Advertisement

The Effect of Natural Selection on Phylogeny Reconstruction Algorithms

  • Dehua Hang
  • Charles Ofria
  • Thomas M. Schmidt
  • Eric Torng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)

Abstract

We study the effect of natural selection on the performance of phylogeny reconstruction algorithms using Avida, a software platform that maintains a population of digital organisms (self-replicating computer programs) that evolve subject to natural selection, mutation, and drift. We compare the performance of neighbor-joining and maximum parsimony algorithms on these Avida populations to the performance of the same algorithms on randomly generated data that evolve subject only to mutation and drift. Our results show that natural selection has several specific effects on the sequences of the resulting populations, and that these effects lead to improved performance for neighbor-joining and maximum parsimony in some settings. We then show that the effects of natural selection can be partially achieved by using a non-uniform probability distribution for the location of mutations in randomly generated genomes.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hillis D.M.: Approaches for Assessing Phylogenetic Accuracy, Syst. Biol. 44(1) (1995) 3–16CrossRefGoogle Scholar
  2. 2.
    Huelsenbeck J.P.: Performance of Phylogenetic Methods in Simulation, Syst. Biol. 44(1) (1995) 17–48CrossRefGoogle Scholar
  3. 3.
    Hillis D., Bull J.J., White M.E., Badgett M.R., Molineux L.J.: Experimental Phylogenetics: Generation of a Known Phylogeny. Science 255 (1992) 589–592CrossRefGoogle Scholar
  4. 4.
    Ramnaut A. and Grassly N. C.: Seq-Gen: An application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic trees. Comput. Appl. Biosci. 13 (1997) 235–238Google Scholar
  5. 5.
    Ofria C., Brown C.T., and Adami C.: The Avida User’s Manual, 297—350 (1998)Google Scholar
  6. 6.
    Wilke C.O., Adami C.: The biology of digital organisms. TRENDS in Ecology and Evolution, 17:11 (2002) 528–532CrossRefGoogle Scholar
  7. 7.
    Adami C., Ofria C., and Collier T.C.: Evolution of Biological Complexity. Proc. Natl. Acad. Sci. USA 97 (2000) 4463–4468CrossRefGoogle Scholar
  8. 8.
    Wilke C.O., et. al.: Evolution of Digital Organisms at High Mutation Rates Leads to Survival of the Flattest. Nature, 412 (2001) 331–333CrossRefGoogle Scholar
  9. 9.
    Lenski R.E., et. al.: Genome Complexity, Robustness, and Genetic Interactions in Digital Organisms. Nature 400 (1999) 661–664CrossRefGoogle Scholar
  10. 10.
    Elena S.F. and Lenski, R.E.: Test of Synergistic Interactions Among Deleterious Mutations in Bacteria. Nature 390 (1997) 395–398CrossRefGoogle Scholar
  11. 11.
    Gaut B.S. and Lewis P.O.: Success of Maximum Likelihood Phylogeny Inference in the Four-Taxon Case, Mol. Biol. Evol 12(1) (1995) 152–162Google Scholar
  12. 12.
    Tateno Y., Takezaki N., and Nei M.: Relative Efficiencies of the Maximum-Likelihood, Neighbor-joining, and Maximum Parsimony Methods When Substitution Rate Varies with Site, Mol. Biol. Evol. 11(2) (1994) 261–277Google Scholar
  13. 13.
    Saitou N. and Nei M.,: The Neighbor-Joining Method: A New Method for Reconstructing Phylogenetic Trees, Mol. Biol. Evol. 4 (1987) 406–425Google Scholar
  14. 14.
    Studier J. and Keppler K.: A Note on the Neighbor-Joining Algorithm of Saitou and Nei, Mol. Biol. Evol. 5 (1988) 729–731Google Scholar
  15. 15.
    Fitch W.: Toward Defining the Course of Evolution: Minimum Change for a Specified Tree Topology, Systematic Zoology, 20 (1971) 406–416CrossRefGoogle Scholar
  16. 16.
    Lenski E., Ofria C., Collier C. and Adami C.: Genome Complexity, Robustness and Genetic Interactions in Digital Organisms, Nature, 400 (1999) 661–664CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Dehua Hang
    • 1
  • Charles Ofria
    • 1
  • Thomas M. Schmidt
    • 2
  • Eric Torng
    • 1
  1. 1.Department of Computer Science & EngineeringMichigan State UniversityEast LansingUSA
  2. 2.Department of Microbiology and Molecular GeneticsMichigan State UniversityEast LansingUSA

Personalised recommendations