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AEGIS: Individual-based modeling of life history evolution
Martin Bagic1, Arian Šajina1,2, William John Bradshaw1,2
1Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Jena, Germany.
Plos Computational Biology
|March 26, 2026
Summary
Life history traits evolve due to environmental factors and past demographics. AEGIS (Aging of Evolving Genomes In Silico) software models this evolution, revealing causes of species-specific lifespans and reproduction.
Area of Science:
- Evolutionary biology
- Ecology
- Computational biology
Background:
- Species exhibit diverse life history strategies influenced by environment and demographics.
- Understanding these traits is key to identifying evolutionary causes of lifespan and reproductive success.
- Past evolutionary events are difficult to reconstruct in natural populations.
Purpose of the Study:
- To develop a computational tool for modeling life history trait evolution.
- To investigate the impact of ecological and demographic factors on evolutionary trajectories.
- To provide a method for inferring evolutionary parameters.
Main Methods:
- Developed AEGIS (Aging of Evolving Genomes In Silico), an individual-based modeling software.
- Simulated life history trait evolution at genotype and phenotype levels.
- Incorporated factors like resource availability, mortality, mutation rates, and reproduction modes.
Main Results:
- AEGIS models the evolution of life history traits in response to selective pressures.
- The software allows for parameter inference against simulated ground truths.
- It can estimate age-dependent mortality and reproduction patterns.
Conclusions:
- AEGIS is a powerful tool for studying the evolution of life history traits.
- It enables direct testing of ecological and demographic influences on evolution.
- The software aids in understanding species-specific adaptations and constraints.
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