*Atelier de BioInformatique,
Service Commun de Bio-Systématique,
and
Equipe Développement et Évolution, Biologie Moléculaire et Cellulaire du Développement, Université Pierre et Marie Curie, Paris, France
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Abstract |
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Introduction |
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In contrast, the basic idea behind molecular morphometrics is to use the molecular structures as a direct source of measurable information. This method is based on the assumption that secondary structure can be phylogenetically as significant as primary sequence. In other words, one can consider the secondary-structure elements of RNA molecules, i.e., the helices, loops, bulges, and separating single-stranded portions, as phylogenetic characters.
For this study, we focused on the rRNA molecules, widely used in comparisons between primary and secondary structure information. It is well known that rRNA structure is highly conserved throughout evolution (Zwieb, Glotz, and Brimacombe 1981
), presumably because most of the folding is functionally essential (Wheeler and Honeycutt 1988) despite primary sequence divergence (Michot, Qu, and Bachellerie 1990
). The mutations are not evenly distributed throughout the rRNA molecule, but are restricted to some highly variable regions termed "expansion segments" (Hassouna, Michot, and Bachellerie 1984
). These regions differ from the more conserved "core" in having a high evolutionary rate compared with other parts of the ribosome (Larson and Wilson 1989
), resulting in a greater size variability of the structural elements.
As a case study, we applied the molecular morphometrics method to the phylogenetic analysis of Cirripedia. The choice of this subclass of Crustacea was prompted by (1) the availability of several recently published sequences of the nuclear gene of the small-subunit (SSU) RNA (Spears, Abele, and Applegate 1994
) and (2) the numerous phylogenetic problems posed by these organisms, still unsolved by previous molecular analyses. Cirripedes are fixed and sometimes parasitic organisms. They were recognized as crustaceans only when Thomson discovered their typical nauplius larvae in 1828 (see Winsor 1969
). They comprise three superorders, the Thoracica, the Acrothoracica, and the Rhizocephala. Thoracican and acrothoracican adults share a common body plan comprising six thoracic segments bearing limbs modified into cirri, hence the name. They are devoid of any complete abdominal segment. Thoracica are divided into two orders: Sessilia (e.g., Balanus) and Pedunculata (e.g., Lepas). All Rhizocephala (e.g., Loxothylacus) are parasites, with a completely unshaped adult morphology, lacking any trace of segmentation. Nevertheless, most of the time they are classified among Cirripedia on the basis of their larval morphology, quite akin to that of bona fide cirripedes. In particular, they share with Thoracica and Acrothoracica a typical larval stage, the cypris. Ascothoracids differ from the other three superorders just mentioned in that (1) their nauplius larvae do not possess the typical frontal horns present in the other species, and (2) they possess an abdomen, basically composed of five segments, the number of which is often reduced in these parasitic species. As a result, the debate bears on the following points: (1) whether or not the Ascothoracica to be included within the Cirripedia (Schram and Høeg 1995
) and (2) whether or not the Rhizocephala belong to the Cirripedia (Høeg 1992
). Minor points deal with (1) the possible para- or polyphyly of Thoracica as a whole, or Sessilia or Pedunculata, and (2) the order of emergence of the various superorders (Anderson 1994
; Mizrahi et al. 1998
).
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Materials and Methods |
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Standardization
Two standardizing procedures were used, each having its own goal. Individual standardization, where each character is centered and reduced according to its own standard deviation, equalized the relative contributions of all the characters regardless of their respective numerical values. Alternatively, we took into account the fact that different evolutionary rates may occur in single-stranded segments as compared with helices (see Results and Discussion). In this standardization scheme, all characters of the same nature (single or double strand) were weighted identically, with the weight being proportional to the inverse of the evolutionary rate. As a weighting ratio, we used (1) the extreme values found by studies with related sequences, where computed evolutionary rate ratios range from 0.61 (Springer, Hollar, and Burk 1995
) to 0.8 (Dixon and Hillis 1993
), and (2) an estimation of this ratio in our data: we averaged the standard deviation computed for each double-strand character individually and divided this value by its single-strand counterpart, thus obtaining a ratio of 0.653. The result of this differential weighting was to give the two sets of characters the same overall contribution to the tree. Both distance and parsimony analyses were performed with and without standardization.
Distance Computation and Neighbor Joining
Character matrices were bootstrapped 1,000 times (Felsenstein 1985
). Trees were then computed by the neighbor-joining method (Saitou and Nei 1987
) in the MUST package (Philippe 1993
), and bootstrap values were computed for each node of the best tree computed from the whole set of characters (fig. 2E
).
Parsimony: Character Encoding and Weighting
The character states are quantitative and discrete. They were encoded according to the NEXUS (Swofford 1991
) format as ordered and unoriented characters (fig. 2F
). The step count for each considered event is therefore independent on the number of nucleotides which it involves. We also explored another encoding form, which takes the actual quantitative nature of characters into account: numerical values (ranging from 0 to 19 within the whole table) were encoded as character states represented by the letters from A (0) to T (19). The number of steps required for all pairwise character changes were computed as the positive algebraic difference between the corresponding numerical values. Trees were then computed with the PAUP computer package (Swofford 1991
) using the branch-and-bound method (fig. 2G
).
Primary Sequence Analysis
Multiple Alignment
A multiple alignment of the 13 sequences was first performed using CLUSTAL W (Thompson, Higgins, and Gibson 1994
) and was then refined by eye with the help of the editing facilities of the MUST package (Philippe 1993
).
Sequence Realignment
The regions containing many gaps, which were difficult to unambiguously align in the first step, were analyzed using secondary-structure information. For this, the same structural information as that considered for molecular morphometrics analysis (see above) was used to refine the alignment in these sequence segments, thus modifying the initial multiple alignment (fig. 3
).
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Parsimony
Parsimony analysis was performed using the PAUP package (Swofford 1991
). The branch-and-bound algorithm led to a single shortest tree based on 590 informative sites. Bootstrapping was performed on 1,000 replicates using the branch-and-bound algorithm.
Software
Two computer programs were developed for molecular morphology analysis: one allows bootstrapping and computation of distance matrices for distance analysis, and the other encodes the characters in the NEXUS format, suitable for parsimony analysis. Options in these programs allow one to choose between different distance and parsimony computation methods and to standardize or not standardize individual characters and sets of characters. The programs are available as C sources at the URL http://wwwabi.snv.jussieu.fr/billoud/MoMo/momo.html.
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Results |
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The tree presented in the left part of figure 4
was computed by neighbor joining (Saitou and Nei 1987
) on a euclidean distance matrix after standardization. The Acrothoracica species (Berndtia and Trypetesa) were found to form a monophyletic taxon with the other cirripedes. This partition was supported by a high bootstrap proportion (BP) (89%); the existence of a clade (Cirripedia sensu stricto + Loxothylacus) was also highly supported (100%). Within the Thoracica, the Sessilia were grouped, while the Pedunculata were not. However, these internal nodes received minimal (<60%) bootstrap support.
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Primary Sequence Analysis
The initial multiple alignment was 2,163 positions long. After refinement according to the secondary structures, the alignment was significantly shortened by 237 sites, ending with 1,926 positions. Among these, 781 were variable and 590 were informative under the parsimony criterion. In further analyses, gaps were referenced as a fifth state. Distance and parsimony methods applied to the aligned sequences yielded very similar tree topologies (fig. 5
). Both the neighbor-joining tree and the most parsimonious tree (RI = 0.836) supported the morphological views arguing for the monophyly of Cirripedia sensu stricto (Thoracica + Rhizocephala + Acrothoracica) (92% and 86% BP, respectively). Similarly, there is strong support (100% BP) for a sister relationship between Rhizocephala, represented by Loxothylacus, and Thoracica. The monophyly of the Thoracica (Pedunculata + Sessilia) and that of Sessilia are also supported (100% and 95% BP). The monophyly of the Pedunculata was not supported (fig. 5
).
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Discussion |
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Molecular Morphometrics
In many studies involving secondary-structure analysis as a tool for inferring phylogenies, RNA folding is used to refine the alignment. Although the "correct" alignment cannot be determined with certainty, in extensively folded molecules, this procedure has been shown to improve the multiple alignment and hence the phylogeny reconstruction (Titus and Frost 1996
). In such a case, the use of secondary structures remains an intermediary step in the sequence alignment process; the phylogeny is based on nucleotide comparison or, as recently proposed, on base pair changes in stems (Otsuka, Terai, and Nakano 1999
).
We present here a new method, called molecular morphometrics, in which the measurable structural parameters of the molecules are directly used as specific characters to construct a phylogenetic tree. These structures are inferred from the sequence of the nucleotides, often using energy minimization (Zuker 1994
; Gaspin and Westhof 1995
; Zuker and Jacobson 1998
; Rivas and Eddy 1999
), or fitted to a known model (Billoud, Kontic, and Viari 1996
). Moreover, as the secondary structures are built on each sequence separately, no computation of a sharp sequence alignment is needed. Then, recognizing homologous characters on these structures appears to be easier than finding the right counterpart for each nucleotide in every other sequence.
Character Independence
Once a structural model is established, several types of characters can provide phylogenetic information. Total-evidence studies use a nonnumerical description of the molecules, together with morphological traits (Winnepenninckx, Reid, and Backeljau 1998
). For molecular morphometrics analysis, numerical characters can be either continuous (atomic distances or angles, pairing energies, relative simplicity factor, etc.) or discrete (number of elements or monomers involved in a structural feature, etc.). These variables are obviously linked to one another and cannot be simultaneously used in a given study. In this work, we chose to simply count the number of nucleotides involved in each substructure. The unitary modifications required to change from one structure to another are basically insertions and deletions, as these events clearly modify the length of structural elements. Substitutions, however, can also lead to such variations, for instance, by allowing a new base pairing between the two bases at the foot of a helix. Thus, special care must be taken to acknowledge correlations between characters; including a nucleotide in (or excluding a nucleotide from) a helix can necessitate subtracting it from (respectively, adding it to) the adjacent single-stranded segment(s). For instance, if a base substitution occurs at the foot of a helix, disrupting the last base pairing, this single event increases the size of the two adjacent single-stranded regions. In such cases, only one of the correlated characters can be used, and this is what we did in this study in the few rare cases that we observed.
Other potential correlations may involve long-distance interactions implied in the secondary structure of ribosomal RNA. Expansion segments seem to be subject to some selective pressure that maintains their particular structure, at both the secondary (Engberg et al. 1990
; Ruiz Linares, Hancock, and Dover 1991
) and the tertiary (Sweeney, Chen, and Yao 1994
) levels. Compensatory mutations were suspected to be related to intramolecular interactions (Expert-Bezançon and Wollenzien 1985
; Haselman, Camp, and Fox 1989
; Woese and Gutell 1989
; Gutell, Larson, and Woese 1994
) and/or extramolecular interactions (Gerbi 1986
; Stern, Weiser, and Noller 1988;
Thanaraj 1994
), especially with the ribosomal proteins and other RNAs (Hancock, Tautz, and Dover 1988
). However, there is, to date, no evidence for such interactions, and expansion segments seem to behave like "extraneous elements" of the ribosome (Nunn et al. 1996
). Therefore, the variable regions, which are expected to provide us with the greatest phylogenetic information, are those where the functional constraints are the most likely to be relaxed (Gerbi 1986
).
Weighting and Standardizing Characters
Like most phylogenetic characters, the structural parameters studied here are subject to the problem of character weighting; mixing single-stranded and double-stranded regions in the same distance evaluation is questionable, as they are not expected to follow the same mutation mechanisms (Douzery and Catzeflis 1995
) and hence they may evolve at different rates. In particular, the constraints to maintain pairing in stems seem to lower the rate of accumulation of transversions (Springer and Douzery 1996
; Tillier and Collins 1998
), resulting in a differential base composition (Vawter and Brown 1993
; Springer, Hollar, and Burk 1995
). Usually, nucleotide mutations of the helices are considered more phylogenetically informative than those of the single-stranded regions (Ellis and Morrison 1995
; Morrison and Ellis 1997
). However, authors disagree on the relative amount of evolution in the two data sets. In eukaryotic 5S rRNA, nucleotide changes were even found to be more frequent in the stems than in the loops (Otsuka, Nakano, and Terai 1997
). Studying the 12S rRNAs of mammals, Springer, Hollar, and Burk (1995)
computed that the base substitution rates in single strands versus double strands are in a ratio of 1 to 0.61; Dixon and Hillis (1993)
stated that in 28S rRNAs of some vertebrates, evolutionary rates for single- and double-stranded regions did not differ by more than 20%. For molecular morphometrics characters, we can compare the evolutionary rates in the single-stranded and double-stranded regions by computing the ratio of their mean standard deviations. We obtained a value of 10.653, which is between the two latter values. When comparing characters evolving at different rates, proportional weighting is often used. The effect of such a treatment is to give each set of characters the same overall contribution to the final result. The parsimony tree presented here was computed with such a weighting. However, it is noticeable that in our case, single-stranded and double-stranded regions taken separately did give the same tree topology, with only small differences in branch lengths. Obviously, any weight applied to these two sets will also give the same tree topology; thus, the rate value is not a critical issue.
Molecular Morphometrics Versus Anatomical Morphometrics and Sequence Comparison
Molecular morphometrics inherits some features from both anatomical quantitative morphometrics and molecular primary sequence comparison. The new method can therefore be compared with both of these methods.
An important difference between anatomical and molecular characters is the number and nature of their determinant genetic "sites": anatomical variations are often due to more than one gene, and, more importantly, the genetic sites responsible for the morphological characters of interest are usually unknown. Molecular structural variations, on the contrary, are due to a reduced set of identifiable mutations, which can be characterized at the single-nucleotide level. Thus, the evolutionary meanings of two independent molecular variations are known to be of the same nature and, hence, comparable. Moreover, the observed anatomical characters are the result of both the genetic characters themselves and some possible epigenetic effects, such as environmental influences, or some gene expression features, such as sexual dimorphism. On the contrary, like any molecular phylogeny method (including primary sequence comparison), molecular morphometrics takes advantage of the fact that the molecular characters remain independent of their somatic expression (Smith, Lafay, and Christen 1992
).
Compared with sequence comparison, molecular morphometrics involves fewer characters, but each of these characters can take many different values. Molecular morphometrics and sequence comparison differ mainly on a methodological point: in a nucleotide sequence, the structural polymorphism appears as size variations, mostly in regions where insertion/deletion events take place (although point mutations can also lead to structural polymorphism). In other words, these regions are those in which the multiple sequence comparison programs lead to poorly reliable alignments, as the signal/noise ratio they provide is too low (Wheeler 1994
; Grundy and Naylor 1999
). In such cases, different candidate alignments can produce very different trees (Xiong and Kocher 1993
). Usually, such regions are realigned by hand, as we did in this study. Although calibration methods have been developed to take the mutation rate differences into account (Van de Peer et al. 1993;
Wheeler, Gatesy, and DeSalle 1995
; Otsuka, Nakano, and Terai 1997
), there is at present no method able to automatically reconstitute an alignment close enough to the one that can be obtained by hand with the help of a structural model (Morrison and Ellis 1997
). Therefore, regions subjected to insertion/deletion events are often not included at all in sequence studies (Okamoto, Sekito, and Yoshida 1996;
Liu, Kato, and Sugane 1997
). As shown in the present work, the secondary structure, although depending on the primary nucleotide sequence, can in fact be considered as a distinct set of informative characters providing their own phylogenetic signal. It therefore makes sense to examine whether the phylogenetic interpretation of data differing in nature will lead to the same result. Every object involved in the evolutionary process has its own variation mode, due to specific mutation and selection mechanisms. However, all of them keep, in different forms, the tracks of the same story. In our case, the phylogenetic tree produced by molecular morphometrics perfectly matches that found after realigning the expansion segments. It is noteworthy that the same holds true for anatomical studies (see above). This congruence reinforces the hypothesized phylogeny, which appears to be the result of a common story rather than an artifact of an analysis process. In that sense, the molecular morphometrics method, allowing for an automated treatment of the variations in structured sequences, appears to be complementary to primary sequence comparison.
Field of Application
In its present version, molecular morphometrics considers only size variations of homologous structural segments. This choice implies that the overall architecture of the molecule remains the same among the observed taxa in order that the "continuity argument" can easily apply to the definition of homologous structures. As a consequence, the molecules have to be rather close to one another and undergo no topological rearrangement while evolving. The taxonomic level at which molecular morphometrics is operational is preferably that of the ordinal or supraordinal rank, depending on the degree of conservation of the considered molecule. With molecules like rRNA, where some domains evolve at different rates, higher levels may be addressed.
What is usually presented in the literature involves the secondary structures being used, for instance, to study protists (Lenaers et al. 1988
), ciliates (Gagnon, Bourbeau, and Levesque 1996
), all eukaryotes (Hendriks et al. 1991
), and up to the three primary kingdoms (Clark 1987
; Bachellerie and Michot 1989
). In all of these cases, comparisons are indeed made on great scale variations. Descriptions of the molecular shape point to conserved regions, while the presence or absence of one or more substructures are shown to be a specific trait characteristic of one clade (Wolff and Kuck 1990
; Spears, Abele, and Applegate 1994
; Gagnon, Bourbeau, and Levesque 1996
; Liu, Kato, and Sugane 1997
; Aleshin et al. 1998
). Such treatments, however, remain quite informal. Some attempts have been made to formalize the secondary-structure comparisons, mainly in relation to the problem of identifying common (sub)structures in a set of sequences (Le, Nussinov, and Maizel 1989
; Benedetti and Morosetti 1996
). However, difficulties persist regarding the topic of defining a distance between two related structures with variable topologies (Shapiro 1988; Margalit et al. 1989
; Shapiro and Zhang 1990
; Magarshak and Benham 1992
; Fontana et al. 1993
; Nakaya, Yonezawa, and Yamamoto 1996
).
It can be expected that insights into the secondary-structure evolution processes will help to determine weightings for the different events (Hancock, Tautz, and Dover 1988
; Hancock 1995
; Muse 1995
). In particular, special mechanisms, like slippage, seem to play a major role in rRNA evolution (Tautz, Trick, and Dover 1986
; Hancock and Dover 1988;
Vogler, Welsh, and Hancock 1997
; Crease and Taylor 1998;
Tautz et al. 1998
). A convincing model accounting for the evolution of structural variations may allow us to gather the different features of the variation of the molecule in a single data matrix, thus expanding the capabilities of molecular morphometrics to the study of high-level taxa.
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Conclusions |
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Acknowledgements |
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Footnotes |
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1 Keywords: molecular phylogeny
secondary structure
small-subunit RNA
cirripede
Crustacea
2 Address for correspondence and reprints: Bernard Billoud, Atelier de BioInformatique, Université Pierre et Marie Curie, 75252 Paris cedex 05, France. E-mail: bernard.billoud{at}snv.jussieu.fr
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