Analysis of plasmid genes by phylogenetic profiling and visualization of homology relationships using Blast2Network
1 Department of Evolutionary Biology, University of Florence, via Romana 17, I-50125 Florence, Italy
2 Computer Laboratory, University of Cambridge, 15 JJ Thompson Avenue, Cambridge, CB3 0FD, UK
3 Laboratoire de Biometrie et Biologie Evolutive, UMR CNRS 5558, Lyon, France
BMC Bioinformatics 2008, 9:551 doi:10.1186/1471-2105-9-551Published: 21 December 2008
Phylogenetic methods are well-established bioinformatic tools for sequence analysis, allowing to describe the non-independencies of sequences because of their common ancestor. However, the evolutionary profiles of bacterial genes are often complicated by hidden paralogy and extensive and/or (multiple) horizontal gene transfer (HGT) events which make bifurcating trees often inappropriate. In this context, plasmid sequences are paradigms of network-like relationships characterizing the evolution of prokaryotes. Actually, they can be transferred among different organisms allowing the dissemination of novel functions, thus playing a pivotal role in prokaryotic evolution. However, the study of their evolutionary dynamics is complicated by the absence of universally shared genes, a prerequisite for phylogenetic analyses.
To overcome such limitations we developed a bioinformatic package, named Blast2Network (B2N), allowing the automatic phylogenetic profiling and the visualization of homology relationships in a large number of plasmid sequences. The software was applied to the study of 47 completely sequenced plasmids coming from Escherichia, Salmonella and Shigella spps.
The tools implemented by B2N allow to describe and visualize in a new way some of the evolutionary features of plasmid molecules of Enterobacteriaceae; in particular it helped to shed some light on the complex history of Escherichia, Salmonella and Shigella plasmids and to focus on possible roles of unannotated proteins.
The proposed methodology is general enough to be used for comparative genomic analyses of bacteria.