Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution

Eduardo Corel (1) , Philippe Lopez (1) , Raphaël Méheust (1) , Eric Bapteste (1)

1 Evolution Paris Seine

The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts.

Keywords: introgression; gene transfer; graph theory; bipartite graph; symbiosis; evolution

Domains: Microbiology and Parasitology

Eduardo Corel, Philippe Lopez, Raphaël Méheust, Eric Bapteste. Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution. Trends in Microbiology, 2016, 24 (3), pp.224-237. ⟨10.1016/j.tim.2015.12.003⟩. ⟨hal-01300043⟩