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Arthropod relationships revealed by phylogenomic analysis of nuclear protein-coding sequences

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Abstract

The remarkable antiquity, diversity and ecological significance of arthropods have inspired numerous attempts to resolve their deep phylogenetic history, but the results of two decades of intensive molecular phylogenetics have been mixed1,2,3,4,5,6,7. The discovery that terrestrial insects (Hexapoda) are more closely related to aquatic Crustacea than to the terrestrial centipedes and millipedes2,8 (Myriapoda) was an early, if exceptional, success. More typically, analyses based on limited samples of taxa and genes have generated results that are inconsistent, weakly supported and highly sensitive to analytical conditions7,9,10. Here we present strongly supported results from likelihood, Bayesian and parsimony analyses of over 41 kilobases of aligned DNA sequence from 62 single-copy nuclear protein-coding genes from 75 arthropod species. These species represent every major arthropod lineage, plus five species of tardigrades and onychophorans as outgroups. Our results strongly support Pancrustacea (Hexapoda plus Crustacea) but also strongly favour the traditional morphology-based Mandibulata11 (Myriapoda plus Pancrustacea) over the molecule-based Paradoxopoda (Myriapoda plus Chelicerata)2,5,12. In addition to Hexapoda, Pancrustacea includes three major extant lineages of ‘crustaceans’, each spanning a significant range of morphological disparity. These are Oligostraca (ostracods, mystacocarids, branchiurans and pentastomids), Vericrustacea (malacostracans, thecostracans, copepods and branchiopods) and Xenocarida (cephalocarids and remipedes). Finally, within Pancrustacea we identify Xenocarida as the long-sought sister group to the Hexapoda, a result confirming that ‘crustaceans’ are not monophyletic. These results provide a statistically well-supported phylogenetic framework for the largest animal phylum and represent a step towards ending the often-heated, century-long debate on arthropod relationships.

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Figure 1: Phylogenetic relationships of 75 arthropod and five outgroup species.
Figure 2: Phylogram of relationships for 75 arthropod and five outgroup species.

Accession codes

Data deposits

All sequences generated for this publication have been deposited in GenBank under the accession numbers given in Supplementary Tables 4 and 5. Full data matrices are available in Supplementary Information.

References

  1. Abele, L. G., Kim, W. & Felgenhauer, B. E. Molecular evidence for inclusion of the phylum Pentastomida in the Crustacea. Mol. Biol. Evol. 6, 685–691 (1989)

    Google Scholar 

  2. Friedrich, M. & Tautz, D. Ribosomal DNA phylogeny of the major extant arthropod classes and the evolution of myriapods. Nature 376, 165–167 (1995)

    Article  ADS  CAS  Google Scholar 

  3. Regier, J. C. & Shultz, J. W. Molecular phylogeny of the major arthropod groups indicates polyphyly of crustaceans and a new hypothesis for the origin of hexapods. Mol. Biol. Evol. 14, 902–913 (1997)

    Article  CAS  Google Scholar 

  4. Giribet, G., Edgecombe, G. D. & Wheeler, W. C. Arthropod phylogeny based on eight molecular loci and morphology. Nature 413, 157–161 (2001)

    Article  ADS  CAS  Google Scholar 

  5. Hwang, U. W., Friedrich, M., Tautz, D., Park, C. J. & Kim, W. Mitochondrial protein phylogeny joins myriapods with chelicerates. Nature 413, 154–157 (2001)

    Article  ADS  CAS  Google Scholar 

  6. Mallatt, J. & Giribet, G. Further use of nearly complete 28S and 18S rRNA genes to classify Ecdysozoa: 37 more arthropods and a kinorhynch. Mol. Phylogenet. Evol. 40, 772–794 (2006)

    Article  CAS  Google Scholar 

  7. Budd, G. E. & Telford, M. J. The origin and evolution of arthropods. Nature 457, 812–817 (2009)

    Article  ADS  CAS  Google Scholar 

  8. Boore, J. L., Lavrov, D. V. & Brown, W. M. Gene translocation links insects and crustaceans. Nature 392, 667–668 (1998)

    Article  ADS  CAS  Google Scholar 

  9. Phillips, M. J., Delsuc, F. & Penny, D. Genome-scale phylogeny and the detection of systematic biases. Mol. Biol. Evol. 21, 1455–1458 (2004)

    Article  CAS  Google Scholar 

  10. Rota-Stabelli, O. & Telford, M. J. A multi criterion approach for the selection of optimal outgroups in phylogeny: recovering some support for Mandibulata over Myriochelata using mitogenomics. Mol. Phylogenet. Evol. 48, 103–111 (2008)

    Article  CAS  Google Scholar 

  11. Snodgrass, R. E. Evolution of the Annelida, Onychophora and Arthropoda (Smithsonian Inst. Press, 1938)

    Google Scholar 

  12. Mallatt, J. M., Garey, J. R. & Shultz, J. W. Ecdysozoan phylogeny and Bayesian inference: first use of nearly complete 28S and 18S rRNA gene sequences to classify the arthropods and their kin. Mol. Phylogenet. Evol. 31, 178–191 (2004)

    Article  CAS  Google Scholar 

  13. Dunn, C. W. et al. Broad phylogenomic sampling improves resolution of the animal tree of life. Nature 452, 745–749 (2008)

    Article  ADS  CAS  Google Scholar 

  14. Timmermans, M. J. T. N., Roelofs, D., Mariën, J. & Van Straalen, N. M. Revealing pancrustacean relationships: phylogenetic analysis of ribosomal protein genes places Collembola (springtails) in a monophyletic Hexapoda and reinforces the discrepancy between mitochondrial and nuclear DNA markers. BMC Evol. Biol. 8, 83 (2008)

    Article  CAS  Google Scholar 

  15. Philippe, H. et al. Phylogenomics revives traditional views on deep animal relationships. Curr. Biol. 19, 706–712 (2009)

    Article  CAS  Google Scholar 

  16. Regier, J. C. et al. Resolving arthropod phylogeny: exploring phylogenetic signal within 41 kb of protein-coding nuclear gene sequence. Syst. Biol. 57, 920–938 (2008)

    Article  CAS  Google Scholar 

  17. Holder, M. T., Zwickl, D. J. & Dessimoz, C. Evaluating the robustness of phylogenetic methods to among-site variability in substitution processes. Phil. Trans. R. Soc. B 363, 4013–4021 (2008)

    Article  CAS  Google Scholar 

  18. Seo, T. & Kishino, H. Statistical comparison of nucleotide, amino acid, and codon substitution models for evolutionary analysis of protein-coding sequences. Syst. Biol. 58, 199–210 (2009)

    Article  CAS  Google Scholar 

  19. Podsiadlowski, L., Braband, A. & Mayer, G. The complete mitochondrial genome of the onychophoran Epiperipatus biolleyi reveals a unique transfer RNA set and provides further support for the Ecdysozoa hypothesis. Mol. Biol. Evol. 25, 42–51 (2008)

    Article  CAS  Google Scholar 

  20. Shultz, J. W. A phylogenetic analysis of the arachnid orders based on morphological characters. Zool. J. Linn. Soc. 150, 221–265 (2007)

    Article  Google Scholar 

  21. Schram, F. R. ed. Crustacean Phylogeny (Balkema, 1983)

    Google Scholar 

  22. Fanenbruck, M., Harzsch, S. & Wagele, J. The brain of the Remipedia (Crustacea) and an alternative hypothesis on their phylogenetic relationships. Proc. Natl Acad. Sci. USA 101, 3868–3873 (2004)

    Article  ADS  CAS  Google Scholar 

  23. Harzsch, S. Neurophylogeny: architecture of the nervous system and a fresh view on arthropod phyologeny. Integr. Comp. Biol. 46, 162–194 (2006)

    Article  Google Scholar 

  24. Boxshall, G. A. Crustacean classification: on-going controversies and unresolved problems. Zootaxa 1668, 313–325 (2007)

    Google Scholar 

  25. Carapelli, A., Liò, P., Nardi, F., van der Wath, E. & Frati, F. Phylogenetic analysis of mitochondrial protein coding genes confirms the reciprocal paraphyly of Hexapoda and Crustacea. BMC Evol. Biol. 7 (suppl. 2). S8 (2007)

    Article  Google Scholar 

  26. Hennig, W. Insect Phylogeny (Wiley, 1981)

    Google Scholar 

  27. Zrzavy, J., Hypsa, V. & Vlaskova, M. in Arthropod Relationships (eds Fortey, R. A. & Thomas, R. H.) 97–107 (Chapman and Hall, 1997)

    Google Scholar 

  28. Gai, Y.-H., Song, D., Sun, H. & Zhou, K. Myriapod monophyly and relationships among myriapod classes based on nearly complete 28S and 18S rDNA sequences. Zool. Sci. 23, 1101–1108 (2006)

    Article  CAS  Google Scholar 

  29. Zwickl, D. J. Genetic Algorithm Approaches for the Phylogenetic Analysis of Large Biological Sequence Datasets under the Maximum Likelihood Criterion. PhD thesis, Univ. Texas Austin (2006)

    Google Scholar 

  30. Goldman, N., Thorne, J. L. & Jones, D. T. Using evolutionary trees in protein secondary structure prediction and other comparative sequence analyses. J. Mol. Biol. 263, 196–208 (1996)

    Article  CAS  Google Scholar 

  31. Remm, M., Storm, C. E. & Sonnhammer, E. L. Automatic clustering of orthologs and in-paralogs from pairwise species comparisons. J. Mol. Biol. 314, 1041–1052 (2001)

    Article  CAS  Google Scholar 

  32. Regier, J. C. & Shi, D. Increased yield of PCR product from degenerate primers with nondegenerate, nonhomologous 5′ tails. Biotechniques 38, 34–38 (2005)

    Article  CAS  Google Scholar 

  33. Staden, R., Judge, D. & Bonfield, J. Sequence assembly and finishing methods. Methods Biochem. Anal. 43, 303–322 (2001)

    CAS  PubMed  Google Scholar 

  34. Smith, S. W., Overbeck, R., Woese, C. R., Gilbert, W. & Gillevet, P. M. The genetic data environment and expandable GUI for multiple sequence analysis. Comp. Appl. Biosci. 10, 671–675 (1994)

    CAS  PubMed  Google Scholar 

  35. Katoh, K., Kuma, K., Toh, H. & Miyata, T. MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic Acids Res. 33, 511–518 (2005)

    Article  CAS  Google Scholar 

  36. PAUP*. v.4.0 (Sinauer Associates, Sunderland, Massachusetts, 2002)

  37. Huelsenbeck, J. P. & Ronquist, F. MRBAYES: Bayesian inference of phylogeny. Bioinformatics 17, 754–755 (2001)

    Article  CAS  Google Scholar 

  38. Ronquist, F. & Huelsenbeck, J. P. MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574 (2003)

    Article  CAS  Google Scholar 

  39. Altekar, G., Dwarkadas, S., Huelsenbeck, J. P. & Ronquist, F. Parallel Metropolis-coupled Markov chain Monte Carlo for Bayesian phylogenetic inference. Bioinformatics 20, 407–415 (2004)

    Article  CAS  Google Scholar 

  40. MRMODELTEST. v.2 (Evolutionary Biology Centre, Uppsala University, 2004)

  41. Regier, J. C. & Shultz, J. W. Elongation factor-2: a useful gene for arthropod phylogenetics. Mol. Phylogenet. Evol. 20, 136–148 (2001)

    Article  CAS  Google Scholar 

  42. Cummings, M. & Huskamp, J. Grid computing. EDUCAUSE Rev. 40, 116–117 (2005)

    Google Scholar 

  43. Bazinet, A. L. & Cummings, M. C. in Distributed & Grid Computing–Science Made Transparent for Everyone. Principles, Applications and Supporting Communities (ed. Weber, M. H. W.) 2–13 (Tectum, 2009)

    Google Scholar 

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Acknowledgements

C.W.C. thanks W. Hartman for early insight into questions of arthropod phylogeny and D. Percy for sequencing. J.W.M. and R.W. thank N. Tait, G. Hampson and R. Hessler for help collecting samples. J.C.R. and A.Z. thank M. Cummings and A. Bazinet for making available grid computing, and the DNA Sequencing Facility at the Center for Biosystems Research, University of Maryland Biotechnology Institute. J.W.S. was supported by the Maryland Agricultural Experiment Station. C.W.C. was supported by the Whiteley Center. This work was funded by two programmes at the US National Science Foundation, namely Biocomplexity in the Environment: Genome-Enabled Environmental Science and Engineering, and Assembling the Tree of Life.

Author Contributions C.W.C., J.C.R., J.W.S., A.Z. and J.W.M. designed the project. J.W.S., J.W.M., R.W. and J.C.R. designed and carried out taxon sampling and collection. J.C.R. and C.W.C. supervised DNA sequencing and editing, with PCR templates generated by J.C.R., B.B. and others. J.C.R., A.Z., C.W.C. and J.W.S. decided on the strategy for data analysis and its implementation, with the degen1 coding method developed and implemented by J.C.R., A.H. and A.Z. J.C.R. and A.Z. assembled the Supplementary Information and submitted sequences to GenBank. J.W.S. and J.W.M. proposed the names for the new, strongly supported clades in the Pancrustacea. C.W.C. wrote the first draft of the manuscript, with major additions by J.C.R. and J.W.S. and additional contributions by J.W.M. and A.Z. All authors commented on the manuscript.

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Correspondence to Clifford W. Cunningham.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-7 with Legends and Supplementary Tables 1-5. (PDF 918 kb)

Supplementary Data

This file contains the nucleotide data matrix, 80 taxa. (TXT 4150 kb)

Supplementary Data

This file contains the degen1 data matrix, 80 taxa. (TXT 4072 kb)

Supplementary Data

This file contains the amino acid data matrix, 85 taxa. (TXT 1087 kb)

Supplementary Data

This file contains the perl script to generate degen1 data matrices. (TXT 9 kb)

Supplementary Information

This file contains explanation of the Degen1_v1_2.pl script. (PDF 29 kb)

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Regier, J., Shultz, J., Zwick, A. et al. Arthropod relationships revealed by phylogenomic analysis of nuclear protein-coding sequences. Nature 463, 1079–1083 (2010). https://doi.org/10.1038/nature08742

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