Objective: Toward the characterization of of bacterial replicons, we are working on analytical methodologies able to represent functional and evolutionary relationships between replicons and relative to a certain set of annoted genes. The genome of bacteria is classically separated into the essential, stable and slow evolving chromosomes and the accessory, mobile and rapidly evolving plasmids. Recently, a new class of genomic elements, in between chromosomes and plasmids, has been highlighted. Named "megaplasmids", "secondary chromosomes" or "chromids", the true nature and evolution of these genomic elements are yet to be determined. Methodology: Using databases of genes functionally related to genetic information transmission systems (GITS) as inputs, we performed a global comparative genomic analysis on all available bacterial genomes with the following methodology: I) Identification and assession of functional homologs in all bacterial genome. II) Construction of clusters of proteins linking the bacterial replicons by their GITS, relative to the shared functions and sequences homologies. III) Unsuperivsed (Visualisation, clustering) and supervised (classification, regression) analyses of the replicons. The comparison and the biological assessment of the obtained results was performed using external criteria based on the taxonomy and structure of replicons and internal criterion based on stability measurements. Result: Bipartite graphs were useful tools to represent meaningfully the replicons according to their GITS proteins. Additionally, community detection algorithms (INFOMAP) gives results with the best performances in term of stability and relative to the bacterial taxonomy compared to traditional clustering methodologies. Based on these results we were able to characterize the third class of replicons relative to chromosomes and plasmids. Conclusion: With a specific representation of the genomic dataset and using a particular methodology, we were able to produce results with strong biological implications. Moreover this study provides the material for supplementary analyses (workflow improvement/enrichment, classifications...) in order to highlight some of the driving forces of the genomes evolution.