title: Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution.
abstract: 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.
authors.affiliation: Equipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France. Electronic address: eduardo.corel@upmc.fr.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Corel
authors.affiliation: Equipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France.
authors.forename: Philippe
authors.initials: P
authors.lastname: Lopez
authors.affiliation: Equipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France.
authors.forename: Raphaël
authors.initials: R
authors.lastname: Méheust
authors.affiliation: Equipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France.
authors.forename: Eric
authors.initials: E
authors.lastname: Bapteste
mesh_terms: D001419:Bacteria / Q000235:genetics*; D019143:Evolution, Molecular; D053263:Gene Regulatory Networks; D022761:Gene Transfer, Horizontal; D016678:Genome; D008957:Models, Genetic; D013559:Symbiosis
keywords: bipartite graph; evolution; gene transfer; graph theory; introgression; symbiosis