Department of Biology and Centro Ricerche Interdepartimentale Biotecnologie Innovative (CRIBI), University of Padova, Padova, Italy
Correspondence: E-mail alessandro.minelli{at}unipd.it.
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Abstract |
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Key Words: Chilopoda Myriapoda Scutigera coleoptrata mitochondrial genome arthropod phylogeny
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Introduction |
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Traditional classifications placed the Chelicerata as sister group of the Mandibulata (Crustacea, Myriapoda, and Hexapoda, with the last two subphyla grouped together in a taxon named Atelocerata). Molecular analyses during the last decade (Boore et al. 1995; Friedrich and Tautz 1995; Boore, Lavrov, and Brown 1998; Burke et al. 1998; Cook et al. 2001; Hwang et al. 2001) have challenged this view and favored an alternative phylogeny in which the Crustacea and the Hexapoda form a monophyletic clade, Pancrustacea, whereas Myriapoda either feature as the sister group of the latter, or are grouped together with the Chelicerata in a not yet formally named clade. Within the Pancrustacea, the hexapods are sometimes found to be the sister group of the Malacostraca (Wilson et al. 2000; Hwang et al. 2001; Nardi et al. 2001): in this case, the Crustacea appears to be a paraphyletic taxon. Molecular data concerning mitochondrial genomes, both as primary sequences and as gene order (Boore et al. 1995; Boore, Lavrov, and Brown 1998; Hwang et al. 2001), has strongly contributed to these new phylogenetic views. However, taxonomic sampling of the main arthropod lineages has been uneven, with Chilopoda being very poorly represented and no known data on the mtDNA of the Scutigeromorpha, the sister group of all remaining centipedes, based on both morphological and molecular evidence (e.g., Edgecombe and Giribet 2002). Hence, we sequenced the complete mitochondrial genome of the common house centipede Scutigera coleoptrata, in order to know more about the higher phylogeny of arthropods, in particular to test whether the Myriapoda are monophyletic (Edgecombe and Giribet 2002) and what their phylogenetic relationships are with the other major arthropodan clades. These questions are obviously central to a reconstruction of the origin of terrestrial habits and corresponding morphological and physiological adaptations evolved in some of the most successful animal lineages on earth.
We show here the results of a phylogenetic analysis based on the complete mitochondrial gene-coding sequences and their products from representatives of these four taxa, including the house centipede Scutigera coleoptrata, whose sequence is discussed for the first time in this article.
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Materials and Methods |
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A long polymerase chain rection (PCR) strategy was applied to amplify the whole mitochondrial genome. To start, a 449-bp fragment of the large ribosomal subunit rrnL was PCR amplified with the two primers 16Sfor (5'-CGG GTT GAA CTC AGA TCA-3') and 16Srev (5'-CGC GCC TGT TTA TCA AAA ACA T-3') which were designed on a multiple alignment of several rrnLs, including the centipede Lithobius forficatus. The DNA sequence obtained from this segment was used to select the two primers ScuHPK16Saa (5'-GAT TAT GCT ACC TTC GCA CGG TCA AAA TAC CG-3') and ScuHPK16Sbb (5'-CAT ATC GAC AAT AAG GGT TGC GAC CTC GAT GTT G-3'). The complete genome was then amplified using the Expand Long Template PCR (Roche Biochemicals) according to the protocol provided, with the ScuHPK16Saa and ScuHPK16Sbb primers. A genome walking strategy was successively applied to sequence directly the products obtained through consecutive long PCR amplifications. Sequencing was performed at the CRIBI Sequencing Service (University of Padova) on automated DNA sequencers.
The complete sequence of the Scutigera coleoptrata mitochondrial genome is available at the European Molecular Biology Laboratory (EMBL) database under accession number AJ507061.
Data Set Selection
Complete mitochondrial genome sequences for taxa other than Scutigera were obtained from GenBank. Taxa were selected according to two criteria: (1) a balanced and representative selection of the major arthropod clades and (2) a selection of genomes having distinct gene orders, thus representing the genomic order diversity within the phylum. The taxa analyzed are listed in table 1. Lumbricus terrestris (Annelida) and Katharina tunicata (Mollusca) were selected as outgroups. The resulting starting number of taxa was 21, including S. coleoptrata. The choice of an annelid and a mollusk as outgroups was made because no complete mitochondrial genome sequences are available for the species more closely related to the Arthopoda sensu strictoi.e., the tardigrads and onychophorans. Complete mitochondrial genomes of nematodes (which, like the arthropods, belong to the ecdysozoan lineage) could have been considered as outgroups, but their extremely high rate of substitution and strong compositional bias made them unsuitable for this purpose (Foster and Hickey 1999; Hwang et al. 2001). The results of the analyses detailed below show that the sequences of the two outgroups are homogeneous for composition and evolved at a comparable rate with the ingroup sequences, thus excluding possible artifacts in the placement of the root within the ingroup.
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On these data sets we investigated the major factors that could potentially bias the phylogenetic analysis and therefore affect tree topology strongly. In particular, we conducted several preliminary investigations to verify possible effects resulting from (1) the rate of the nucleotide substitution process, (2) the amount of phylogenetic signal present in the data sets, (3) the compositional bias in NUC19T and PRO19T, (4) taxon sampling, and (5) usage of the protein data set versus the nucleotide data set.
Rate of the Nucleotide-Substitution Process
The level of saturation in the whole codons, and at the first, second, and third codon positions separately, was analyzed using scatter plot graphics, comparing the uncorrected p-distances (i.e., the distances obtained by dividing the number of observed differences between each couple of sequences by the length of the pairwise alignment) with the distances calculated by applying the best-fit evolutionary model (GTR + G + I) selected by the Modeltest program (Posada and Crandall 1998). In the absence of saturation in the nucleotide substitution process, GTR + G + I distances coincide with p-distances; conversely, GTR + G + I distances are larger than p-distances when the level of saturation increases. GTR + G + I distances are distinctly larger than p-distances in the case of saturation of the nucleotide-substitution process.
Phylogenetic Signal Detection
A priori estimation of the phylogenetic signal present in the analyzed data sets was performed according to the maximum likelihood mapping method (Strimmer and von Haeseler 1997) using the Tree-Puzzle 5.0 program (Schmidt et al. 2002). With this approach, the amount of phylogenetic signal present in a multiple alignment is mirrored by the percentage of the fully resolved quartets (Strimmer and von Haeseler 1997). Moreover, the length of the alignment affects the phylogenetic resolution. In the case of the nucleotide data sets, the amount of phylogenetic signal was estimated for first, second, third, and first + second positions separately.
Compositional Bias
The statistical significance of the nucleotide compositional biases was investigated for whole codons, as well as for all possible combinations of first, second, and third positions. The departure from homogeneity in base composition across the taxa was checked by applying the 2 test available in the PAUP 4.10 program (Swofford 2002) to nucleotide data sets. Conversely, the protein compositional bias was analyzed with the Tree-Puzzle 5.0 program (Schmidt et al. 2002).
Taxon Sampling
Many preliminary analyses were conducted on different intermediate data sets obtained from NUC19T or PRO19T by inclusion/exclusion of selected taxa and inclusion/exclusion of first/second and third positions or protein sequences (data not shown). Phylogenetic methods applied to these data sets are presented in detail below, under Tree Reconstruction. These analyses were performed to investigate the effects due to factors considered above in the sequence alignment and blocks selection paragraphs.
Among the numerous intermediate data sets investigated, we selected two final nucleotide data sets to (1) minimize departure from compositional homogeneity, (2) maximize taxon sampling, (3) maximize the amount of phylogenetic signal, (4) reduce the amount of homoplasy due to saturation, and (5) speed up the computational efforts, particularly in the ML bootstrap test. The two final data sets are described below. The first (hereafter named 14T4452) includes both first and second codon positions of 14 taxa (length: 4,452 bases) and was obtained by exclusion of the A. franciscana, D. pulex, R. sanguineus, I. hexagonus, and T. bielanensis sequences. The second data set (hereafter named 19T2226) includes all 19 taxa and is based on the second codon positions only (length: 2,226 bases). Parallel to the nucleotide data sets, we considered also two protein data sets. The first (named PRO14T) includes the same taxa present in 14T4452 data set and was obtained by removing from the PRO19T the above-mentioned taxa. The second data set was PRO19T itself. This choice allowed an easy comparison among trees obtained from nucleotide data sets and those obtained from protein data sets.
Tree Reconstruction
Phylogenetic analyses on the PRO19T, PRO14T, 14T4452, and 19T2226 data sets were performed according to the Bayesian inference (BI) (Huelsenbeck et al. 2001), maximum likelihood (ML), minimum evolution (ME) or Neighbor-Joining (NJ), maximum parsimony (MP) (Nei and Kumar 2000), and quartet-puzzling (QP) methods (Strimmer and von Haeseler 1996). Our results were derived mainly from analyses performed applying ML methods (including BI). In fact ML methods are very flexible due to their plasticityi.e., the possibility to implement and apply complex evolutionary models that account for several biases faced by sequences during evolution. Moreover, ML methods are theoretically very sound and statistically consistent and have proved to be very efficient in recovering correct phylogenies, even when the sequences analyzed have evolved through very complicated evolutionary pathways (Whelan, Liò, and Goldman 2001).
The ML, ME, and MP phylogenetic analyses on the nucleotide data sets were performed with PAUP 4.10 (Swofford 2002). The branch swapping was performed applying the tree bisection-reconnection TBR algorithm with the steepest descent option activated. For the ML and ME trees, the (GTR + G + I) models fitting best to the data sets were selected with the Modeltest program and according to the akaike criterion (Posada and Crandall 1998). Parsimony analyses were limited to parsimony-informative characters. Bayesian phylogenetic analyses were performed with MrBayes 2.1 (Huelsenbeck and Ronquist 2001). A GTR + G + I evolutionary model was applied in all analyses. The Metropolis-coupled Markov chain Monte Carlo sampling approach was used to calculate posterior probabilities. Prior probabilities for all trees were equal, starting trees were random, tree sampling was done every 20 generations, and burn-in values were determined empirically from the likelihood values. To check for consistency of results, four Markov chains were run simultaneously for 100,000 generations.
The NJ, MP, ML, and QP analyses on protein data sets were performed with the PHYLIP 3.6a3 and Tree-Puzzle programs (Felsenstein 2002; Schmidt et al. 2002).
Neighbor-Joining analysis was conducted in two steps: the ML distances were calculated with Tree-Puzzle, applying the mtREV24 substitution matrix (Adachi and Hasegawa 1996), then the ML distances matrices were provided to the NEIGHBOR program in the PHYLIP package to built up the final NJ trees. The same strategy was used for the nonparametric bootstrap, starting from 100 data matrices obtained respectively from PRO14T and PRO19T, using the program SEQBOOT in the PYLIP package. Maximum parsimony analysis was conducted using PROTPARS with the Jumble option active. Maximum likelihood trees were built up using PROML, with the Jumble and Global rearrangement options active, applying both the Dayhoff-PAM and JTT substitution matrices (Dayhoff, Schwartz, and Orcutt 1978; Jones, Taylor, and Thornton 1992). Alternatively, QP trees were built up with Tree-Puzzle, applying the mtREV24 substitution matrix and a four rate approximated gamma distribution of among-site rate heterogeneity with or without a portion of the sites considered invariable. In this case the best tree was selected by the Kishino-Hasegawa test (Kishino and Hasegawa 1989).
Bayesian inference analysis on PRO14T and PRO19T data sets were done using the MrBayes 3 program (Ronquist and Huelsenbeck 2003). An mtREV substitution matrix (Adachi and Hasegawa 1996) was used while the invgamma option corresponding to G + I was used to treat the among-site rate variation. All other options were identical to those applied to the nucleotide data sets.
Nonparametric Bootstrap Test
The nonparametric bootstrap test (BT) (Felsenstein 1985) was performed to test the robustness of tree topologies. In the case of the 14T4452 and 19T2226 nucleotide data sets we performed 100 replicates for the ML trees and 1,000 replicates for the ME and MP trees. For the protein PRO14T and PRO19T data sets, 100 replicates were always performed.
Testing for Alternative Tree Topologies
To evaluate alternative phylogenetic hypotheses, the almost unbiased test (AU) and the weighted Shimodaira-Hasegawa test (WSH) (Shimodaira 2002) were calculated for different tree topologies. Calculations were done on 14T4452 and 19T4452 data sets using the CONSEL program (Shimodaira and Hasegawa 2001). The 19T4452 data set was obtained from NUC19 by deleting third codon positions. This set presents a distinctly higher level of phylogenetic signal than the 19T2226 data set (see Results). Maximum likelihood and BI tree topologies obtained from 19T4452 match perfectly with those obtained from the 19T2226 data set. We could not use the 19T4452 data set in our ML bootstrap test because of the extremely long computational time required with the available computer facilities. Alternative tree topologies obtained from protein data sets were evaluated with the Bayesian posterior probability (BPP) as implemented in MrBayes 3.
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Results |
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Rate of the Nucleotide Substitution Process
The level of nucleotide substitution in the NUC19T data set, as evaluated by scatter plot graphics, is presented in figure 1. Second positions show the lowest level of saturation. First positions present a higher level of saturation, especially in those species (T. bielanesis, A. franciscana, D. pulex, I. hexagonus, and R. sanguineus) that have GTR + G + I distances >1 from many other taxa of the ingroup. Third positions are fully saturated.
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The BI tree obtained from PRO19T is mostly congruent with the nucML tree, from which it however differs in favoring the L. migratoria + T. dimidiata clade (BI support 95%). The protML tree was the same, irrespective of the substitution matrix used and the treatment of site rate variation. This tree differs from the nucML tree in recovering a monophyletic Myriapoda (without QP or BT support) sister group of Chelicerata and the L. migratoria + T. dimidiata clade (BT support 70% only). Maximum parsimony analysis on PROT19T produced a single tree, which presented some unusual groupings: Chelicerata are disrupted with L. polyphemus sister taxon of Diplopoda, whereas the two ticks form a clade with T. bielanensis (marginally BT supported, 57%). Moreover, this latter group is placed as sister taxon to all remaining Arthropoda. Finally, the protNJ tree mostly agrees with the nucML tree, except for the myriapod clade that is recovered as monophyletic, but not receiving BT support, and sister group of Chelicerata.
Testing for Alternative Tree Topologies
To avoid overinterpretation of our results, we performed on the nucleotide data sets the AU and WSH statistical tests that allow comparison of alternative phylogenetic hypotheses. Possible controversial points in our tree topologies can thus be evaluated as follows. AU as well as WSH tests were not significant in rejecting (1) the monophyly of the Myriapoda, (2) the paraphyly of Crustacea, or (3) the placement of T. bielanensis within the Hexapoda. The monophyly of Myriapoda received also marginal support in the ML analysis, and a more robust support in BI reconstructions on protein data sets. Conversely AU tests strongly reject (P < 0.001) the hypothesis of the Myriapoda as sister group of the Hexapoda, or as basal clade of the Mandibulata (P < 0.001). These results were also supported by the very conservative WSH test (P < 0.05). Bayesian posterior probability tests performed on the protein data sets give results very similar to those obtained on the 14T4452 and 19T4452 nucleotide data sets. In particular, these tests rejected strongly the placement of the Myriapoda as either sister group of Hexapoda (P < 0.001) or as a basal clade of the Mandibulata (P < 0.05), whereas they were not significant in solving the above-mentioned pointsi.e., the monophyly vs. paraphyly of Myriapodaas well as the placement of T. bielanensis and the paraphyly of Crustacea.
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Discussion |
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Analyses performed on the protein data sets give results that agree, in large part, with those obtained from nucleotide data sets when analyzed with BI and ML methods. Differences observed (see details in the Results) cannot be solved with the data sets at hand. The ML topologies obtained from the PRO14T and PRO19T multiple alignments receive poor bootstrap support in some of the more basal and phylogenetically critical nodes. These results were expected as a consequence of the selection process of conserved amino acid blocks (Castresana 2000). In fact, the choice made by the Gblocks program of conserved amino acid portions has two positive effects: (1) the level of homogeneity among the sequences is markedly increased and (2) chances are very low that positional homology is lost. These are, of course, very desirable properties of the final alignment. Conversely, this method may remove the more diverging or some misleading coincidentally biased positions, thus reducing particularly the support of basal nodes in the ML tree (see Castresana 2000 for a more detailed discussion). This effect, however, does not appear to influence the nucleotide multiple alignments, which produced topologies well supported even at the basal nodes whenever a high phylogenetic signal was present (see fig. 2).
Main Phylogenetic Results
In our analysis based on the 19T2226 and PRO19T data sets, the Crustacea were recovered as a monophyletic group (nucBI, nucML, protML, protNJ, and protMP analyses) whereas some previous molecular analyses had indicated a paraphyletic Crustacea with respect to Hexapoda (Wilson et al. 2000; Cook et al. 2001; Nardi et al. 2001). Moreover, the spring-tail Tetrodontophora bielanensis does not group with the other hexapods. This result is in agreement with previous molecular studies (Nardi et al. 2001, 2003), suggesting an isolated position for the Collembola within the Pancrustacea. Heterometabolous Hexapoda were recovered, alternatively monophyletic or paraphyletic, but this point was not settled by statistical tests. Finally, our analysis adds strong support to previous molecular studies (Friedrich and Tautz 1995; Burke et al. 1998; Cook et al. 2001; Hwang et al. 2001) that grouped myriapods with chelicerates, as well as crustaceans with hexapods. However, we recovered a paraphyletic myriapod clade with the result that the Chilopoda were more closely related to the Chelicerata than to the Diplopoda. This is the first molecular evidence suggesting a paraphyletic Myriapoda with respect to Chelicerata, even if this finding is not conclusive.
Myriapod Paraphyly and the Arthropod Water-to-Land Transition
Paraphyly of the Myriapoda in the context of the Mandibulata has been repeatedly suggested, mainly using morphological data (Borucki 1996; Kraus 1998; Edgecombe et al. 2000; Giribet and Ribera 2000). A monophyletic Myriapoda as basal clade of the Mandibulata has been recently recovered (Giribet, Edgecombe, and Wheeler 2001) following a combined analysis of morphological and molecular data, and a monophyletic Myriapoda as basal clade of all Arthropoda was obtained (Regier and Shultz 2001) in a tree based on the nuclear gene elongation factor-2. Finally, immunocytochemical and neuroanatomical studies (Loesel, Nässel, and Strausfeld 2002) provided evidence in favor of a paraphyletic Myriapoda as basal clade within the Arthropoda. Our phylogenetic analyses, in agreement with a variety of molecular and developmental studies (Boore et al. 1995; Friedrich and Tautz 1995; Boore, Lavrov, and Brown 1998; Burke et al. 1998; Cook et al. 2001; Hwang et al. 2001; Dove and Stollewerk 2003), support a close relationship between Myriapoda and Chelicerata and go even further favoring a paraphyletic myriapodan clade, although this finding requires more decisive evidence. Conversely, our results are conclusive in rejecting the monophyly of the mandibulate clade. This has strong implications for the origin of terrestriality within the Arthropoda. According to our results, a water-to-land transition occurred at least three times during the evolution of this phylum (not to mention the woodlice and other more or less strictly terrestrial crustaceans). The more striking circumstance is the independent water-to-land transition of myriapods and hexapods that led to the parallel acquisition of many morphological features whose similarities require new interpretations.
Our analysis could even suggest (fig. 5) two additional independent transitions from water to land, one for the collembolans, represented here by T. bielanensis, if separate from the true insects, and the other for the diplopods, if these are the sister group of centipedes + chelicerates. The phylogenetic support for these two latter events is still open to question. Nevertheless, comparative morphology suggests a few possible synapomorphies of Chilopoda + Chelicerata, including the peculiar feeding mechanism, the segmental position of the excretory organs and a morphological instability frequently observed around mid-trunk.
The vast majority of chelicerates and centipedes, but not the millipedes, feed on fluid food, mostly of animal origin and digested preorally or extraorally (Brusca and Brusca 2002).
As for the excretory system, arachnids have "coxal glands" that mostly open behind legs I and III (Kaestner 1968), whereas centipedes have a "maxillary rein" opening on the second maxillary segment (Rilling 1968). This segmental distribution might represent an instance of positional homology. In fact, despite the different kind of appendages borne on these segments, the third leg pair of arachnids and the second maxillary segment of the centipedes are both regarded as segmentally homologous to the insect labium (respectively, Telford and Thomas 1998; Kraus and Kraus 1994).
Finally, in chelicerates and centipedes, but not in millipedes, one or a few trunk segments around mid-body are either reduced or distinguished by unique morphological markers. In several chelicerates, the sternum of one or more anterior segments of the opisthosoma becomes "subducted" under neighboring sclerites (Shultz 1993). This feature has a segmental equivalent in the "mid-body anomaly" of centipedes (Minelli et al. 2000). In the centipede Lithobius, at least, this segmental anomaly does probably correspond to an early, transient embryonic expression of Abdominal-B (Hughes and Kaufmann 2002). Further comparative studies, morphological, embryological, and molecular, will eventually check the robustness of the phylogenetic relationships suggested by our analysis.
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Acknowledgements |
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Footnotes |
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