Journal of Molecular Evolution

, Volume 11, Issue 2, pp 129–142 | Cite as

Construction of phylogenetic trees for proteins and nucleic acids: Empirical evaluation of alternative matrix methods

  • Ellen M. Prager
  • Allan C. Wilson
Article

Summary

The methods of Fitch and Margoliash and of Farris for the construction of phylogenetic trees were compared. A phenetic clustering technique - the UPGMA method — was also considered.

The three methods were applied to difference matrices obtained from comparison of macromolecules by immunological, DNA hybridization, electrophoretic, and amino acid sequencing techniques. To evaluate the results, we used the goodness-of-fit criterion. In some instances, the F-M and Farris methods gave a comparably good fit of the output to the input data, though in most cases the F-M procedure gave a much better fit. By the fit criterion, the UPGMA procedure was on the average better than the Farris method but not as good as the F-M procedure.

On the basis of the results given in this report and the goodness-of-fit criterion, it is suggested that where input data are likely to include overestimates as well as true estimates and underestimates of the actual distances between taxonomic units, the F-M method is the most reasonable to use for constructing phylogenies from distance matrices. Immunological, DNA hybridization, and electrophoretic data fall into this category. By contrast, where it is known that each input datum is indeed either a true estimate or an underestimate of the actual distance between 2 taxonomic units, the Farris procedure appears, on theoretical grounds, to be the matrix method of choice. Amino acid and nucleotide sequence data are in this category.

Key words

Fitch-Margoliash Trees Farris Trees Distance Wagner Procedure UPGMA Clustering Immunology Micro-Complement Fixation Electrophoresis DNA Hybridization Amino Acid Sequences Protein Evolution 

The following abbreviations are used in this work

F-M

Fitch-Margoliash

UPGMA

unweighted pair-group method using arithmetic averages

SD

percent standard deviation

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Benveniste, R.E., Todaro, G.J. (1976). Nature261, 101–108Google Scholar
  2. Bisbee, C.A., Baker, M.A., Wilson, A.C., Hadji-Azimi, I., Fischberg, M. (1977). Science195, 785–787Google Scholar
  3. Case, S.M. (1976). Ph. D. Thesis, Univ. of Calif., BerkeleyGoogle Scholar
  4. Champion, A.B., Prager, E.M., Wachter, D., Wilson, A.C. (1974). Microcomplement fixation. In: Biochemical and immunological taxonomy of animals, C.A. Wright, ed., p. 397. London: Academic PressGoogle Scholar
  5. Cronin, J.E., Sarich, V.M. (1975). J. Human Evol.4, 357–375Google Scholar
  6. Farris, J.S. (1972). Am. Natur.106, 645–668Google Scholar
  7. Farris, J.S. (1973). Syst. Zool.22, 50–54Google Scholar
  8. Farris, J.S. (1974). Evolution28, 158–160Google Scholar
  9. Fitch, W.M. (1977a). The phyletic interpretation of macromolecular sequence information. Simple methods. In: Major patterns in vertebrate evolution, M.K. Hecht et al., eds., p. 169. New York: Plenum PressGoogle Scholar
  10. Fitch, W.M. (1977b). The phyletic interpretation of macromolecular sequence information. Sample cases. In: Major patterns in vertebrate evolution, M.K. Hecht et al., eds., p. 211. New York: Plenum PressGoogle Scholar
  11. Fitch, W.M., Margoliash, E. (1967). Science155, 279–284Google Scholar
  12. Goodman, M., Barnabas, J., Matsuda, G., Moore, G.W. (1971). Nature233, 604–613Google Scholar
  13. Ho, C.Y.-K., Prager, E.M., Wilson, A.C., Osuga, D.T., Feeney, R.E. (1976). J. Mol. Evol.8, 271–282Google Scholar
  14. Jollès, J., Schoentgen, F., Jollès, P., Prager, E.M., Wilson, A.C. (1976). J. Mol. Evol.8, 59–78Google Scholar
  15. Kidd, K.K., Sgaramella-Zonta, L.A. (1971). Am. J. Hum. Genet.23, 235–252Google Scholar
  16. Kohne, D.E., Chiscon, J.A., Hoyer, B.H. (1972). J. Human Evol.1, 627–644Google Scholar
  17. Lakovaara, S., Saura, A., Falk, C.T. (1972). Evolution26, 177–184Google Scholar
  18. Maxson, L.R., Wilson, A.C. (1975). Syst. Zool.24, 1–15Google Scholar
  19. Moore, G.W., Barnabas, J., Goodman, M. (1973). J. Theor. Biol.38, 459–485Google Scholar
  20. Nei, M. (1971). Am. Natur.105, 385–398Google Scholar
  21. Nei, M. (1975). Molecular population genetics and evolution. Amsterdam: North Holland Pub. Co.Google Scholar
  22. Nei, M. (1977). J. Mol. Evol.9, 203–211Google Scholar
  23. Peacock, D., Boulter, D. (1975). J. Mol. Biol.95, 513–527Google Scholar
  24. Prager, E.M., Fowler, D.P., Wilson, A.C. (1976a). Evolution30, 637–649Google Scholar
  25. Prager, E.M., Wilson, A.C. (1976). J. Mol. Evol.9, 45–57Google Scholar
  26. Prager, E.M., Wilson, A.C., Osuga, D.T., Feeney, R.E. (1976b). J. Mol. Evol.8, 283–294Google Scholar
  27. Sarich, V.M. (1969a). Syst. Zool.18, 286–295Google Scholar
  28. Sarich, V.M. (1969b). Syst. Zool.18, 416–422Google Scholar
  29. Sarich, V.M. (1973). Nature245, 218–220Google Scholar
  30. Sarich, V.M. (1976). Trans. Zool. Soc. Lond.33, 165–171Google Scholar
  31. Sarich, V.M., Cronin, J.E. (1976). Molecular systematics of the primates. In: Molecular anthropology, M. Goodman and R.E. Tashian, eds., p. 139. New York: Plenum PressGoogle Scholar
  32. Sneath, P.H.A., Sokal, R.R. (1973). Numerical taxonomy. San Francisco: W.H. Freeman and Co.Google Scholar
  33. Wallace, D.G., King, M.-C., Wilson, A.C. (1973). Syst. Zool.22, 1–13Google Scholar
  34. Wilson, A.C., Carlson, S.S., White, T.J. (1977). Ann. Rev. Biochem.46, 573–639Google Scholar

Copyright information

© Springer-Verlag 1978

Authors and Affiliations

  • Ellen M. Prager
    • 1
  • Allan C. Wilson
    • 1
  1. 1.Department of BiochemistryUniversity of CaliforniaBerkeleyUSA

Personalised recommendations