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Published online before print
August 9, 2006, 10.1101/gr.5322306 Genome Res. 16:1099-1108, 2006 ©2006 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/06 $5.00
Letter Phylogenetic analyses of cyanobacterial genomes: Quantification of horizontal gene transfer events1Genome Atlantic and Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Nova Scotia B3H 1X5, Canada; 2Department of Molecular and Cell Biology, University of Connecticut, Storrs, Connecticut 06269, USA
Using 1128 protein-coding gene families from 11 completely sequenced cyanobacterial genomes, we attempt to quantify horizontal gene transfer events within cyanobacteria, as well as between cyanobacteria and other phyla. A novel method of detecting and enumerating potential horizontal gene transfer events within a group of organisms based on analyses of "embedded quartets" allows us to identify phylogenetic signal consistent with a plurality of gene families, as well as to delineate cases of conflict to the plurality signal, which include horizontally transferred genes. To infer horizontal gene transfer events between cyanobacteria and other phyla, we added homologs from 168 available genomes. We screened phylogenetic trees reconstructed for each of these extended gene families for highly supported monophyly of cyanobacteria (or lack of it). Cyanobacterial genomes reveal a complex evolutionary history, which cannot be represented by a single strictly bifurcating tree for all genes or even most genes, although a single completely resolved phylogeny was recovered from the quartets’ plurality signals. We find more conflicts within cyanobacteria than between cyanobacteria and other phyla. We also find that genes from all functional categories are subject to transfer. However, in interphylum as compared to intraphylum transfers, the proportion of metabolic (operational) gene transfers increases, while the proportion of informational gene transfers decreases.
Cyanobacteria occupy a diverse range of habitats. The 11 genome sequences included in this study represent freshwater, marine, and hot spring species, including four closely related marine cyanobacteria from the Prochlorococcus/marine Synechococcus group. Based on the shared traits of oxygenic photosynthesis, several single gene analyses (e.g., Giovannoni et al. 1988  ), and analyses of shared indels (Gupta et al. 2003), all cyanobacteria form a monophyletic phylogenetic group. Indeed, the "coherence" of cyanobacteria—by which we mean monophyly for all or the vast majority of genes—is often considered self-evident, and asserted without elaboration or citation (e.g., Hagen and Meeks 2001; Otero and Vincenzini 2004).
In 1979, Rippka et al. (1979)
Horizontal (or lateral) gene transfer (HGT), potentially followed by recombination with or replacement of resident homologs (orthologous replacement), is now recognized as a major force shaping evolutionary histories of prokaryotes (e.g., Koonin et al. 2001
Atypical nucleotide composition methods indicate that individual cyanobacterial genomes have acquired between 9.5% and 16.6% of their genes through HGT (Ochman et al. 2000
In spite of such evidence for HGT involving individual gene families in cyanobacteria and many other bacterial groups, coherence of the phyla is often assumed, and invoked as evidence that HGT is in the long run a weak force, and no serious challenge to the historical accuracy of the rRNA-based Tree of Life. There have been few systematic and exhaustive assessments of the extent to which bacterial phyla really are coherent (Beiko et al. 2005
More frequent within-phylum orthologous replacement (and homologous recombination) would serve to maintain similarity between members, while allowing divergence between phyla. Thus, the preferential sharing of a common gene pool could be itself the principal cause of coherence (Gogarten et al. 2002
Selection of sets of orthologous genes Detection of orthologous genes is an important step in attempts to estimate HGT events. Poor selection of sets of orthologous genes leads to hidden paralogy, which is a serious problem in phylogenetic reconstruction. Several different approaches are used frequently to detect sets of orthologous genes (e.g., Zhaxybayeva and Gogarten 2002 ; Lerat et al. 2003; Tatusov et al. 2003; Harlow et al. 2004); none is perfect. Our very conservative method (see Zhaxybayeva and Gogarten 2002 for methodology), requiring a reciprocal top-scoring BLAST hit for each member of a set of orthologs, may miss many sets of legitimate orthologous genes, but it minimizes data sets contaminated with paralogs.
Many genome-wide analyses (including analyses of cyanobacterial genomes in Zhaxybayeva et al. 2004
Embedded quartet decomposition analyses For this analysis, we developed a new tool that allows the inclusion of sets of orthologous genes with missing data. The tool is designed to examine all possible "embedded quartets" for each set of orthologous genes detected in a group of analyzed genomes, that is, all possible four-taxon trees that are consistent with (embedded within) a corresponding gene tree (Fig. 1). This method—"embedded quartet decomposition analyses" or "quartet decomposition," for short—is conceptually similar to the spectral analysis method of Hendy and Penny (1993) and Lento et al. (1995). A data set of orthologous genes can be, in principle, as small as four taxa (containing one quartet) or as large as 11 taxa (containing 330 embedded quartets). The resulting embedded quartets can be summarized to depict the evolutionary relationships among the genomes that are supported by a plurality of orthologous sets, as well as to delineate genes that conflict with this plurality consensus. We applied this method to the relaxed core of cyanobacteria.
Screening quartets for minimization of false inferences Quartets with a very short internal branch can produce misleading results because of the absence of sufficient phylogenetic information, thus we removed from our relaxed core data sets all quartets with fewer than three amino acid substitutions along the internal branch: 27 data sets had at least one embedded quartet with such a very short internal branch. To reduce long branch attraction artifacts (Felsenstein 1978 ), we also excluded embedded quartets with any unbroken external branch more than 10 times longer than the internal branch, and 798 data sets had at least one quartet excluded at this step.
Power of detection as assessed through simulations
We found that when >30% of the data sets resolve an embedded quartet (i.e., support one of the three possible tree topologies with at least 80% bootstrap support), the number of false positives is negligible (see Table 2 and Supplemental material). However, simulations introducing HGT events showed that the conservative approach of excluding quartets resolved by <30% of the data sets increases the number of false negatives (i.e., undetected transfer events). Simulations of either sort produced similar results whether analyzed with PhyML (Guindon and Gascuel 2003
Plurality signal and estimation of conflicts within the cyanobacterial group based on analyses of the relaxed core All embedded quartets retained after removal of those with short internal or long external branches were resolved by at least 30% of data sets. We summarized the plurality support for all embedded quartets across all data sets as well as conflicts with plurality in a diagram that we call a quartet spectrum (because we assess all possible combinations of four taxa, providing a full spectrum of possible relationships) (see Fig. 2). All quartet topologies supported by a plurality of data sets are compatible with each other, and therefore only one most parsimonious tree exists (a so-called perfect phylogeny, Felsenstein 2004 ). This tree, found using a supertree reconstruction algorithm (see Methods), is shown in Figure 3.
While the plurality signal supports one fully resolved tree topology, we found that a substantial proportion of data sets (685 data sets, or roughly 61% of analyzed data sets) exhibits conflict with the plurality signal in at least one embedded quartet. Some of these conflicts (those involving alternative sister relationships between terminal taxa and having at least 80% bootstrap support) are visualized in Figure 3. In the Supplemental material, we provide trees for the 131 data sets involved in conflicts indicated in Figure 3. One example is provided in Figure 4. Among genes conflicting with the plurality signal are genes involved in photosynthesis (see Table 3), including genes recently found in phages infecting Prochlorococcus (Lindell et al. 2004 ) and marine Synechococcus (Millard et al. 2004).
Incongruence of gene histories among Prochlorococcus/Synechococcus Among the 11 genomes, four belong to the Prochlorococcus/ marine Synechococcus group. Members of the Prochlorococcus genus have only been recently discovered because of their anomalously low fluorescence and small size (Chisholm et al. 1988 ). Marine Synechococcus and Prochlorococcus are proposed to diverge from a common phycobilisome-containing ancestor (Ting et al. 2002). While marine Synechococcus still uses phycobilisomes as light-harvesting antennae, members of the Prochlorococcus genus lack phycobilisomes and use a different antenna complex (Pcb), as well as possessing derivatives of chlorophyll a and b that are unique to this genus (for a recent review, see Partensky et al. 1999). In addition, marine Synechococcus and Prochlorococcus are adapted to different ecological niches: Marine Synechococcus is prevalent in coastal waters, while Prochlorococcus is ubiquitous in open subtropical and tropical ocean. Within Prochlorococcus marinus, two "ecotypes" are differentiated: low-light-adapted and high-light-adapted types (Rocap et al. 2003). In the 16S rRNA tree, high-light-adapted Prochlorococcus spp. arise from within a low-light-adapted clade (Ting et al. 2002).
We find numerous conflicts between these four genomes, those involving highly supported apparent transfers between terminal taxa being shown in Figure 3. Similarly, in a recent study, Beiko et al. (2005)
Transfers between cyanobacteria and other phyla Out of 1128 data sets, 879 had detectable homologs in selected prokaryotic genomes, and the remaining 249 data sets were "cyanobacteria-specific" (and therefore not suitable for estimation of interphylum transfers). Seven hundred of these 879 data sets were "phylogenetically useful," that is, were sufficiently resolved and either had cyanobacteria as a coherent group with 80% bootstrap support or had other taxa grouping within cyanobacteria at 80% bootstrap support. Of these 700 data sets, 540 support cyanobacteria as a coherent group (~77%), while 160 data sets (~23%) either have sequences from other taxa interspersed among cyanobacteria or some cyanobacterial sequences grouping somewhere else, suggesting possible transfer events to or from cyanobacteria (an example of such a data set is shown in Fig. 5, and additional examples are available as Supplemental material). Interestingly, 294 out of 540 data sets that support
cyanobacteria as a monophyletic group (54%, or 42% of the 700 phylogenetically useful data sets) conflict with the plurality consensus based on the quartet decomposition analyses (see above). This estimation suggests that there are more conflicts observed within cyanobacteria than between cyanobacteria and other phyla.
Distribution of genes among functional categories
Several recent studies attempt to estimate the number of HGT events at different taxonomic levels (e.g., Snel et al. 2002 ; Lerat et al. 2003; Mirkin et al. 2003; Beiko et al. 2005; Ge et al. 2005; Kunin et al. 2005). In some, investigators were only interested in the transfer of novel genes into genomes (Snel et al. 2002; Mirkin et al. 2003; Kunin et al. 2005), thus neglecting orthologous replacement, and underestimating the total number of transfer events among genomes of interest. In others, addressing orthologous replacement, investigators have limited themselves to analyses of very strictly defined (ubiquitous) core genes (Lerat et al. 2003; Ge et al. 2005), also underestimating the total number of horizontally transferred genes. In studies of either sort, consensus trees derived from bootstrap or posterior probability analyses, or trees based on concatenated data sets have been used as references against which to assess HGT. The former are often only partially resolved (e.g., as in Snel et al. 2002) and thus preclude detection of many phylogenetic conflicts, while the latter, as commonly used, entail the assumption that most genes do have a single history. For instance, Lerat et al. (2003) assume that individual data sets that do not statistically reject a tree based on their concatenated sequences have not experienced HGT when, in fact, their weak phylogenetic signals are compatible with many conflicting topologies (Bapteste et al. 2004). To avoid such problems, we make an a priori assumption that individual sets of orthologous genes may not have to have the same evolutionary history, and therefore are not suitable for concatenation. Quartet decomposition analyses also avoid the "averaging" effect of consensus trees, since they partition trees inferred for each bootstrapped sample into sets of possible embedded quartets, and allow summarizing data sets with varying numbers of taxa in a single diagram (Fig. 2). In addition, the quartet decomposition method represents an improvement over methods that rely on analyses of bipartitions, since the support values for individual embedded quartets do not decay when the internal branches become shorter because of more sequences being included in the analysis.
While a majority of analyzed extended data sets (~77%) support coherence (monophyly) of cyanobacteria, some do not, and we find significant conflicting phylogenetic signals within cyanobacteria (~61% of analyzed data sets). Such conflicts could be caused by (1) instances of horizontally transferred genes; (2) differentially lost paralogs, which are impossible to discriminate from transfer events; (3) systematic artifacts of phylogenetic reconstruction (e.g., long branch attraction, compositional biases, or biases introduced through wrong models of phylogenetic reconstruction); and (4) false positives caused by insufficient phylogenetic signal. All analyses based on phylogenetic inference face these problems (Gogarten and Townsend 2005 False negatives are also inevitable. Transfers between sister taxa are undetectable, as will be many from unsequenced donors with no sequenced close relatives. Simulations confirm that many transfers escape detection (Table 2), probably because of the causes mentioned above. Thus, the number of detected transfers in cyanobacteria that we report here should, indeed, be considered an underestimate.
Although a majority of our data sets conflict with the plurality signal, all plurality quartets are compatible with a single fully resolved phylogenetic tree (see Fig. 3). Does the plurality topology reflect an "organismal phylogeny"? Gary Olsen has suggested a rope metaphor to illustrate the evolution of organisms and their genes (cited in Zhaxybayeva et al. 2004 Given this definition of organismal lineage, our plurality topology can be interpreted as a snapshot of relationships among extant cyanobacterial lineages. However, the picture is incomplete without providing information about observed conflicts to the plurality signal. Figure 3 depicts 135 conflicts observed between the tips of the plurality topology. This accounts only for a subset of all 685 observed conflicts, since the majority of transfers, deeper in the tree, affect the positions of multiple taxa. The relationships recovered for the Prochlorococcus/ Synechococcus group point toward extensive gene flow between well-characterized groups of organisms.
The three Prochlorococcus marinus strains share many derived characteristics including cell shape, environment, type of antenna pigments (Partensky et al. 1999
Distribution of genes across functional categories shows that genes from all functional categories are transferred (see Figs. 6 and 7). We do not see a bias toward any biological function among the intraphylum HGT events (see Fig. 6), contradicting a recent report by Nakamura et al. (2004)
The fact that we detect that ~50% of extended gene families putatively have a history of HGT (either between cyanobacteria and other phyla, or within cyanobacteria, or both) suggests that HGT plays an important role in the evolution of cyanobacteria, and the relationships among the taxa of this phylogenetic group cannot be represented by a strictly bifurcating tree. We find more conflicts within cyanobacteria than between cyanobacteria and other phyla, as did Beiko et al. (2005) Nevertheless, cyanobacteria are far from a fully coherent group (all genes supporting monophyly). Twenty-three percent of the 700 data sets for which monophyly was tested failed the test, showing non-cyanobacteria within the cyanobacterial clade, or cyanobacteria embedded within other phyla. Interestingly, even among those genes supporting cyanobacterial monophyly, a majority showed evidence of HGT within the cyanobacteria.
Quartet decomposition analyses We analyzed 11 cyanobacterial genomes from NCBI and JGI databases: Anabaena sp. PCC7120, Trichodesmium erythraeum IMS101, Synechocystis sp. PCC6803, Prochlorococcus marinus CCMP1375 (also known as SS120), Prochlorococcus marinus MED4 (also known as CCMP1986), Prochlorococcus marinus MIT9313, marine Synechococcus WH8102, Thermosynechococcus elongatus BP-1, Gloeobacter violaceus PCC7421, Nostoc punctiforme ATCC29133, and Crocosphaera watsonii WH8501. We detected sets of orthologous protein-coding genes defined as mutual fully transitive reciprocal BLASTP (Altschul et al. 1997 ) hits (with E-value below 10–4) (see Zhaxybayeva and Gogarten 2002 for methodology). There are 3804 genes present in at least four of the genomes (see Table 1). In the analyses of the "relaxed core" presented, we used the 1128 genes present in at least nine of the genomes. Each data set was aligned using the CLUSTALW program version 1.83 (Thompson et al. 1994). For each data set, the shape parameter for a  distribution to approximate among-site rate variation (Yang 1994) was estimated using TREE-PUZZLE version 5.2 (Schmidt et al. 2002) with four discrete categories. One hundred bootstrap samples were generated using the SEQBOOT program from PHYLIP package version 3.6 (Felsenstein 1993), and for each bootstrap sample, a distance matrix was calculated using TREE-PUZZLE version 5.2 with the shape parameter set as estimated for the original data set. Phylogenetic trees from the distance matrices were calculated with the NEIGHBOR program from the PHYLIP package version 3.6 (Felsenstein 1993). For each data set of orthologous genes, we generated a list of embedded quartets (i.e., all possible combinations of four taxa contained in the data set). For each embedded quartet in each data set the bootstrap support vector was calculated, that is, the bootstrap support for each of the three alternative quartet topologies (see Zhaxybayeva and Gogarten 2003 for methodology and discussion of advantages of embedded quartet analyses). False inferences were screened as described in Results, and quartets with at least 80% bootstrap support for one of three possible unrooted tree topologies were summarized in a quartet spectrum diagram (see Fig. 2).
Plurality signal reconstruction
Functional category assignments
Simulations
In simulations to estimate false positives, no HGT was allowed. We selected 11 out of the 50 simulated genomes and performed the quartet decomposition analysis as described above. In addition, the same analysis was performed but using phylogenetic trees calculated instead with the PhyML program, version 2.4.4 (Guindon and Gascuel 2003 To estimate false negatives (i.e., instances of HGT that are not detected), the second and third sets of simulations were conducted using the same parameters, but permitting relations-biased HGT (more transfer among more recently diverged genomes), at one of two rates (nominally 1.0 event per generation, and nominally 0.5 events, respectively, within the entire population). Each of the resulting 50 genomes had ~22%–25% of genes with a history of HGT in the one simulation, and 11%–13% of genes with a history of HGT in the other simulation. We selected the same 11 genomes and performed the quartet decomposition analysis as described above. Since not every family that had a history of HGT during a simulation would have an impact on the phylogeny of the subset of 11 genomes used in the analysis, we corrected the number of genes with a history of transfer only to include those whose history could cause phylogenetic incongruities in the 11-taxon subtree.
Extended data sets analyses
Other software used
This work was supported through NASA Exobiology Program (NAG5-11470), NASA AISR (NNG04GP90G), and NSF Microbial Genetics Program (MCB-0237197) grants to J.P.G. and through CIHR (MOP-4467) and Genome Atlantic grants to W.F.D. O.Z. is supported through a CIHR Postdoctoral Fellowship and is an honorary Killam Postdoctoral Fellow at Dalhousie University.
3 Corresponding author.
E-mail olgazh{at}dal.ca; fax (902) 494-1355. Supplemental material is available online at http://www.genome.org. and http://carrot.mcb.uconn.edu/cyano/. Article published online ahead of print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.5322306.
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-Proteobacteria. PLoS Biol. 1:–E19.