Table 2. Genes in uptake/transformation dataset. Gene name Length (bp) Predicted Function comA comB comC comD$ comE comE1 comF comM* comN comO comP comQ crp cyaA dprA icc ligA% murE pilA pilB pilC pilD# pilF2 radC rec-1 rec-2 ssb sxy 0365 0659 798 507 522 414 1338 339 687 1530 513 717 684 306 675 2532 1122 825 558 1467 450 1395 1221 693 540 705 1065 2367 507 654 1173 297 Transformation DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake Regulation Regulation Regulation Unknown Unknown DNA uptake DNA uptake DNA uptake DNA uptake DNA uptake Transformation Transformation Transformation DNA uptake Transformation Regulation Unknown Unknown Predicted functions related only to competence and transformation are listed. $frameshift in R3021. *frameshift in strain R2866. %nonsense mutation in PittAA. #frameshift in strain 22.1-21. doi:10.1371/journal.pone.0005854.t002 sites in the aligned blocks. If the former, we would expect most trees to have at least some clades resolved, so we counted the number of clades resolved in each tree of the genome dataset (the other datasets had too few trees to be informative). 75% of trees had at least 9 of 11 possible clades resolved and 90% had at least 5 clades resolved, indicating that most trees had appreciable resolution despite the evidence for recombination within align- ment blocks. Visual inspection of individual topologies confirmed this (see Figure 3A for an example). Thus disagreement between topologies resulted in the lack of resolution in the consensus tree, consistent with ubiquitous recombination throughout the genome. Although individual trees disagreed in the clades they supported, many trees also had unresolved relationships. If this lack of resolution was caused by insufficient informative sites, the longer aligned blocks should have had more resolving power. Indeed, aligned block length explained a significant portion of the variation in the number of clades resolved (Figure 3B; r2 = 0.61; Phylogeny of Competence Table 3. Number of aligned blocks with evidence for recombination. Dataset MLST Genome (.1000 nt) Genome (,1000 nt) Competence PhiTest RDP 2 of 7 aligned blocks 0 of 7 aligned blocks 88 of 90 aligned blocks 78 of 90 aligned blocks 2 of 11 aligned blocks 0 of 11 aligned blocks 18 of 30 aligned blocks 5 of 30 aligned blocks doi:10.1371/journal.pone.0005854.t003 P,2.2610216). This relationship was partially driven by the 12 aligned blocks shorter than 1 kb; excluding these reduced the coefficient of determination but did not change it being significant (r2 = 0.21; P = 561026). Therefore, the poor resolution of the MrBayes consensus trees is because some alignments had too few informative sites and because many of the clades supported in one tree were not supported in all trees. Given the strong evidence for recombination, we proceeded with additional phylogenetic analysis using three inference methods specifically designed to deal with recombinant sequences: BUCKy [32], SplitsTree [27,28], and ClonalFrame [33]. The results from each analysis are discussed in turn below. BUCKy is a Bayesian method of inference that combines information from individual trees to infer one tree [32]; it differs from standard consensus tree approaches in considering the support for each clade in each input tree during inference of the final tree. For each of our three datasets, the distribution of trees from each alignment block (standard output of MrBayes) was used as input for BUCKy, giving one tree for each dataset (Figure 4). The numbers next to each clade in Figure 4 are concordance factors indicating the number of alignment blocks that have that clade. Few clades were supported by the majority of alignment blocks, indicating that combining information from multiple alignment blocks for inference in BUCKy does little to increase support for clades, especially those that are basal. Nevertheless some clades were found in trees from all datasets; these include the PittAA/3655 clade and the R2866/PittII/22.1-21 clade. SplitsTree infers evolutionary relationships without assuming that evolution occurs only by bifurcation [27,28], allowing the evolution of strains to be represented as a network containing both bifurcations and reticulations. We concatenated all alignment blocks for each dataset and used the resulting three alignments as input for SplitsTree. Consistent with the evidence for recombina- tion given above, this showed extensive network structure, particularly in basal relationships (Figure 5). The R2866/PittII/ 22.1-21 clade was found in the network from each dataset; otherwise there was no agreement between the relationships inferred by BUCKy and SplitsTree for the Genome and Uptake/ transformation datasets. In contrast, many of the clades in the MLST BUCKy tree were also found in the SplitsTree network, indicating that the MLST data may give more reproducible results with different inference methods. Resolving strain relationships may improve if regions of recombination were removed from the alignment blocks. To do this, we used ClonalFrame, a coalescent-based Bayesian method that excludes putative recombinant regions before inferring strain relationships [33]. This method is computationally intensive so we only applied it to the MLST dataset. Three replicate runs were done to assess convergence of results, producing the consensus topology shown in Figure 6. Although most of the basal PLoS ONE | www.plosone.org 4 June 2009 | Volume 4 | Issue 6 | e5854