Predicting Evolution Using Regulatory Architecture

Philippe Nghe, Marjon G.J. de Vos, Enzo Kingma, Manjunatha Kogenaru, Frank J. Poelwijk, Liedewij Laan, Sander J. Tans

Research output: Contribution to journalReview articlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)181-197
JournalAnnual Review of Biophysics
Volume49
DOIs
Publication statusPublished - 2020

Keywords

  • epistasis
  • evolutionary constraint
  • gene regulation
  • pleiotropy
  • prediction
  • regulation networks

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