Using Computer Simulation to Understand Mutation Accumulation Dynamics and Genetic Load

  • John Sanford
  • John Baumgardner
  • Wes Brewer
  • Paul Gibson
  • Walter ReMine
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4488)


Long-standing theoretical concerns about mutation accumulation within the human population can now be addressed with numerical simulation. We apply a biologically realistic forward-time population genetics program to study human mutation accumulation under a wide-range of circumstances. Using realistic estimates for the relevant biological parameters, we investigate the rate of mutation accumulation, the distribution of the fitness effects of the accumulating mutations, and the overall effect on mean genotypic fitness. Our numerical simulations consistently show that deleterious mutations accumulate linearly across a large portion of the relevant parameter space. This appears to be primarily due to the predominance of nearly-neutral mutations. The problem of mutation accumulation becomes severe when mutation rates are high. Numerical simulations strongly support earlier theoretical and mathematical studies indicating that human mutation accumulation is a serious concern. Our simulations indicate that reduction of mutation rate is the most effective means for addressing this problem.


genetic load Mendel’s Accountant mutation accumulation population genetics simulation 


  1. 1.
    Muller, H.J.: Our load of mutations. Amer. J. Human Genetics 2, 111–176 (1950)Google Scholar
  2. 2.
    Wallace, B.: Fifty years of genetic load. J. Hered. 78, 134–142 (1987)Google Scholar
  3. 3.
    Kondrashov, A.S.: Contamination of the genome by very slightly deleterious mutations: why have we not died 100 times over? J. Theor. Biol. 175, 583–594 (1995)CrossRefGoogle Scholar
  4. 4.
    Crow, J.F.: The high spontaneous mutation rate: a health risk? PNAS 94, 8380–8386 (1997)CrossRefGoogle Scholar
  5. 5.
    Sanford, J., Baumgardner, J., Gibson, P., Brewer, W., Remine, W.: Mendel’s Accountant: a biologically realistic forward-time population genetics program. SCPE 8(2) (submitted)Google Scholar
  6. 6.
    Kimura, M.: Model of effectively neutral mutations in which selective constraint is incorporated. PNAS 76, 3440–3444 (1979)zbMATHCrossRefGoogle Scholar
  7. 7.
    Kimura, M.: Neutral Theory of Molecular Evolution, pp. 30–31. Cambridge University Press, New York (1983)Google Scholar
  8. 8.
    Haldane, J.B.S.: The cost of natural selection. J. Genetics 55, 511–524 (1957)CrossRefGoogle Scholar
  9. 9.
    Muller, H.J.: The relation of recombination to mutational advance. Mutation Research 1, 2–9 (1964)Google Scholar
  10. 10.
    Loewe, L.: Quantifying the genomic decay paradox due to Muller’s ratchet in human mitochondrial DNA. Genetical Research 87, 133–159 (2006)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • John Sanford
    • 1
  • John Baumgardner
    • 2
  • Wes Brewer
    • 3
  • Paul Gibson
    • 4
  • Walter ReMine
    • 5
  1. 1.Dept. Hort. Sci., Cornell University, Geneva, NY, 14456USA
  2. 2.Los Alamos National Laboratory, Los Alamos, NM, retiredUSA
  3. 3.Computational Engineering, Mississippi State University, MSUSA
  4. 4.Dept. Plant, Soil and Agric. Syst., Southern Illinois University, Carbondale, ILUSA
  5. 5.Science and Math Dept., Northwestern College, St. Paul, MNUSA

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