Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.


Science 12 September 2003:
Vol. 301. no. 5639, p. 1482
DOI: 10.1126/science.1087632

Technical Comments

Response to Comment on "Hexapod Origins: Monophyletic or Paraphyletic?"

Assessing the relationships among arthropod taxa is an intensely debated issue in metazoan phylogeny, with various studies testing different character sets, phylogenetic methods, and strategies for analyzing molecular data (13). Delsuc et al. (4) criticize our recent hypothesis that Hexapoda is not monophyletic (3) on methodological grounds, including use of a suboptimal substitution matrix, lack of correction for among-site rate variation (ASRV), and biased taxon selection. They further introduce a method (5) that recodes nucleotide sequences into only two categories— purines (R) and pyrimidines (Y)—and use a maximum-likelihood approach to reanalyze our data recoded in this fashion. They claim that this method corrects for artefactual clustering of taxa that results from compositional bias of nucleotide content; this view is bolstered by the correct placement of the honeybee and louse, which were anomalously placed in our tree and others (1, 6, 7), within Insecta. Their reanalysis places collembolans at the base of Hexapoda, although with moderate to low support, and thus questions the main conclusion of our study.

Despite the correct placement of the honeybee and louse, it is not clear that the Delsuc et al. method performs better generally. In fact, one might expect that reducing nucleotide sequence data set to only two states (R and Y) might exacerbate saturation at many sites, and be more susceptible to problems of nonstationarity of substitutions than an amino acid data set (8). In the latter, the model of substitution reflects the probability of a replacement to be fixed, and the use of 20-state characters decreases the possibility of overlooking convergence. The inference of phylogenies based on amino acid sequences is common practice and is generally accepted as among the most reliable of methods (810). Although the matrix of amino acid change used in the first of our two analyses was based on vertebrate sequences, it has been extensively used to study relationships among invertebrates with no reports of significant flaws (1, 6).

In our previous study (3), we used an alignment of amino acid sequences and two likelihood-based methods of analysis: A classical likelihood reconstruction using a fixed-parameter model of amino acid substitution, and a Bayesian analysis based on a general time reversible (GTR) model of substitution and modeling rate variation across sites using an invariant + {Gamma} distribution. Both analyses converged on the same topology, which supports the placement of Collembola outside of the Insecta + Crustacea assemblage.

The correction for rate variation among sites has been shown to potentially affect estimates of branch lengths and divergence times, but it seems to have only a limited effect on topology (11). To further address this issue, we calculated the likelihood of competing trees under the same matrix, but modeled ASRV using a {Gamma} distribution (12). Table 1 shows that the trees we produce (with Collembola outside Insecta + Crustacea) give higher likelihood scores, although with different degrees of significance, regardless of the use of {Gamma} correction.


Table 1. Comparison of tree topologies under the amino acid substitution model mtREV24 implemented in PAML (12, 19) and incorporating a {Gamma}-correction for ASRV [pKH = P value of the Kishino-Hasegawa test (17); pSH = P value of the Shimodaira-Hasegawa test (18); pRELL = P value of the RELL bootstrap (17)]. In the 15-taxon data set, the topology derived in Nardi et al. (3) is compared with a topology derived in Delsuc et al. (4), after pruning extra taxa and exchanging Anopheles gambiae with A. quadrimaculatus. In the 25-taxon data set, the topology from Fig. 1 is compared with the topology derived in (4). In the 35-taxon data set, the two topologies derived in (3) and (4) are compared.
Tree Likelihood alpha (of {Gamma}) pKH (17) pSH (18) pRELL (17)

15 taxa Nardi et al. -18488.559 0.42838 1.000 1.000 0.914
Delsuc et al. -18507.904 0.42228 0.087 0.090 0.086
25 taxa Nardi et al. -25482.424 0.41111 1.000 1.000 0.883
Delsuc et al -25492.299 0.41063 0.121 0.119 0.117
35 taxa Nardi et al. -34838.359 0.47124 1.000 1.000 0.920


Delsuc et al

-34881.787

0.45337

0.077

0.076

0.080

To investigate the possible effects of taxon exclusion on the analysis, we repeated the analysis described in (3) on the 25-taxon data set of Delsuc et al. (4). To rule out the possibility that the analysis is negatively affected by use of a suboptimal substitution matrix and lack of ASRV correction, we used the Bayesian method outlined in (3) (Fig. 1). Again, Collembola fall outside the Insecta + Crustacea clade, although with only moderate support.


 Fig. 1. Maximum likelihood tree obtained applying the method outlined in (3) as implemented in MrBayes ver. 2.1 (20) (aamodel = gtr; rates = invgamma) to the 25-taxon data set of Delsuc et al. (4). The analysis was run for 570,000 generations and sampled every 100 generations. The first 150,000 generations were excluded from the analysis as the burn-in of the search. Numbers at each node indicate posterior probabilities. Branch lengths are drawn according to estimates obtained with PAML. [View Larger Version of this Image (24K GIF file)]
 

Our past (3) and present analyses, the analysis of Delsuc et al. (4), as well as other molecular studies (13) demonstrate that a reliable reconstruction of the phylogeny of Arthropoda—and the assessment of the mono- or paraphyly of Hexapoda, specifically—are still disputable. Results differ when subjecting the same data set to different methods of analysis or when using different subsets of data with the same methods. This leaves the impression that none of the competing hypotheses can yet be rejected with certainty. However, we believe that the theory of hexapod nonmonophyly proposed by several studies (3, 7, 14, 15) must be considered. In this context, the recent discovery of a marine hexapod from the Lower Devonian (16) undermines the traditional association between terrestrialization and the evolution of hexapods, leaving room for alternative hypotheses concerning hexapod origins.

Francesco Nardi
Giacomo Spinsanti

Department of Evolutionary Biology
University of Siena
via Aldo Moro 2
53100 Siena, Italy
E-mail: nardifra{at}unisi.it

Jeffrey L. Boore
U.S. Department of Energy Joint
Genome Institute and Lawrence
Berkeley Laboratory
Walnut Creek, CA 94598, USA

Antonio Carapelli
Romano Dallai
Francesco Frati

Department of Evolutionary Biology
University of Siena


References and Notes

  • 1. U. W. Hwang, M. Friedrich, D. Tautz, C. J. Park, W. Kim, Nature 413, 154 (2001). [CrossRef] [Medline]
  • 2. G. Giribet, G.D. Edgecombe, W.C. Wheeler, Nature 413, 157 (2001). [CrossRef] [Medline]
  • 3. F. Nardi et al., Science 299, 1887 (2003).[Abstract/Free Full Text]
  • 4. F. Delsuc, M. J. Phillips, D. Penny, Science 301, 1482 (2003); www.sciencemag.org/cgi/content/full/301/5639/1482d.
  • 5. M. J. Phillips, D. Penny, Mol. Phylogenet. Evol. 28, 171 (2003). [CrossRef] [Web of Science] [Medline]
  • 6. K. Wilson, V. Cahill, E. Ballment, J. Benzie, Mol. Biol. Evol. 17, 863 (2000).[Abstract/Free Full Text]
  • 7. F. Nardi, A. Carapelli, P. P. Fanciulli, R. Dallai, F. Frati, Mol. Biol. Evol. 18, 1293 (2001).[Abstract/Free Full Text]
  • 8. P. J. Waddell, H. Kishino, R. Ota, Genome Inform. 12, 141 (2001).
  • 9. S. Whelan, P. Liò, N. Goldman, TrendsGenet. 17, 262 (2001). [CrossRef] [Web of Science] [Medline]
  • 10. P. Liò, N. Goldman, J. Mol. Evol. 54, 519 (2002). [CrossRef] [Web of Science] [Medline]
  • 11. T. R. Buckley, C. Simon, G. K. Chambers, Syst. Biol. 50, 67 (2001).[Abstract/Free Full Text]
  • 12. Z. Yang, CABIOS 13, 555 (1997).
  • 13. M. Friedrich, D. Tautz, Ann. Soc. Entomol. Fr. 37, 21 (2001).
  • 14. E. Handschin, Mém. Soc. Roy. Entomol. Belgique 27, 40 (1955).
  • 15. T. Spears, G. Abele, in Arthropod Relationships, R. A. Fortey, R. H. Thomas, Eds. (Chapman & Hall, London, 1997), pp. 169–188.
  • 16. F. Haas, D. Waloszek, R. Hartenberger, Org. Divers. Evol. 3, 39 (2003).
  • 17. H. Kishino, M. Hasegawa, J. Mol. Evol. 29, 170 (1989). [CrossRef] [Web of Science] [Medline]
  • 18. H. Shimodaira, M. Hasegawa, Mol. Biol. Evol. 45, 1114 (1999).
  • 19. This methodology, as implemented in PAML (12), is unfortunately not suitable to conduct a full likelihood search. However, it is efficient for comparing a limited number of trees.
  • 20. The amino acid substitution model "gtr," present as an option in MrBayes 2.1, has not been implemented, in its original form, in the latest release MrBayes 3. It is not clear to us if the method is still available under a different set of commands or if it has been removed altogether.
  • 21. We thank P. Liò for useful discussion on this topic.

Received for publication 4 June 2003. Accepted for publication 18 August 2003.



THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Nonstationary Evolution and Compositional Heterogeneity in Beetle Mitochondrial Phylogenomics.
N. C. Sheffield, H. Song, S. L. Cameron, and M. F. Whiting (2009)
Syst Biol 58, 381-394
   Abstract »    Full Text »    PDF »
Mitochondrial genomes suggest that hexapods and crustaceans are mutually paraphyletic.
C. E Cook, Q. Yue, and M. Akam (2005)
Proc R Soc B 272, 1295-1304
   Abstract »    Full Text »    PDF »
Visualizing Conflicting Evolutionary Hypotheses in Large Collections of Trees: Using Consensus Networks to Study the Origins of Placentals and Hexapods.
B. R. Holland, F. Delsuc, V. Moulton, and A. Baker (2005)
Syst Biol 54, 66-76
   Abstract »    Full Text »    PDF »



To Advertise     Find Products

ADVERTISEMENT

Featured Jobs

Science. ISSN 0036-8075 (print), 1095-9203 (online)