Linking molecular mechanisms to their evolutionary consequences: a primer

A major obstacle to predictive understanding of evolution stems from the complexity of biological systems, which prevents detailed characterization of key evolutionary properties. Here, we highlight some of the major sources of complexity that arise when relating molecular mechanisms to their evolutionary consequences and ask whether accounting for every mechanistic detail is important to accurately predict evolutionary outcomes. To do this, we developed a mechanistic model of a bacterial promoter regulated by 2 proteins, allowing us to connect any promoter genotype to 6 phenotypes that capture the dynamics of gene expression following an environmental switch. Accounting for the mechanisms that govern how this system works enabled us to provide an in-depth picture of how regulated bacterial promoters might evolve. More importantly, we used the model to explore which factors that contribute to the complexity of this system are essential for understanding its evolution, and which can be simplified without information loss. We found that several key evolutionary properties-the distribution of phenotypic and fitness effects of mutations, the evolutionary trajectories during selection for regulation-can be accurately captured without accounting for all, or even most, parameters of the system. Our findings point to the need for a mechanistic approach to studying evolution, as it enables tackling biological complexity and in doing so improves the ability to predict evolutionary outcomes.

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Publication Details

Journal
Genetics
Published
2024-11-27
DOI
https://doi.org/10.1093/genetics/iyae191
Citations
2
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
1.10

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article

Linking molecular mechanisms to their evolutionary consequences: a primer

Mato Lagator, Gašper Tkačik, Călin C. Guet, Rok Grah
2 citations
Genetics
Evolution and Genetic Dynamics
1.10
article

Linking molecular mechanisms to their evolutionary consequences: a primer

Mato Lagator, Gašper Tkačik, Călin C. Guet, Rok Grah
article en
2 citations

Abstract

A major obstacle to predictive understanding of evolution stems from the complexity of biological systems, which prevents detailed characterization of key evolutionary properties. Here, we highlight some of the major sources of complexity that arise when relating molecular mechanisms to their evolutionary consequences and ask whether accounting for every mechanistic detail is important to accurately predict evolutionary outcomes. To do this, we developed a mechanistic model of a bacterial promoter regulated by 2 proteins, allowing us to connect any promoter genotype to 6 phenotypes that capture the dynamics of gene expression following an environmental switch. Accounting for the mechanisms that govern how this system works enabled us to provide an in-depth picture of how regulated bacterial promoters might evolve. More importantly, we used the model to explore which factors that contribute to the complexity of this system are essential for understanding its evolution, and which can be simplified without information loss. We found that several key evolutionary properties-the distribution of phenotypic and fitness effects of mutations, the evolutionary trajectories during selection for regulation-can be accurately captured without accounting for all, or even most, parameters of the system. Our findings point to the need for a mechanistic approach to studying evolution, as it enables tackling biological complexity and in doing so improves the ability to predict evolutionary outcomes.

GeneticsVol. 229(2)
Institute of Science and Technology Austria (AT), University of Manchester (GB), Biology of Infection (FR)
Wellcome Trust
Life in Land
Openalex Percentile: Top 18%
Evolution and Genetic Dynamics
1.10
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