Predicting Evolution Using Regulatory Architecture

Review (2020)

Authors

Marjon G.J. de Vos Rijksuniversiteit Groningen
E. Kingma BN/Liedewij Laan Lab - AS
Manjunatha Kogenaru Imperial College London
Frank J. Poelwijk Dana-Farber Cancer Institute, Boston
L. Laan BN/Liedewij Laan Lab - AS
S.J. Tans BN/Sander Tans Lab - AS
Research Group
BN/Liedewij Laan Lab (AS) (TU Delft)
Prediction Gene regulation Pleiotropy Epistasis Evolutionary constraint Regulation networks
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Published Date

2020

Language

English

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Faculty

Applied Sciences

Department

BN/Bionanoscience

Research Group

BN/Liedewij Laan Lab

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.