Springer Protocols: Abstract: 16. Phylogenetic Model Evaluation

16. Phylogenetic Model Evaluation

By: Lars Sommer Jermiin³, Vivek Jayaswal⁴, Faisal Ababneh⁵, John Robinson⁶

Abstract

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Most phylogenetic methods are model-based and depend on Markov models designed to approximate the evolutionary rates between nucleotides or amino acids. When Markov models are selected for analysis of alignments of these characters, it is assumed that they are close approximations of the evolutionary processes that gave rise to the data. A variety of methods have been developed for estimating the fit of Markov models, and some of these methods are now frequently used for the selection of Markov models. In a growing number of cases, however, it appears that the investigators have used the model-selection methods without acknowledging their inherent shortcomings. This chapter reviews the issue of model selection and model evaluation.

Affiliation(s): (3) School of Biological Sciences, Sydney Bioinformatics and Centre for Mathematical Biology, University of Sydney, Sydney, New South Wales, Australia
(4) School of Mathematics and Statistics, Sydney Bioinformatics and Centre for Mathematical Biology, University of Sydney, Sydney, New South Wales, Australia
(5) Department of Mathematics and Statistics, Al-Hussein Bin Talal University, Ma'an, Jordan
(6) School of Mathematics and Statistics and Centre for Mathematical Biology, University of Sydney, Sydney, New South Wales, Australia

Book Title: Bioinformatics: Data, Sequence Analysis and Evolution

Series: Methods in Molecular Biology | Volume: 452 | Pub. Date: May-01-2008 | Page Range: 331-364 | DOI: 10.1007/978-1-60327-159-2_16

Subject: Bioinformatics

Key Words: Evolutionary processes - Markov models - phylogenetic assumptions - model selection - model evaluation

References

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1.	Zakharov, E. V., Caterino, M. S., Sperling, F. A. H. (2004) Molecular phylogeny, historical biogeography, and divergence time estimates for swallowtail butterflies of the genus Papilio (Lepidoptera: Papilionidae). Syst Biol 53, 193–215.

2.	Brochier, C., Forterre, P., Gribaldo, S. (2005) An emerging phylogenetic core of Archaea: phylogenies of transcription and translation machineries converge following addition of new genome sequences. BMC Evol Biol 5, 36.

3.	Hardy, M. P., Owczarek, C. M., Jermiin, L. S., et al. (2004) Characterization of the type I interferon locus and identification of novel genes. Genomics 84, 331–345.

4.	de Queiroz, K., Gauthier, J. (1994) Toward a phylogenetic system of biological nomenclature. Trends Ecol Evol 9, 27–31.

5.	Board, P. G., Coggan, M., Chelnavayagam, G., et al. (2000) Identification, characterization and crystal structure of the Omega class of glutathione transferases. J Biol Chem 275, 24798–24806.

6.	Pagel, M. (1999) Inferring the historical patterns of biological evolution. Nature 401, 877–884.

7.	Charleston, M. A., Robertson, D. L. (2002) Preferential host switching by primate lentiviruses can account for phylogenetic similarity with the primate phylogeny. Syst Biol 51, 528–535.

8.	Jermann, T. M., Opitz, J. G., Stackhouse, J., et al. (1995) Reconstructing the evolutionary history of the artiodactyl ribonuclease superfamily. Nature 374, 57–59.

9.	Posada, D., Crandall, K. A. (1998) MOD-ELTEST: testing the model of DNA substitution. Bioinformatics 14, 817–818.

10.	Abascal, F., Zardoya, R., Posada, D. (2005) ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21, 2104–2105.

11.	Weisburg, W. G., Giovannoni, S. J., Woese, C. R. (1989) The Deinococcus and Thermus phylum and the effect of ribosomal RNA composition on phylogenetic tree construction. Syst Appl Microbiol 11, 128–134.

12.	Loomis, W. F., Smith, D. W. (1990) Molecular phylogeny of Dictyostelium discoideum by protein sequence comparison. Proc Natl Acad Sci USA 87, 9093–9097.

13.	Penny, D., Hendy, M. D., Zimmer, E. A., et al. (1990) Trees from sequences: panacea or Pandora's box? Aust Syst Biol 3, 21–38.

14.	Lockhart, P. J., Howe, C. J., Bryant, D. A., et al. (1992) Substitutional bias confounds inference of cyanelle origins from sequence data. J Mol Evol 34, 153–162.

15.	Lockhart, P. J., Penny, D., Hendy, M. D., et al. (1992) Controversy on chloroplast origins. FEBS Lett 301, 127–131.

16.	Hasegawa, M., Hashimoto, T. (1993) Ribosomal RNA trees misleading? Nature 361, 23.

17.	Olsen, G. J., Woese, C. R. (1993) Ribos-omal RNA: a key to phylogeny. FASEB J 7, 113–123.

18.	Sogin, M. L., Hinkle, G., Leipe, D. D. (1993) Universal tree of life. Nature 362, 795.

19.	Klenk, H. P., Palm, P., Zillig, W. (1994) DNA-dependent RNA polymerases as phylogenetic marker molecules. Syst Appl Microbiol 16, 638–647.

20.	Foster, P. G., Jermiin, L. S., Hickey, D. A. (1997) Nucleotide composition bias affects amino acid content in proteins coded by animal mitochondria. J Mol Evol 44, 282–288.

21.	van den Bussche, R. A., Baker, R. J., Huelsenbeck, J. P., et al. (1998) Base compositional bias and phylogenetic analyses: a test of the “flying DNA” hypothesis. Mol Phylogenet Evol 10, 408–416.

22.	Foster, P. G., Hickey, D. A. (1999) Compositional bias may affect both DNA-based and protein-based phylogenetic reconstructions. J Mol Evol 48, 284–290.

23.	Chang, B. S. W., Campbell, D. L. (2000) Bias in phylogenetic reconstruction of vertebrate rhodopsin sequences. Mol Biol Evol 17, 1220–1231.

24.	Conant, G. C., Lewis, P. O. (2001) Effects of nucleotide composition bias on the success of the parsimony criterion on phylogenetic inference. Mol Biol Evol 18, 1024–1033.

25.	Tarrío, R., Rodriguez-Trelles, F., Ayala, F. J. (2001) Shared nucleotide composition biases among species and their impact on phylogenetic reconstructions of the Drosophilidae. Mol Biol Evol 18, 1464–1473.

26.	Goremykin, V. V., Hellwig, F. H. (2005) Evidence for the most basal split in land plants dividing bryophyte and tracheophyte lineages. Plant Syst Evol 254, 93–103.

27.	Barry, D., Hartigan, J. A. (1987) Statistical analysis of hominoid molecular evolution. Stat Sci 2, 191–210.

28.	Reeves, J. (1992) Heterogeneity in the substitution process of amino acid sites of proteins coded for by the mitochondrial DNA. J Mol Evol 35, 17–31.

29.	Steel, M. A., Lockhart, P. J., Penny, D. (1993) Confidence in evolutionary trees from biological sequence data. Nature 364, 440–442.

30.	Lake, J. A. (1994) Reconstructing evolutionary trees from DNA and protein sequences: paralinear distances. Proc Natl Acad Sci USA 91, 1455–1459.

31.	Lockhart, P. J., Steel, M. A., Hendy, M. D., et al. (1994) Recovering evolutionary trees under a more realistic model of sequence evolution. Mol Biol Evol 11, 605–612.

32.	Steel, M. A. (1994) Recovering a tree from the leaf colourations it generates under a Markov model. Appl Math Lett 7, 19–23.

33.	Galtier, N., Gouy, M. (1995) Inferring phylogenies from DNA sequences of unequal base compositions. Proc Natl Acad Sci USA 92, 11317–11321.

34.	Steel, M. A., Lockhart, P. J., Penny, D. (1995) A frequency-dependent significance test for parsimony. Mol Phylogenet Evol 4, 64–71.

35.	Yang, Z., Roberts, D. (1995) On the use of nucleic acid sequences to infer early branches in the tree of life. Mol Biol Evol 12, 451–458.

36.	Gu, X., Li, W.-H. (1996) Bias-corrected paralinear and logdet distances and tests of molecular clocks and phylogenies under nonstationary nucleotide frequencies. Mol Biol Evol 13, 1375–1383.

37.	Gu, X., Li, W.-H. (1998) Estimation of evolutionary distances under stationary and non-stationary models of nucleotide substitution. Proc Natl Acad Sci USA 95, 5899–5905.

38.	Galtier, N., Gouy, M. (1998) Inferring pattern and process: maximum-likelihood implementation of a nonhomogenous model of DNA sequence evolution for phylogenetic analysis. Mol Biol Evol 15, 871–879.

39.	Galtier, N., Tourasse, N., Gouy, M. (1999) A nonhyperthermophilic common ancestor to extant life forms. Science 283, 220–221.

40.	Tamura, K., Kumar, S. (2002) Evolutionary distance estimation under heterogeneous substitution pattern among lineages. Mol Biol Evol 19, 1727–1736.

41.	Foster, P. G. (2004) Modeling compositional heterogeneity. Syst Biol 53, 485–495.

42.	Thollesson, M. (2004) LDDist: a Perl module for calculating LogDet pair-wise distances for protein and nucleotide sequences. Bioinformatics 20, 416–418.

43.	Jayaswal, V., Jermiin, L. S., Robinson, J. (2005) Estimation of phylogeny using a general Markov model. Evol Bioinf Online 1, 62–80.

44.	Jayaswal, V., Robinson, J., Jermiin, L. S. (2007) Estimation of phylogeny and invariant sites under the General Markov model of nucleotide sequence evolution. Syst Biol, 56, 155–162.

45.	Sullivan, J., Arellano, E. A., Rogers, D. S. (2000) Comparative phylogeography of Mesoamerican highland rodents: concerted versus independent responses to past climatic fluctuations. Am Nat 155, 755–768.

46.	Demboski, J. R., Sullivan, J. (2003) Extensive mtDNA variation within the yellow-pine chipmunk, Tamias amoenus (Rodentia: Sciuridae), and phylogeographic inferences for northwestern North America. Mol Phylogenet Evol 26, 389–408.

47.	Carstens, B. C., Stevenson, A. L., Degen-hardt, J. D., et al. (2004) Testing nested phylogenetic and phylogeographic hypotheses in the Plethodon vandykei species group. Syst Biol 53, 781–792.

48.	Tavaré, S. (1986) Some probabilistic and statistical problems on the analysis of DNA sequences. Lect Math Life Sci 17, 57–86.

49.	Ababneh, F., Jermiin, L. S., Robinson, J. (2006) Generation of the exact distribution and simulation of matched nucleotide sequences on a phylogenetic tree. J Math Model Algor 5, 291–308.

50.	Bryant, D., Galtier, N., Poursat, M.-A. (2005) Likelihood calculation in molecular phylogenetics, in (Gascuel, O., ed.), Mathematics in Evolution and Phylogeny. Oxford University Press, Oxford, UK, pp. 33–62.

51.	Penny, D., Hendy, M. D., Steel, M. A. (1992) Progress with methods for constructing evolutionary trees. Trends Ecol Evol 7, 73–79.

52.	Drouin, G., Prat, F., Ell, M., et al. (1999) Detecting and characterizing gene conversion between multigene family members. Mol Biol Evol 16, 1369–1390.

53.	Posada, D., Crandall, K. A. (2001) Evaluation of methods for detecting recombination from DNA sequences: computer simulations. Proc Natl Acad Sci USA 98, 13757–13762.

54.	Posada, D. (2002) Evaluation of methods for detecting recombination from DNA sequences: empirical data. Mol Biol Evol 19, 708–717.

55.	Martin, D. P., Williamson, C., Posada, D. (2005) RDP2: Recombination detection and analysis from sequence alignments. Bioinformatics 21, 260–262.

56.	Bruen, T. C., Philippe, H., Bryant, D. (2006) A simple and robust statistical test for detecting the presence of recombination. Genetics 172, 2665–2681.

57.	Ragan, M. A. (2001) On surrogate methods for detecting lateral gene transfer. FEMS Microbiol Lett 201, 187–191.

58.	Dufraigne, C., Fertil, B., Lespinats, S., et al. (2005) Detection and characterization of horizontal transfers in prokaryotes using genomic signature. Nucl Acid Res 33, e6.

59.	Azad, R. K., Lawrence, J. G. (2005) Use of artificial genomes in assessing methods for atypical gene detection. PLoS Comp Biol 1, 461–473.

60.	Tsirigos, A., Rigoutsos, I. (2005) A new computational method for the detection of horizontal gene transfer events. Nucl Acid Res 33, 922–933.

61.	Ragan, M. A., Harlow, T. J., Beiko, R. G. (2006) Do different surrogate methods detect lateral genetic transfer events of different relative ages? Trends Microbiol 14, 4–8.

62.	Beiko, R. G., Hamilton, N. (2006) Phyloge-netic identification of lateral genetic transfer events. BMC Evol Biol 6, 15.

63.	Fitch, W. M. (1986) An estimation of the number of invariable sites is necessary for the accurate estimation of the number of nucleotide substitutions since a common ancestor. Prog Clin Biol Res 218, 149–159.

64.	Lockhart, P. J., Larkum, A. W. D., Steel, M. A., et al. (1996) Evolution of chlorophyll and bacteriochlorophyll: the problem of invariant sites in sequence analysis. Proc Natl Acad Sci USA 93, 1930–1934.

65.	Yang, Z. (1996) Among-site rate variation and its impact on phylogenetic analysis. Trends Ecol Evol 11, 367–372.

66.	Waddell, P. J., Steel, M. A. (1997) General time reversible distances with unequal rates across sites: mixing Г and inverse Gaussian distributions with invariant sites. Mol Phylogenet Evol 8, 398–414.

67.	Gowri-Shankar, V., Rattray, M. (2006) Compositional heterogeneity across sites: Effects on phylogenetic inference and modeling the correlations between base frequencies and substitution rate. Mol Biol Evol 23, 352–364.

68.	Schöniger, M., von Haeseler, A. (1994) A stochastic model for the evolution of auto-correlated DNA sequences. Mol Phylogenet Evol 3, 240–247.

69.	Tillier, E. R. M. (1994) Maximum likelihood with multiparameter models of substitution. J Mol Evol 39, 409–417.

70.	Hein, J., Støvlbœk, J. (1995) A maximum-likelihood approach to analyzing nonover-lapping and overlapping reading frames. J Mol Evol 40, 181–190.

71.	Muse, S. V. (1995) Evolutionary analyses of DNA sequences subject to constraints on secondary structure. Genetics 139, 1429–1439.

72.	Rzhetsky, A. (1995) Estimating substitution rates in ribosomal RNA genes. Genetics 141, 771–783.

73.	Tillier, E. R. M., Collins, R. A. (1995) Neighbor joining and maximum likelihood with RNA sequences: addressing the interdependence of sites. Mol Biol Evol 12, 7–15.

74.	Pedersen, A.-M. K., Wiuf, C., Christiansen, F. B. (1998) A codon-based model designed to describe lentiviral evolution. Mol Biol Evol 15, 1069–1081.

75.	Tillier, E. R. M., Collins, R. A. (1998) High apparent rate of simultaneous compensatory base-pair substitutions in ribosomal RNA. Genetics 148, 1993–2002.

76.	Higgs, P. G. (2000) RNA secondary structure: physical and computational aspects. Q Rev Biophys 30, 199–253.

77.	Pedersen, A.-M. K., Jensen, J. L. (2001) A dependent-rates model and an MCMC-based methodology for the maximum-likelihood analysis of sequences with overlapping frames. Mol Biol Evol 18, 763–776.

78.	Savill, N. J., Hoyle, D. C., Higgs, P. G. (2001) RNA sequence evolution with secondary structure constraints: comparison of substitution rate models using maximum-likelihood methods. Genetics 157, 339–411.

79.	Jow, H., Hudelot, C., Rattray, M., et al. (2002) Bayesian phylogenerics using an RNA substitution model applied to early mammalian evolution. Mol Biol Evol 19, 1591–1601.

80.	Lockhart, P. J., Steel, M. A., Barbrook, A. C., et al. (1998) A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages. Mol Biol Evol 15, 1183–1188.

81.	Jukes, T. H., Cantor, C. R. (1969) Evolution of protein molecules, in (Munro, H. N., ed.), Mammalian Protein Metabolism. Academic Press, New York.

82.	Lanave, C., Preparata, G., Saccone, C., et al. (1984) A new method for calculating evolutionary substitution rates. J Mol Evol 20, 86–93.

83.	Naylor, G. P. J., Brown, W. M. (1998) Amphioxus mitochondrial DNA, chordate phylogeny, and the limits of inference based on comparisons of sequences. Syst Biol 47, 61–76.

84.	Ho, S. Y. W., Jermiin, L. S. (2004) Tracing the decay of the historical signal in biological sequence data. Syst Biol 53, 623–637.

85.	Jermiin, L. S., Ho, S. Y. W., Ababneh, F., et al. (2004) The biasing effect of compositional heterogeneity on phylogenetic estimates may be underestimated. Syst Biol 53, 638–643.

86.	Ababneh, F., Jermiin, L. S., Ma, C., et al. (2006) Matched-pairs tests of homogeneity with applications to homologous nucleotide sequences. Bioinformatics 22, 1225–1231.

87.	Ho, J. W. K., Adams, C. E., Lew, J. B., et al. (2006) SeqVis: Visualization of compositional heterogeneity in large alignments of nucleotides. Bioinformatics 22, 2162–2163.

88.	Lanave, C., Pesole, G. (1993) Stationary MARKOV processes in the evolution of biological macromolecules. Binary 5, 191–195.

89.	Rzhetsky, A., Nei, M. (1995) Tests of applicability of several substitution models for DNA sequence data. Mol Biol Evol 12, 131–151.

90.	Waddell, P. J., Cao, Y., Hauf, J., et al. (1999) Using novel phylogenetic methods to evaluate mammalian mtDNA, including amino acid-invariant sites-LogDet plus site stripping, to detect internal conflicts in the data, with special reference to the positions of hedgehog, armadillo, and elephant. Syst Biol 48, 31–53.

91.	Bowker, A. H. (1948) A test for symmetry in contingency tables. J Am Stat Assoc 43, 572–574.

92.	Stuart, A. (1955) A test for homogeneity of the marginal distributions in a two-way classification. Biometrika 42, 412–416.

93.	Jermiin, L. S., Ho, S. Y. W., Ababneh, F., et al. (2003) Hetero: a program to simulate the evolution of DNA on a four-taxon tree. Appl Bioinf 2, 159–163.

94.	Muse, S. V., Weir, B. S. (1992) Testing for equality of evolutionary rates. Genetics 132, 269–276.

95.	Cannings, C., Edwards, A. W. F. (1968) Natural selection and the de Finetti diagram. Ann Hum Genet 31, 421–428.

96.	Huelsenbeck, J. P., Rannala, B. (1997) Phylogenetic methods come of age: Testing hypotheses in an evolutionary context. Science 276, 227–232.

97.	Whelan, S., Goldman, N. (1999) Distributions of statistics used for the comparison of models of sequence evolution in phylogenetics. Mol Biol Evol 16, 11292–11299.

98.	Goldman, N., Whelan, S. (2000) Statistical tests of gamma-distributed rate heterogeneity in models of sequence evolution in phylogenetics. Mol Biol Evol 17, 975–978.

99.	Goldman, N. (1993) Statistical tests of models of DNA substitution. J Mol Evol 36, 182–198.

100.	Telford, M. J., Wise, M. J., Gowri-Shankar, V. (2005) Consideration of RNA secondary structure significantly improves likelihood-based estimates of phylogeny: examples from the bilateria. Mol Biol Evol 22, 1129–1136.

101.	Goldman, N., Yang, Z. (1994) A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol Biol Evol 11, 725–736.

102.	Muse, S. V., Gaut, B. S. (1994) A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome. Mol Biol Evol 11, 715–724.

103.	Dayhoff, M. O., Schwartz, R. M., Orcutt, B. C. (eds.) (1978) A Model of Evolutionary Change in Proteins. National Biomedical Research Foundation, National Biomedical Research Foundation, Washington, DC.

104.	Jones, D. T., Taylor, W. R., Thornton, J. M. (1992) The rapid generation of mutation data matrices from protein sequences. Comp Appl Biosci 8, 275–282.

105.	Henikoff, S., Henikoff, J. G. (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci USA 89, 10915–10919.