The Effect of Natural Selection on Phylogeny Reconstruction Algorithms
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.
Unable to display preview. Download preview PDF.
- 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.Ofria C., Brown C.T., and Adami C.: The Avida User’s Manual, 297—350 (1998)Google Scholar
- 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.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.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.Studier J. and Keppler K.: A Note on the Neighbor-Joining Algorithm of Saitou and Nei, Mol. Biol. Evol. 5 (1988) 729–731Google Scholar