大参数空间大幅度减少到可以最佳实现生物学功能的较小子空间,我们提供了可以在不久的将来从数据中轻松推断出的丰富模型。

更新日期:2020-12-16
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