Predicting Evolutionary Constraints by Identifying Conflicting Demands in Regulatory Networks
Manjunatha Kogenaru1, Philippe Nghe2, Frank J Poelwijk3
1AMOLF, Science Park 104, Amsterdam 1098 XG, the Netherlands; Department of Life Sciences, Imperial College London, London SW7 2AZ, UK.
Cell Systems
|June 20, 2020
Summary
Gene regulation networks evolve to adapt to new environments. Partial order analysis predicts evolutionary constraints by ranking network outputs, guiding adaptation strategies and revealing how networks change structure or fine-tune components to improve fitness.
Area of Science:
- Systems Biology
- Evolutionary Biology
- Synthetic Biology
Background:
- Organisms adapt to environmental niches using gene regulation networks.
- The evolutionary constraints on gene regulation network evolution are not well understood.
- Partial order analysis offers a novel approach to identify these constraints.
Purpose of the Study:
- To investigate the evolutionary constraints on gene regulation networks.
- To test the predictive power of partial order analysis in experimental evolution.
- To understand how engineered networks adapt to different environments.
Main Methods:
- Developed and applied partial order analysis to predict evolutionary constraints.
- Experimentally evolved an engineered signal-integrating network in multiple environments.
- Analyzed population fitness expansion and changes in network components and structure.
Main Results:
- Populations expanded fitness along the Pareto-optimal front by fine-tuning binding affinities.
- Populations also expanded beyond the Pareto-optimal front via alterations in network structure.
- Partial order predictions were validated without needing network architecture or genetic details.
Conclusions:
- Partial order analysis effectively identifies evolutionary constraints on gene regulation.
- Evolutionary adaptation involves both fine-tuning existing network components and structural changes.
- Understanding current regulatory phenotypes can predict future evolutionary trajectories.
Keywords:
Pareto frontconstraint predictionexperimental evolutiongenetic networkpartial orderregulatory conflictvariable environmentsMore Related Videos
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