The concept of a fitness landscape arose in theoretical biology, while that of effective fitness has its origin in evolutionary computation. Both have emerged as useful conceptual tools with which to understand the dynamics of evolutionary processes, especially in the presence of complex genotype-phenotype relations. In this contribution we attempt to provide a unified discussion of these two approaches, discussing both their advantages and disadvantages in the context of some simple models. We also discuss how fitness and effective fitness change under various transformations of the configuration space of the underlying genetic model, concentrating on coarse-graining transformations and on a particular coordinate transformation that provides an appropriate basis for illuminating the structure and consequences of recombination.

A l’ère des omiques, l’étude des relations génotype-phénotype repose sur l’intégration de données diverses décrivant des aspects complémentaires des systèmes biologiques. La génomique comparative offre un angle d’approche original, celui de l’évolution, qui permet d’exploiter la grande diversité phénotypique du Vivant. Dans ce contexte, mes travaux de thèse ont porté sur la conception de marqueurs évolutifs décrivant les gènes selon leur histoire évolutive. Dans un premier temps, j’ai construit une ressource d’orthologie complète, OrthoInspector 3.0 pour extraire une information évolutive synthétique des données génomiques. J’ai ensuite développé des outils d’exploration de ces marqueurs en relation avec les données fonctionnelles et/ou phénotypiques. Ces méthodes ont été intégrées à la ressource OrthoInspector ainsi qu’au réseau social MyGeneFriends et appliquées à l’étude des ciliopathies, conduisant à l’identification de 87 nouveaux gènes ciliaires. / In the omics era, the study of genotype-phenotype relations requires the integration of a wide variety of data to describe diverse aspects of biological systems. Comparative genomics provides an original perspective, that of evolution, allowing the exploitation of the wide phenotypic diversity of living species. My thesis focused on the design of evolutionary markers to describe genes according to their evolutionary history. First, I built an exhaustive orthology resource, called OrthoInspector 3.0, to extract synthetic evolutionary information from genomic data. I then developed methods to explore the markers in relation to functional or phenotypic data. These methods have been incorporated in the OrthoInspector resource, as well as in the MyGeneFriends social network and applied to the study of ciliopathies, leading to the identification of 87 new ciliary genes.