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A General Solution of the Wright–Fisher Model of Random Genetic Drift

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Abstract

We introduce a general solution concept for the Fokker–Planck (Kolmogorov) equation representing the diffusion limit of the Wright–Fisher model of random genetic drift for an arbitrary number of alleles at a single locus. This solution will continue beyond the transitions from the loss of alleles, that is, it will naturally extend to the boundary strata of the probability simplex on which the diffusion is defined. This also takes care of the degeneracy of the diffusion operator at the boundary. We shall then show the existence and uniqueness of a solution. From this solution, we can readily deduce information about the evolution of a Wright–Fisher population.

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References

  1. Buss, S.R., Clote, P.: Solving the Fisher–Wright and coalescence problems with a discrete Markov chain analysis. Adv. Appl. Probab. 36(4), 1175–1197 (2004)

    Article  MathSciNet  Google Scholar 

  2. Bürger, R.: The Mathematical Theory of Selection, Recombination, and Mutation. John Wiley, New York (2000)

    MATH  Google Scholar 

  3. Epstein, C.L., Mazzeo, R.: Wright–Fisher diffusion in one dimension. SIAM J. Math. Anal. 42, 568–608 (2010)

    Article  MathSciNet  Google Scholar 

  4. Epstein, C.L., Mazzeo, R.: Degenerate Diffusion Operators Arising in Population Biology. Princeton University Press, Princeton (2013)

    Book  Google Scholar 

  5. Ethier, S.N.: A class of degenerate diffusion processes occurring in population genetics. Commun. Pure Appl. Math. 29, 483–493 (1976)

    Article  MathSciNet  Google Scholar 

  6. Ethier, S.N., Kurtz, T.: Markov Processes: Characterization and Convergence. Wiley (1986), New York (2005)

  7. Ethier, S.N., Nagylaki, T.: Diffusion approximations of Markov chains with two time scales and applications to population genetics. Adv. Appl. Probab. 12, 14–49 (1980)

    Article  MathSciNet  Google Scholar 

  8. Ethier, S.N., Nagylaki, T.: Diffusion approximations of the two-locus Wright–Fisher model. J. Math. Biol. 27, 17–28 (1989)

    Article  MathSciNet  Google Scholar 

  9. Ewens, W.J.: Mathematical population genetics I. Theoretical introduction. In: Interdisciplinary Applied Mathematics, 2nd edn. Springer, New York (2004)

    Book  Google Scholar 

  10. Felsenstein, J.: The rate of loss of multiple alleles in finite haploid populations. Theor. Popul. Biol. 2, 391–403 (1971)

    Article  MathSciNet  Google Scholar 

  11. Fisher, R.A.: On the dominance ratio. Proc. R. Soc. Edinb. 42, 321–341 (1922)

    Article  Google Scholar 

  12. Gill, W.: Modified fixation probability in multiple alleles models in the asymmetric sharply-peaked landscape. J. Korean Phys. Soc. 55(2), 709–717 (2009)

    Article  Google Scholar 

  13. Gladstien, K.: Subdivided populations the characteristic values and rate of loss of alleles. J. Appl. Prob. 241, 241–248 (1977)

    Article  MathSciNet  Google Scholar 

  14. Karlin, S., Taylor, H.M.: A Second Course in Stochastic Processes. Academic Press, New York (1981)

    MATH  Google Scholar 

  15. Kimura, M.: Solution of a process of random genetic drift with a continuous model. PNAS-USA 41(3), 144–150 (1955)

    Article  Google Scholar 

  16. Kimura, M.: Random genetic drift in multi-allele locus. Evolution 9, 419–435 (1955)

    Article  Google Scholar 

  17. Kimura, M.: Random genetic drift in a tri-allelic locus; exact solution with a continuous model. Biometrics 12, 57–66 (1956)

    Article  Google Scholar 

  18. Lessard, S., Lahaie, P.: Fixation probability with multiple alleles and projected average allelic effect on selection. Theor. Popul. Biol. 75, 266–277 (2009)

    Article  Google Scholar 

  19. Littler, R.A., Good, A.J.: Ages, extinction times, and first passage probabilities for a multiallele diffusion model with irreversible mutation. Theor. Popul. Biol. 1(3), 214–225 (1978)

    Article  MathSciNet  Google Scholar 

  20. Littler, R.A.: Loss of variability at one locus in a finite population. Math. Biosci. 25, 151–163 (1975)

    Article  MathSciNet  Google Scholar 

  21. Marth, G., et al.: Sequence variations in the public human genome data reflect a bottlenecked population history. Proc. Natl. Acad. Sci. 100.1, 376–381 (2003)

    Article  Google Scholar 

  22. Nagylaki, T.: The decay of genetic variability in geographically structured populations. PNAS 71, 2932–2936 (1974)

    Article  MathSciNet  Google Scholar 

  23. Tran, T.D., Hofrichter, J., Jost, J.: An introduction to the mathematical structure of the Wright–Fisher model of population genetics. Theory Biosci. 1–10 (2012). doi:10.1007/s12064-012-0170-3

    Article  Google Scholar 

  24. Walker, A.C., Smith, S.D., Smith, S.D.: Mitochondrial DNA and human evolution. Nature 325, 1–5 (1987)

    Article  Google Scholar 

  25. Wright, S.: Evolution in Mendelian populations. Genetics 16, 97–159 (1931)

    Google Scholar 

Download references

Acknowledgments

We would like to thank the anonymous referee for helpful comments, in particular suggestions concerning SNPs and mitochondrial DNA, as mentioned in Sect. 4. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. 267087.

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Correspondence to Jürgen Jost.

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The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. 267087. T. D. Tran and J. Hofrichter have also been supported by the IMPRS “Mathematics in the Sciences”, and the material presented in this paper is largely based on the first author’s thesis.

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Tran, T.D., Hofrichter, J. & Jost, J. A General Solution of the Wright–Fisher Model of Random Genetic Drift. Differ Equ Dyn Syst 27, 467–492 (2019). https://doi.org/10.1007/s12591-016-0289-7

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