Model Description

Introduction

Aevol is a forward-in-time evolutionary simulator that models the evolution of a population of organisms through a process of variation and selection. Each artificial organism has an explicit genome, on which RNAs and genes can be identified. The design of the model focuses on the realism of the genome structure and of the mutational process: mutations affect directly the sequence, without any a priori fitness effect. Aevol can therefore be used to decipher the effect of different operators or processes on genome evolution.

Aevol exists in three flavors: Standard, Eukaryote and 4-Bases. The first two use a binary genomic sequence while the third uses an ATGC-based sequence. Most of the model is identical among the different flavors, and variations will be presented explicitly throughout the model presentation. In short:

In Standard Aevol, is inspired by prokaryotec organisms: each organism is asexual, haploid, and owns a single circular chromosome. The genome is encoded as a double-strand binary string. Most experiments historically used this version (see Publications).
In Eukaryote Aevol, each organism owns two linear chromosomes, and the reproduction is sexual and includes a meiotic recombination event. The genome is encoded as a double-strand binary string.
In 4-Bases Aevol, the genome is not binary but encoded with the 4 letters ATGC. This changes the genotype-to-phenotype map, but not the rest of the model. It has been used in Liard et al. 2017 and Daudey et al. 2024.

Note: While the Standard flavor has undergone extensive validation and is considered stable for routine use, the 4-Bases and Eukaryote flavors implement more recent methodological developments and are therefore provided as advanced versions. While they are fully operational, some features are still being refined and may evolve in future releases. We welcome user feedback to support their continued maturation. Both the Eukaryote and 4-Bases versions could also possibly work together, but this has not been sufficiently tested yet, and no executable file are currently provided.

References

Vincent Liard, Jonathan Rouzaud-Cornabas, Nicolas Comte, Guillaume Beslon (2017). A 4-base model for the Aevol in-silico experimental evolution platform. Proceedings of ECAL 2017, the Fourteenth European Conference on Artificial Life.
Hugo Daudey, David P. Parsons, Eric Tannier, Vincent Daubin, Bastien Boussau, Vincent Liard, Romain Gallé, Jonathan Rouzaud-Cornabas, Guillaume Beslon (2024). Aevol_4b: Bridging the gap between artificial life and bioinformatics. Proceedings of the 2024 Artificial Life Conference.