Evolvability

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[edit] Introduction

Wagner (2005) describes two definitions of evolvability which have two main meanings. The first one is: a biological system is evolvable if its properties show heritable genetic variation, and if natural selection can thus change these properties. The second one is a biological system is evolvable if it can acquire novel functions through genetic change, functions that help the organism survive and reproduce.

These definitions can be applied on all levels of biological organisation, from macromolecules to mammals. The two meanings are not synonymous. Not all systems that are evolvable in the first sense are evolvable in the second sense. An example is given by Wagner (2005).


[edit] Example

Consider an enzyme-coding gene that undergoes different mutations in different individuals of a population. Because of the mutations, the activity of the enzyme fluctuates among different individuals. If this mutation is heritable and influences fitness than natural selection can act on the enzyme’s activity. The enzyme’s activity is thus evolvable in the first sense. However, after millions of years, no mutation might give this enzyme a trait which might permit survival in a new environment. Thus, although the enzyme’s activity is evolvable in the first sense, that does not mean it is evolvable in the second sense. The opposite, does not work. Every innovative, evolvable system can evolve by natural selection.

Organisms are incredibly complex, yet also highly robust to genetic change on all levels of organization. This robustness is one of a few aspects that can affect evolvability in the first and the second sense.


[edit] Robustness and evolvability

Robustness will not increase evolvability in the first sense. In organisms with a high level of robustness, mutations will have smaller phenotypic effects than in organisms with a low level of robustness. Thus, robustness reduces the amount of heritable genetic variation on which selection can act. One can see this conclusion in two ways: The first way is that robustness causes mutations to be neutral and therefore no innovation will occur. The second way gives neutral mutations an important function in innovation. Although many neutral mutations do not change primary functions, they can change other system features for future evolution. So, robustness can facilitate exaptation. From this point of view, robustness implies that many mutations are neutral and such neutrality promotes innovation.



[edit] References

  • Altenberg, L. 1995. Genome growth and the evolution of the genotype-phenotype map. In Evolution and Biocomputation: Computational Models of Evolution, ed. Wolfgang Banzhaf and Frank H. Eeckman. Lecture Notes in Computer Science vol. 899. Springer-Verlag, pp. 205-259. isbn=0387590463.
  • Conrad, M. 1979. Bootstrapping on the adaptive landscape. BioSystems 11: 167–182.
  • Dawkins, R. 1989. The evolution of evolvability. In C. G. Langton, editor, Artificial life, the proceedings of an Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems. Addison-Wesley, Redwood City, CA.
  • Eshel, I. 1973. Clone-selection and optimal rates of mutation. Journal of Applied Probability 10: 728–738.
  • Kirschner, M. and J. Gerhart, 1998. Evolvability. PNAS 95(15): 8420-8427.
  • Riedl, R. J. 1977. A systems-analytical approach to macroevolutionary phenomena. Quarterly Review of Biology 52: 351–370.
  • Wagner, Andreas. 2005. Robustness and Evolvability in Living Systems (Princeton Studies in Complexity). Princeton University Press. isbn=0691122407.
  • Wagner, A., 2005. Robustness, evolvability and neutrality. FEBS Letters 579, 1772-1778.
  • Wagner, G. P. and L. Altenberg. 1996. Complex adaptations and the evolution of evolvability. Evolution 50 (3): 967-976.


[edit] See also


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