Inferring Evolutionary Trees with PAUundefined
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- Abstract
- Table of Contents
- Figures
- Literature Cited
Abstract
This unit provides a general description of reconstructing evolutionary trees using PAUundefined 4.0. The protocol takes users through an example analysis of mitochondrial DNA sequence data using the parsimony and the likelihood criteria to infer optimal trees. The protocol also discusses searching options available in PAUundefined and demonstrates how to import non?NEXUS formats. Finally, a general discussion is given regarding the pros and cons of the ?model?free? and ?model?based? methods used throughout the protocol.
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PDF or HTML at Wiley Online LibraryTable of Contents
- Basic Protocol 1: Using PAUundefined to Infer Parsimony Trees from DNA Sequences
- Alternate Protocol 1: Using PAUundefined to Infer a Maximum‐Likelihood Tree from DNA Sequences
- Support Protocol 1: Using PAUundefined to Import Non‐NEXUS Data Files
- Guidelines for Understanding Results
- Commentary
- Figures
- Tables
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PDF or HTML at Wiley Online LibraryFigures
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Figure 6.4.1 A sample NEXUS data set composed of 4 sequences and 60 nucleotide characters. View Image -
Figure 6.4.2 The Open File dialog box automatically launched when the Windows and Macintosh versions of PAUundefined are first started. View Image -
Figure 6.4.3 The PAUundefined main display after executing the sample data set. View Image -
Figure 6.4.4 The command‐line interface located at the bottom of the Macintosh and Windows main display window. View Image -
Figure 6.4.5 The assumptions block included at the end of the sample data set. The block contains the character and taxa sets and the user‐defined character types that are used in the example analysis. View Image -
Figure 6.4.6 Character‐status summary after several data management operations. View Image -
Figure 6.4.7 A summary of the available options under the heuristic search command and the current default setting of each option. View Image -
Figure 6.4.8 The summary display of the random addition heuristic search. View Image -
Figure 6.4.9 A simple diagram of the tree found by the random addition sequence heuristic search. View Image -
Figure 6.4.10 Phylogram of the single most parsimonious tree. View Image -
Figure 6.4.11 The table of branches and linkages output by the describetrees command. View Image -
Figure 6.4.12 Model parameters estimated on the neighbor‐joining tree under the General Time Reversible model (see Yang, ) with among site rate heterogeneity estimated using the invariable sites plus gamma model (Gu et al., ; Waddell and Penny, ). View Image -
Figure 6.4.13 Model parameters estimated on the neighbor‐joining tree under the General Time Reversible model minus among site rate heterogeneity. View Image -
Figure 6.4.14 Model parameters estimated on the neighbor‐joining tree under the HKY + Γ model plus among the gamma distribute rates. View Image -
Figure 6.4.15 Commands needed to run and in batch mode. Note that each command and its associated options must end with a semicolon. In this way, two commands can occupy a single line, provided that a semicolon separates them. Likewise, one command can span multiple lines provided the last line ends in a semicolon. View Image
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Literature Cited
| Literature Cited | |
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| Hall, B. 2001. Phylogenetic Trees Made Easy: A How‐to Manual for Molecular Biologists. Sinauer Associates,, Sunderland, Mass | |
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| Hendy, M.D. and Penny, D.A. 1989. A framework for the quantitative study of evolutionary trees. Syst. Zool. 38:297‐309. | |
| Hillis, D.M., Bull, J.J., White, M.E., Badgett, M.R., and Molineux, I.J. 1992. Experimental phylogenetics: Generation of a known phylogeny. Science 255:589‐592. | |
| Hillis, D.M., Huelsenbeck, J.P., and Swofford, D.L. 1994a. Hobgoblin of phylogenetics?. Nature 369:363‐364. | |
| Hillis, D.M., Huelsenbeck, J.P., and Cunningham, C.W. 1994b. Application and accuracy of molecular phylogenies. Science 264:671‐677. | |
| Hillis, D.M., Mable, B.K., and Moritz, C. 1996. Applications of molecular systematics: The state of the field and a look to the future. In Molecular Systematics, 2nd ed. (D.M. Hillis, C. Moritz, and B.K. Mable, eds.), pp. 515‐543. Sinauer Associates, Sunderland, Mass. | |
| Huelsenbeck, J.P. and Hillis, D.M. 1993. Success of phylogenetic methods in the four‐taxon case. Syst. Biol. 42:247‐265. | |
| Huelsenbeck, J.P. 1995. Performance of phylogenetic methods in simulation. Syst. Biol. 44:17‐48. | |
| Kim, J. 1996. General inconsistency conditions for maximum parsimony: Effects of branch lengths and increasing numbers of taxa. Syst. Biol. 45:363‐374. | |
| Kishino, H. and Hasegawa, M. 1989. Evolution of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. J. Mol. Evol. 29:170‐179. | |
| Kishino, H., Miyata, T., and Hasegawa, M. 1990. Maximum likelihood inference of protein phylogeny and the origin of chloroplasts. J. Mol. Evol. 30:151‐160. | |
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| Lockhart, P.J., Steel, M.A., Hendy, M.D., and Penny, P. 1994. Recovering evolutionary trees under a more realistic model of sequence evolution. Mol. Biol. Evol. 11:605‐612. | |
| Maddison, D.R., Swofford, D.L., and Maddison, W.P. 1997. NEXUS: An extensible file format for systematic information. Syst. Biol. 46:590‐621. | |
| Page, R.D. and Holmes, E.C. 1998. Molecular Evolution: A Phylogenetic Approach. Blackwell Science, Oxford, U.K.. | |
| Penny, D. and Hendy, M.D. 1985. Testing methods of evolutionary tree construction. Cladistics 1:266‐272. | |
| Posada, D. and Crandall, K.A. 1998. MODELTEST: Testing the model of DNA substitution. Bioinformatics 14:817‐818. | |
| Rogers, J.S. 1997. On the consistency of maximum likelihood estimation of phylogenetic trees from nucleotide sequences. Syst. Biol. 46:354‐357. | |
| Sanderson, M.J. and Kim, J. 2000. Parametric phylogenetics? Syst. Biol. 49:817‐829. | |
| Sankoff, D. 1975. Minimal mutation trees of sequences. SIAM J. Appl. Math. 28:35‐42. | |
| Shimodaira, H. and Hasegawa, M. 1999. Multiple Comparisons of Log‐Likelihoods with Applications to Phylogenetic Inference. Mol. Biol. Evol. 16:1114‐1116. | |
| Steel, M. 1994. Recovering a tree from the Markov leaf colourations it generates under a Markov model. Appl. Math. Lett. 7:19‐23. | |
| Sullivan, J. and Swofford, D.L. 1997. Are guinea pigs rodents? The utility of models in molecular phylogenetics. J. Mamm. Evol. 4:77‐86. | |
| Sullivan, J. and Swofford, D.L. 2001. Should we use model‐based methods for phylogenetic inference when we know assumptions about among‐site rate variation and nucleotide substitution pattern are violated? Syst. Biol. 50:723‐729. | |
| Swofford, D.L. 2002. PAUundefined. Phylogenetic Analysis Using Parsimony ~undefinedand Other Methods). Version 4. Sinauer Associates, Sunderland, Mass. | |
| Swofford, D.L. and Maddison, W.P. 1987. Reconstructing ancestral character states under Wagner parsimony. Math. Biosci. 87:199‐229. | |
| Swofford, D.L., Olsen, G.J., Waddell, P.J., and Hillis, D.M. 1996. Phylogenetic inference. In Molecular systematics, 2nd ed. (D.M. Hillis, C. Moritz, and B.K. Mable, eds.). pp. 407‐514. Sinauer Associates, Sunderland, Mass. | |
| Swofford, D.L., Waddell, P.J., Huelsenbeck, J.P., Foster, P.J., Lewis, P.O., and Rogers, J.S. 2001. Bias in phylogenetic estimation and its relevance to the choice between parsimony and likelihood methods. Syst. Biol. 50:525‐539. | |
| Templeton, A.R. 1983. Convergent evolution and non‐parametric inferences from restriction fragment and DNA sequence data. In Statistical Analysis of DNA Sequence Data. (B. Weir, ed.) pp. 151‐179. Marcel Dekker, New York. | |
| Tuffley, C. and Steel, M. 1997. Links between maximum likelihood and maximum parsimony under a simple model of site substitution. Bull. Math. Biol. 59:581‐607. | |
| Waddell, P.J. and Penny, D. 1996. Evolutionary trees of apes and humans from DNA sequences. In Handbook of symbolic evolution (A.J. Lock and C.R. Peters, eds.) pp. 53‐73. Clarendon Press, Oxford, U.K. | |
| Yang, Z. 1994a. Estimating the pattern of nucleotide substitution. J. Mol. Evol. 39:105‐111. | |
| Yang, Z. 1994b. Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate methods. J. Mol. Evol. 39:306‐314. | |
| Internet Resources | |
| http://paup.csit.fsu.edu/ | |
| PAUundefined Web site. | |
| http://pauptech.csit.fsu.edu/∼paupforum/ | |
| PAUundefined technical forum. | |
| http://mailer.csit.fsu.edu/mailman/listinfo/paupinfo/ | |
| PAUundefined information mailing list. | |
| http://www.sinauer.com/ | |
| PAUundefined publisher, Sinauer Associates, Inc. Web site. | |
| Key References | |
| Hillis et al., 1996. See above. | |
| A general discussion of issues and controversies pertaining to phylogenetic analyses. | |
| Page and Holmes, 1998. See above. | |
| An accessible introduction to phylogenetic theory, terminology, and practice. | |
| Swofford et al., 1996. See above. | |
| A detailed description of most methods commonly used in phylogenetic inference. |
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