Journal of Molecular Evolution

, Volume 18, Issue 6, pp 387–404

Accuracy of estimated phylogenetic trees from molecular data

I. Distantly Related Species
  • Yoshio Tateno
  • Masatoshi Nei
  • Fumio Tajima


The accuracies and efficiencies of four different methods for constructing phylogenetic trees from molecular data were examined by using computer simulation. The methods examined are UPGMA, Fitch and Margoliash's (1967) (F/M) method, Farris' (1972) method, and the modified Farris method (Tateno, Nei, and Tajima, this paper). In the computer simulation, eight OTUs (32 OTUs in one case) were assumed to evolve according to a given model tree, and the evolutionary change of a sequence of 300 nucleotides was followed. The nucleotide substitution in this sequence was assumed to occur following the Poisson distribution, negative binomial distribution or a model of temporally varying rate. Estimates of nucleotide substitutions (genetic distances) were then computed for all pairs of the nucleotide sequences that were generated at the end of the evolution considered, and from these estimates a phylogenetic tree was reconstructed and compared with the true model tree. The results of this comparison indicate that when the coefficient of variation of branch length is large the Farris and modified Farris methods tend to be better than UPGMA and the F/M method for obtaining a good topology. For estimating the number of nucleotide substitutions for each branch of the tree, however, the modified Farris method shows a better performance than the Farris method. When the coefficient of variation of branch length is small, however, UPGMA shows the best performance among the four methods examined. Nevertheless, any tree-making method is likely to make errors in obtaining the correct topology with a high probability, unless all branch lengths of the true tree are sufficiently long. It is also shown that the agreement between patristic and observed genetic distances is not a good indicator of the goodness of the tree obtained.

Key words

Nucleotide substitution Genetic distance Species tree Gene tree UPGMA Fitch/Margoliash method Farris method Modified Farris method 


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  1. Cavalli-Sforza LL, Edwards AWF (1967) Phylogenetic analysis: models and estimation procedures. Am J Hum Gen 19:233–257Google Scholar
  2. Chakraborty R (1977) Estimation of time of divergence from phylogenetic studies. Can J Genet Cytol 19:217–223Google Scholar
  3. Dayhoff MO (ed) (1969) Atlas of protein sequence and structure, Vol. 4. Natl Biomed Res Found, Silver Spring, MDGoogle Scholar
  4. Doolittle RF, Blombäck B (1964) Amino-acid sequence investigations of fibrinopeptides from various mammals: evolutionary implications. Nature 202:147–152Google Scholar
  5. Edwards AWF, Cavalli-Sforza LL (1965) A method for cluster analysis. Biometrics 21:362–375Google Scholar
  6. Farris JS (1972) Estimating phylogenetic trees from distance matrices. Am Nat 106:645–668Google Scholar
  7. Farris JS (1979) On the naturalness of phylogenetic classification. Syst Zool 28:200–214Google Scholar
  8. Farris JS, Kluge AG, Mickevich MF (1979) Paraphyly of theRana boylii species group. Syst Zool 28:627–634Google Scholar
  9. Fitch WM, Margoliash E (1967) Construction of phylogenetic trees. Science 155:279–284Google Scholar
  10. Goodman M, Moore GW, Barnabas J, Matsuda G (1974) The phylogeny of human globin genes investigated by the maximum parsimony method. J Mol Evol 3:1–48Google Scholar
  11. Jukes TH, Cantor CR (1969) Evolution of protein molecules. In: Munro HN (ed) Mammalian protein metabolism. Academic Press, New York, pp 21–123Google Scholar
  12. Kimura M (1969) The rate of molecular evolution considered from the standpoint of population genetics. Proc Natl Acad Sci USA 63:1181–1188Google Scholar
  13. King, JL, Jukes TH (1969) Non-Darwinian evolution. Science 164:788–798Google Scholar
  14. Langley CH, Fitch WM (1974) An examination of the constancy of the rate of molecular evolution. J Mol Evol 3:161–177Google Scholar
  15. Li W (1981) Simple method for constructing phylogenetic trees from distance matrices. Proc Natl Acad Sci USA 78:1085–1089Google Scholar
  16. Margoliash E, Smith EL (1965) Structural and functional aspects of cytochrome c in relation to evolution. In: Bryson V, Vogel HJ (eds) Evolving genes and proteins. Academic Press, New York, pp 221–242Google Scholar
  17. Moore GW, Barnabas J, Goodman M (1973a) A method for constructing maximum parsimony ancestral amino acid sequences on a given network. J Theor Biol 38:459–485Google Scholar
  18. Moore GW, Goodman M, Barnabas J (1973b) An iterative approach from the standpoint of the additive hypothesis to the dendrogram problem posed by molecular data sets. J Theor Biol 38:423–457Google Scholar
  19. Nei M (1972) Genetic distance between populations. Am Nat 106:283–292Google Scholar
  20. Nei M (1975) Molecular population genetics and evolution. North Holland, Amsterdam and New YorkGoogle Scholar
  21. Nei M (1977) Standard error of immunological dating of evolutionary time. J Mol Evol 9:203–211Google Scholar
  22. Nei M (1978) Genetic distance and molecular taxonomy. Abstract in: Proc XIV Intl Cong Genet. Nauka Publishing Office, Moscow, pp 84–85Google Scholar
  23. Nei M, Tateno Y (1978) Nonrandom amino acid substitution and estimation of the number of nucleotide substitutions in evolution. J Mol Evol 11:333–347Google Scholar
  24. Ohta T (1976) Simulation studies on the evolution of amino acid sequences. J Mol Evol 8:1–12Google Scholar
  25. Ohta T, Kimura M (1971) On the constancy of the evolutionary rate of cistrons. J Mol Evol 1:18–25Google Scholar
  26. Peacock D, Boulter D (1975) Use of amino acid sequence data in phylogeny and evaluation of methods using computer simulation. J Mol Biol 95:513–527Google Scholar
  27. Prager EM, Wilson AC (1971) The dependence of immunological cross-reactivity upon sequence resemblance among lysozymes. J Biol Chem 246:5978–5989Google Scholar
  28. Prager EM, Wilson AC (1978) Construction of phylogenetic trees for proteins and nucleic acids: empirical evaluation of alternative matrix methods. J Mol Evol 11:129–142Google Scholar
  29. Robinson DF, Foulds LR (1981) Comparison of phylogenetic trees. Math Biosci 53:131–147Google Scholar
  30. Sarich VM, Wilson AC (1966) Quantitative immunochemistry and the evolution of primate albumins: micro-complement fixation. Science 154:1563–1566Google Scholar
  31. Sneath PHA, Sokal RR (1973) Numerical taxonomy. WH Freeman, San FranciscoGoogle Scholar
  32. Sokal RR, Michener CD (1958) A statistical method for evaluating systematic relationships. Univ Kansas Sci Bull 28: 1409–1438Google Scholar
  33. Swofford DL (1981) On the utility of the distance Wagner procedure. In: Funk VA, Brooks DR (eds) Advances in cladistics. Cladistics Publications, Bronx, New YorkGoogle Scholar
  34. Tateno Y (1978) Statistical studies on the evolutionary changes of macromolecules. Ph.D. Dissertation, University of Texas at HoustonGoogle Scholar
  35. Tateno Y, Nei M (1978) Goodman et al.'s method for augmenting the number of nucleotide substitutions. J Mol Evol 11:67–73Google Scholar
  36. Waterman MS, Smith TF (1978) On the similarity of dendrograms. J Theor Biol 73:789–800Google Scholar
  37. Wilson AC, Carlson SS, White TJ (1977) Biochemical evolution. Ann Rev Biochem 46:573–639Google Scholar
  38. Zuckerkandl E, Pauling L (1962) Molecular disease, evolution, and genetic heterogeneity. In: Kasha M, Pullman B (eds) Horizons in biochemistry. Academic Press, New York, pp 189–225Google Scholar
  39. Zuckerkandl E, Pauling L (1965) Evolutionary divergence and convergence in proteins. In: Bryson V, Vogel HJ (eds) Evolving genes and proteins. Academic Press, New York, pp 97–166Google Scholar

Copyright information

© Springer-Verlag 1982

Authors and Affiliations

  • Yoshio Tateno
    • 1
  • Masatoshi Nei
    • 1
  • Fumio Tajima
    • 1
  1. 1.Center for Demographic and Population GeneticsUniversity of Texas at HoustonHoustonUSA
  2. 2.Institute of Physical and Chemical ResearchSaitamaJapan

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