Macroevolution simulated with autonomously replicating computer programs

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Abstract

The process of adaptation occurs on two timescales. In the short term, natural selection merely sorts the variation already present in a population, whereas in the longer term genotypes quite different from any that were initially present evolve through the cumulation of new mutations. The first process is described by the mathematical theory of population genetics. However, this theory begins by defining a fixed set of genotypes and cannot provide a satisfactory analysis of the second process because it does not permit any genuinely new type to arise. The evolutionary outcome of selection acting on novel variation arising over long periods is therefore difficult to predict. The classical problem of this kind is whether ‘replaying the tape of life’ would invariably lead to the familiar organisms of the modern biota1,2. Here we study the long-term behaviour of populations of autonomously replicating computer programs and find that the same type, introduced into the same simple environment, evolves on any given occasion along a unique trajectory towards one of many well-adapted end points.

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Figure 1: Variety of evolutionary end points.
Figure 2

References

  1. 1

    Gould, S. J. Wonderful Life: The Burgess Shale and the Nature of History (W. W. Norton, New York, 1989)

  2. 2

    Dykhuizen, D. Experimental studies of natural selection in bacteria. Annu. Rev. Ecol Syst. 21, 373–398 (1990)

  3. 3

    Fisher, R. A. The Genetical Theory of Natural Selection (Dover, New York, 1930)

  4. 4

    Atwood, K. C., Schneider, L. K. & Ryan, F. J. Selective mechanisms in bacteria. Cold Spring Harb. Symp. Quant. Biol. 16, 345–355 (1951)

  5. 5

    Gerrish, P. J. The rhythm of microbial adaptation. Nature 413, 299–302 (2001)

  6. 6

    Dykhuizen, D. & Hartl, D. L. Evolution of competitive ability in Escherichia coli. Evolution 35, 581–594 (1981)

  7. 7

    Travisano, M., Mongold, J. A., Bennett, A. F. & Lenski, R. E. Experimental tests of the roles of adaptation, chance, and history in evolution. Science 267, 87–90 (1995)

  8. 8

    Kramer, F. R., Mills, D. R., Cole, P. E., Nishihara, T. & Spiegelman, S. Evolution in vitro: sequence and phenotype of a mutant RNA resistant to ethidium bromide. J. Mol. Biol. 89, 719–736 (1974)

  9. 9

    Bull, J. J. et al. Exceptional convergent evolution in a virus. Genetics 147, 1497–1507 (1997)

  10. 10

    Nakatsu, C. H. et al. Parallel and divergent genotypic evolution in experimental populations of Ralstonia sp. J. Bacteriol. 180, 4325–4331 (1998)

  11. 11

    Lenski, R. & Travisano, M. Dynamics of adaptation and diversification: a 10,000 generation experiment with bacterial populations. Proc. Natl Acad. Sci. USA 91, 6808–6814 (1994)

  12. 12

    Korona, R., Nakatsu, C. H., Forney, L. J. & Lenski, R. E. Evidence for multiple adaptive peaks from populations of bacteria evolving in a structured habitat. Proc. Natl Acad. Sci. USA 91, 9037–9041 (1994)

  13. 13

    Travisano, M. Long-term experimental evolution in Escherichia coli. VI. Environmental constraints on adaptation and divergence. Genetics 146, 471–479 (1997)

  14. 14

    Hartley, B. S. Experimental evolution of ribitol dehydrogenase. Microorganisms as Model Systems for Studying Evolution (ed. Mortlock, R. P.) 23–54 (Plenum, New York, 1984)

  15. 15

    Yin, J. Evolution of bacteriophage T7 in a growing plaque. J. Bacteriol. 175, 1272–1277 (1993)

  16. 16

    Cohan, F. M. & Hoffmann, A. A. Genetic divergence under uniform selection. II. Different responses to selection for knockdown resistance to ethanol among Drosophila melanogaster populations and their replicate lines. Genetics 114, 145–163 (1986)

  17. 17

    Hoffmann, A. A. & Harshman, L. G. Desiccation and starvation resistance in Drosophila: Patterns of variation at the species, population and intrapopulation levels. Heredity 83, 637–643 (1999)

  18. 18

    Ray, T. S. An approach to the synthesis of life. Artificial Life II, Santa Fe Institute Studies in the Sciences of Complexity (eds Farmer, D. J., Langton, C., Rasmussen, S. & Taylor, C.) Vol. 11 371–408 (Addison Wesley, Redwood City, California, 1991)

  19. 19

    Ray, T. S. Tierra v. 5.0, with documentation. Available via anonymous ftp from the Tierra home page at http://www.isd.atr.co.jp/~ray/tierra

  20. 20

    Wilke, C. O., Wang, J. L., Ofria, C., Lenski, R. E. & Adami, C. Evolution of digital organisms at high mutation rates leads to survival of the flattest. Nature 412, 331–333 (2001)

  21. 21

    Yedid, G. & Bell, G. Microevolution in an electronic microcosm. Am. Nat. 157, 465–487 (2001)

  22. 22

    Mani, G. S. & Clarke, B. C. Mutational order: a major stochastic process in evolution. Proc. R. Soc. Lond. B 240, 29–37 (1990)

  23. 23

    Johnson, P. A., Lenski, R. E. & Hoppensteadt, F. C. Theoretical analysis of divergence in mean fitness between genetically identical populations. Proc. R. Soc. Lond. B 259, 125–130 (1995)

  24. 24

    Wahl, L. M. & Krakauer, D. C. Models of experimental evolution: the role of genetic chance and selective necessity. Genetics 156, 1437–1448 (2000)

  25. 25

    Adami, C. Learning and complexity in genetic auto-adaptive systems. Physica D 80, 154–170 (1995)

  26. 26

    Adami, C., Ofria, C. & Collier, T. C. Evolution of biological complexity. Proc. Natl Acad. Sci. USA 97, 4463–4468 (2000)

  27. 27

    Spiegelman, S. An approach to the experimental analysis of precellular evolution. Q. Rev. Biophys. 4, 213–253 (1971)

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Acknowledgements

This research was supported by a Research Grant from the Natural Sciences and Engineering Research Council of Canada to G.B.

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Correspondence to Graham Bell.

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Yedid, G., Bell, G. Macroevolution simulated with autonomously replicating computer programs. Nature 420, 810–812 (2002) doi:10.1038/nature01151

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