Bousios et al. BMC Genomics 2010, 11:89 http://www.biomedcentral.com/1471-2164/11/89 As vast sequence data become available from whole- genome sequencing projects, the findings of this work should enable the detailed analysis of how Sireviruses interact with their plant hosts and shape their genomes, towards which the fact that Sireviruses inhabit only plants may have important implications. While our knowledge on the evolutionary depth, distribution and genomic organization of Sireviruses will expand, more informed functional analysis of the herein introduced motifs will elucidate how and why the Sirevirus life cycle differs from other retrotransposons. In light of such knowledge, in the modern era of large-scale tran- scriptome analysis, and in possession of new evidence for the major influence of retrotransposon acticity on the cell transcriptional output (alternative promoters, noncoding RNAs, bidirectional transcription) [54,55], we should be able to move closer to elucidating the role of Sireviruses in the epigenetic regulation of plant genes [56]. Finally, based on recent models that propose trans- posable elements as being major suppliers of cis-regula- tory elements to host genomes [57], Sireviruses with their novel type of RM may have been involved in the evolution of plant gene regulatory networks. Methods Ty1/copia datasets The Sirevirus and classic retrotransposon datasets were constructed by retrieving sequences from various sources. The information for each element, including the source, host species and Pseudoviridae genus is pro- vided (Table S1 in Additional file 1). The Pseudoviridae classification according to the ICTV database can be found at http://www.ncbi.nlm.nih.gov/ICTVdb/ICTVdB/ 00.097.htm. The raw sequence data (where all the con- served motifs are highlighted) of our Sirevirus database is available at http://bat.ina.certh.gr/downloads/Sirevir- us_sequence_data.doc. Sequence analysis tools Multiple alignments were carried out using ClustalW at default parameters [58] and the Jalview multiple align- ment editor [59] from the EBI website http://www.ebi. ac.uk/. MEGA4 [60] was used to construct the phyloge- netic tree using the neighbor-joining distance method [61]. Bootstrap test of phylogeny was calculated based on 1000 replicate trees and the evolutionary distances were computed using the Poisson correction model [62]. The RT-RH peptide alignment used for the analysis is provided (Additional file 4). Identification of the RM boxes and the IR were aided by the Tandem Repeat Fin- der [63] and Inverted Repeat Finder algorithms [64], respectively, available at the Laboratory for Biocomput- ing and Informatics http://tandem.bu.edu/tools.html. The RMs were compared against known plant cis-acting Page 12 of 14 regulatory sequences in the PLACE database [27,65], in order to identify target sites of DBFs. Finally, CpG islands were predicted using the CpGplot package [66] from the EBI website. TEIRESIAS pattern discovery algorithm Discovery of sequence motifs was performed with the use of the TEIRESIAS algorithm [25]. Importantly, TEIRESIAS is guaranteed to report all maximal patterns (i.e. patterns that cannot be made more specific and still keep on appearing at the exact same positions within the input sequences, or else non-redundant patterns) meeting the structural restrictions set by the user through parameters. In other words, no heuristics are employed in the discovery process. The complete set of parameters of TEIRESIAS used in this analysis is as fol- lows: nucleotides in the pattern (-l), number of overlap- ping characters in the convolved pattern (-c), maximum length of an elementary pattern (-w), minimum number of appearances of the pattern (-k), flag for the support k to be the minimum number of sequences in which a pattern should appear (compared to the minimum num- ber of instances of the pattern) (-v). Several sets of values for l, w, and k were used to obtain a comprehen- sive picture of the conservation of motifs in the input and this information was used critically and in context to produce the final observations. Additional file 1: The Pseudoviridae dataset used in this analysis. This file contains supplementary Table S1 showing the source, accession number, host species and Pseudoviridae genus for each retrotransposon. Click here for file [ http://www.biomedcentral.com/content/supplementary/1471-2164-11- 89-S1.PDF ] Additional file 2: Phylogenetic and structural domain analysis of the Sirevirus and classic Ty1/copia retrotransposons. This file contains supplementary Figure S1 showing the phylogenetic analysis of the Ty1/copia retrotransposons based on the RT/RH domains, supplementary Figures S2 and S3 with alignments of the IR arms of each Sirevirus and classic retrotransposon respectively, supplementary Figure S4 showing the distribution of the novel Sirevirus RM boxes, and supplementary Figure S5 with the 5’LTR alignment of the OPIE-2 and PREM-2 Sireviruses. Click here for file [ http://www.biomedcentral.com/content/supplementary/1471-2164-11- 89-S2.PDF ] Additional file 3: The stress-related DNA binding factors that target core sites within the RMs. This file contains supplementary Table S2 with information related to the binding site and its orientation within each RM and the stress nature of the DBFs. Click here for file [ http://www.biomedcentral.com/content/supplementary/1471-2164-11- 89-S3.PDF ] Additional file 4: List of the RT/RH peptide sequences that were used for the construction of the Ty1/copia phylogenetic tree. Click here for file [ http://www.biomedcentral.com/content/supplementary/1471-2164-11- 89-S4.PDF ]