*Institute for Molecular Systematics, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand;
Department of Biology, Duke University;
Department of Ecology and Evolutionary Biology, University of Connecticut; and
§Institute of Statistical Mathematics, Tokyo, Japan
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Abstract |
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Introduction |
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We used 1,520 bp of mitochondrial DNA sequence data from the cytochrome oxidase subunit I (COI), ATPase subunits 6 (A6) and 8 (A8), and the transfer RNA aspartic acid (tRNAAsp) genes to reconstruct phylogenetic relationships among species of the genus Maoricicada. Using the SH test and various character weighting schemes, we critically evaluated competing hypotheses relating to the phylogenetic position of two key species; M. iolanthe and M. campbelli, in the Maoricicada radiation.
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Materials and Methods |
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We used the polymerase chain reaction (PCR) to amplify an 819-bp target from the COI gene with the primers C1-J-2195 and TL2-N-3014 (Simon et al. 1994
). We also amplified a second region of 771 bp from the A6, A8, transfer RNA lysine (tRNALys), and transfer RNA aspartic acid (tRNAAsp) genes with primers TK-J-3799 and A6-N-4570 (this study). All primer sequences are given in table 2 . PCR reactions contained 1.0 µl of purified DNA solution, 1.5 µl MgCl2 (50 mM), 2.5 µl dNTPs (20 mM), 5.0 µl 10 x GibcoBRL Taq buffer, 2.5 µl of each primer (10 µM), 2.5 units GibcoBRL Taq polymerase (Life Technologies), and 34.5 µl ddH2O overlaid with 35 µl of mineral oil. Thermal cycling conditions using a Perkin Elmer Cetus DNA Thermal Cycler 480 were denaturation at 94°C for 45 s, annealing at 5657°C for 45 s, and extension at 72°C for 75 s for 30 cycles. Negative controls containing no DNA were used in all sets of PCR reactions.
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The PCR conditions used for amplification of the overlapping gene targets were the same as those listed above, except 5 µl of BSA (10 mg/ml) was added to each reaction, and primer annealing was performed at 45°C for 35 cycles. To test for possible contamination in the DNA extraction and amplification process, PCR reactions containing the blank extraction were also included. Initial amplicons were gel-purified and reamplified using the same conditions, except no BSA was added and only 30 cycles were necessary to generate sufficient template for cycle sequencing.
PCR amplicons were purified by excision from a 1% low-melting-point agarose gel and centrifuged at top speed for 10 min, and the supernatant was used directly in cycle sequencing reactions. Alternatively, PCR products were purified using the PrepAGene (Biorad) kit following the manufacturer's instructions. Purified PCR products were cycle-sequenced using the Perkin Elmer Big Dye Terminator Cycle Sequencing Ready Reaction kit following the manufacturer's instructions. Cycle sequencing products were purified by ethanol precipitation and separated by electrophoresis on an ABI Prism 377 DNA sequencer. Sequences were checked for accuracy using the ABI sequence analysis software and were manually aligned using ESEE3.2 (Cabot and Beckenbach 1989
), facilitated by the conserved amino acid sequences and the absence of indels.
Patterns of Sequence Variation
Unless otherwise noted, all analyses were conducted using PAUP*, version 4.0b2a (Swofford 1998
). We calculated the numbers of varied sites, parsimony-informative sites, and base frequencies for each gene and codon position. The null hypothesis of base frequency stationarity among sequences was evaluated using the
2 heterogeneity test as implemented in PAUP*, version 4.0b2a (Swofford 1998
). We examined all sites and parsimony sites only in order to assess the potentially confounding effects of unvaried sites, which, by definition, have stationary base frequencies (Waddell et al. 1999
). We note that the
2 heterogeneity test ignores the lack of independence among sequences due to a shared phylogenetic history; therefore, the results may be biased.
Phylogenetic Analyses
To detect the presence of significant heterogeneity in signal among data sets, we implemented the partition homogeneity test (PHT; Farris et al. 1994
) by dividing the characters according to two criteria. First, characters were partitioned into third positions versus all other sites combined. This was done in order to detect the presence of misleading signal in the third positions, which, as we have shown elsewhere (Buckley, Simon, and Chambers 2001
), have a higher substitution rate than the first, second, and tRNAAsp sites and are therefore more likely to suffer from homoplastic substitutions (e.g., Simon et al. 1994
). Second, we partitioned the data into A6 and A8 genes combined versus the COI gene. The tRNAAsp sites were excluded and the A8 sites were combined with the A6 sites, because the tRNAAsp gene contains only a small number of parsimony-informative sites, and both the A6 and the A8 genes are part of the same enzyme complex. Following Cunningham (1997)
, invariant sites were removed before the PHT was performed, under a heuristic search with 500 replications. The PHT was repeated under six-parameter parsimony (Williams and Fitch 1989, 1990
; see below).
Phylogenetic analyses were conducted under the maximum-parsimony (MP; Fitch 1971
) and ML (Felsenstein 1981
) optimality criteria. We followed this approach because for both of these two methods there is a theoretical expectation of the behavior of the method given various sets of relative branch lengths (relative rates of evolution among taxa). Thus, comparing topologies and nodal support under different optimality criteria can provide clues to confounding artifacts present in the data. For the MP analyses, we constructed trees under equal weights, six-parameter parsimony (Williams and Fitch 1989, 1990
), and downweighting of third-position sites. To obtain appropriate step-matrices, R-matrices (underlying relative substitution rates among the four nucleotides) were estimated under the general time reversible model (e.g., Yang 1994a
) using ML optimization and transformed by taking the natural log of each relative frequency parameter (Cunningham 1997
; Stanger-Hall and Cunningham 1998
). Because they violated the assumption of triangle inequality, some of the step matrices were adjusted using PAUP*, version 4.0. Heuristic searches were performed on an initial stepwise addition tree followed by tree bisection-reconnection (TBR) branch swapping. The third positions were also progressively downweighted relative to the first, second, and tRNAAsp sites by ratios ranging from 1:2 to 1:15. We used a range of weighting ratios, because the comparison of tree lengths across weighting schemes is not valid, thus making the selection of such values arbitrary to an extent (Sullivan, Markert, and Kilpatrick 1997
). We have shown elsewhere (Buckley, Simon, and Chambers 2001
) that the third codon positions in the Maoricicada mitochondrial genes examined here evolve at a faster rate, making them potential candidates for downweighting.
For the ML analyses, we estimated substitution model parameters using a best-fit model approach as described by Frati et al. (1997)
and Sullivan, Markert, and Kilpatrick (1997)
. Substitution models tested included those of Jukes and Cantor (1969
; JC69), Kimura (1980
; K80), Hasegawa, Kishino, and Yano (1985
; HKY85), and Yang (1994a
; GTR). These substitution models were also coupled with a series of parameters describing the distribution of among-site rate variation, including invariable sites (I sites; e.g., Hasegawa, Kishino, and Yano 1985
), gamma distributed rates (
rates; Yang 1994b
), a mixed model of gamma distributed rates and invariable sites (I+
; Gu, Fu and Li 1995
), and a site-specific rates model (SSR; Swofford et al. 1996
; Buckley, Simon, and Chambers 2001
). For the SSR model, each codon position for each of the three protein-coding genes and all the tRNAAsp sites together were assigned their own relative substitution rate (SSR10 model).
To calculate genetic distances, we used the estimator described in equation (4) of Waddell and Steel (1997)
as implemented in PAUP*, version 4.0. This estimator produces what are usually referred to as ML distances (e.g., Swofford et al. 1996
), in which the relative-rate matrix is optimized using ML from all of the data and fixed for each pairwise comparison. We used this method because Waddell and Steel (1997)
found through simulation studies that homogenizing R for all distance comparisons tends to yield estimates with a lower variance than the more commonly used distance estimators. Nonparametric bootstrapping (Felsenstein 1985
) was performed with 500 replicates for the MP analyses and 100 replicates for the ML analyses. To detect increases in substitution rates among various Maoricicada lineages, we implemented the ML relative-rate test from HY-PHY, version 0.7b (Kosakovsky and Muse 2000
).
We also used marginal ancestral-state reconstruction under ML (Yang, Kumar, and Nei 1995
), implemented in PAUP*, version 4.0, to estimate the spatial location and substitution type of synapomorphies that unite the species M. iolanthe with M. campbelli. This was done in order to assess the nature of the synapomorphies supporting the grouping of these two species (see below).
The Shimodaira-Hasegawa Test
We used the particular implementation of the SH test referred to as the MS method by Shimodaira and Hasegawa (1999)
, which corresponds to the posNPncd test described by Goldman, Anderson, and Rodrigo (2001)
, except that our implementation is a weighted version. We emphasize to readers that there are other possible implementations of the SH test as described by Shimodaira and Hasegawa (1999)
. In this particular implementation of the SH test, the maximum of the standardized difference of log likelihoods is used as the test statistic, and the nonparametric bootstrap with reestimated log likelihoods (RELL) approximation (Kishino, Miyata, and Hasegawa 1990
) is used for resampling the log likelihoods. The RELL approximation is used to avoid reestimation of the parameters in the nonparametric bootstrap replicates. There is room to improve the SH test while controlling the coverage probability approximately, and the P values will be between those of the KH test and those of the SH test. We also note that it is possible to construct a parametric test to perform a similar a posteriori test using parametric bootstrap techniques (Goldman 1993
; Huelsenbeck and Rannala 1997
; Goldman, Anderson, and Rodrigo 2001
).
Using the SH approach, we examined the phylogenetic position of M. iolanthe and M. campbelli by taking the ML tree estimated under the GTR+I+ model and evaluating it against a series of topologies where the M. iolanthe and M. campbelli clade was shifted to a range of alternative phylogenetic positions. In constructing the alternative topologies, we avoided breaking up monophyletic groups that were consistently recovered in all phylogenetic analyses. In all, we tested 13 alternative phylogenetic topologies against the optimal ML GTR+I+
tree. The set of topologies that we selected were therefore a mixture of a priori and a posteriori hypotheses, exactly the situation in which the KH test is inappropriate. Sitewise log likelihoods were calculated under the GTR+SSR10 and GTR+I+
models for each topology tested using PAUP*, version 4.0, and exported into programs written by H.S. (under development) for calculation of SH test P values. Substitution model parameters were reoptimized for each topology in order to maximize the likelihood score of each tree and minimize the selection bias. For comparative purposes, we also included results from pairwise KH tests performed under the GTR+I+
model and pairwise Templeton (1983)
tests performed under six-parameter parsimony. The P values calculated from the KH and Templeton tests were halved in order to convert the test to a one-sided test, because one of the topologies being tested was known to be the optimal topology (Goldman, Anderson, and Rodrigo 2001
). The significance levels of both the KH and the Templeton tests were adjusted using a Bonferroni correction.
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Results |
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Phylogenetic Relationships Among Maoricicada Species
All corrected genetic distances given in this section were estimated using ML under the GTR+I+ model and represent the expected number of substitutions per site. We do not report the GTR+SSR10 distances, because we have previously shown that this model underestimates branch lengths relative to gamma and invariable-sites models (Buckley, Simon, and Chambers 2001
). The following description of phylogenetic relationships among Maoricicada species begins with the inferred root of the tree and proceeds up the tree to the more derived taxa.
Both ML and MP supported the monophyletic status of the genus Maoricicada, with all bootstrap support values 85% (figs. 2 and 3 ). The two outgroup species, K. scutellaris and R. leptomera, were differentiated from the ingroup taxa by corrected genetic distances ranging from 0.19 to 0.28. Starting at the base of the Maoricicada phylogeny, we observed a split between M. hamiltoni, M. myersi, and M. lindsayi on the one hand and the remaining Maoricicada radiation on the other hand. The three former species are all restricted to low-altitude habitats such as coastal rock fans and associated stream channels (M. myersi), clay banks (M. lindsayi), and riverbeds (M. hamiltoni). Among these three low-altitude species, M. myersi and M. lindsayi are sister species, with all methods giving 100% estimates of bootstrap support (figs. 2 and 3
).
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Most of the phylogenetic methods placed M. cassiope and M. tenuis as sister species; however, all estimates of bootstrap support were less than 50%, with the exception of the two ML trees (fig. 3 ). Relationships among M. cassiope, M. tenuis, and M. mangu were poorly resolved under both optimality criteria (figs. 2 and 3 ).
The Maoricicada species M. campbelli, M. iolanthe, M. alticola, M. otagoensis, M. nigra, M. clamitans, and M. oromelaena, and M. phaeoptera and the M. mangu mangu from Awakino formed a monophyletic clade in the ML, equal-weighted, and six-parameter MP analyses. However, bootstrap support for this clade was >50% in the ML analyses (fig. 3 ). Within this clade, most relationships were poorly resolved. However, we consistently observed a relationship between M. nigra and M. otagoensis, with bootstrap values ranging from 58% (fig. 2 ) to 65% (fig. 3A ). Another well-supported sister species relationship existed between M. oromelaena and M. clamitans (figs. 2 and 3 ). Estimates of bootstrap support for this grouping were all >95%. A consensus tree showing well-supported relationships among Maoricicada species with habitat preferences is given in figure 6 .
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Discussion |
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The result of the SH tests indicates that the precise placement of the M. iolanthe and M. campbelli clade is not statistically well supported. This clade can be shifted to a range of alternative positions in the ML tree without a significant change in likelihood score. Goldman, Anderson, and Rodrigo (2001)
have noted that the results of the SH test are highly dependent on the total number of topologies made available for simultaneous comparison. Ideally, all possible a priori topologies should be included in this set to ensure that the true tree is available for testing. However, with a data set the size of ours, this is difficult, if not impossible. If we were to include more topologies, the test would simply become more conservative, and our ultimate biological conclusion would not be altered.
The data presented here clearly demonstrate that the overconfidence of the KH test can affect the general biological conclusions of an empirical study in the absence of corrections for multiple comparisons. For example, when this bias was ignored, we were able to incorrectly reject the hypothesis that M. iolanthe and M. campbelli are sister species to the remaining Maoricicada radiation. The pairwise KH and Templeton tests seemed to offer greater resolution than the SH test, because the P values calculated using the KH and Templeton tests were much lower; however, this result is misleading, since the KH and Templeton tests give overconfidence in a topology because sampling error due to estimation of the topology is ignored (unlike in the SH test, which explicitly accounts for this problem; Shimodaira and Hasegawa 1999
). The problem of multiple testing can be compensated for using a Bonferroni correction (see also Bar-Hen and Kishino [2000] for a similar approach). For example, many of the P values obtained from both the Templeton test and the KH test were rendered nonsignificant following the appropriate adjustment. Although the Bonferroni correction is statistically valid, it is far more conservative than the SH test. Therefore, when comparing many topologies, the SH test will always be preferable. Our observations regarding the relative power of the SH and KH tests agrees with the prediction of Goldman, Anderson, and Rodrigo (2001)
, who noted that if the adjusted (one-tailed) P value from the KH test indicates acceptance of the null hypothesis, then the SH test will imply the same result. However, this is not a reason to incorrectly apply the KH test, because, as Goldman, Anderson, and Rodrigo (2001)
point out, one cannot predict the result of the SH test if the KH test indicates rejection of the null hypothesis.
How can we explain the inferred derived phylogenetic placement of M. iolanthe and M. campbelli together apart from the other lowland species? There are two classes of explanations: (1) the tree is incorrect (consistent with the SH-test) because (a) M. iolanthe is a long branch, or (b) the substitution models that we used may not fit the data well; or (2) the tree is correct (the SH test is too conservative), but (a) due to lineage sorting, the gene tree does not match the species phylogeny, or (b) the derived position results from the fact that the montane lineages could have sequentially split off M. iolanthe and M. campbelli, both of which retained the ancestral Maoricicada phenotype, or (c) M. iolanthe and M. campbelli represent evolutionary reversals regarding habitat preferences.
Our analyses indicate that M. iolanthe forms one of the longest branches in the phylogeny (fig. 3
) and is evolving at a significantly higher rate than at least two of the M. campbelli lineages. It is well known that long branches can bias phylogenetic analysis due to the accumulation of multiple substitutions obscuring phylogenetic signal (Felsenstein 1978
; Hendy and Penny 1989
; Swofford et al. 1996
). We deliberately employed methods that are known to be less susceptible to the confounding effects of long branches, such as ML using a best-fit substitution model (Swofford et al. 1996
; Cunningham, Zhu, and Hillis 1998
). However, there are numerous artifacts of the evolutionary process that have the potential to mislead our analyses. If the model of evolution fits poorly, noisy data may cause serious problems even for ML. These observations indicate that the M. iolanthe sequence analyzed here may be in a window of nucleotide variation where sufficient noise exists at third positions to be misleading, yet not enough variation is present at more conserved first, second, and tRNAAsp sites to overwhelm this noise or to strongly support an alternative hypothesis (e.g., Halanych and Robinson 1999
). Despite the results of the PHT tests, there may not be enough variation at the more conserved (i.e., first, second, and tRNAAsp) sites to support a finding of any significant incongruence. If this is the case, then we note that even the most general of the commonly used substitution models (i.e., GTR+I+
and GTR+SSR10) are unable to overcome this misleading signal, as noted in other studies (e.g., Cao et al. 1998
). However, importantly, the complex models indicate that the difference between the optimal topology and the alternative topologies are nonsignificant. Sequence data from a nuclear locus, longer mtDNA sequences containing, presumably, more informative nonsynonymous replacements, or improvements in knowledge regarding the substitution process may ultimately be required to stabilize the phylogenetic position of M. iolanthe and M. campbelli.
If the topology is correct (and the SH test is too conservative), then we must invoke alternative explanations to account for the derived position of M. iolanthe and M. campbelli. First, retention of ancestral polymorphisms could cause the inferred gene tree to be a misleading estimate of the species phylogeny. Thus, sequence data from a nuclear gene could be used to evaluate this hypothesis. However, Moore (1995, 1997)
demonstrated that the probability that the mtDNA gene tree will track the population tree is much greater than that of a gene tree derived from a single nuclear locus. Hoelzer (1997)
has raised possible exceptions to this explanation that invoke gender-biased dispersal or extremely polygynous breeding systems. Although we cannot formally discount the possibility of gender-biased dispersal or polygyny within any species of Maoricicada, dispersal is a rare phenomenon in cicadas generally (Itô and Nagamine 1981
; Williams and Simon 1995
; deBoer and Duffels 1996
) and in the few instances when it does occur, it tends to involve female rather than male dispersal (Williams and Simon 1995
).
Second, it is possible that montane lineages could have sequentially split off M iolanthe and M. campbelli, both of which retained the ancestral Maoricicada phenotype. Evolutionary processes of this sort would produce the phylogenetic pattern that we observed whereby modern M. iolanthe and M. campbelli are nested within the Maoricicada radiation, yet still represent the ancestral phenotype. Although this hypothesis is possible, we believe that it is more likely that systematic error in the data is responsible for some of the observed phylogenetic patterns within Maoricicada. Further studies are now being initiated to test this hypothesis.
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Acknowledgements |
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Footnotes |
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1 Keywords: multiple-comparison test
Shimodaira-Hasegawa test
Kishino-Hasegawa test
maximum likelihood
phylogenetics
Maoricicada
2 Address for correspondence and reprints: Thomas Buckley, Department of Biology, Box 90338, Duke University, Durham, North Carolina 27708. E-mail: tbuckley{at}duke.edu
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