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Evolution of digital organisms at high mutation rates leads to survival of the flattest

Abstract

Darwinian evolution favours genotypes with high replication rates, a process called ‘survival of the fittest’. However, knowing the replication rate of each individual genotype may not suffice to predict the eventual survivor, even in an asexual population. According to quasi-species theory, selection favours the cloud of genotypes, interconnected by mutation, whose average replication rate is highest1,2,3,4,5. Here we confirm this prediction using digital organisms that self-replicate, mutate and evolve6,7,8,9. Forty pairs of populations were derived from 40 different ancestors in identical selective environments, except that one of each pair experienced a 4-fold higher mutation rate. In 12 cases, the dominant genotype that evolved at the lower mutation rate achieved a replication rate >1.5-fold faster than its counterpart. We allowed each of these disparate pairs to compete across a range of mutation rates. In each case, as mutation rate was increased, the outcome of competition switched to favour the genotype with the lower replication rate. These genotypes, although they occupied lower fitness peaks, were located in flatter regions of the fitness surface and were therefore more robust with respect to mutations.

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Figure 1: Competitions for one pair of organisms at four different mutation rates.
Figure 2: Genotype distributions after 15 generations from populations seeded uniformly with either A or B.
Figure 3: Critical mutation rates obtained from competition experiments versus predicted estimates based on each organism's intrinsic replication rate, w0, and mutational robustness parameters, a and b.

References

  1. Eigen, M. Self-organization of matter and the evolution of biological macromolecules. Naturwissenschaften 58, 465–523 (1971).

    ADS  CAS  Article  PubMed  Google Scholar 

  2. Eigen, M. & Schuster, P. The Hypercycle: A Principle of Natural Self-Organization (Springer, Berlin, 1979).

    Book  Google Scholar 

  3. Schuster, P. & Swetina, J. Stationary mutant distributions and evolutionary optimization. Bull. Math. Biol. 50, 636–660 (1988).

    MathSciNet  MATH  Article  Google Scholar 

  4. Eigen, M., McCaskill, J. & Schuster, P. The molecular quasi-species. Adv. Chem. Phys. 75, 149–263 (1989).

    CAS  Google Scholar 

  5. Nowak, M. A. What is a quasi-species? Trends Ecol. Evol. 7, 118–121 (1992).

    CAS  PubMed  Article  Google Scholar 

  6. Ray, T. S. in Artificial Life II (eds Langton, C. G., Taylor, C., Farmer, J. D. & Rasmussen, S.) 372–408 (Addison-Wesley, Redwood City, 1991).

    Google Scholar 

  7. Adami, C. Introduction to Artificial Life (Springer, New York, 1998).

    MATH  Book  Google Scholar 

  8. Lenski, R. E., Ofria, C., Collier, T. C. & Adami, C. Genome complexity, robustness and genetic interactions in digital organisms. Nature 400, 661–664 (1999).

    ADS  CAS  PubMed  Article  Google Scholar 

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

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. Gerrish, P. J. & Lenski, R. E. The fate of competing beneficial mutations in an asexual population. Genetica 102/103, 127–144 (1998).

    Article  Google Scholar 

  11. De Visser, J. A. G. M., Zeyl, C. W., Gerrish, P. J., Blanchard, J. L. & Lenski, R. E. Diminishing returns from mutation supply rate in asexual populations. Science 283, 404–406 (1999).

    ADS  CAS  Article  Google Scholar 

  12. Taddei, F. et al. Role of mutator alleles in adaptive evolution. Nature 387, 700–702 (1997).

    ADS  CAS  PubMed  Article  Google Scholar 

  13. Sniegowski, P. D., Gerrish, P. J. & Lenski, R. E. Evolution of high mutation rates in experimental populations. of E. coli. Nature 387, 703–705 (1997).

    ADS  CAS  PubMed  Article  Google Scholar 

  14. Johnson, T. The approach to mutation–selection balance in an infinite asexual population, and the evolution of mutation rates. Proc. R. Soc. Lond. B 266, 2389–2397 (1999).

    CAS  Article  Google Scholar 

  15. Waddington, C. H. Canalization of development and genetic assimilation of acquired characters. Nature 183, 1654–1655 (1959).

    ADS  CAS  PubMed  Article  Google Scholar 

  16. Nowak, M. A., Boerlijst, M. C., Cooke, J. & Maynard Smith, J. Evolution of genetic redundancy. Nature 388, 167–171 (1997).

    ADS  CAS  PubMed  Article  Google Scholar 

  17. Wagner, G. P., Booth, G. & Bagheri-Chaichian, H. A population genetic theory of canalization. Evolution 51, 329–347 (1997).

    PubMed  Article  Google Scholar 

  18. Freeland, S. J. & Hurst, L. D. Load minimization of the genetic code: history does not explain the pattern. Proc. R. Soc. Lond. B 265, 2111–2119 (1998).

    CAS  Article  Google Scholar 

  19. Burch, C. L. & Chao, L. Evolvability of an RNA virus is determined by its mutational neighbourhood. Nature 406, 625–628 (2000).

    ADS  CAS  PubMed  Article  Google Scholar 

  20. van Nimwegen, E., Crutchfield, J. P. & Huynen, M. Neutral evolution of mutational robustness. Proc. Natl Acad. Sci. USA 96, 9716–9720 (1999).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  21. Wike, C. O. Adaptive evolution on neutral networks. Bull. Math. Biol. (in the press).

  22. Haldane, J. B. S. The effect of variation on fitness. Am. Nat. 71, 337–349 (1937).

    Article  Google Scholar 

  23. Muller, H. J. Our load of mutations. Am. J. Hum. Genet. 2, 111–176 (1950).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Charlesworth, B. Mutation–selection balance and the evolutionary advantage of sex and recombination. Genet. Res. 55, 199–221 (1990).

    CAS  PubMed  Article  Google Scholar 

  25. Drake, J. W. Rates of spontaneous mutation among RNA viruses. Proc. Natl Acad. Sci. USA 90, 4171–4175 (1993).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  26. Drake, J. W., Charlesworth, B., Charlesworth, D. & Crow, J. W. Rates of spontaneous mutation. Genetics 148, 1667–1686 (1998).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. Eyre-Walker, A. & Keightley, P. D. High genomic deleterious mutation rates in hominids. Nature 397, 344–347 (1999).

    ADS  CAS  PubMed  Article  Google Scholar 

  28. Lynch, M. et al. Spontaneous deleterious mutation. Evolution 53, 645–663 (1999).

    PubMed  Article  Google Scholar 

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Acknowledgements

This work was supported by the National Science Foundation. Part of this work as carried out at the Jet Propulsion Laboratory, under a contract with the National Aeronautics and Space Administration. J.L.W. acknowledges the support of an Axline SURF fellowship.

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Correspondence to Claus O. Wilke.

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Wilke, C., Wang, J., Ofria, C. et al. Evolution of digital organisms at high mutation rates leads to survival of the flattest. Nature 412, 331–333 (2001). https://doi.org/10.1038/35085569

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