The limits of evolution have long fascinated biologists. However, the causes of evolutionary constraint have remained elusive due to a poor mechanistic understanding of studied phenotypes. Recently, a range of innovative approaches have leveraged mechanistic information on regulatory networks and cellular biology. These methods combine systems biology models with population and single-cell quantification and with new genetic tools, and they have been applied to a range of complex cellular functions and engineered networks. In this article, we review these developments, which are revealing the mechanistic causes of epistasis at different levels of biological organization-in molecular recognition, within a single regulatory network, and between different networks-providing first indications of predictable features of evolutionary constraint.

中文翻译：

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使用监管体系结构预测演进。

进化的极限使生物学家长期着迷。但是，由于对所研究表型的机械理解较差，进化约束的原因仍然难以捉摸。最近，一系列创新方法已经利用了有关调节网络和细胞生物学的机械信息。这些方法将系统生物学模型与种群和单细胞定量以及新的遗传工具相结合，已被应用于一系列复杂的细胞功能和工程网络。在本文中，我们回顾了这些进展，揭示了在单个调控网络内以及在不同网络之间在不同生物组织水平（分子识别）中上位的机制的原因，这是进化约束的可预测特征的第一指征。