Introduction to Inferring Evolutionary Relationships
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- Abstract
- Table of Contents
- Figures
- Literature Cited
Abstract
This unit provides a general introduction to phylogeny. It defines common terms and discusses the issue of rooting trees, in addition to comparing gene and species trees. Methods for inferring phylogenies, such as distance methods, parsimony methods, and maximum likelihood are also presented. The unit concludes with discussion of how to assess tree confidence.
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- Introduction to Trees
- Methods for Inferring Phylogenies
- Confidence
- What Method is Best?
- Literature Cited
- Figures
- Tables
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Figure 6.1.1 A phylogeny showing some basic tree terms. View Image -
Figure 6.1.2 Unrooted and rooted trees for human, mouse, fugu and Drosophila . The rooted tree (bottom) is obtained by rooting the unrooted tree along the edge leading to Drosophila . View Image -
Figure 6.1.3 The five rooted trees that can be derived from an unrooted tree for four sequences. Each of the rooted trees 1 to 5 corresponds to placing the root on the corresponding numbered edge of the unrooted tree. View Image -
Figure 6.1.4 Three different methods of rooting an unrooted tree. Outgroup rooting places the root between the outgroup (in this example Drosophila ) and the ingroup (fugu, mouse, human). Midpoint rooting places the root at the midpoint of the longest path in the tree. Gene duplication rooting places the root between paralogous gene copies. View Image -
Figure 6.1.5 Phylogeny for the fugu, mouse, and humans, and six genes (1 to 6) that stem from a gene duplication resulting in two paralogous sets of genes, α and β. The α genes 1 to 3 are orthologous with each other, as are the β genes 4 to 6. However, each α gene is paralogous with each β gene, as they are separated by a gene duplication event, not a speciation event. View Image -
Figure 6.1.6 An additive distance matrix between four sequences and the corresponding additive tree. For any two sequences, the value in the distance matrix corresponds to the sum of the edge lengths along the path between the two sequences on the tree (after figure 2.18 in Page and Holmes, ). View Image -
Figure 6.1.7 A set of four DNA sequences and the corresponding distance matrix. A parsimony tree and a distance tree for the same sequence data are shown. Note that both trees have the same topology and branch lengths, but that the parsimony tree identifies which site (numbered 1 to 7) contributes to the length of each branch (after figure 6.1 in Page and Holmes, ) View Image -
Figure 6.1.8 The three possible unrooted trees for four sequences. For each tree, the number of events that each of the ten nucleotide sites requires to evolve on that tree is scored. The evolution of site 2 is reconstructed on each tree. Trees 1 and 2 require a minimum of two nucleotide substitutions, but tree 3 can explain by a single substitution the sharing of A by Drosophila and fugu and G by mouse and human. Those sites marked with an asterisk ~undefined) are parsimony‐informative, i.e., they discriminate between the three trees. The remaining sites have the same score for each tree and hence are uninformative (modified from Stewart, ). View Image
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Literature Cited
| Akmaev, V.R., Kelley, S.T., and Stormo, G.D. 2000. Phylogenetically enhanced statistical tools for RNA structure prediction. Bioinformatics 16:501‐512. | |
| Bafna, V., Hannenhalli, S., Rice, K., and Vawter, L. 2000. Ligand‐receptor pairing via tree comparison. J. Comput. Biol. 7:59‐70. | |
| Duret, L., Mouchiroud, D., and Gouy, M. 1994. HOVERGEN: A database of homologous vertebrate genes. Nucleic Acids Res. 22:2360‐2365. | |
| Eisen, J. 1998. Phylogenomics: Improving functional predictions for uncharacterized genes. Genome Res. 8:163‐167. | |
| Farris, J.S., Albert, V.A., Källersjö, M., Lipscomb, D., and Kluge, A.G. 1996. Parsimony jackknifing outperforms neighbor‐joining. Cladistics 12:99‐124. | |
| Felsenstein, J. 1978. Cases in which parsimony and compatibility methods will be positively misleading. Syst. Zool. 27:401‐410. | |
| Felsenstein, J. 1985. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39:783‐791. | |
| Felsenstein, J. and Kishino, H. 1993. Is there something wrong with the bootstrap on phylogenies? A reply to Hillis and Bull. Syst. Biol. 42:193‐200. | |
| Fitch, W.M. 1970. Distinguishing homologous from analogous proteins. Syst. Zool. 19:99‐113. | |
| Gulko, B. and Haussler, D. 1996. Using multiple alignments and phylogenetic trees to detect RNA secondary structure. In Biocomputing: Proceedings of the 1996 Pacific Symposium (L. Hunter and T. Klein, eds.) World Scientific Press. Singapore. | |
| Hall, B.G. 2001. Phylogenetic Trees Made Easy: A How‐to Manual for Molecular Biology. Sinauer Associates, Sunderland, Mass. | |
| Harvey, P.H. and Pagel, M.D. 1991. The Comparative Method in Evolutionary Biology. Oxford University Press. Oxford. | |
| Hein, J. 1990. Unified approach to alignment and phylogenies. Methods Enzymol. 183:626‐645. | |
| Hillis, D.M. and Bull, J.J. 1993. An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Syst. Biol. 42:182‐92. | |
| Huelsenbeck, J.P. and Hillis, D.M. 1993. Success of phylogenetic methods in the four‐taxon case. Syst. Biol. 42:247‐264. | |
| Huelsenbeck, J.P. and Rannala, B. 1997. Phylogenetic methods come of age: Testing hypotheses in an evolutionary context. Science 276:227‐232. | |
| Huelsenbeck, J.P. and Ronquist, F. 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17:754‐755. | |
| Huelsenbeck, J.P., Ronquist, F., Nielsen, R., and Bollback, J.P. 2001. Bayesian inference of phylogeny and its impact on evolutionary biology. Science 294:2310‐2314. | |
| Iwabe, N., Kuma, K.I., Hasegawa, M., Osawa, S., and Miyata, T. 1989. Evolutionary relationship of archaebacteria, eubacteria, and eukaryotes inferred from phylogenetic trees of duplicated genes. Proc. Natl. Acad. Sci. U.S.A. 86:9355‐9359. | |
| Kim, J. 1993. Improving the accuracy of phylogenetic estimation by combining different methods. Syst. Biol. 42:331‐340. | |
| Kim, J. and Salisbury, B.A. 2001. A tree obscured by vines: Horizontal gene transfer and the median tree method of estimating species phylogeny. Pac. Symp. Biocomput. 6:571‐582. | |
| Knudsen, B. and Hein, J. 1999. RNA secondary structure prediction using stochastic context‐free grammars and evolutionary history. Bioinformatics 15:446‐454. | |
| Korbel, J.O., Snel, B., Huynen, M.A., and Bork, P. 2002. SHOT: A Web server for the construction of genome phylogenies. Trends Genet. 18:158‐162. | |
| Krause, A., Stoye, J., and Vingron, M. 2000. The SYSTERS protein sequence cluster set. Nucleic Acids Res. 28:270‐272. | |
| Li, P., Goldman, N., Thorne, J.L., and Jones, D.T. 1998. PASSML: Combining evolutionary inference and protein secondary structure prediction. Bioinformatics 14:726‐733. | |
| Page, R.D.M. and Charleston, M.A. 1997. From gene to organismal phylogeny: Reconciled trees and the gene tree/species tree problem. Mol. Phylog. Evol. 28:231‐240. | |
| Page, R.D.M. and Charleston, M.A. 1998. Trees within trees: Phylogeny and historical associations. Trends Ecol. Evol. 13:356‐359. | |
| Page, R.D.M. and Holmes, E.C. 1998. Molecular Evolution: A Phylogenetic Approach. Blackwell Science, Oxford, U.K. | |
| Phillips, A., Janies, D., and Wheeler, W. 2000. Multiple sequence alignment in phylogenetics. Mol. Phylog. Evol. 17:317‐330. | |
| Rehmsmeier, M. and Vingron, M. 2001. Phylogenetic information improves homology detection. Proteins 45:360‐371. | |
| Steel, M. and Penny, D. 2000. Parsimony, likelihood, and the role of models in molecular phylogenetics. Mol. Biol. Evol. 17:839‐850. | |
| Stewart, C.‐B. 1993. The powers and pitfalls of parsimony. Nature 361:603‐607. | |
| Storm, C.E.V. and Sonnhammer, E.L.L. 2001. Automated ortholog inference from phylogenetic trees and calculation of orthology reliability. Bioinformatics 18:92‐99. | |
| Swofford, D.L., Olsen, G.J., Waddell, P.J., and Hillis, D.M. 1996. Phylogenetic inference. In Molecular Systematics (D.M. Hillis, C. Moritz, and B.K. Mable, eds.) pp. 407‐514. Sinauer Associates, Sunderland, Mass. | |
| Wang, L.‐S., Jansen, R.K., Moret, B.M.E., Raubeson, L.A., and Warnow, T. 2002. Fast phylogenetic methods for the analysis of genome rearrangement data: An empirical study. In Pacific Symposium on Biocomputing 2002 (R.B. Altman, A.K. Dunker, L. Hunter, K. Lauderdale and T.E. Klein, eds.), pp. 524‐535. World Scientific Publishing. Singapore. | |
| Yuan, Y.P., Eulenstein, O., Vingron, M., and Bork, P. 1998. Towards detection of orthologs in sequence databases. Bioinformatics 14:285‐289. | |
| Zmasek, C.M. and Eddy, S.R. 2001. A simple algorithm to infer gene duplication and speciation events on a gene tree. Bioinformatics 17:821‐828. | |
| Zmasek, C.M. and Eddy, S.R. 2002. RIO: Analyzing proteomes by automated phylogenomics using resampled inference of orthologs. BMC Bioinformatics 3:14. | |
| Key References | |
| Page and Holmes, 1998. See above. | |
| An introduction to molecular evolution and phylogenetic analysis. | |
| Sanderson, M.J. and Shaffer, H.B. 2002. Troubleshooting molecular phylogenetic analyses. Annu. R. Ecol. Syst. 33:49‐72. | |
| Excellent overview of the problems encountered when building phylogenies, with helpful suggestions for what (if anything) can be done. | |
| Hall, 2001. See above. | |
| A nicely written how‐to manual describing how to build trees using Clustal, PAUundefined, and MrBayes, among other programs. | |
| Swofford et al., 1996. See above. | |
| Detailed review of phylogenetic methods. | |
| Internet Resources | |
| http://evolution.genetics.washington.edu/phylip/software.html | |
| Joe Felsenstein's list of phylogeny programs. | |
| http://www.bioinf.org/molsys/ | |
| Online molecular systematics and evolution course run by The Natural History Museum, London, and the National University of Ireland, Maynooth. |
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