Author(s): Tobes R, Pareja E
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Abstract BACKGROUND: Mobile elements are involved in genomic rearrangements and virulence acquisition, and hence, are important elements in bacterial genome evolution. The insertion of some specific Insertion Sequences had been associated with repetitive extragenic palindromic (REP) elements. Considering that there are a sufficient number of available genomes with described REPs, and exploiting the advantage of the traceability of transposition events in genomes, we decided to exhaustively analyze the relationship between REP sequences and mobile elements. RESULTS: This global multigenome study highlights the importance of repetitive extragenic palindromic elements as target sequences for transposases. The study is based on the analysis of the DNA regions surrounding the 981 instances of Insertion Sequence elements with respect to the positioning of REP sequences in the 19 available annotated microbial genomes corresponding to species of bacteria with reported REP sequences. This analysis has allowed the detection of the specific insertion into REP sequences for ISPsy8 in Pseudomonas syringae DC3000, ISPa11 in P. aeruginosa PA01, ISPpu9 and ISPpu10 in P. putida KT2440, and ISRm22 and ISRm19 in Sinorhizobium meliloti 1021 genome. Preference for insertion in extragenic spaces with REP sequences has also been detected for ISPsy7 in P. syringae DC3000, ISRm5 in S. meliloti and ISNm1106 in Neisseria meningitidis MC58 and Z2491 genomes. Probably, the association with REP elements that we have detected analyzing genomes is only the tip of the iceberg, and this association could be even more frequent in natural isolates. CONCLUSION: Our findings characterize REP elements as hot spots for transposition and reinforce the relationship between REP sequences and genomic plasticity mediated by mobile elements. In addition, this study defines a subset of REP-recognizer transposases with high target selectivity that can be useful in the development of new tools for genome manipulation.
This article was published in BMC Genomics
and referenced in Journal of Data Mining in Genomics & Proteomics