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  • 1Molecular Genetics and Genomics Program,Washington University in St. Louis,St. Louis,Missouri, 63110,USA.

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This study introduces an additive fitness model that significantly reduces mutation load compared to traditional models. This new model better explains synergistic epistasis in mutation accumulation data, offering a more accurate understanding of genetic load.

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Area of Science:

  • Evolutionary genetics
  • Population genetics
  • Genomics

Background:

  • Traditional mutation load models assume multiplicative fitness effects, leading to high genetic loads (1-e-U) with increasing deleterious mutation rates (U).
  • Synergistic epistasis has been proposed to reduce this load, but experiments often use quadratic fitness models, yielding inconclusive results on epistasis prevalence.
  • Previous research on epistasis detection has primarily focused on quadratic fitness models, often concluding epistasis is rare or weak.

Purpose of the Study:

  • To present and analyze a new model of additive fitness effects for understanding mutation load.
  • To demonstrate that the additive model results in a significantly lower genetic load compared to the traditional multiplicative model, especially at high mutation rates.
  • To re-evaluate epistasis in mutation accumulation data using the additive model and compare its predictive power against the quadratic model.

Main Methods:

  • Developed an analytical model for genetic load based on additive fitness effects.
  • Performed numerical iterations to validate the model's approximation under biologically relevant parameters.
  • Applied regression analysis to existing Drosophila mutation accumulation data.

Main Results:

  • The additive model yields a genetic load of U/(U+1), which is substantially lower than the multiplicative model's 1-e-U for large U.
  • The additive model provides a good approximation for biologically relevant selection coefficients and mutation rates.
  • Regression analysis on Drosophila data shows the additive model fits well and indicates synergistic epistasis, challenging conclusions drawn from quadratic models.
  • The additive model predicts a greater reduction in genetic load than the quadratic model using the same data.

Conclusions:

  • The additive fitness model offers a more accurate representation of genetic load, particularly under high mutation rates.
  • This model suggests synergistic epistasis may be more common than previously thought, as indicated by its fit to mutation accumulation data.
  • It is crucial to consider the additive fitness model alongside the quadratic model when inferring epistasis from mutation accumulation experiments.