Grup de Biologia Evolutiva, Departament de Genètica i Microbiologia, Universitat Autònoma de Barcelona, Barcelona, Spain
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Abstract |
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Introduction |
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The buzzatii complex includes endemic and sub-cosmopolitan species (e.g., D. buzzatii, a recent colonist in the Old World and Australia; Fontdevila et al. 1982
; Barker et al. 1985
), with instances of sympatric (the martensis cluster species) and allopatric (the stalkeri cluster) distributions. The reproductive affinities in the complex (Marín et al. 1993
) suggest the occurrence of prezygotic and postzygotic isolation mechanisms. One species, D. serido, is considered a superspecies consisting of many semi-isolated populations in the process of split (Sene, Pereira, and Vilela 1982
; Fontdevila et al. 1988
). The ecological niche and population dynamics of the species are amenable to study (Hasson, Naveira, and Fontdevila 1992
; Santos, Ruiz, and Fontdevila 1989
; Barker 1982
). For these reasons, the buzzatii complex has attracted much attention from evolutionary geneticists. Yet, the phylogeny of the complex remains to be elucidated.
Former analyses of the overlapping paracentric inversions of the polytene chromosome 2 led Wasserman (1982)
to include the martensis and buzzatii clusters within the mulleri complex and to consider the stalkeri cluster a distinct complex within the mulleri subgroup. Subsequent closer inspection of the chromosomal inversion patterns forced Ruiz and Wasserman (1993)
to raise buzzatii to the rank of a separate complex within the mulleri subgroup. Unfortunately, chromosomal inversion data contained too little information to settle the relationships within the clusters and their branching order (Ruiz and Wasserman 1993
). The most parsimonious reconstruction, which places stalkeri as the oldest cluster of the complex, differs by only a single inversion from a hypothesis invoking the martensis cluster as the earliest derived clade (Ruiz and Wasserman 1993
). The phylogeny of the buzzatii complex has more recently been addressed using mitochondrial DNA markers (Spicer 1995
). The sequences analyzed, however, evolved much too fast to resolve the relationships on the relatively short timescale involved in the diversification of the buzzatii complex (Spicer 1995
).
The present study seeks to determine the phylogenetic relationships in the buzzatii complex using molecular data. We sequenced part of the Xdh coding region in 10 species and also analyzed published data from three mitochondrial loci (Spicer 1995
). We followed a statistical model-fitting approach within the maximum-likelihood (ML) framework of phylogenetic inference (e.g., Ritland and Clegg 1987
; Yang, Lauder, and Lin 1995
; Kumar 1996
; Rodríguez-Trelles, Tarrío, and Ayala 1999
).
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Materials and Methods |
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Molecular Methods
The Xdh coding region investigated spans 2,085 bp (~52% of the total Xdh codons), including about half of exon II (1,113 bp) and most of exon III (972 bp). Genomic DNA was prepared from 0.2 g of flies according to the method of Piñol et al. (1988)
. The Xdh region was amplified with EcoTaq DNA polymerase (Ecogen). PCR products were purified with the Wizard PCR Preps DNA Purification kit (Promega). The amplified region was ligated into the pGEM-T easy vector (Promega) and cloned into Escherichia coli XL1-Blue or JM109 competent cells according to the manufacturer's protocol. Plasmid DNA was prepared for sequencing using the Wizard Plus Minipreps DNA Purification System kit (Promega). For each species, one clone was sequenced by Sanger's dideoxynucleotide chain-termination method for denatured double-stranded plasmid DNA. Sequencing was carried out automatically using the A.L.F. express DNA Sequencer (Pharmacia; Unitat de Microbiologia of the Universitat Autònoma de Barcelona), except for primer RT3 sequences, which were obtained with the AB1377 sequencer (Perkin Elmer Centre d'Investigació i Desenvolupament, CSIC, Barcelona). Compressions and ambiguities were resolved by multiple sequencing of both strands. Details on the PCR conditions and primers are given in Tarrío, Rodríguez-Trelles, and Ayala (1998)
. For sequencing, we used, in addition to the standard M13/pUC sequencing oligonucleotides, the following primers: LT2, 5'-ACGGCGARCTSTWTCTGG-3'; LT3, 5'-CCATCGARCACRAGTCC-3'; LT4, 5'-GTGYTGGAYGTGATGGCAG-3'; RT2, 5'-TGCCATRCCRTTYAGATC-3'; RT3, 5'-GCAATCRTYGAAGCAGCG-3'; RT5, 5'-GATAGAARTGCYCCTGGC-3'. Sequences were aligned with CLUSTAL W, version 1.5 (Thompson, Higgins, and Gibson 1994
). The Xdh sequences of this study were deposited in GenBank under accession numbers AF226950AF226975.
In addition to Xdh, we analyzed published sequences from the mitochondrial cytochrome oxidases I (CO I) (419 bp), II (CO II) (687 bp), and III (CO III) (423 bp) (Spicer 1995
). The sequences from these three regions included all the species of this study except D. koepferae, D. uniseta, and D. mulleri.
Statistical Analyses
In order to control possible errors in model fitting caused by imperfect prior knowledge of the phylogeny, we considered two tree topologies (figs. 1 and 2
). Figure 2
is based on the Xdh sequence data. This topology is stable after applying the computer programs DNAML and DNAPARS from the PHYLIP package (Felsenstein 1993
) using the default options. Figure 1
represents the relationships proposed by Ruiz and Wasserman (1993)
on the basis of chromosomal inversion data.
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Among-sites rate variation was accommodated by the models following two approaches (Yang 1996b
): (1) allowing different rates for codon positions (referred to as C models; codon positionspecific rates are considered as parameters [denoted c1, c2, and c3, for codon positions 1, 2 and 3 of the Xdh gene]; c1 is set equal to 1, so that c2 and c3 become rate ratios relative to c1) and (2) treating rate differences among sites as a random effect using the discrete gamma distribution (eight equal-probability categories of rates, represented by the mean) with shape parameter
(denoted as dG models). The value of
is inversely related to the extent of rate variation (Yang 1996a
). As nucleotide frequencies at equilibrium, we used the ML estimates which, for a few models examined, yielded consistently higher likelihood scores. Analyses were conducted with the BASEML program of PAML, version 2.0g (Yang 1999
), and the PAUP*, version 4.0b2 (Swofford 1999
), package.
The relevance of specific parameters for describing the evolution of Xdh was evaluated by means of the likelihood ratio test (Yang 1996b
; Huelsenbeck and Crandall 1997
). For a given tree topology (e.g., fig. 1
), a model (H1) with p parameters and log-likelihood L1 fits the data significantly better than a nested submodel (H0) with q = p - n restrictions and likelihood L0 if the deviance D = -2 log
= -2(log L1 - log L0) falls in the rejection region of a
2 distribution with n degrees of freedom. Specifically for the test of rate constancy among sites, where the H0 (
=
) is equivalent to fixing
at the boundary of the parameter space of the H1 (
<
), H0 tends to be rejected more often than expected from the nominal significance level (see Yang 1996b
). Yet, the likelihood differences of this study were all very large, so this inaccuracy of the
2 approximation is not expected to alter the conclusions of the tests.
Among-sites rate variation can be incorporated into the substitution models either before or after increasing the number of substitution types from one (i.e., the JC69 model) to six (the REV model). Varying the parameter addition sequence can affect best-fit model selection (Cunninghan, Zhu, and Hillis 1998
). We took into account this potential source of bias by assaying different parameter addition sequences. Identified best models remained the same (results not shown).
The model found to satisfactorily describe the substitution process was used to generate candidate tree topologies by ML. Statistical support values for nodes of the ML trees were assessed by the quartet puzzling method (setting 1,000 puzzling steps). Support estimates for internal branches produced by this method can be interpreted as bootstrap scores (Strimmer and von Haeseler 1996
). In addition, we used distance-based neighbor-joining (NJ) and weighted parsimony criteria to choose candidate trees. Estimates of
and transition/transversion bias used in distance computation and weighing schemes for maximum parsimony are those obtained simultaneously by the joint likelihood comparison of all sequences in the first stage, which can be considered the most reliable (Yang 1996a
). NJ trees were generated using the best-fit model identified by the likelihood-ratio test in the ML analysis. Parsimony analyses were conducted using the branch-and-bound algorithm with options MULTREES, furthest addition, MAXTREES = 100 (PAUP*, version 4.0b2; Swofford 1999
). Statistical support for nodes of the NJ and maximum-parsimony trees was assessed with the bootstrap method (retaining nodes representing >50% from 1,000 bootstrap replications; Felsenstein 1985
). In the case of maximum parsimony, bootstrap replicates were obtained with the heuristic method: MULTREES, simple stepwise addition sequence, MAXTREES = 100, and TBR branch swapping (PAUP*, version 4.0b2; Swofford 1999
).
Phylogenetic hypotheses derived from the analyses of each gene region are compared by the resampling estimated log-likelihood (RELL) method of Kishino, Miyata, and Hasegawa (1990)
(as it is implemented in PAML, version 2.0g; Yang 1999
). For a given model of evolution, this test provides an estimate of the significance of a difference between the log-likelihood scores of several candidate tree topologies.
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Results |
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The Process of Nucleotide Substitution Along Xdh
Table 2
shows the log-likelihood ratio statistic values for models obtained assuming the topology shown in figure 2
. Nested models were always rejected when compared against the next full model. The best description so far of the substitution process along the Xdh region was provided by the REV + C model, which allows six different substitution classes (two transitions, CT and A
G, and four transversions, C
A, C
G, T
A, and T
G) and different substitution rates for codon positions.
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As for Xdh, the most satisfactory description of the substitution process in the three mitochondrial regions was attained with the REV + C model (results not shown; ln L = -1,289.09, -1,870.18, and -1,207.77, for CO I, CO II, and CO III, respectively).
Figure 3
represents the rate variation among codon positions (first, second, and third) and regions (Xdh, CO I, CO II, and CO III) as inferred with the REV + C model (allowing 12 categories of rates) using the topology shown in figure 2
. Estimates are scaled to the substitution rate in first codon positions of Xdh. CO I exhibits the greatest heterogeneity, with third codon positions evolving >200 times as fast as second positions (~7.31:0.03). First and second codon positions evolve the fastest in Xdh, followed by CO III. Even though rate differences among codon positions were largest for CO I, values obtained separately for each region indicated that the overall among-sites rate variation was largest for CO II (
= 0.209 vs.
= 0.192 for CO I and CO II, respectively). This seemingly contradictory result reflects the different ways in which c and
interpret the rate variation among sites. c values represent substitution rates for the average site of a codon position, whereas
measures the extent of among-sites rate variation regardless the codon position of the site (Yang 1996b
). A likelihood ratio test of the null hypothesis that the four regions fit the same gamma distribution indicated differences among genes in their extent of among-sites rate variation (-2 log
= 8.76, df = 3, P
0.02).
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Phylogenetic Relationships in the buzzatii Complex
Figure 2
shows the ML tree obtained from the Xdh data set with the REV + C model (table 2
). This is a fully resolved tree with well-supported nodes (quartet puzzling scores >80 in all cases), which coincides with the working topology also presented by this figure. Accordingly, the stalkeri cluster is the oldest lineage and is paraphyletic, with D. richardsoni derived before D. stalkeri. Next, the martensis and buzzatii clusters, which are monophyletic sister clades, split. Within the martensis cluster, D. martensis derived the earliest, followed by D. uniseta and D. starmeri and D. venezolana. Within the buzzatii cluster, D. buzzatii derived first, followed by D. koepferae and D. borborema and D. serido. These relationships are fully congruent with the chromosomal evolution of the complex as proposed by Ruiz and Wasserman (1993
; fig. 1
).
Figure 4A
shows the NJ tree based on the REV model (assuming constant rates for sites; see table 2
) and the complete Xdh data set. The NJ tree was topologically identical to the ML tree, with well-supported nodes (by the 70% or greater criterion of Hillis and Bull [1993]
) except for the node determining the paraphyly of the stalkeri cluster (retained 454 times in the bootstrap test; not shown). The relatively low support for this node might reflect an inconsistency of the NJ algorithm that could be attributed to not taking into consideration the Xdh among-sites rate variation for the distance model. Using the REV + dG model with
set to 0.427 (see table 3
) yielded a similar NJ topology (fig. 4B
), but the bootstrap support for the paraphyly of the stalkeri cluster was strengthened. Analogously, unweighted maximum parsimony yielded two equally most-parsimonious trees 922 steps long that corresponded to the ML topology (fig. 2
) and a topology clustering D. martensis and D. uniseta as a monophyletic group within the martensis cluster (fig. 4C
). Setting the overall transition/transversion ratio R = 1.8 (see table 3
; step-matrix 9 by 5 in PAUP*), the single most-parsimonious tree is figure 4D
(and fig. 2
); bootstrap values for this tree are very similar to those for the NJ tree shown in figure 4B.
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Discussion |
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All four of the gene regions analyzed in this study showed large substitution rate differences among sites. Furthermore, the degrees of among-sites rate variation were different for different genes. It is not circumstantial that the two regions exhibiting the greatest extent of among-sites rate variation, CO I and CO II, also produce disparate estimates of the phylogeny relative to what we consider the best estimate (see fig. 5
). High levels of among-sites rate variation indicate that most substitutions occur in only a few positions, while the majority of sites never experience substitutions (Yang 1996a
). Since neither sites with very few changes nor sites saturated with substitutions contain much phylogenetic information, it is not surprising that CO I and CO II yielded unreasonable topologies. It is noteworthy, however, that despite their different degrees of among-sites rate variation, combining the four genes under a common gamma distribution of rates resulted in a reinforced phylogenetic signal for the tree assumed by us to be the right tree. Apparently, there is phylogenetic signal in CO I and CO II. Presumably, this signal is present in slowly evolving sites, but it is overridden by some systematic bias at rapidly evolving sites, even though the among-sites rate variation seems to have been adequately accounted for by our best-fit model. In this respect, our conclusions strengthen the results from other studies (Barret, Donogue, and Sober 1991
; Sullivan, Holsinger, and Simon 1995
), indicating that phylogenetic signal can be additive when data from genes with different evolutionary processes are analyzed under a common reconstruction model.
That four independent molecular data sets, representing nuclear (Xdh) and mitochondrial (CO I, CO II, and CO III) protein-coding regions, converge to the same topology, which is furthermore fully consistent with the relationships inferred from chromosomal inversion data, supports the conclusion that the correct phylogeny of the buzzatii complex has been determined. Yet, our molecular analyses are more informative than the extensive cytological surveys conducted so far in the complex (Wasserman 1982
; Ruiz and Wasserman 1993
). Inversion data provide weak support for the basal position of the stalkeri cluster: it is the shortest of two nearly equal-length (one step difference) paths for the evolution of chromosome 2 (Ruiz and Wasserman 1993
). The primitiveness of the stalkeri cluster is further attested to by the fact that its X, 3, 4, and 5 chromosomes seem to have remained unchanged relative to the hypothetical ancestral caryotype of the complex (Ruiz and Wasserman 1993
). Chromosomal evolution also favors the monophyly of the martensis cluster, with D. uniseta, D. venezolana, and D. starmeri being more closely related to each other than to D. martensis (Ruiz and Wasserman 1993
).
The phylogeny of buzzatii has recently been addressed using data from three cytochrome oxidases (CO I, CO II, and CO III) (Spicer 1995
). Neither separately nor combined do these sequences allow statistical discrimination of the branching order in the complex, apart from the identification of the buzzatii cluster and the closeness between D. venezolana and D. starmeri (Spicer 1995
; results herein). Estimates of the degree of among-sites rate variation obtained by Spicer (1995)
are larger than those obtained by us (Spicer's estimates vs. ours for CO I, CO II, and CO III, respectively: 0.346 vs. 0.209, 0.371 vs. 0.192, and 0.481 vs. 0.279). The discrepancy can be attributed to the different analytical methods used. Spicer's (1995)
estimates of
differ from our ML estimates in that they are based on the number of changes at sites inferred by parsimony, which tends to overlook substitutions at the fastest-evolving sites, thus producing overestimates of
(Yang 1996a
).
Our results challenge some current ideas on the evolution of the buzzatii complex. After combining the inversion data with information about the contemporary distribution of the species, Ruiz and Wasserman (1993)
postulated that the ancestor of the complex inhabited the region now occupied by the martensis cluster (Venezuela and Colombia). From this primitive lineage, there was an early invasion of the Caribbean islands by migrants which evolved into the present stalkeri cluster. According to this scenario, the stalkeri cluster should be monophyletic. On the contrary, we infer that the stalkeri cluster is paraphyletic, which requires at least two independent colonizing events: one by migrants which evolved into the D. richardsoni lineage, followed by a second one that gave birth to D. stalkeri. Subsequently, the continental lineage stemmed into southern South America, where it evolved into the present buzzatii cluster, whereas the northern South American area continued to change and is now the martensis cluster.
Until the work of Fontdevila et al. (1988)
, who identified it as a distinct species, D. koepferae had been erroneously considered as a geographical form of the morphologically polytypic D. serido (Ruiz, Fontdevila, and Wasserman 1982
). In our study, the Argentinian (A) and Bolivian (B) strains of D. koepferae cluster in a monophyletic group clearly separated from D. serido (figs. 2 and 3
). The Xdh sequence of D. koepferae A is more diverged from D. serido (0.0089; fig. 2
) than the Xdh sequence of D. koepferae B (0.0065; fig. 2
). Differences are nonsignificant (P
0.87), but they occur in the same direction as for allozyme and interspecific crossability data (Fontdevila et al. 1988
).
This study eliminates doubts about the use of D. mulleri as an outgroup for the phylogeny of buzzatii. Crossability experiments had revealed unsuspected levels of intercomplex mating between several species of the buzzatii and mulleri complexes (Ruiz and Wasserman 1993
). Females of D. mulleri strains produced third-instar larvae when crossed with males of D. buzzatii, D. martensis, and D. venezolana. Analogously, males of D. mulleri produced first- or second-instar larvae when crossed to D. borborema females. Also, before the work of Ruiz and Wasserman (1993)
, the buzzatii and martensis clusters were classified within the mulleri complex. According to our analyses, however, D. mulleri falls well outside the buzzatii complex.
In order to examine the assumption that rates of substitution are constant along different parts of the tree, we carried out likelihood ratio tests of the molecular-clock hypothesis for Xdh, CO I, CO II, and CO III separately and for all four regions lumped together. Strictly speaking, this comparison is valid only if the likelihood values are calculated using the true topology. The topology shown in figure 2
is well supported by the analyses of this study and is consistent with the chromosomal phylogeny of the complex; therefore, it seems a reasonable hypothesis for tests of the molecular clock. We used the REV + C model to calculate the likelihood values either with or without the clock assumption. The REV + C clock hypothesis was rejected for each region taken separately (-2 log = 43.22, df = 12, P < 10-4; -2 log
= 19.38, df = 8, P
0.013; -2 log
= 24.90, df = 8, P
0.002; and -2 log
= 34.76, df = 8, P < 10-4 for Xdh, CO I, CO II, and CO III, respectively) and for all four regions combined (-2 log
= 82.98, df = 8, P < 10-4). This result does not depend on the inclusion of D. hydei in the tests, because after removing this species, the outcome remained virtually unchanged. However, when only the species of the martensis and buzzatii clusters were considered in the analysis, all of the data sets can be assumed to fit the clock assumption (-2 log
= 6.70, df = 8, P
0.57; -2 log
= 4.06, df = 5, P
0.54; -2 log
= 5.24, df = 5, P
0.39; -2 log
= 11.46, df = 5, P
0.04; and -2 log
= 3.06, df = 5, P
0.69 for Xdh, CO I, CO II, CO III, and the combined data set, respectively). Hence, the deviation from the clock model detected above for the entire buzzatii complex must be caused by differences in the rate of evolution between the stalkeri cluster and the martensis and buzzatii clusters. It is apparent in figures 1 and 7
that the latter two clusters evolve faster than the former. Interestingly enough, from a cytogenetical standpoint, both the martensis and the buzzatii clusters have diverged more from the hypothetical ancestral caryotype than the stalkeri cluster (Ruiz and Wasserman 1993
). This observation suggests the existence of a positive association between the rates of molecular and chromosomal evolution. Further analyses of the substitution rates by classes (e.g., synonymous vs. nonsynonymous, etc.) might help to clarify this question.
For a molecular marker to be useful for phylogenetic inference its amount of evolution should match the relevant divergence times. The Xdh region analyzed here had successfully been used before to resolve the phylogenetic relationships among the major subgroups of the Drosophila saltans species group (Rodríguez-Trelles, Tarrío, and Ayala 1999
). Because it comprises intermediate-evolving first and second codon positions and fast-changing third codon positions with little rate variation from site to site, Xdh was highlighted as a suitable marker for studies seeking to resolve evolutionary relationships among recently derived taxa (i.e., within species groups or subgroups). The successful application of Xdh to the resolution of the evolutionary relationships among the closely related species of the buzzatii complex in this study strengthens this conclusion.
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Acknowledgements |
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Footnotes |
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1 Keywords: Drosophila buzzatii complex
xanthine dehydrogenase,
cytochrome oxidase,
molecular evolution
maximum-likelihood phylogeny
molecular clock
2 Address for correspondence and reprints: Francisco Rodríguez-Trelles, Instituto de Investigaciones Agrobiológicas de Galicia (CSIC), Avenida de Vigo sln, 15706-Santiago de Compostela, Spain. E-mail: ftrelles{at}iiag.cesga.es
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