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.

Additional Metadata
Keywords Biophysics, Cell Biology, Biochemistry, Bioengineering, Structural Biology
Publisher Annual Reviews
Funder NWO , ERC
Persistent URL dx.doi.org/10.1146/annurev-biophys-070317-032939
Journal Annu. Rev. Biophys.
Citation
Nghe, P, de Vos, M.G.J, Kingma, E, Kogenaru, M, Poelwijk, F.J, Laan, L, & Tans, S.J. (2020). Predicting Evolution Using Regulatory Architecture. Annu. Rev. Biophys., 49(1), 181–197. doi:10.1146/annurev-biophys-070317-032939