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Mutational robustness can facilitate adaptation

Author

Listed:
  • Jeremy A. Draghi

    (Department of Biology,)

  • Todd L. Parsons

    (Department of Biology,)

  • Günter P. Wagner

    (Yale University, New Haven, Connecticut 06520, USA)

  • Joshua B. Plotkin

    (Department of Biology,
    Program in Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA)

Abstract

A robust approach to flexibility The role of mutational robustness in evolution has been a topic of much debate and controversy. On the one hand, it would seem to impede adaptation by making it less easy for a new phenotype to develop in the event of environmental changes; on the other it is surely advantageous for an organism to buffer its phenotype against possibly unhelpful mutations. How can an organism handle this paradox, and be both robust and adaptable? A quantitative population genetics model gives a possible resolution to this problem, by showing that mutational robustness can either impede or facilitate adaptation, depending on the population size, the mutation rate and the structure of the fitness landscape.

Suggested Citation

  • Jeremy A. Draghi & Todd L. Parsons & Günter P. Wagner & Joshua B. Plotkin, 2010. "Mutational robustness can facilitate adaptation," Nature, Nature, vol. 463(7279), pages 353-355, January.
    • Handle: RePEc:nat:nature:v:463:y:2010:i:7279:d:10.1038_nature08694
    DOI: 10.1038/nature08694
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    Citations

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    Cited by:

    1. Alexander J. Stewart & Joshua B. Plotkin, 2015. "The Evolvability of Cooperation under Local and Non-Local Mutations," Games, MDPI, vol. 6(3), pages 1-20, July.
    2. Zeina Shreif & Vipul Periwal, 2014. "A Network Characteristic That Correlates Environmental and Genetic Robustness," PLOS Computational Biology, Public Library of Science, vol. 10(2), pages 1-23, February.
    3. Sam F Greenbury & Steffen Schaper & Sebastian E Ahnert & Ard A Louis, 2016. "Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-27, March.
    4. Rendel, Mark D., 2011. "Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes," Theoretical Population Biology, Elsevier, vol. 79(1), pages 12-18.
    5. Proulx, Stephen R., 2011. "The rate of multi-step evolution in Moran and Wright–Fisher populations," Theoretical Population Biology, Elsevier, vol. 80(3), pages 197-207.
    6. Rigato, Emanuele & Fusco, Giuseppe, 2020. "A heuristic model of the effects of phenotypic robustness in adaptive evolution," Theoretical Population Biology, Elsevier, vol. 136(C), pages 22-30.
    7. Alicia Sanchez-Gorostiaga & Djordje Bajić & Melisa L Osborne & Juan F Poyatos & Alvaro Sanchez, 2019. "High-order interactions distort the functional landscape of microbial consortia," PLOS Biology, Public Library of Science, vol. 17(12), pages 1-34, December.
    8. Miguel A Fortuna & Luis Zaman & Charles Ofria & Andreas Wagner, 2017. "The genotype-phenotype map of an evolving digital organism," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-20, February.
    9. Tobias Sikosek & Erich Bornberg-Bauer & Hue Sun Chan, 2012. "Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts," PLOS Computational Biology, Public Library of Science, vol. 8(9), pages 1-17, September.

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