Bosi et al. BMC Genomics 2011, 12:403 http://www.biomedcentral.com/1471-2164/12/403 and conjugation (7.9%, 7.3% and 7%, respectively, see red bars in Figure 5). Notably, this result partially vali- dates the applied approach for PAGs detection, since genes that are able to move across different molecules are also expected to differ from a compositional view- point from the correspondig hosting molecule. More- over, we found that another important fraction (303 sequences, corresponding to 10.9% of all the PAGs for which a putative function was retrieved) is represented by proteins involved in transcription regulation (DNA- mediated). A further investigation revealed that these proteins are mainly involved in important biological processes that are usually associated to plasmids and\or trasposons and that have a (more or less) long docu- mentated history of HGTs, such as mercury detoxifica- tion (e.g. MerD transcriptional regulator from plasmid pEC-IMP, GI: 226807665), tetracycline resistance (e.g. TetR trascriptional regulator of Salmonella typhimurium R64 plasmid, GI: 32470145) and virulence (e.g. VirF trascriptional regulator in plasmid pSS_046 of Shigella sonnei Ss046, GI: 74314878). The presence of such pro- teins within the assembled PAGs dataset is intriguing. Indeed, it might be expected that the introgression of proteins capable of interfering with the overall (com- plex) regulatory network of the cell might be (quite) “dangerous” (from a biological viewpoint) and prone to be counterselected by the novel hosting cell. However, further analyses (see below) revealed that, a considerable amount of PAGs are embedded in more or less compact clusters, involved in processes that are known to be often spread by HGT (including virulence, antibiotic resistance and heavy metals detoxification). Accordingly, atypical trascriptional regulators might be part of this gene clusters and, consequently, might be involved in the regulation of the flanking regions. Alternatively, it can be surmised that, after the introgression of the aty- pical transcriptional regulator, some modifications (i.e. mutations) might have occurred, rendering the newly acquired sequence compatible with the overall “new” regulatory network, that is more easily recognizable by the transcriptional apparatus of the host cell, as experi- mentally demonstrated [38]. After these two biological processes, we found that pathogenesis- and antibiotic resistance-related sequences are the most abundant among annotated PAGs (6.8% and 5.2%, respectively). Remarkably, the finding that these two biological pro- cesses are highly represented among atypical genes underlines the key role that HGT possesses in the spreading of these two important biological features within the microbial world. Finally, the high percentage of PAGs that did not retrieve any BLAST hit during the B2GO searches, might speak towards the presence of an important frac- tion of pseudogenes within our PAGs dataset. Page 7 of 12 Accordingly, these genes might represent aberrant sequences that, in the absence of strong selective pres- sure, have accumulated a great number of mutations and have evolved beyond recognition. The fact that we identified them as PAGs might rely on the observation that pseudogenes are often originated from failed HGT events between two different source molecules [39]. Interestingly, also premature stop codons (and, conse- quently, shorter proteins) have been indicated as a typi- cal characteristic of pseudogenes that, in turn, are known to originate (at least in part) from failed HGT [39]. Indeed, PAGs encoded proteins are, on average, shorter (136,5 aminoacids) than not-atypical ones (274,2 aminoacids, Figure 6), suggesting that part of the PAGs retrieved might indeed be pseudogenes, probably origi- nated from unsuccessful integration in the host plas- mids. Notably, PAGs datasests retrieved at different thresholds followed the same overall trend (Additional File 7). PAGs source molecules As previously pointed out, PAGs may derive from homo- logous recombination or homology-facilitated illegitimate recombination between a given plasmid and/or other informative molecules, that is phages, chromosomes or other plasmids. Hence, we aimed at identifying the puta- tive source molecule of PAGs. To this purpose, we have developed a computational approach (see Methods) that, on the basis of the number of orthologs present in differ- ent (and randomly assembled) plasmid, chromosome and phage databases allows to assign the most likely source molecule to a set of sequences (in our case the 8065 Figure 6 PAGs length. The length of PAGs encoded proteins (red line) compared to the length of all the other plasmids encoded proteins (blue line) present in the dataset.