Advertisement

Journal of Molecular Evolution

, Volume 19, Issue 1, pp 9–19 | Cite as

Computer comparison of new and existing criteria for constructing evolutionary trees from sequence data

  • Roger L. Blanken
  • Lynn C. Klotz
  • Alan G. Hinnebusch
Article

Summary

Three new methods for constructing evolutionary trees from molecular sequence data are presented. These methods are based on a theory for correcting for non-constant evolutionary rates (Klotz et al. 1979; Klotz and Blanken 1981). Extensive computer simulations were run to compare these new methods to the commonly used criteria of Dayhoff (1978) and Fitch and Margoliash (1967). The results of these simulations showed that two of the new methods performed as well as Dayhoff's criterion, significantly better than that of Fitch and Margoliash, and as well as a simple variation of the latter (Prager and Wilson 1978) where any topology containing negative branch mutations is discarded. However, no method yielded the correct topology all of the time, which demonstrated the need to determine confidence estimates in a particular result when evolutionary trees are determined from sequence data.

Key words

Simple Cluster Analysis Present-Day Ancestor Evolutionary Trees Molecular Evolution DNA Sequence Evolution Simulated Evolution 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dayhoff MO, Park CM, McLaughlin PJ (1972) Cytochrome C Group. In: Dayhoff MO (ed) Atlas of Protein Sequence and Structure. National Biomedical Research Foundation, Washington DC, p 12Google Scholar
  2. Dayhoff MO (1978) Survey of New Data and Computer Methods of Analysis. In: Dayhoff MO (ed) Atlas of Protein Sequence and Structure. National Biomedical Research Foundation. Washington DC, p 7 and p 327Google Scholar
  3. Dayhoff MO (1978) Ribosomal and Other RNAs. In: Dayhoff MO (ed) Atlas of Protein Sequence and Structure. National Biomedical Research Foundation, Washington DC, p 308Google Scholar
  4. Dobzhansky T, Ayala FJ, Stebbins GL, Valentine JW (1977) The Molecular Clock of Evolution. In: Evolution. Freeman, San Francisco, p 308Google Scholar
  5. Finn JD (1974) General Model for Multivariate Analysis. Holt, Rinehart and Winston, New York, p 92Google Scholar
  6. Fitsch WM (1971) Toward Defining the Course of Evolution: Minimum Change for a Specific Tree Topology. Syst Zool 20:406–416Google Scholar
  7. Fitch WM (1977) On the Problem of Discovering the Most Parsimonious Tree. Am Nat 11:223–257Google Scholar
  8. Fitch WM, Margoliash E (1967) Construction of Phylogenetic Trees: A Method Based on Mutation Distances as Estimated from Cytochrome C Sequences is of General Applicability. Science 155:279–284PubMedGoogle Scholar
  9. Hinnebusch AG, Klotz LC, Immengut E, Loeblich AR III (1980) Deoxyribonucleic Acid Sequence Organization in the Genome of the Dinoflagellate Crypthecodinium cohnii. Biochemistry 19:1744–1755PubMedGoogle Scholar
  10. Holmquist R (1972) Theoretical Foundations for a Quantitative Approach to Paleogenetics P.I:DNA. J Mol Evol 1:115–133Google Scholar
  11. Holmquist R (1979) The Method of Parsimony: An Experimental Test and Theoretical Analysis of the Adequacy of Molecular Restoration Studies. J Mol Biol 135:939–958PubMedGoogle Scholar
  12. Hori H, Osawa S (1979) Evolutionary Change in 5S RNA Secondary Structure and a Phylogenic Tree of 54 5S RNA Species. Proc Natl Acad Sci USA 76:381–385PubMedGoogle Scholar
  13. Iiuzuka M, Kazushige I, Mutusuda H (1975) Comments on Holmquist's Theory for Paleogenetics: The Effect of Multiple Hits on Nucleotide Differences between Homologous DNA's. J Mol Evol 5:249–254PubMedGoogle Scholar
  14. Klotz LC, Komar N, Blanken RL, Mitchel RM (1979) Calculation of Evolutionary Trees from Sequence Data. Proc Natl Acad Sci USA 76:4516–4520PubMedGoogle Scholar
  15. Klotz LC, Blanken RL (1981) A Practical Method for Calculating Evolutionary Trees from Sequence Data. J Theor Biol 91:261–272PubMedGoogle Scholar
  16. Maxam AM, Gilbert W (1977) A New Method for Sequencing DNA. Proc Natl Acad Sci USA 74:560–564PubMedGoogle Scholar
  17. Moore GW, Goodman M, Barnabas J (1973) An Iterative Approach from the Standpoint of the Additive Hypothesis to the Dendrogram Problem Posed by Molecular Data Sets. J Theor Biol 38:423–457PubMedGoogle Scholar
  18. Peattic DA (1979) Direct Chemical Method for Sequencing RNA. Proc Natl Acad Sci USA 76:1760–1764PubMedGoogle Scholar
  19. Prager EM, Wilson AC (1978) Construction of Phylogenetic Trees for Proteins and Nucleic Acids: Empirical Evaluation of Alternative Matrix Methods. J Mol Evol 11:129–142PubMedGoogle Scholar
  20. Ratner VA, Zharkikh AA, Rodin SN (1977) In: Ratner VA (ed) Mathematical Models of Evolution and Selection. USSR Novosibirsk, p 1Google Scholar
  21. Sanger F, Nicklen S, Coulson AR (1977) DNA Sequencing with Chain-Terminating Inhibitors. Proc Natl Acad Sci USA 74:5463–5467PubMedGoogle Scholar
  22. Sokol RR, Sneath PAH (1973a) A Taxonomy of Clustering Methods. In: Numerical Taxonomy. Freeman, San Francisco, p 201Google Scholar
  23. Sokol RR, Sneath PAH (1973b) Cladistic Analysis. In: Numerical Taxonomy. Freeman, San Francisco, p 319Google Scholar

Copyright information

© Springer-Verlag 1982

Authors and Affiliations

  • Roger L. Blanken
    • 1
  • Lynn C. Klotz
    • 1
  • Alan G. Hinnebusch
    • 2
  1. 1.Bio Technica InternationalCambridgeUSA
  2. 2.Department of BiochemistryCornell UniversityIthacaUSA

Personalised recommendations