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Can Aging Develop as an Adaptation to Optimize Natural Selection? (Application of Computer Modeling for Searching Conditions When the “Fable of Hares” Can Explain the Evolution of Aging)

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Abstract

There are two points of view on the evolution of aging. The classical theory of aging suggests that natural selection does not efficiently eliminate mutations or alleles that are harmful to organisms at later age. Another hypothesis is that the genetic program of aging has evolved as an adaptation that contributes to the optimization of the evolutionary process. Academician V. P. Skulachev advocates the latter hypothesis, which he has illustrated with the “Fable of hares”. In this paper, we have used computer simulation to search for conditions when, according to the “Fable”, aging develops as an adaptation required for the evolution of useful traits. The simulation has shown that the evolutionary mechanism presented in the “Fable of hares” is only partially functional. We have found that under certain conditions, programmed deterioration of some organismal functions makes it possible to increase the efficiency of natural selection of other functions. However, we have not identified mechanisms that would ensure the distribution and support of genes of aging within the population.

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Abbreviations

A :

aging rate

C :

intelligence

F :

“intelligence fine”

T A :

threshold age

V :

running speed

References

  1. Jones, O. R., Scheuerlein, A., Salguero–Gomez, R., Camarda, C. G., Schaible, R., Casper, B. B., Dahlgren, J. P., Ehrlen, J., Garcia, M. B., Menges, E. S., Quintana–Ascencio, P. F., Caswell, H., Baudisch, A., and Vaupel, J. W. (2014) Diversity of ageing across the tree of life, Nature, 505, 169–173.

    Article  CAS  Google Scholar 

  2. Hamilton, W. D. (1966) The moulding of senescence by natural selection, J. Theor. Biol., 12, 12–45.

    Article  CAS  PubMed  Google Scholar 

  3. Rose, M. (1991) Evolutionary Biology of Aging, Oxford University Press, Oxford.

    Google Scholar 

  4. Medawar, P. B. (1952) An Unsolved Problem of Biology, HK Lewis, London.

    Google Scholar 

  5. Williams, G. C. (1957) Pleiotropy, natural selection, and the evolution of senescence, Evolution, 11, 398–411.

    Google Scholar 

  6. Severin, F. F., and Skulachev, V. P. (2009) Programmed cell death as a target for struggle against aging of organism, Uspekhi Gerontol., 22, 37–48.

    CAS  Google Scholar 

  7. Skulachev, V. P. (2003) Aging and the programmed death phenomena, Top. Curr. Genet., 3, 191–238.

    Article  Google Scholar 

  8. Heredia, D., Sanz, V., Urquia, A., and Sandin, M. (2015) A systemic approach for modeling biological evolution using Parallel DEVS, Biosystems, 134, 56–70.

    Article  PubMed  Google Scholar 

  9. Markov, M. A., and Markov, A. V. (2014) Computer simulation of the ontogeny of organisms with different types of symmetry, Paleontol. J., 48, 1143–1151.

    Article  Google Scholar 

  10. Markov, M. A., and Markov, A. V. (2011) Self–organization in ontogenesis of multicellular organisms: an experience of simulation modeling, Zh. Obshch. Biol., 5, 323–39.

    Google Scholar 

  11. Menshutkin, V. V., and Natochin, Y. V. (2008) Simulation modeling of the generation of multicellular animals, Paleontol. J., 2, 3–12.

    Google Scholar 

  12. Menshutkin, V. V. (2003) Computer simulation of different type of evolution process, Zh. Obshch. Biol., 4, 328–36.

    Google Scholar 

  13. Peck, S. L. (2004) Simulation as experiment: a philosophical reassessment for biological modeling, Trends Ecol. Evol., 10, 530–534.

    Article  Google Scholar 

  14. Chistyakov, V. A., Denisenko, D. V., and Bren, A. B. (2018) Presence of old individuals in a population accelerates and optimizes the process of selection: in silico experiments, Biochemistry (Moscow), 83, 159–168.

    Article  CAS  Google Scholar 

  15. Wright, S. (1932) The roles of mutation, inbreeding, cross–breeding and selection in evolution, in Proc. Sixth Int. Congr. of Genetics (Jone, D. F., ed.) Brooklyn Botanic Garden, Menasha, WI, pp. 356–366.

    Google Scholar 

  16. Crow, J. F., and Kimura, M. (1970) An Introduction to Population Genetics Theory, Harper and Row, N. Y.

    Google Scholar 

  17. Barton, N. H. (2000) Genetic hitchhiking, Philos. Trans. R. Soc. Lond. B Biol. Sci., 355, 1553–1562.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Correspondence to E. Yu. Yakovleva.

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Original Russian Text © A. V. Markov, M. A. Barg, E. Yu. Yakovleva, 2018, published in Biokhimiya, 2018, Vol. 83, No. 12, pp. 1844–1858.

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Markov, A.V., Barg, M.A. & Yakovleva, E.Y. Can Aging Develop as an Adaptation to Optimize Natural Selection? (Application of Computer Modeling for Searching Conditions When the “Fable of Hares” Can Explain the Evolution of Aging). Biochemistry Moscow 83, 1504–1516 (2018). https://doi.org/10.1134/S0006297918120088

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  • DOI: https://doi.org/10.1134/S0006297918120088

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