Using Avida to test the effects of natural selection on phylogenetic reconstruction methods

  • Authors:

  • George I. Hagstrom;Dehua H. Hang;Charles Ofria;Eric Torng

  • Affiliations:

  • California Institute of Technology, Pasadena, CA;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI

  • Venue:
  • Artificial Life
  • Year:
  • 2004

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Abstract

Phylogenetic trees group organisms by their ancestral relationships. There are a number of distinct algorithms used to reconstruct these trees from molecular sequence data, but different methods sometimes give conflicting results. Since there are few precisely known phylogenies, simulations are typically used to test the quality of reconstruction algorithms. These simulations randomly evolve strings of symbols to produce a tree, and then the algorithms are run with the tree leaves as inputs. Here we use Avida to test two widely used reconstruction methods, which gives us the chance to observe the effect of natural selection on tree reconstruction. We find that if the organisms undergo natural selection between branch points, the methods will be successful even on very large time scales. However, these algorithms often falter when selection is absent.