*School of Biological Sciences, Washington State University;
Department of Biological Sciences, University of Idaho;
Marine Science Institute, Department of Marine Science, University of Texas at Austin;
Department of Zoology, University of Washington
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Abstract |
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Introduction |
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For over a century, biologists have debated the interrelationships among major taxa within the deuterostomes, focusing particularly on chordate and vertebrate ancestry (Gee 1996
). A large number of studies based on anatomical, embryological, and paleontological data have generated contrasting hypotheses of deuterostome evolution, sustaining the controversy over chordate and vertebrate origins (see for example Gaskell 1890
; Garstang 1928
; Berrill 1955
; Romer 1967
; Jollie 1973
; Gutmann 1981
; Jefferies 1986
; Maisey 1986
; Schaeffer 1987
; Jensen 1988
; Swalla 2001
).
Molecular studies of deuterostome phylogeny have used small-subunit ribosomal RNA (SSU rRNA), also called 18S rRNA, gene sequences. The results of Turbeville, Schulz, and Raff (1994)
and Wada and Satoh (1994)
showed that 18S data alone did not provide strong support for interrelationships among deuterostome subgroups and thus could not reveal chordate monophyly. However, utilizing the total-evidence approach (see review by de Queiroz, Donoghue, and Kim 1995
), Turbeville, Schulz, and Raff (1994)
combined their 18S data matrix with 11 morphological traits and an additional molecular character and found some evidence for chordate monophyly (61% bootstrap support).
In the first thorough analysis of metazoan phylogeny incorporating total evidence, Zrzavy et al. (1998)
compared 18S data and 276 morphological characters across nearly all animal phyla. Through a sensitivity analysis of these data, they inferred a monophyletic Deuterostomia, Chordata, and Ambulacraria (echinoderms + hemichordates; Metschnikoff 1881)
. Giribet et al. (2000)
expanded on the study of Zrzavy et al. (1998)
by adding many new 18S sequences, using only triploblast animals (to avoid the confounding effects of too distant and long-branched outgroups), and employing unique analyses. They also recovered monophyletic deuterostome, chordate, and Ambulacrarian clades, but within the chordates, their results supported a nontraditional pairing of urochordates and vertebrates.
Cameron, Garey, and Swalla (2000)
added many new hemichordate and urochordate taxa to the SSU rRNA-gene database and found strongly supported relationships among the major deuterostome groups. Their analyses utilized species with slow rates of sequence substitution to minimize taxonomic artifacts caused by long-branch attraction. For some analyses, they used a phylogenetic search algorithm, Gambit, designed to be insensitive to unequal rate effects and able to accommodate an evolutionary model accounting for site-to-site variation in substitution rate (Lake 1995
). Despite finding ample support for a lancelet + vertebrate clade and an Ambulacrarian clade, a monophyletic Chordata was not supported by most of their analyses. However, by using Gambit and restricting their comparison to the 16 deuterostomes and 1 protostome with the slowest rates of SSU rDNA evolution, Cameron, Garey, and Swalla (2000)
did find evidence for a monophyletic Chordata (85% bootstrap support). Additionally, their SSU data suggested that within the hemichordates, the pterobranchs might have evolved from an enteropneust (acorn worm) ancestor, thus supporting the notion of acorn worm paraphyly, a topology first shown by Halanych (1995)
.
In the current study, we continue the investigation of deuterostome interrelationships by adding different rRNA genes. Mallatt and Sullivan (1998)
and Mallatt, Sullivan, and Winchell (2001)
have demonstrated the usefulness of chordate large-subunit ribosomal RNA (LSU rRNA)-gene sequences for deep-level phylogenetics, especially when combined with SSU-gene sequences. The large subunit of the metazoan ribosome contains three RNA molecules (5S, 5.8S, 28S), whereas the 18S rRNA molecule is the only one incorporated into the small ribosomal subunit (Alberts et al. 1994
, p. 379). Here, we have obtained nearly complete 28S sequences for 14 deuterostomes and 3 protostomes, complete 18S sequences for five of these taxa, and we sequenced all or part of the 5.8S rRNA gene for many of them. By including GenBank sequences from 11 additional animals, we employed the largest rRNA-gene data set to date (consisting of 18S + 5.8S + 28S rRNA-gene sequences, averaging about 4,000 aligned sites per taxon) for estimating the phylogeny of deuterostomes. We constructed these relationships with minimum evolution (ME) (using LogDet distances), maximum parsimony (MP), and maximum likelihood (ML) analyses. Nonparametric bootstrapping (Felsenstein 1985
) and spectral analysis (Lento et al. 1995
; Penny et al. 1999
) provided examination of nodal support. We used our results to evaluate various classical hypotheses of deuterostome evolution.
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Materials and Methods |
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It should be noted that in a few cases, the SSU and LSU genes were from different species within a genus: 28S from A. macrodactylum and 18S from A. mexicanum; 28S from A. forbesii and 18S from A. amurensis; 28S from C. salma and 18S from C. sykion. However, rRNA genes evolve slowly enough that there should be only minimal differences between organisms in the same genus (Hillis and Dixon 1991
). Also, we combined the 28S rRNA gene of the crinoid F. serratissima with the 18S gene of Antedon serrata, which is in a different but closely related genus of the same family (Hyman 1955
, pp. 9597). This is justifiable because the first 371 bases of the 28S gene of Antedon are known (GenBank accession AJ225818; Lafay, Smith, and Christen 1995
), and they are 96% similar to our Florometra sequence, suggesting that the entire 28S genes of these two genera are very similar.
Genomic DNA was extracted from tissue preserved in 70%95% ethanol, using the cetyltrimethylammonium bromide method (Winnepenninckx, Backeljau, and De Wachter 1993
). Tissue sources included: vertebrate tail fin clips; urochordate pharynx and gonad; acorn worm proboscis muscle and skin; entire Cephalodiscus animals; echinoderm muscle, gonads, and tube feet; and Eisenia cuticle, muscle, and pharynx. For the small polychaete, Proceraea (about 1 mm in length), we obtained DNA by grinding a whole animal in 15 µl of TE buffer (pH 8.0) and included 1 µl of this slurry in the PCRs. We used this same approach with Limulus book-gill tissue. We performed DNA amplification, purification, sequencing, and fragment assembly, as described in Mallatt and Sullivan (1998)
. In some animals, we could only amplify 28S genes in smaller segments; occasionally, when sequencing such segments, we found the overlap between them to alternate between matching perfectly and showing minor divergences. Such discordant segments were obtained in Triakis, Asterias, and Cucumaria and must represent parts of alternate forms of the 28S genes or even pseudogenes. Wada (1998)
also experienced this phenomenon with the urochordate, Doliolum nationalis. Resequencing from larger amplified segments allowed us to recognize and eliminate the pseudogenes in all cases. For amplifying the 18S genes (previously unreported), we used the same procedures but with primers 18e 5'-CTGGTTGATCCTGCCAGT-3' (Hillis and Dixon 1991
) and 18P-C 5'-TAATGATCCTTCCGCAGGTTCACCT-3' (K. Halanych, personal communication). For sequencing, we used additional 18S primers: 18Q-C 5'-GTTATCGGAATTAACCAGACA-3' and its complement 18Q-S (K. Halanych, personal communication); 18h 5'-AGGGTTCGATTCCGGAGAGGGAGC-3' and its complement 18i; 18j 5'-GCCTGCGGCTTAATTTGACTCAACACGGG-3' and its complement 18k (Hillis and Dixon 1991
).
We imported the rRNA-gene sequences into SeqLab, a Macintosh X Window application (see Smith et al. 1994
). We aligned concatenated 28S, 5.8S, and 18S rRNA genes entirely by eye, using, as guides, the LSU rRNA secondary structure of X. laevis (Schnare et al. 1996
) and the SSU secondary structures of X. laevis and S. purpuratus (Gutell 1994
).
Two characteristic types of regions exist within the eukaryote 28S rRNA genes: conserved regions, which have a slow evolutionary rate of nucleotide substitution and are collectively called the conserved core of the molecule; and divergent domains, which evolve at a much higher rate (Hassouna, Michot, and Bachellerie 1984
). The 28S genes contain 12 divergent domains, which comprise about one-third of the molecule; see Mallatt, Sullivan, and Winchell (2001)
for the locations of and sequences immediately before and after all divergent domains in X. laevis, B. floridae, and S. plicata. Because it is difficult to align the divergent domains of distantly related taxa (such as those compared here), we excluded these variable regions from our analyses and restricted our 28S comparisons to the core regions only, which are easily and unambiguously aligned by eye.
Overall, we compared 1,635, 151, and 2,338 aligned sites in the 18S, 5.8S, and 28S genes, representing about 90%, 90%, and 65% of the total length of these genes, respectively, and a total of about 4,000 bases. Our alignments are deposited in the EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/index.html) under the accession numbers ALIGN_000057 (LSU genes) and ALIGN_000058 (SSU genes).
Phylogenetic Analyses
Tree Estimation
We used three data sets to conduct our analyses: (1) LSU genes only, (2) SSU genes only, and (3) combined LSU + SSU genes. The issue of whether to analyze multiple genes separately or combined is complex, and no single test can provide utterly reliable guidance (e.g., Sullivan 1996
). Although the incongruence length difference test (Farris et al. 1994
; Cunningham 1997
) suggested some degree of incongruence between the LSU and SSU genes (P = 0.052), the phylogenetic signal in these data sets may well be additive. Thus, we analyzed the data sets both separately and combined. The search strategies employed for inferring optimal trees included equally weighted MP, ML (Felsenstein 1981
), and ME using LogDet-Paralinear distances (Lake 1994
; Lockhart et al. 1994
). We implemented each of these optimality criteria with PAUP*, Version 4.0 beta 4a (Swofford 1998
). We used ML as in our previous studies (Mallatt and Sullivan 1998
; Mallatt, Sullivan, and Winchell 2001
): first, we loaded a starting tree (constructed with MP) into PAUP and then calculated the likelihood score of this tree under 16 different models of nucleotide substitution, as well as the parameters specifying each model. The most general of these models, GTR + I +
, described our data best in all cases (results not shown). We then followed the iterative search strategy outlined by Swofford et al. (1996)
to obtain the optimal ML tree. Basically, using the GTR + I +
model parameters of the MP starting tree, we performed an ML search which found a tree with a better likelihood score. We then calculated parameters of this first ML tree under the same model and incorporated these values into a second ML search. For each data set, the first ML tree was the best because it was found again after one iteration.
ML and MP methods assume stationary nucleotide frequencies across all aligned sequences. If unrelated taxa converge in their nucleotide composition, these methods may incorrectly join them on a tree, despite their different ancestry (Lake 1994
; Lockhart et al. 1994
). Because our sequences did exhibit nonstationary base frequencies (see Results), we used the ME method based on the LogDet (Lockhart et al. 1994
), or Paralinear (Lake 1994
), data transformation. This technique was specifically designed to produce additive genetic distances from sequences that differ in base composition by assuming a very general evolutionary model that allows each of the 12 nonreversible nucleotide substitution types to occur at a different rate. However, unlike ML, this method does not account for different rates of evolution across nucleotide sites. Nonetheless, a good way of approximating this rate heterogeneity, and accounting for functional constraint in these rRNA molecules, is to use an invariable sites model (e.g., Waddell, Penny, and Moore 1997
; Mallatt, Sullivan, and Winchell 2001
). To this end, we estimated the proportion of invariable sites (Pinv) across taxa (for each of our data sets) via ML using the GTR + I model. However, as mentioned previously, our data violate at least one of the ML assumptions; so we used a range of Pinv values from 0.15 to 0.6067 (for our combined-gene data set only) to gauge the sensitivity of our findings to variation in this Pinv parameter. The upper limit of this range (0.6067) is the highest possible value for Pinv because it represents the actual percentage of sites observed to be constant across all taxa in our combined LSU + SSU data set. Because our taxa so clearly have nonstationary nucleotide frequencieswhich violate the assumptions of MP and MLwe emphasize the ME method using LogDet distances in this study.
To measure nodal support on our ME, ML, and MP trees, we performed nonparametric bootstrap analyses (Felsenstein 1985
) with 1,000 replicates for all MP and ME searches and 100 replicates for all ML searches.
Spectral Analysis
Because bootstrapping only assesses support for clades and does not directly report any information regarding contradictory signal for a certain grouping (i.e., conflict), we also performed spectral analyses (e.g., Lento et al. 1995
; Penny et al. 1999
) on the calculated LogDet distances, in order to assess relative amounts of support and conflict for competing hypotheses of deuterostome phylogeny. These analyses were performed on our combined LSU + SSU-gene data set using the Spectrum program (Charleston 1998
, http://taxonomy.zoology.gla.ac.uk/
mac/spectrum/spectrum), with the Pinv set to the ML estimate of 0.5948.
Spectral analysis is a quantitative method that is well suited for testing alternative phylogenetic hypotheses when relationships among taxa are controversial. With the ability to use either sequence data or distance matrices, the Spectrum program creates a complete array of bipartitions, or splits, in the data, which includes every possible grouping among the taxa used. Therefore, a strength of this method is that it works independently of any one particular tree. We displayed the calculated support and conflict values as a histogram called a Lento plot (Lento et al. 1995
), which provides a visual representation of the phylogenetic spectrum of bipartitions (groupings of taxa) and facilitates comparison of competing hypotheses of evolutionary history. Support values were computed using a threshold value of 0.0003, in order to limit the number of groups returned.
In Spectrum, the conflict for a given bipartition is measured as the sum of support values for all bipartitions that contradict the given split. Because there may be many alternatives to a given bipartition, its conflict value may seem so large as to overwhelm its level of support. Therefore, we standardized all conflict values following Lento et al. (1995)
.
Because the Spectrum program has a limit of 20 taxa, we had to delete 8 of the 28 taxa that were used in the tree-building analyses. We trimmed taxa from the more heavily sampled groups of deuterostomes, retaining taxa that provided essentially the same ME bootstrap support values and tree topology as the 28-taxa data set. Specifically, we excluded five gnathostomes (Xenopus, Latimeria, Acipenser, Raja, Squalus) and three hemichordates (Saccoglossus sp. CC-03-00, Harrimania, Ptychodera sp.) from the spectral analysis.
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Results |
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The combined LSU and SSU tree is shown in figure 1C and can be compared to the tree based on the SSU gene alone (fig. 1B ). This comparison indicates that adding LSU data increases the bootstrap support for the following groups, mostly to around 100%: lancelets + vertebrates; Ambulacraria; hemichordates; cyclostomes; Chondrichthyes; elasmobranchs; nonlarvacean urochordates; noncrinoid echinoderms; and sea cucumber Cucumaria + sea urchin Stongylocentrotus. On the other hand, addition of LSU data slightly lowered the bootstrap support for the group of Cephalodiscus + harrimaniid enteropneusts (compare fig. 1C with B ). Support for most other groups stayed about the same.
Unlike the 70% bootstrap support shown for chordates in the SSU tree, the combined-gene tree failed to support a monophyletic Chordata. Specifically, the optimal ME tree of figure 1C placed urochordates as the outgroup to all other deuterostomes, thus displaying an ([echinoderm, hemichordate], [lancelet, vertebrate]) subtree. The ME bootstrap value for this particular node was only 47%, whereas the bootstrap value for the alternate clade showing a monophyletic Chordata is slightly higher, 49.5% (not illustrated). Clearly, the support for either of these groupings is weak and indistinguishable. In other words, these tree-based analyses effectively show a three-group polytomy at the base of the deuterostomes: urochordates; Ambulacraria; and lancelets + vertebrates.
Table 2 shows how changing the proportion of invariable sites (Pinv) in the combined data set affects ME bootstrap support for eight splits. Although support for some groups remained high over the entire range of Pinv (>75% support: deuterostomes, Ambulacraria, lancelet + vertebrates, cyclostomes, pterobranch + harrimaniids), the bootstrap support for other groups changed markedly with Pinv (urochordates + protostomes, chordates, sea cucumber + sea urchin). Especially noteworthy is the increase in support for monophyletic chordates and the decrease in support for urochordates + protostomes, at the higher Pinv values.
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Figure 3
shows the optimal tree that was inferred from the results of our spectral analysis under the manhattan distance criterion (Charleston 1998
). The nodes are labeled with letters corresponding to splits in figure 2B.
As a method of measuring confidence for the clades on the manhattan tree (fig. 3
), we compared their spectral analysis support levels to those of alternative clades resulting from nearest-neighbor interchanges (fig. 4
). That is, every internal edge on the manhattan tree was rearranged, and spectral analysis support values for the three possible topologies were compared (see fig. 5
for an example). As shown in figure 4
, the arrangement of groups congruent with the manhattan tree always had the highest supportusually overwhelmingly. However, splits J (cyclostomes), M (acorn worms), and Q (ascidian urochordates) have alternative pairings with significant support.
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Discussion |
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Chordates
The animals classified within the phylum Chordataurochordates, cephalochordates, and vertebratesshare the following anatomic synapomorphies: a notochord, a dorsal hollow nerve cord, a tail extending behind the visceral cavity, a thyroid gland (or endostyle), and other features (Brusca and Brusca 1990
, p. 873). Despite such strong morphological evidence for this clade, molecular systematists have not been able to obtain strong evidence for chordate monophyly using the SSU gene (Turbeville, Schulz, and Raff 1994
; Wada and Satoh 1994
). The only evidence for a chordate clade from molecular (SSU) data was obtained when comparing a select sample of deuterostome and outgroup taxa, i.e., those with the shortest branch lengths (Cameron, Garey, and Swalla 2000
).
We experienced the same complications because the urochordate LSU + SSU sequences did not always group with those of other chordates. Although spectral analysis, an efficient method for identifying both support and conflict in the data, showed chordate monophyly (fig. 4
and table 3
), none of the tree-based phylogenetic methods placed urochordates with the other chordates (fig. 1C
and table 2
, but see fig. 1B
for moderate 18S support). Because the internal branches resolving relationships among the three main groups of deuterostomes shown in figure 1C
(urochordates; echinoderms + hemichordates; and cephalochordates + vertebrates), are so short, it is possible that the combined data contain signal for urochordates as chordates, but it is too weak to overcome noise with only 4,000 bases. To test this, we conducted bootstrap analyses with increasingly large pseudoreplicate data sets (2x, 3x, 4x, 5x, and 10x the size of the original matrix) using PAUP*. Because this analysis preserves the imbalances in base frequencies in the preliminary data set, we conducted ME analyses on LogDet distances with Pinv = 0.588 (the ML estimate under a GTR + I model) for each data set. In none of these analyses did either placement of urochordatesurochordates nested within a monophyletic Chordata or urochordates as the basal deuterostome lineagereceive more than 55% or less than 43% bootstrap support (table 4
). Thus, tree-based analyses of rRNA genes cannot discriminate between these hypotheses. Interestingly, no other placement of urochordates received substantial support in any tree-based analysis.
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Testing NonMolecular Hypotheses of Deuterostome Interrelationships
Deuterostome phylogeny has been a topic of interest among biologists of many subdisciplines and is discussed in most biology and comparative vertebrate anatomy textbooks (Pough, Janis, and Heiser 1999
, p. 33; Kardong 2002
, p. 47). Many morphological hypotheses of the relationships among the groups of deuterostomes have been championed and will be assessed here. A number of radical hypotheses have been proposed, such as those of Gaskell (1890)
and Patten (1890)
, who claimed vertebrates evolved from an arthropod ancestor similar to the horseshoe crab, Limulus, and that of Jensen and others (see Jensen 1988
), who claimed a nemertean-worm ancestry for the vertebrates. We will exclude these hypotheses from our discussion because both are firmly refuted by rRNA genes and other evidence indicating arthropods and nemerteans are protostomes (fig. 1C;
Sundberg, Turbeville, and Härlin 1998
; Zrzavy et al. 1998
; Giribet et al. 2000
; Mallatt and Winchell 2002
). For other hypotheses, we will summarize each in the form of a cladogram (fig. 6
) and assess its validity using spectral analysis and bootstrapping of our combined-gene data set (table 5
). Because spectral analysis is only capable of measuring support and conflict for bipartitions within a data set, we cannot evaluate an overall topology incorporating every subgroup at the same time, but we can dissect relationships essential to each hypothesis and evaluate its components.
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Garstang's (1928)
hypothesis (see Jefferies 1986
, p. 347), dominant a generation ago and still cited (Berrill 1955
; Romer 1967
; Pough, Janis, and Heiser 1999
; Kardong 2002
), was based on the proposal that the ancestral forms of every deuterostome group were sessile suspension feeders and that a neotenic transformation of a lineage with ascidian-like larvae generated the free-swimming cephalochordate + vertebrate line. Garstang's phylogeny (fig. 6B
) resembles the classical hypothesis, except that it proposes a paraphyletic Hemichordata with an enteropneust + chordate clade arising from a pterobranch-like ancestor. In contrast, our data strongly favor a monophyletic hemichordate clade over an enteropneust + chordate grouping (see table 5, part B). Garstang's hypothesis also proposed a sister relationship between urochordates of the classes Larvacea and Thaliacea, but our rRNA-gene data strongly united all nonlarvacean urochordates (see table 5, part B).
Berrill's (1955)
hypothesis (see Gee 1996
, p. 122) is much like Garstang's, except that it explicitly states the neotenic ancestor of larvaceans and thaliaceans gave rise to the cephalochordate + vertebrate clade (fig. 6C
). That is, Berrill proposed only one neotenic event giving rise to a common ancestor of larvaceans, thaliaceans, cephalochordates, and vertebrates, whereas Garstang had proposed two parallel neotenic events: one giving rise to larvaceans and the other to the ancestor of cephalochordates and vertebrates. Berrill's phylogeny (fig. 6C
) suggests paraphyly of the urochordates (lancelet + vertebrates as the sister group to thaliaceans + larvaceans), but this received much less support from our data than the alternative hypothesis of a monophyletic urochordata (see table 5, part C).
The strange Paleozoic fossils known as carpoids, which bear large calcium carbonate plates, are considered by most paleontologists to be extinct echinoderms (see Peterson 1995
). However, the calcichordate hypothesis (Jefferies 1986, 1996
) posits that various carpoids are stem-group echinoderms, urochordates, cephalochordates, and vertebrates. Jefferies' analysis of these fossils led him to conclude that the sister group to vertebrates is urochordates (not cephalochordates) and that echinoderms are not the sister group of hemichordates but instead are the sister group to the chordates (fig. 6D
). Our results from spectral analysis of rRNA genes do not support these claims. As shown in table 5
(see table 5, part D), the support and conflict values strongly favor a cephalochordate + vertebrate pairing over a urochordate + vertebrate pairing and favor a hemichordate + echinoderm pairing over an echinoderm + chordate pairing. Incidentally, we interpret carpoids as resembling stem echinoderms only, which had many pleisiomorphic deuterostome traits; Conway Morris (2000)
and Gee (2001)
drew the same conclusion.
While this paper was in review, Jefferies accepted the ambulacrarian concept uniting hemichordates and echinoderms (Jefferies 2001) but without changing any key aspect of his calcichordate hypothesis. Nonetheless, our evidence against a urochordate + vertebrate group still contradicts the carpoid theory of vertebrate origins.
Jollie (1973)
compared anatomic details of the deuterostome subgroups and proposed: (1) monophyly of the hemichordates + echinoderms based on similarities in larval morphology, and (2) monophyly of the urochordates + lancelets based on details of their embryology (fig. 6E
). Although the first grouping is supported by our data, the second receives no support and is strongly refuted by our evidence for a lancelet + vertebrate group (see table 5, part E).
Finally, Gutmann (1981) proposed a phylogeny, based on a functional-mechanical analysis of the coelom and body musculature, that concluded deuterostomes evolved from a cephalochordate-like ancestor (fig. 6F ). His hypothesis implies that cephalochordates are not particularly closely related to vertebrates, that chordates do not form a natural group, and that hemichordates are paraphyletic (that is, pterobranchs gave rise to echinoderms). Our data refute this; we found the cephalochordate + vertebrate pairing to be robust (split P), our spectral analysis supports a monophyletic Chordata (split R), and we do not support his pterobranch + echinoderm clade (instead, spectral analysis confirms a monophyletic Hemichordata; Split S, see table 5, part F).
In summary, our molecular data refute many aspects of previously proposed hypotheses. However, we emphasize that our data are from just one gene familya minute portion of any genomeand to test these hypotheses rigorously much more genetic data, particularly protein-coding genes, should also be considered. Although they refute all of the above hypotheses, our main results based on rRNA genes (figs. 1C and 2B ) are not radical but uphold many widely accepted and traditional aspects of deuterostome phylogeny. In particular, monophyly of the lancelets + vertebrates has long been a favored view; we do not refute a monophyletic Chordata; and evidence for a hemichordate + echinoderm clade is now gaining widespread acceptance.
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Acknowledgements |
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Footnotes |
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1 Present address: Department of Organismic Biology, Ecology, and Evolution, University of California, Los Angeles
Keywords: deuterostome
chordate
phylogeny
28S rRNA
SSU
LSU
spectral analysis
Address for correspondence and reprints: Jon Mallatt, P.O. Box 644236, School of Biological Sciences, Washington State University, Pullman, Washington 99164-4236. jmallatt{at}mail.wsu.edu
.
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References |
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