Laboratoire de Biochimie, UMR CBI 8231, ESPCI Paris, PSL Research University, 75005 Paris, France.
University of Groningen, GELIFES, 9747 AG Groningen, The Netherlands.
Annu Rev Biophys. 2020 May 6;49:181-197. doi: 10.1146/annurev-biophys-070317-032939. Epub 2020 Feb 4.
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.
进化的限制长期以来一直吸引着生物学家。然而，由于对所研究表型的机制理解不足，进化约束的原因仍然难以捉摸。最近，一系列创新方法利用了关于调控网络和细胞生物学的机制信息。这些方法将系统生物学模型与群体和单细胞定量以及新的遗传工具相结合，并已应用于一系列复杂的细胞功能和工程网络。在本文中，我们回顾了这些发展，这些发展揭示了在不同层次的生物组织中，在分子识别、单个调控网络内以及不同网络之间的上位性的机制原因，为进化约束的可预测特征提供了初步迹象。
