Predicting Evolution Using Regulatory Architecture

Review (2020)
Author(s)

Philippe Nghe (ESPCI)

Marjon G.J. de Vos (Rijksuniversiteit Groningen)

E. Kingma (TU Delft - BN/Liedewij Laan Lab)

Manjunatha Kogenaru (Imperial College London)

Frank J. Poelwijk (Dana-Farber Cancer Institute, Boston)

Liedewij Laan (TU Delft - BN/Liedewij Laan Lab)

S.J. Tans (TU Delft - BN/Sander Tans Lab)

Research Group
BN/Liedewij Laan Lab
DOI related publication
https://doi.org/10.1146/annurev-biophys-070317-032939
More Info
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Publication Year
2020
Language
English
Research Group
BN/Liedewij Laan Lab
Volume number
49
Pages (from-to)
181-197

Abstract

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.

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