Abstract
The comparative and evolutionary analysis of molecular data has allowed researchers to tackle biological questions that have long remained unresolved. The evolution of DNA and amino acid sequences can now be modeled accurately enough that the information conveyed can be used to reconstruct the past. The methods to infer phylogeny (the pattern of historical relationships among lineages of organisms and/or sequences) range from the simplest, based on parsimony, to more sophisticated and highly parametric ones based on likelihood and Bayesian approaches. In general, molecular systematics provides a powerful statistical framework for hypothesis testing and the estimation of evolutionary processes, including the estimation of divergence times among taxa. The field of molecular systematics has experienced a revolution in recent years, and, although there are still methodological problems and pitfalls, it has become an essential tool for the study of evolutionary patterns and processes at different levels of biological organization. This review aims to present a brief synthesis of the approaches and methodologies that are most widely used in the field of molecular systematics today, as well as indications of future trends and state-of-the-art approaches.
[1] Page, R.D.M. and Holmes, E.C. Molecular evolution: a phylogenetic approach, Blackwell Science, Oxford, 1998. Search in Google Scholar
[2] Korber, B., Muldoon, M., Theiler, J., Gao, F., Gupta, R., Lapedes, A., Hahn, B.H., Wolinsky, S. and Bhattacharya, T. Timing the Ancestor of the HIV-1 Pandemic Strains. Science 288 (2000) 1789–1796. http://dx.doi.org/10.1126/science.288.5472.178910.1126/science.288.5472.1789Search in Google Scholar
[3] Smith, G.J.D., Vijaykrishna, D., Bahl, J., Lycett, S.J., Worobey, M., Pybus, O.G., Ma, S.K., Cheung, C.L., Raghwani, J., Bhatt, S., Peiris, J.S.M., Guan, Y. and Rambaut, A. Origins and evolutionary genomics of the 2009 swineorigin H1N1 influenza A epidemic. Nature 459 (2009) 1122–1125. http://dx.doi.org/10.1038/nature0818210.1038/nature08182Search in Google Scholar
[4] Rokas, A. and Holland, P.W.H. Rare genomic changes as a tool for phylogenetics. Trends Ecol. Evol. 15 (2000) 454–459. http://dx.doi.org/10.1016/S0169-5347(00)01967-410.1016/S0169-5347(00)01967-4Search in Google Scholar
[5] Hillis, D.M., Moritz, C. and Mable, B.K., Eds. Molecular systematics. Sinauer Associates, Inc., Sunderland, MA, 1996. 10.2307/1447682Search in Google Scholar
[6] Hillis, D.M. and Wiens, J.J. Molecules versus morphology in systematics: conflicts, artifacts, and misconceptions. in: Phylogenetic analysis of morphological data (Wiens, J.J., Ed.), Smithsonian Institution Press, Washington, DC, 2000, 1–19. Search in Google Scholar
[7] Maley, L.E. and Marshall, C.R. The coming of age of molecular systematics. Science 279 (1998) 505–506. http://dx.doi.org/10.1126/science.279.5350.50510.1126/science.279.5350.505Search in Google Scholar PubMed
[8] Stevens, J.R. and Schofield, C.J. Phylogenetics and sequence analysis — some problems for the unwary. Trends Parasitol. 19 (2003) 582–588. http://dx.doi.org/10.1016/j.pt.2003.10.00410.1016/j.pt.2003.10.004Search in Google Scholar PubMed
[9] Doyle, J.J. Gene trees and species trees: molecular systematics as onecharacter taxonomy. Syst. Bot. 17 (1992) 144–163. http://dx.doi.org/10.2307/241907010.2307/2419070Search in Google Scholar
[10] Rokas, A., Williams, B.L., King, N. and Carroll, S.B. Genome-scale approaches to resolving incongruence in molecular phylogenies. Nature 425 (2003) 798–804. http://dx.doi.org/10.1038/nature0205310.1038/nature02053Search in Google Scholar PubMed
[11] Cummings, M.P., Otto, S.P. and Wakeley, J. Sampling properties of DNA sequence data in phylogenetic analysis. Mol. Biol. Evol. 12 (1995) 814–822. Search in Google Scholar
[12] Graybeal, A. Is it better to add taxa or characters to a difficult phylogenetic problem? Syst. Biol. 47 (1998) 9–17. http://dx.doi.org/10.1080/10635159826099610.1080/106351598260996Search in Google Scholar PubMed
[13] Huelsenbeck, J.P. Performance of phylogenetic methods in simulation.. Syst. Biol. 44 (1995) 17–48. Search in Google Scholar
[14] Maddison, W.P. Gene trees in species trees. Syst. Biol. 46 (1997) 523–536. Search in Google Scholar
[15] Pääbo, S., Poinar, H., Serre, D., Jaenicke-Despres, V., Hebler, J., Rohland, N., Kuch, M., Krause, J., Vigilant, L. and Hofreiter, M. Genetic analyses from ancient DNA. Annu. Rev. Genet. 38 (2004) 645–679. http://dx.doi.org/10.1146/annurev.genet.37.110801.14321410.1146/annurev.genet.37.110801.143214Search in Google Scholar PubMed
[16] Organ, C.L., Schweitzer, M.H., Zheng, W., Freimark, L.M., Cantley, L.C. and Asara, J.M. Molecular phylogenetics of mastodon and Tyrannosaurus rex. Science 320 (2008) 499. http://dx.doi.org/10.1126/science.115428410.1126/science.1154284Search in Google Scholar
[17] Tautz, D., Arctander, P., Minelli, A., Thomas, R.H. and Vogler, A.P. A plea for DNA taxonomy. Trends Ecol. Evol. 18 (2003) 70–74. http://dx.doi.org/10.1016/S0169-5347(02)00041-110.1016/S0169-5347(02)00041-1Search in Google Scholar
[18] Pons, J., Barraclough, T.G., Gomez-Zurita, J., Cardoso, A., Duran, D.P., Hazell, S., Kamoun, S., Sumlin, W.D. and Vogler, A.P. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst. Biol. 55 (2006) 595–609. http://dx.doi.org/10.1080/1063515060085201110.1080/10635150600852011Search in Google Scholar
[19] Hebert, P.D.N., Cywinska, A., Ball, S.L. and deWaard, J.R. Biological identifications through DNA barcodes. Proc. R. Soc. Lond. B 270 (2003) 313–321. http://dx.doi.org/10.1098/rspb.2002.221810.1098/rspb.2002.2218Search in Google Scholar
[20] Swofford, D.L., Olse, G.J., Waddell, P.J. and Hillis, D.M. Phylogenetic inference. in: Molecular systematics (Hillis, D.M., Moritz, C. and Mable, B.K., Eds.), Sinnauer Associates, Sunderland, MA, 1996, 407–514. Search in Google Scholar
[21] Whelan, S., Liò, P. and Goldman, N. Molecular phylogentics: state-of-theart methods for looking into the past. Trends Genet. 17 (2001) 262–272. http://dx.doi.org/10.1016/S0168-9525(01)02272-710.1016/S0168-9525(01)02272-7Search in Google Scholar
[22] Felsenstein, J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17 (1981) 368–376. http://dx.doi.org/10.1007/BF0173435910.1007/BF01734359Search in Google Scholar PubMed
[23] Posada, D. Selecting models of evolution. in: The phylogenetic handbook (Salemi, M. and Vandamme, A.-M., Eds.), Cambridge University Press, Cambridge, 2003, 256–282. Search in Google Scholar
[24] Yang, Z. Estimating the pattern of of nucleotide substitution. J. Mol. Evol. 39 (1994) 105–111. Search in Google Scholar
[25] Fitch, W.M. and Margoliash, E. A method for estimating the number of invariant amino acid coding positions in a gene, using cytochrome c as a model case. Biochem. Genet. 1 (1967) 65–71. http://dx.doi.org/10.1007/BF0048773810.1007/BF00487738Search in Google Scholar PubMed
[26] Wakeley, J. Substitution rate variation among sites in hypervariable region 1 of human mitochondrial DNA. J. Mol. Evol. 37 (1993) 613–623. http://dx.doi.org/10.1007/BF0018274710.1007/BF00182747Search in Google Scholar PubMed
[27] Reeves, J.H. Heterogeneity in the substitution process of amino acid sites of proteins coded for by mitochondrial DNA. J. Mol. Evol. 35 (1992) 17–31. http://dx.doi.org/10.1007/BF0016025710.1007/BF00160257Search in Google Scholar PubMed
[28] Hasegawa, M., Kishino, H. and Yano, T. Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J. Mol. Evol. 22 (1985) 160–174. http://dx.doi.org/10.1007/BF0210169410.1007/BF02101694Search in Google Scholar PubMed
[29] Yang, Z. Maximum likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites. Mol. Biol. Evol. 10 (1993) 1396–1401. Search in Google Scholar
[30] Yang, Z. Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. J. Mol. Evol. 39 (1994) 306–314. http://dx.doi.org/10.1007/BF0016015410.1007/BF00160154Search in Google Scholar
[31] Felsenstein, J. Inferring phylogenies. Sinauer Associates, Inc., Sunderland, MA, 2004. Search in Google Scholar
[32] Adachi, J. and Hasegawa, M. Model of amino acid substitution in proteins encoded by mitochondrial DNA. J. Mol. Evol. 42 (1996) 459–468. http://dx.doi.org/10.1007/BF0249864010.1007/BF02498640Search in Google Scholar
[33] Jones, D.T., Taylor, W.R. and Thornton, J.M. The rapid generation of mutation data matrices from protein sequences. Comp. Appl. Biosci. 8 (1992) 275–282. Search in Google Scholar
[34] Rodríguez, F., Oliver, J.F., Marín, A. and Medina, J.R. The general stochastic model of nucleotide substitution. J. Theor. Biol. 142 (1990) 485–501. http://dx.doi.org/10.1016/S0022-5193(05)80104-310.1016/S0022-5193(05)80104-3Search in Google Scholar
[35] Ren, F., Tanaka, H. and Yang, Z. An empirical examination of the utility of codon-substitution models in phylogeny reconstruction. Syst. Biol. 54 (2005) 808–818. http://dx.doi.org/10.1080/1063515050035468810.1080/10635150500354688Search in Google Scholar PubMed
[36] Tavaré, S., Adams, D.C., Fedrigo, O. and Naylor, G.J.P. A model for phylogenetic inference using structural and chemical covariates. in: Pacific Symposium on Biocomputing (Altman, R.B., Dunker, A.K., Hunter, L., Lauderdale, K. and Klein, T.E., Eds.), World Scientific, Singapore, 2001, 215–225. Search in Google Scholar
[37] Galtier, N. Maximum-likelihood phylogenetic analysis under a covarion-like model. Mol. Biol. Evol. 18 (2001) 866–873. Search in Google Scholar
[38] Huelsenbeck, J.P. Testing a covariotide model of DNA substitution. Mol. Biol. Evol. 19 (2002) 698–707. Search in Google Scholar
[39] Cunningham, C.W., Zhu, H. and Hillis, D.M. Best-fit maximum-likelihood models for phylogenetic inference: empirical tests with known phylogenies. Evolution 52 (1998) 978–987. http://dx.doi.org/10.2307/241123010.2307/2411230Search in Google Scholar
[40] Bruno, W.J. and Halpern, A.L. Topological bias and inconsistency of maximum likelihood using wrong models. Mol. Biol. Evol. 16 (1999) 564–566. Search in Google Scholar
[41] Huelsenbeck, J.P. and Hillis, D.M. Success of phylogenetic methods in the four-taxon case. Syst. Biol. 42 (1993) 247–264. Search in Google Scholar
[42] Holder, M. and Lewis, P.O. Phylogeny estimation: traditional and Bayesian approaches. Nat. Rev. Genet. 4 (2003) 275–284. http://dx.doi.org/10.1038/nrg104410.1038/nrg1044Search in Google Scholar PubMed
[43] Posada, D. and Crandall, K.A. Selecting the best-fit model of nucleotide substitution. Syst. Biol. 50 (2001) 580–601. http://dx.doi.org/10.1080/10635150175043512110.1080/106351501750435121Search in Google Scholar
[44] Huelsenbeck, J.P. and Crandall, K.A. Phylogeny estimation and hypothesis testing using maximum likelihood. Ann. Rev. Ecol. Syst. 28 (1997) 437–466. http://dx.doi.org/10.1146/annurev.ecolsys.28.1.43710.1146/annurev.ecolsys.28.1.437Search in Google Scholar
[45] Akaike, H. Information theory as an extension of the maximum likelihood principle. in: Second international symposium of information theory (Petrov, B.N. and Csaki, F., Eds.), Akademiai Kiado, Budapest, Hungary, 1973. Search in Google Scholar
[46] Schwarz, G. Estimating the dimensions of a model. Ann. Stat. 6 (1978) 461–464. http://dx.doi.org/10.1214/aos/117634413610.1214/aos/1176344136Search in Google Scholar
[47] Posada, D. and Buckley, T.R. Model selection and model averaging in phylogenetics: Advantages of Akaike information criterion and Bayesian approaches over likelihood ratio tests. Syst. Biol. 53 (2004) 793–808. http://dx.doi.org/10.1080/1063515049052230410.1080/10635150490522304Search in Google Scholar PubMed
[48] Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J. and Wheeler, D.L. GenBank. Nucleic Acids Res. 35 (2007) D21–D25. http://dx.doi.org/10.1093/nar/gkl98610.1093/nar/gkl986Search in Google Scholar
[49] Kitching, I.L., Forey, P.L., Humphries, C.J. and Williams, D.M. Cladistics. ed. 2. The theory and practice of parsimony analysis, Oxford University Press, Oxford, 1998. Search in Google Scholar
[50] Smith, A.B. Rooting molecular trees: problems and strategies. Biol. J. Linn. Soc. 51 (1994) 279–292. http://dx.doi.org/10.1111/j.1095-8312.1994.tb00962.x10.1111/j.1095-8312.1994.tb00962.xSearch in Google Scholar
[51] Phillips, A., Janies, D. and Wheeler, W. Multiple sequence alignment in phylogenetic analysis. Mol. Phylogenet. Evol. 16 (2000) 317–330. http://dx.doi.org/10.1006/mpev.2000.078510.1006/mpev.2000.0785Search in Google Scholar
[52] Goldman, N. Effects of sequence alignment procedures on estimates of phylogeny. BioEssays 20 (1998) 287–290. http://dx.doi.org/10.1002/(SICI)1521-1878(199804)20:4<287::AID-BIES4>3.0.CO;2-N10.1002/(SICI)1521-1878(199804)20:4<287::AID-BIES4>3.0.CO;2-NSearch in Google Scholar
[53] Ogden, T.H. and Rosenberg, M.S. Multiple sequence alignment accuracy and phylogenetic inference. Syst. Biol. 55 (2006) 314–328. http://dx.doi.org/10.1080/1063515050054173010.1080/10635150500541730Search in Google Scholar
[54] Edgar, R.C. and Batzoglou, S. Multiple sequence alignment. Curr. Opin. Struct. Biol. 16 (2006) 368–373. http://dx.doi.org/10.1016/j.sbi.2006.04.00410.1016/j.sbi.2006.04.004Search in Google Scholar
[55] Notredame, C. Recent evolutions of multiple sequence alignment algorithms. PLoS Comput. Biol. 3 (2007) e123. http://dx.doi.org/10.1371/journal.pcbi.003012310.1371/journal.pcbi.0030123Search in Google Scholar
[56] Thompson, J.D., Plewniak, F. and Poch, O. A comprehensive comparison of multiple sequence alignment programs. Nucleic Acids Res. 7 (1999) 2682–2690. http://dx.doi.org/10.1093/nar/27.13.268210.1093/nar/27.13.2682Search in Google Scholar
[57] Feng, D.F. and Doolittle, R.F. Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J. Mol. Evol. 25 (1987) 351–361. http://dx.doi.org/10.1007/BF0260312010.1007/BF02603120Search in Google Scholar
[58] Morrison, D.A. Why would phylogeneticists ignore computerized sequence alignment? Syst. Biol. 58 (2009) 150–158. http://dx.doi.org/10.1093/sysbio/syp00910.1093/sysbio/syp009Search in Google Scholar
[59] Hickson, R.E., Simon, C. and Perrey, S.W. The performance of several multiple-sequence alignment programs in relation to secondary-structure features for an rRNA sequence. Mol. Biol. Evol. 17 (2000) 530–539. Search in Google Scholar
[60] Hofacker, I.L. Vienna RNA secondary structure server. Nucleic Acids Res. 31 (2003) 3429–3431. http://dx.doi.org/10.1093/nar/gkg59910.1093/nar/gkg599Search in Google Scholar PubMed PubMed Central
[61] Wong, K.M., Suchard, M.A. and Huelsenbeck, J.P. Alignment uncertainty and genomic analysis. Science 319 (2008) 473–476. http://dx.doi.org/10.1126/science.115153210.1126/science.1151532Search in Google Scholar PubMed
[62] Löytynoja, A. and Goldman, N. Phylogeny-aware gap placement prevents errors in sequence alignment and evolutionary analysis. Science 320 (2008) 1632–1635. http://dx.doi.org/10.1126/science.115839510.1126/science.1158395Search in Google Scholar PubMed
[63] Thorne, J.L., Kishino, H. and Felsenstein, J. An evolutionary model for maximum likelihood alignment of DNA sequences. J. Mol. Evol. 33 (1991) 114–124. http://dx.doi.org/10.1007/BF0219362510.1007/BF02193625Search in Google Scholar PubMed
[64] Fitch, W.M. Toward defining the course of evolution: minimal change for a specific tree topology. Syst. Zool. 20 (1971) 406–416. http://dx.doi.org/10.2307/241211610.2307/2412116Search in Google Scholar
[65] Farris, J.S. The logical basis of phylogenetic systematics. in: Advances in Cladistics (Platnick, N.I. and Funk, V.A., Eds.), Columbia University Press, New York, 1983, 7–36. Search in Google Scholar
[66] Hennig, W. Grundzüge einer theorie der phylogenetischen systematik, Deutsche Zentral Verlag, Berlin, 1950. Search in Google Scholar
[67] Felsenstein, J. Cases in which parsimony or compatibility methods will be positively misleading. Syst. Zool. 27 (1978) 401–410. http://dx.doi.org/10.2307/241292310.2307/2412923Search in Google Scholar
[68] Huelsenbeck, J.P. Is Felsenstein zone a fly trap? Syst. Biol. 46 (1997) 69–74. Search in Google Scholar
[69] Goldman, N. Maximum likelihood inference of phylogenetic trees, with special reference to a Poisson process model of DNA substitution and to parsimony analysis. Syst. Zool. 39 (1990). 10.2307/2992355Search in Google Scholar
[70] Cavalli-Sforza, L.L. and Edwards, A.W.F. Phylogenetic analysis: Models and estimation procedures. Evolution 21 (1967) 550–570. http://dx.doi.org/10.2307/240661610.2307/2406616Search in Google Scholar
[71] Fitch, W.M. and Margoliash, E. Construction of phylogenetic trees. Science 155 (1967) 279–284. http://dx.doi.org/10.1126/science.155.3760.27910.1126/science.155.3760.279Search in Google Scholar PubMed
[72] Sneath, P.H.A. and Sokal, R.R. Numerical taxonomy, W.H. Freeman, San Francisco, 1973. Search in Google Scholar
[73] Saitou, N. and Nei, M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4 (1987) 406–425. Search in Google Scholar
[74] Rzhetsky, A. and Nei, M. A simple method for estimating and testing minimum-evolution trees. Mol. Biol. Evol. 9 (1992) 945–967. Search in Google Scholar
[75] Nei, M. and Kumar, S. Molecular evolution and phylogenetics, Oxford University Press, Oxford, 2000. Search in Google Scholar
[76] Edwards, A.W.F. Likelihood, Cambridge University Press, Cambridge, 1972. Search in Google Scholar
[77] Edwards, A.W.F. and Cavalli-Sforza, L.L. Reconstruction of evolutionary trees. in: Phenetic and phylogenetic classification (Heywood, V.H. and McNeill, J., Eds.), Systematics Association Publ. No. 6, London, 1964, 67–76. Search in Google Scholar
[78] Neyman, J. Molecular studies of evolution: a source of novel statistical problems. in: Statistical decision theory and related topics (Gupta, S.S. and Yackel, J., Eds.), Academic Press, New York, 1971, 1–27. Search in Google Scholar
[79] Swofford, D.L. PAUP*: phylogenetic analysis using parsimony (*and other methods), version 4.0, Sinauer Associates, Inc., Sunderland, MA, USA, 1998. Search in Google Scholar
[80] Kosakovsky Pond, S.L., Frost, S.D.W. and Muse, S.V. HyPhy: hypothesis testing using phylogenies. Bioinformatics 21 (2005) 676–679. http://dx.doi.org/10.1093/bioinformatics/bti07910.1093/bioinformatics/bti079Search in Google Scholar PubMed
[81] Stamatakis, A. RAxML-VI-HPC: Maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22 (2006) 2688–2690. http://dx.doi.org/10.1093/bioinformatics/btl44610.1093/bioinformatics/btl446Search in Google Scholar PubMed
[82] Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24 (2007) 1586–1591. http://dx.doi.org/10.1093/molbev/msm08810.1093/molbev/msm088Search in Google Scholar PubMed
[83] Yang, Z. How often do wrong models produce better phylogenies? Mol. Biol. Evol. 14 (1997) 105–108. Search in Google Scholar
[84] Guindon, S. and Gascuel, O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52 (2003) 696–704. http://dx.doi.org/10.1080/1063515039023552010.1080/10635150390235520Search in Google Scholar PubMed
[85] Huelsenbeck, J.P., Ronquist, F.R., Nielsen, R. and Bollback, J.P. Bayesian inference of phylogeny and its impact on evolutionary biology. Science 294 (2001) 2310–2314. http://dx.doi.org/10.1126/science.106588910.1126/science.1065889Search in Google Scholar PubMed
[86] Rannala, B. and Yang, Z. Probability distribution of molecular evolutionary trees: a new method of phylogenetic inference. J. Mol. Evol. 43 (1996) 304–311. http://dx.doi.org/10.1007/BF0233883910.1007/BF02338839Search in Google Scholar PubMed
[87] Larget, B. and Simon, D.L. Markov chain Monet Carlo algorithms for the Bayesian analysis of phylogenetic trees. Mol. Biol. Evol. 16 (1999) 750–759. Search in Google Scholar
[88] Gilks, W.R., Richardson, S. and Spiegelhalter, D.J., Eds. Markov Chain Monte Carlo in Practice. Chapman & Hall, London, 1996. 10.1201/b14835Search in Google Scholar
[89] Hastings, W.K. Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57 (1970) 97–109. http://dx.doi.org/10.1093/biomet/57.1.9710.1093/biomet/57.1.97Search in Google Scholar
[90] Metropolis, N., Rosenbluth, A.W., Teller, A.H. and Teller, E. Equations of state calculations by fast computing machines. J. Chem. Phys. 21 (1953) 1087–1091. http://dx.doi.org/10.1063/1.169911410.1063/1.1699114Search in Google Scholar
[91] Nylander, J.A.A., Wilgenbusch, J.C., Warren, D.L. and Swofford, D.L. AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics. Bioinformatics 24 (2008) 581–583. http://dx.doi.org/10.1093/bioinformatics/btm38810.1093/bioinformatics/btm388Search in Google Scholar PubMed
[92] Goldman, N., Anderson, J.P. and Rodrigo, A.G. Likelihood-based tests of topologies in phylogenetics. Syst. Biol. 49 (2000) 652–670. http://dx.doi.org/10.1080/10635150075004975210.1080/106351500750049752Search in Google Scholar PubMed
[93] Felsenstein, J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39 (1985) 783–791. http://dx.doi.org/10.2307/240867810.2307/2408678Search in Google Scholar
[94] Hedges, S.B. The number of replications needed for accurate estimation of the bootstrap P value in phylogenetic studies. Mol. Biol. Evol. 9 (1992) 366–369. Search in Google Scholar
[95] Zharkikh, A. and Li, W.-H. Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. II. Four taxa without a molecular clock. J. Mol. Evol. 35 (1992) 356–366. http://dx.doi.org/10.1007/BF0016117310.1007/BF00161173Search in Google Scholar PubMed
[96] Hillis, D.M. and Bull, J.J. An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Syst. Biol. 42 (1993) 182–192. Search in Google Scholar
[97] Suzuki, Y., Glazko, G.V. and Nei, M. Overcredibility of molecular phylogenies obtained by Bayesian phylogenetics. Proc. Natl. Acad. Sci. USA 99 (2002) 16138–16143. http://dx.doi.org/10.1073/pnas.21264619910.1073/pnas.212646199Search in Google Scholar PubMed PubMed Central
[98] Huelsenbeck, J.P. and Rannala, B. Frequentist properties of Bayesian posterior probabilities of phylogenetic trees under simple and complex substitution models. Syst. Biol. 53 (2004) 904–913. http://dx.doi.org/10.1080/1063515049052262910.1080/10635150490522629Search in Google Scholar PubMed
[99] Erixon, P., Svennblad, B., Britton, T. and Oxelman, B. Reliability of Bayesian posterior probabilities and bootstrap frequencies in phylogenetics. Syst. Biol. 52 (2003) 665–673. http://dx.doi.org/10.1080/1063515039023548510.1080/10635150390235485Search in Google Scholar PubMed
[100] Alfaro, M.E., Zoller, S. and Lutzoni, F. Bayes or bootstrap? A simulation study comparing the performance of Bayesian Markov chain Monte Carlo sampling and bootstrapping in assessing phylogenetic confidence. Mol. Biol. Evol. 20 (2003) 255–256. http://dx.doi.org/10.1093/molbev/msg02810.1093/molbev/msg028Search in Google Scholar PubMed
[101] Lewis, P.O., Holder, M.T. and Holsinger, K.E. Polytomies and Bayesian phylogenetic inference. Syst. Biol. 54 (2005) 241–253. http://dx.doi.org/10.1080/1063515059092420810.1080/10635150590924208Search in Google Scholar PubMed
[102] Templeton, A.R. Phylogenetic inference from restriction endonuclease cleavage site maps with particular reference to the evolution of human and the apes. Evolution 37 (1983) 221–244. http://dx.doi.org/10.2307/240833210.2307/2408332Search in Google Scholar
[103] Wilks, S.S. The large-sample distribution of the likelihood ratio for testing composite hypotheses. Ann. Math. Statist. 9 (1938) 60–62. http://dx.doi.org/10.1214/aoms/117773236010.1214/aoms/1177732360Search in Google Scholar
[104] Huelsenbeck, J.P., Hillis, D.M. and Jones, R. Parametric bootstrapping in molecular phylogenetics: Applications and performance. in: Molecular Zoology: Advances, Strategies, and Protocols (Ferarris, J.D. and Palumbi, S.R., Eds.), Wiley-Liss, New York, 1996, 19–45. Search in Google Scholar
[105] Goldman, N. Statistical tests of models of DNA substitution. J. Mol. Evol. 36 (1993) 182–198. http://dx.doi.org/10.1007/BF0016625210.1007/BF00166252Search in Google Scholar PubMed
[106] Efron, B. Bootstrap confidence intervals for a class of parametric problems. Biometrika 72 (1985) 45–58. http://dx.doi.org/10.1093/biomet/72.1.4510.1093/biomet/72.1.45Search in Google Scholar
[107] Kishino, H. and Hasegawa, M. Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. J. Mol. Evol. 29 (1989) 170–179. http://dx.doi.org/10.1007/BF0210011510.1007/BF02100115Search in Google Scholar PubMed
[108] Shimodaira, H. and Hasegawa, M. Multiple comparisons of Log-likelihoods with applications to phylogenetic inference. Mol. Biol. Evol. 16 (1999) 1114–1116. Search in Google Scholar
[109] Shimodaira, H. An approximately unbiased test of phylogenetic tree selection. Syst. Biol. 51 (2002) 492–508. http://dx.doi.org/10.1080/1063515029006991310.1080/10635150290069913Search in Google Scholar PubMed
[110] Buckley, T.R. Model misspecification and probabilistic tests of topology: evidence from empirical data sets. Syst. Biol. 51 (2002) 509–523. http://dx.doi.org/10.1080/1063515029006992210.1080/10635150290069922Search in Google Scholar PubMed
[111] Aris-Brosou, S. Least and most powerful tests to elucidate the origin of seed plants in the presence of conflicting signals under misspecified models. Syst. Biol. 52 (2003) 781–793. Search in Google Scholar
[112] Gissi, C., San Mauro, D., Pesole, G. and Zardoya, R. Mitochondrial phylogeny of Anura (Amphibia): A case study of congruent phylogenetic reconstruction using amino acid and nucleotide characters. Gene 366 (2006) 228–237. http://dx.doi.org/10.1016/j.gene.2005.07.03410.1016/j.gene.2005.07.034Search in Google Scholar PubMed
[113] San Mauro, D., Gower, D.J., Oommen, O.V., Wilkinson, M. and Zardoya, R. Phylogeny of caecilian amphibians (Gymnophiona) based on complete mitochondrial genomes and nuclear RAG1. Mol. Phylogenet. Evol. 33 (2004) 413–427. http://dx.doi.org/10.1016/j.ympev.2004.05.01410.1016/j.ympev.2004.05.014Search in Google Scholar PubMed
[114] Strimmer, K. and Rambaut, A. Inferring confidence sets of possible misspecified gene trees. Proc. R. Soc. London B 269 (2001) 137–142. http://dx.doi.org/10.1098/rspb.2001.186210.1098/rspb.2001.1862Search in Google Scholar PubMed PubMed Central
[115] Zuckerkandl, E. and Pauling, L. Evolutionary divergence and convergence in proteins. in: Evolving genes and proteins (Bryson, V. and Vogel, H., Eds.), Academic Press, New York, 1965, 97–166. 10.1016/B978-1-4832-2734-4.50017-6Search in Google Scholar
[116] Li, W.-H. and Graur, D. Fundamentals of Molecular Evolution, Sinauer, Sunderland, MA., 1991. Search in Google Scholar
[117] Nei, M. Molecular evolutionary genetics, Columbia University Press, New York, 1987. 10.7312/nei-92038Search in Google Scholar
[118] Kimura, M. The neutral theory of molecular evolution, Cambridge University Press, Cambridge, 1983. http://dx.doi.org/10.1017/CBO978051162348610.1017/CBO9780511623486Search in Google Scholar
[119] Kimura, M. Evolutionary rate at the molecular level. Nature 217 (1968) 624–626. http://dx.doi.org/10.1038/217624a010.1038/217624a0Search in Google Scholar PubMed
[120] Benton, M.J. and Ayala, F.J. Dating the tree of life. Science 300 (2003) 1698–1700. http://dx.doi.org/10.1126/science.107779510.1126/science.1077795Search in Google Scholar PubMed
[121] Rodríguez-Trelles, F., Tarrío, R. and Ayala, F.J. A methodological bias toward overstimation of molecular evolutionary time scales. Proc. Natl. Acad. Sci. USA 99 (2002) 8112–8115. http://dx.doi.org/10.1073/pnas.12223129910.1073/pnas.122231299Search in Google Scholar PubMed PubMed Central
[122] Bromham, L. and Penny, D. The modern molecular clock. Nat. Rev. Genet. 4 (2003) 216–224. http://dx.doi.org/10.1038/nrg102010.1038/nrg1020Search in Google Scholar PubMed
[123] Wu, C.I. and Li, W.H. Evidence for higher rates of nucleotide substitution in rodents than in man. Proc. Natl. Acad. Sci. USA 82 (1985) 1741–1745. http://dx.doi.org/10.1073/pnas.82.6.174110.1073/pnas.82.6.1741Search in Google Scholar PubMed PubMed Central
[124] Ohta, T. Near-neutrality in evolution of genes and in gene regulation. Proc. Natl. Acad. Sci. USA 99 (2002) 16134–16137. http://dx.doi.org/10.1073/pnas.25262689910.1073/pnas.252626899Search in Google Scholar PubMed PubMed Central
[125] Martin, A.P. and Palumbi, S.R. Body size, metabolic rate, generation time and the molecular clock. Proc. Natl. Acad. Sci. USA 90 (1993) 4087–4091. http://dx.doi.org/10.1073/pnas.90.9.408710.1073/pnas.90.9.4087Search in Google Scholar PubMed PubMed Central
[126] Ota, R. and Penny, D. Estimating changes in mutational mechanisms of evolution. J. Mol. Evol. 57 (2003) S233–S240. http://dx.doi.org/10.1007/s00239-003-0032-110.1007/s00239-003-0032-1Search in Google Scholar PubMed
[127] Welch, J.J. and Bromham, L. Molecular dating when rates vary. Trends Ecol. Evol. 20 (2005) 320–327. http://dx.doi.org/10.1016/j.tree.2005.02.00710.1016/j.tree.2005.02.007Search in Google Scholar PubMed
[128] Ho, S.Y.W. An examination of phylogenetic models of substitution rate variation among lineages. Biol. Lett. 5 (2009) 421–424. http://dx.doi.org/10.1098/rsbl.2008.072910.1098/rsbl.2008.0729Search in Google Scholar PubMed PubMed Central
[129] Douzery, E.J.P., Snell, E.A., Baptese, E., Delsuc, F. and Philippe, H. The timing of eukaryotic evolution: Does a realxed molecular clock reconcile proteins and fossils? Proc. Natl. Acad. Sci. USA 101 (2004) 15386–15391. http://dx.doi.org/10.1073/pnas.040398410110.1073/pnas.0403984101Search in Google Scholar PubMed PubMed Central
[130] Sanderson, M.J. Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Mol. Biol. Evol. 19 (2002) 101–109. 10.1093/oxfordjournals.molbev.a003974Search in Google Scholar PubMed
[131] Sanderson, M.J. A nonparametric approach to estimating divergence times in the absence of rate constancy. Mol. Biol. Evol. 14 (1997) 1218–1231. Search in Google Scholar
[132] Kishino, H., Thorne, J.L. and Bruno, W.J. Performance of a divergence time estimation method under a probabilistic model of rate evolution. Mol. Biol. Evol. 18 (2001) 352–361. Search in Google Scholar
[133] Thorne, J.L., Kishino, H. and Painter, I.S. Estimating the rate of evolution of the rate of molecular evolution. Mol. Biol. Evol. 15 (1998) 1647–1657. Search in Google Scholar
[134] Thorne, J.L. and Kishino, H. Divergence time and evolutionary rate estimation with multilocus data. Syst. Biol. 51 (2002) 689–702. http://dx.doi.org/10.1080/1063515029010245610.1080/10635150290102456Search in Google Scholar PubMed
[135] Drummond, A.J., Ho, S.Y.W., Phillips, M.J. and Rambaut, A. Relaxed phylogenetics and dating with confidence. PLoS Biology 4 (2006) 699–710. http://dx.doi.org/10.1371/journal.pbio.004008810.1371/journal.pbio.0040088Search in Google Scholar PubMed PubMed Central
[136] Drummond, A.J. and Rambaut, A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7 (2007) 214. http://dx.doi.org/10.1186/1471-2148-7-21410.1186/1471-2148-7-214Search in Google Scholar PubMed PubMed Central
[137] Sanderson, M.J. R8S: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock. Bioinformatics 19 (2003) 301–302. http://dx.doi.org/10.1093/bioinformatics/19.2.30110.1093/bioinformatics/19.2.301Search in Google Scholar PubMed
[138] Lepage, T., Bryant, D., Philippe, H. and Lartillot, N. A general comparison of relaxed molecular clock models. Mol. Biol. Evol. 24 (2007) 2669–2680. http://dx.doi.org/10.1093/molbev/msm19310.1093/molbev/msm193Search in Google Scholar PubMed
[139] Donoghue, P.C. and Benton, M.J. Rocks and clocks: calibrating the Tree of Life using fossils and molecules. Trends Ecol. Evol. 22 (2007) 424–431. http://dx.doi.org/10.1016/j.tree.2007.05.00510.1016/j.tree.2007.05.005Search in Google Scholar PubMed
[140] Graur, D. and Martin, W. Reading the entrails of chickens: molecular timescales of evolution and the illusion of precision. Trends Genet. 20 (2004) 80–86. http://dx.doi.org/10.1016/j.tig.2003.12.00310.1016/j.tig.2003.12.003Search in Google Scholar PubMed
[141] Hedges, S.B. and Kumar, S. Precision of molecular time estimates. Trends Genet. 20 (2004) 242–247. http://dx.doi.org/10.1016/j.tig.2004.03.00410.1016/j.tig.2004.03.004Search in Google Scholar PubMed
[142] Ho, S.Y.W. Calibrating molecular estimates of substitution rates and divergence times in birds. J. Avian Biol. 38 (2007) 409–414. Search in Google Scholar
[143] Ho, S.Y.W. and Phillips, M.J. Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times. Syst. Biol. DOI:10.1093/sysbio/syp035 (2009). 10.1093/sysbio/syp035Search in Google Scholar PubMed
[144] Yang, Z. and Rannala, B. Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds. Mol. Biol. Evol. 23 (2006) 212–226. http://dx.doi.org/10.1093/molbev/msj02410.1093/molbev/msj024Search in Google Scholar PubMed
[145] Avise, J.C. Molecular Markers, Natural History and Evolution, Chapman & Hall, New York, 1994. 10.1007/978-1-4615-2381-9Search in Google Scholar
[146] Saiki, R.K., Gelfand, D.H., Stoffel, S., Scharf, S., Higuchi, R., Horn, G.T., Mullis, K.B. and Erlich, H.A. Primer-directed enzymatic amplification of DNA with a thermostable DNA polymerase. Science 239 (1988) 487–491. http://dx.doi.org/10.1126/science.244887510.1126/science.2448875Search in Google Scholar PubMed
[147] Cummings, M.P. and Meyer, A. Magic bullets and golden rules: data sampling in molecular phylogenetics. Zoology 108 (2005) 329–336. http://dx.doi.org/10.1016/j.zool.2005.09.00610.1016/j.zool.2005.09.006Search in Google Scholar PubMed
[148] Rokas, A. and Carroll, S.B. More genes or more taxa? The relative contribution of gene number and taxon number to phylogenetic accuracy. Mol. Biol. Evol. 22 (2005) 1337–1344. http://dx.doi.org/10.1093/molbev/msi12110.1093/molbev/msi121Search in Google Scholar PubMed
[149] Wiens, J.J. Missing data, incomplete taxa, and phylogenetic accuracy. Syst. Biol. 52 (2003) 528–538. http://dx.doi.org/10.1080/1063515039021833010.1080/10635150390218330Search in Google Scholar PubMed
[150] Wiens, J.J. Missing data and the design of phylogenetic analyses. J. Biomed. Inform. 39 (2006) 34–42. http://dx.doi.org/10.1016/j.jbi.2005.04.00110.1016/j.jbi.2005.04.001Search in Google Scholar PubMed
[151] Hillis, D.M. Taxonomic sampling, phylogenetic accuracy, and investigatior bias. Syst. Biol. 47 (1998) 3–8. http://dx.doi.org/10.1080/10635159826098710.1080/106351598260987Search in Google Scholar PubMed
[152] Poe, S. and Swofford, D.L. Taxon sampling revisited. Nature 398 (1999) 299–300. http://dx.doi.org/10.1038/1859210.1038/18592Search in Google Scholar PubMed
[153] Pollock, D.D. and Bruno, W.J. Assessing an unknown evolutionary process: effect of increasing site-specific knowledge through taxon addition. Mol. Biol. Evol. 17 (2000) 1854–1858. Search in Google Scholar
[154] Pollock, D.D., Zwickl, D.J., McGuire, J.A. and Hillis, D.M. Increased taxon sampling is advantageous for phylogenetic inference. Syst. Biol. 51 (2002) 664–671. http://dx.doi.org/10.1080/1063515029010235710.1080/10635150290102357Search in Google Scholar PubMed PubMed Central
[155] Rannala, B., Huelsenbeck, J.P., Yang, Z. and Nielsen, R. Taxon sampling and the accuracy of large phylogenies. Syst. Biol. 47 (1998) 702–710. http://dx.doi.org/10.1080/10635159826068010.1080/106351598260680Search in Google Scholar PubMed
[156] Zwickl, D.J. and Hillis, D.M. Increased taxon sampling greatly reduces phylogenetic error. Syst. Biol. 51 (2002) 588–598. http://dx.doi.org/10.1080/1063515029010233910.1080/10635150290102339Search in Google Scholar PubMed
[157] Kim, J. Large-scale phylogenies and measuring the performance of phylogenetic estimators. Syst. Biol. 47 (1998) 43–60. http://dx.doi.org/10.1080/10635159826102110.1080/106351598261021Search in Google Scholar PubMed
[158] Rosenberg, M.S. and Kumar, S. Incomplete taxon sampling is not a problem for phylogenetic inference. Proc. Natl. Acad. Sci. USA 98 (2001) 10751–10756. http://dx.doi.org/10.1073/pnas.19124849810.1073/pnas.191248498Search in Google Scholar PubMed PubMed Central
[159] Palumbi, S.R., Martin, A., Romano, S., Owen MacMillan, W., Stice, L. and Grabowski, G. The simple fool’s guide to PCR, Department of Zoology, University of Hawaii, Honolulu, 1991. Search in Google Scholar
[160] Kocher, T.D., Thomas, W.K., Meyer, A., Edwards, S.V., Pääbo, S., Villablanca, F.X. and Wilson, A.C. Dynamics of mitochondrial DNA evolution in animals: amplification and sequencing with conserved primers. Proc. Natl. Acad. Sci. USA 86 (1989) 6196–6200. http://dx.doi.org/10.1073/pnas.86.16.619610.1073/pnas.86.16.6196Search in Google Scholar PubMed PubMed Central
[161] Ballard, J.W.O. and Rand, D.M. The population biology of mitochondrial DNA and its phylogenetics implications. Annu. Rev. Ecol. Evol. Syst. 36 (2005) 621–642. http://dx.doi.org/10.1146/annurev.ecolsys.36.091704.17551310.1146/annurev.ecolsys.36.091704.175513Search in Google Scholar
[162] Russo, C.A.M., Takezaki, N. and Nei, M. Efficiencies of different genes and different tree-building methods in recovering a known vertebrate phylogeny. Mol. Biol. Evol. 13 (1996) 525–536. Search in Google Scholar
[163] Zardoya, R. and Meyer, A. Phylogenetic performance of mitochondrial protein-coding genes in resolving relationships among vertebrates. Mol. Biol. Evol. 13 (1996) 933–942. Search in Google Scholar
[164] Delsuc, F., Brinkmann, H. and Philippe, H. Phylogenomics and the reconstruction of the tree of life. Nat. Rev. Genet. 6 (2005) 361–375. http://dx.doi.org/10.1038/nrg160310.1038/nrg1603Search in Google Scholar PubMed
[165] Philippe, H., Delsuc, F., Brinkmann, H. and Lartillot, N. Phylogenomics. Annu. Rev. Ecol. Evol. Syst. 36 (2005) 541–562. http://dx.doi.org/10.1146/annurev.ecolsys.35.112202.13020510.1146/annurev.ecolsys.35.112202.130205Search in Google Scholar
[166] Springer, M.S., DeBry, R.W., Douady, C.J., Amrine, H.M., Madsen, O., deJong, W.W. and Stanhope, M.J. Mitochondrial versus nuclear gene sequences in deep-level mammalian phylogeny reconstruction. Mol. Biol. Evol. 18 (2001) 132–143. Search in Google Scholar
[167] Groth, J.G. and Barrowclough, G.F. Basal divergences in birds and the phylogenetic utility of the nuclear RAG-1 gene. Mol. Phylogenet. Evol. 12 (1999) 115–123. http://dx.doi.org/10.1006/mpev.1998.060310.1006/mpev.1998.0603Search in Google Scholar PubMed
[168] Liolios, K., Tavernarakis, N., Hugenholtz, P. and Kyrpides, N.C. The Genomes On Line Database (GOLD) v.2: a monitor of genome projects worldwide. Nucl. Acids. Res. 34 (2006) D332–D334. http://dx.doi.org/10.1093/nar/gkj14510.1093/nar/gkj145Search in Google Scholar PubMed PubMed Central
[169] AToL initiative. (Assembling the Tree of Life). http://atol.sdsc.edu/. Search in Google Scholar
[170] Boore, J.L. The use of genome-level characters for phylogenetic reconstruction. Trends Ecol. Evol. 21 (2006) 439–446. http://dx.doi.org/10.1016/j.tree.2006.05.00910.1016/j.tree.2006.05.009Search in Google Scholar PubMed
[171] Rannala, B. and Yang, Z. Phylogenetic inference using whole genomes. Annu. Rev. Genomics Hum. Genet. 9 (2008) 217–231. http://dx.doi.org/10.1146/annurev.genom.9.081307.16440710.1146/annurev.genom.9.081307.164407Search in Google Scholar PubMed
[172] Sanderson, M.J., Boss, D., Chen, D., Cranston, K.A. and Wehe, A. The PhyLoTA Browser: processing GenBank for molecular phylogenetics research. Syst. Biol. 57 (2008) 335–346. http://dx.doi.org/10.1080/1063515080215868810.1080/10635150802158688Search in Google Scholar PubMed
[173] Beaumont, M.A. and Rannala, B. The Bayesian revolution in genetics. Nat. Rev. Genet. 5 (2004) 251–261. http://dx.doi.org/10.1038/nrg131810.1038/nrg1318Search in Google Scholar PubMed
[174] Cyberinfrastructure for Phylogenetic Research (CIPRES). Available at http://www.phylo.org/. Search in Google Scholar
[175] Goldman, N. Phylogenetic information and experimental design in molecular systematics. Proc. R. Soc. Lond. B 265 (1998) 1779–1786. http://dx.doi.org/10.1098/rspb.1998.050210.1098/rspb.1998.0502Search in Google Scholar PubMed PubMed Central
[176] Geuten, K., Massingham, T., Darius, P., Smets, E. and Goldman, N. Experimental design criteria in phylogenetics: where to add taxa. Syst. Biol. 56 (2007) 609–622. http://dx.doi.org/10.1080/1063515070149956310.1080/10635150701499563Search in Google Scholar PubMed
[177] San Mauro, D., Gower, D.J., Massingham, T., Wilkinson, M., Zardoya, R. and Cotton, J.A. Experimental design in caecilian systematics: phylogenetic information of mitochondrial genomes and nuclear rag1. Syst. Biol. 58 (2009) 425–438. http://dx.doi.org/10.1093/sysbio/syp04310.1093/sysbio/syp043Search in Google Scholar PubMed
[178] Cotton, J.A. and Page, R.D.M. Tangled trees from molecular markers: reconciling conflict between phylogenies to build molecular supertrees. in: Phylogenetic supertrees: combining information to reveal the Tree of Life (Bininda-Emonds, O.R.P., Ed.), Kluwer Academic, Dordrecht, the Netherlands, 2004, 107–125. Search in Google Scholar
[179] Maddison, W.P. and Knowles, L.L. Inferring phylogeny despite incomplete lineage sorting. Syst. Biol. 55 (2006) 21–30. http://dx.doi.org/10.1080/1063515050035492810.1080/10635150500354928Search in Google Scholar PubMed
[180] de Queiroz, A. and Gatesy, J. The supermatrix approach to systematics. Trends Ecol. Evol. 22 (2007) 34–41. http://dx.doi.org/10.1016/j.tree.2006.10.00210.1016/j.tree.2006.10.002Search in Google Scholar PubMed
[181] Kearney, M. Fragmentary taxa, missing data, and ambiguity: mistaken assumptions and conclusions. Syst. Biol. 51 (2002) 369–381. http://dx.doi.org/10.1080/1063515025289982410.1080/10635150252899824Search in Google Scholar
[182] Campbell, V. and Lapointe, F.-J. The use and validity of composite taxa in phylogenetic analysis. Syst. Biol. 58 (2009) 560–572. http://dx.doi.org/10.1093/sysbio/syp05610.1093/sysbio/syp056Search in Google Scholar
[183] Hartmann, S. and Vision, T.J. Using ESTs for phylogenomics: can one accurately infer a phylogenetic tree from a gappy alignment? BMC Evol. Biol. 8 (2008) 95. http://dx.doi.org/10.1186/1471-2148-8-9510.1186/1471-2148-8-95Search in Google Scholar
[184] Wheeler, W.C. Search-based optimization. Cladistics 19 (2003) 348–355. http://dx.doi.org/10.1111/j.1096-0031.2003.tb00378.x10.1111/j.1096-0031.2003.tb00378.xSearch in Google Scholar
[185] Wheeler, W.C. Homology and the optimization of DNA sequence data. Cladistics 17 (2001) S3–S11. http://dx.doi.org/10.1111/j.1096-0031.2001.tb00100.x10.1111/j.1096-0031.2001.tb00100.xSearch in Google Scholar
[186] Simmons, M.P. Independence of alignment and tree search. Mol. Phylogenet. Evol. 31 (2004) 874–879. http://dx.doi.org/10.1016/j.ympev.2003.10.00810.1016/j.ympev.2003.10.008Search in Google Scholar
[187] Bininda-Emonds, O.R.P. The evolution of supertrees. Trends Ecol. Evol. 19 (2004) 315–322. http://dx.doi.org/10.1016/j.tree.2004.03.01510.1016/j.tree.2004.03.015Search in Google Scholar
[188] Sanderson, M.J., Purvis, A. and Henze, C. Phylogenetic supertrees: assembling the trees of life. Trends Ecol. Evol. 13 (1998) 105–109. http://dx.doi.org/10.1016/S0169-5347(97)01242-110.1016/S0169-5347(97)01242-1Search in Google Scholar
[189] Gatesy, J., Matthee, C., DeSalle, R. and Hayashi, C. Resolution of a supertree/supermatrix paradox. Syst. Biol. 51 (2002) 652–664. http://dx.doi.org/10.1080/1063515029010231110.1080/10635150290102311Search in Google Scholar PubMed
[190] Wilkinson, M., Cotton, J.A., Creevey, C., Eulenstein, O., Harris, S.R., Lapointe, F.-J., Levasseur, C., McInerney, J.O., Pisani, D. and Thorley, J.L. The shape of supertrees to come: tree shape related properties of fourteen supertree methods. Syst. Biol. 54 (2005) 419–431. http://dx.doi.org/10.1080/1063515059094983210.1080/10635150590949832Search in Google Scholar PubMed
[191] Roshan, U., Moret, B.M.E., Williams, T.L. and Warnow, T. Performance of supertree methods on various data set decompositions. in: Phylogenetic supertrees: Combining information to reveal the Tree of Life (Bininda-Emonds, O.R.P., Ed.), Kluwer Academic, Dordrecht, The Netherlands, 2004, 301–328. 10.1007/978-1-4020-2330-9_15Search in Google Scholar
[192] Wilkinson, M. and Cotton, J.A. Supertree methods for building the Tree of Life: Divide-and-conquer approaches to large phylogenetic problems. in: Reconstructing the Tree of Life. Taxonomy and systematics of species rich taxa (Hodkinson, T.R. and Parnell, J.A.N., Eds.), The Systematics Association and CRC Press, London, 2007, 61–75. Search in Google Scholar
[193] Ren, F., Tanaka, H. and Yang, Z. A likelihood look at the supermatrix-supertree controversy. Gene 441 (2009) 119–125. http://dx.doi.org/10.1016/j.gene.2008.04.00210.1016/j.gene.2008.04.002Search in Google Scholar PubMed
[194] Smith, S.A., Beaulieu, J.M. and Donoghue, M.J. Mega-phylogeny approach for comparative biology: an alternative to supertree and supermatrix approaches. BMC Evol. Biol. 9 (2009) 37. http://dx.doi.org/10.1186/1471-2148-9-3710.1186/1471-2148-9-37Search in Google Scholar PubMed PubMed Central
[195] http://evolution.gs.washington.edu/phylip/software.html. Search in Google Scholar
[196] Thompson, J.D., Higgins, D.G. and Gibson, T.J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Res. 22 (1994) 4673–4680. http://dx.doi.org/10.1093/nar/22.22.467310.1093/nar/22.22.4673Search in Google Scholar PubMed PubMed Central
[197] Katoh, K., Kuma, K., Toh, H. and Miyata, T. MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic Acids Res. 33 (2005) 511–518. http://dx.doi.org/10.1093/nar/gki19810.1093/nar/gki198Search in Google Scholar PubMed PubMed Central
[198] Katoh, K., Misawa, K., Kuma, K. and Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30 (2002) 3059–3066. http://dx.doi.org/10.1093/nar/gkf43610.1093/nar/gkf436Search in Google Scholar PubMed PubMed Central
[199] Notredame, C., Higgins, D.G. and Heringa, J. T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 302 (2000) 205–217. http://dx.doi.org/10.1006/jmbi.2000.404210.1006/jmbi.2000.4042Search in Google Scholar PubMed
[200] Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17 (2000) 540–552. Search in Google Scholar
[201] Posada, D. and Crandall, K.A. MODELTEST: testing the model of DNA substitution. Bioinformatics 14 (1998) 817–818. http://dx.doi.org/10.1093/bioinformatics/14.9.81710.1093/bioinformatics/14.9.817Search in Google Scholar PubMed
[202] Posada, D. jModelTest: phylogenetic model averaging. Mol. Biol. Evol. 25 (2008) 1253–1256. http://dx.doi.org/10.1093/molbev/msn08310.1093/molbev/msn083Search in Google Scholar PubMed
[203] Abascal, F., Zardoya, R. and Posada, D. ProtTest: Selection of best-fit models of protein evolution. Bioinformatics 21 (2005) 2104–2105. http://dx.doi.org/10.1093/bioinformatics/bti26310.1093/bioinformatics/bti263Search in Google Scholar PubMed
[204] Felsenstein, J. PHYLIP — Phylogeny inference package (Version 3.2.). Cladistics 5 (1989) 164–166. Search in Google Scholar
[205] Tamura, K., Dudley, J., Nei, M. and Kumar, S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24 (2007) 1596–1599. http://dx.doi.org/10.1093/molbev/msm09210.1093/molbev/msm092Search in Google Scholar PubMed
[206] Zwickl, D.J. (2006) Garli. Available from the author at http://www.bio.utexas.edu/faculty/antisense/garli/Garli.html. Search in Google Scholar
[207] Ronquist, F. and Huelsenbeck, J.P. MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19 (2003) 1572–1574. http://dx.doi.org/10.1093/bioinformatics/btg18010.1093/bioinformatics/btg180Search in Google Scholar PubMed
[208] Huelsenbeck, J.P. and Ronquist, F.R. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17 (2001) 754–755 http://dx.doi.org/10.1093/bioinformatics/17.8.75410.1093/bioinformatics/17.8.754Search in Google Scholar PubMed
[209] Shimodaira, H. and Hasegawa, M. CONSEL: for assessing the confidence of phylogenetic tree selection. Bioinformatics 17 (2001) 1246–1247. http://dx.doi.org/10.1093/bioinformatics/17.12.124610.1093/bioinformatics/17.12.1246Search in Google Scholar PubMed
[210] Maddison, W.P. and Maddison, D.R. MacClade: analysis of phylogeny and character evolution, Sinauer Associates Inc., Sunderland, Massachusetts, USA, 1992. Search in Google Scholar
[211] Maddison, W.P. and Maddison, D.R. (2009) Mesquite: a modular system for evolutionary analysis. Available from the authors at http://mesquiteproject.org. Search in Google Scholar
[212] Yang, Z. PAML: a program package for phylogenetic analysis by maximum likelihood. Comput. Appl. Biosci. 13 (1997) 555–556. Search in Google Scholar
[213] Foster, P.G. (2009) P4. Available from the author at http://www.bmnh.org/~pf/p4.html. Search in Google Scholar
[214] Thorne, J.L. and Kishino, H. (2003) Multidivtime. Available from the authors at http://statgen.ncsu.edu/thorne/multidivtime.html. Search in Google Scholar
[215] Page, R.D.M. TREEVIEW: An application to display phylogenetic trees on personal computers. Comp. Appl. Biosci. 12 (1996) 357–358. Search in Google Scholar
[216] Rambaut, A. (2006) FigTree. Available from the author at http://tree.bio.ed.ac.uk/software/figtree/. Search in Google Scholar
© 2010 University of Wrocław, Poland
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.