The role of standing genetic variation in adaptation of digital organisms to a new environment

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Abstract

Evolutionary adaptation to a new environment depends on the availability of beneficial alleles. Beneficial alleles may appear as new mutations or may come from standing genetic variation - alleles already present in the population prior to the environmental change. Adaptation from standing genetic variation in sexually-reproducing populations is expected to be faster than from new mutations because beneficial alle-les from standing genetic variation occur at a higher starting frequency and are immediately available. The distribution of fitness effects of alleles from standing genetic variation are expected to be different from that of new mutations because standing genetic variation has been 'pre-tested' by selection. Whether adaptation uses standing genetic variation or new mutations as a source of beneficial alleles is unknown. In this study, I conducted experimental evolution of digital organisms to determine the source of beneficial alle-les during adaptation. I also tested the speed of adaptation and the fitness effect of alleles under these two sources of genetic variation. I found that the major source of beneficial alleles after an environmental change was standing genetic variation, but new mutations were necessary for long-term evolution. I also found that adaptation from standing genetic variation was faster than from new mutations, and the mean fitness effect of alleles from standing genetic variation were neutral, whereas new mutations were deleterious. Interestingly, I found that an important advantage of standing genetic variation was that recombination appeared to bring together beneficial combinations of alleles from standing genetic variation. These results support the hypothesis that adaptation occurs mostly from standing genetic variation and provide an additional advantage for such adaptation. © 2012 Massachusetts Institute of Technology.

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Anderson, C. J. R. (2012). The role of standing genetic variation in adaptation of digital organisms to a new environment. In Artificial Life 13: Proceedings of the 13th International Conference on the Simulation and Synthesis of Living Systems, ALIFE 2012 (pp. 3–10). MIT Press Journals. https://doi.org/10.7551/978-0-262-31050-5-ch001

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