FP7 EvoEvo

EvoEvo : Evolution of Evolution

[2013-2016]

Variation and Selection are the two core engines of Darwinian Evolution. Yet, both are directly regulated by many processes that are themselves products of evolution (e.g. DNA repair, mutator genes, transposable elements, horizontal transfer, stochasticity of gene expression, sex, network modularity, niche construction…). This ability is the core of the EvoEvo process. Different “Evolution of Evolution” strategies have been proposed in the literature, including regulation of variability, robustness/evolvability strategies, bet-hedging … However, most of them are poorly characterized and the conditions under which they evolve as well as their consequences are generally unknown.

To develop a better understanding of EvoEvo, we propose to build a conceptual framework based on two important concepts of evolutionary biology: the genotype-to-phenotype mapping and the fitness landscape. The genotype-to-phenotype mapping summarizes in a single conceptual entity the complex molecular processes by which information flows from the genetic sequence to the organism’s phenotype. It thus concatenates in a single abstract process different phenomena such as mRNA transcription, gene translation, protein folding, biochemistry and cell dynamics. The central idea of the fitness landscape is that organisms or populations in evolution can be represented as points on a landscape where the altitude represents the fitness. Selection can be represented by the local gradient of altitude and the mutation can be represented as a random noise added to individual positions.

We propose to study EvoEvo by focusing on four characteristics of the genotype-to-phenotype mapping and the fitness landscape:

Variability.

Variability is the ability to generate new phenotypes, by mutations or by stochastic fluctuations. It is a necessary condition for any evolutionary process to take place. However, in biological organisms, the amount of variability is controlled by complex pathways that e.g. correct DNA mismatches or double-strand breaks. Mutational operators are highly diversified, including point mutations, but also large chromosomal rearrangements that can rapidly reshuffle the chromosome organisation, extend or reduce the gene repertoire of an organism or even duplicate its entire genome through whole genome duplication.

Robustness.

Although mandatory, variability is a very dangerous process since it permanently produces deleterious mutations that lead to poorly adapted individuals. Robustness may evolve to correct these deleterious effects. It enables evolving systems to support mutational events without loosing fitness through e.g. canalisation or the selection of structures that creates neutral landscapes.

Evolvability.

Depending on the genotype-to-phenotype mapping, the pro- portion of deleterious/neutral/favorable mutational events may change. Evolvability is the ability of a specific genotype-to-phenotype mapping to increase the proportion of favorable events. This can be done by the selection of specific genome structures or by the selection of specific network structures.

Open-endedness.

Biological evolution is not directed towards a specific target. On the opposite, evolution has the ability to generate new challenges while evolving by e.g. exploiting new niches created by the evolution of other species.

The central concept of EvoEvo is the following: if the genotype-to-phenotype mapping and the fitness landscape are allowed to change over time, if they can be (indirectly) selected, then they can evolve and acquire properties than could favor evolution in changing environments.

Jonathan Rouzaud-Cornabas
Jonathan Rouzaud-Cornabas
Associate Professor of Computer Science

My research interests include computational biology, high performance computing and ordinary differential equations.