"The comparison of molecular sequences from organisms, environmental samples and mobile genetic elements is fundamental in evolutionary biology to study genes, genomes and species evolution. Although phylogenetic methods play a major role in these analyses, through the inference of phylogenetic trees or networks based on families of homologous sequences, many data remained underexplored as the number of molecular sequences of interest exponentially grows, with typical environmental samples containing thousands of species represented by millions of sequences. In order to further enhance the evolutionary comparison of molecular sequences, this project will develop a complementary approach, the use of large complex similarity networks (typically a few million nodes and tens of millions of edges), adapted to evolutionary biology questions. Such networks, inspired by the studies on social and regulatory networks, are only currently studied by a limited number of research teams. They allow for fast inclusive comparative analyses of both (highly) divergent and conserved sequences, fully or partly similar. This project will consist in developing similarity networks to (i) identify and study chimeric genes and genomes, (ii) detect and analyze the common genetic goods shared between gene families and within microbial communities, (iii) test whether genetic diversity in environmental sequences is significantly larger, both quantitatively and qualitatively, than genetic diversity in the gene families of cultured organisms (and their MGE), (iv) improve the statistical framework to compare similarity networks. If funded, this project will provide an additional comparative framework, new methods of detection of environmental/genomic sequences of medical and biological interest, and a novel description of the structure of genetic diversity on Earth, unraveling the main partnerships and barriers to the exchange of sequences of DNA between genes, genomes, species and environments."