Estimation of the rate and effects of deleterious genomic mutations in finite populations with linkage disequilibrium

Heredity (Edinb). 2005 Jul;95(1):59-68. doi: 10.1038/sj.hdy.6800689.

Abstract

Under several assumptions such as infinite population size with unlinked loci at linkage equilibrium (LD) under mutation-selection (M-S) balance, the rate (U), and the average effects (dominance and selection coefficients h and s) of deleterious genomic mutations (DGM) can be estimated by the Deng-Lynch method in some natural populations. However, all natural populations are finite in size and many of them are not large enough to be considered as approximately infinite. In the absence of an analytical estimation approach to characterize DGM in finite populations, we test the robustness and applicability of the Deng-Lynch method in finite populations with computer simulations. The results indicate that the estimation obtained by the Deng-Lynch method in finite populations with LD is generally robust when population size is greater than 400. With constant mutation effects, in outcrossing populations, the estimates U and ĥ are unbiased or only slightly upwardly biased, and ŝ is unbiased for most cases. In highly selfing populations, U and ĥ are upwardly biased, U is no more than 1.5U and ĥ is less than 1.1 h, and ŝ is either unbiased or slightly downwardly biased. With variable mutation effects, U ranges from 0.56 to 0.72U, and s ranges from 1.4 to 1.8s. Generally speaking, with the same finite population size, the estimation in outcrossing populations is better than in highly selfing populations. Given that even the order of the magnitude of the parameters of DMG (U in particular) is controversial, our investigation here may provide a basis for using the Deng-Lynch method to characterize DGM in finite populations of size greater than 400 in the presence of LD.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Genetics, Population*
  • Linkage Disequilibrium*
  • Models, Genetic*
  • Mutation*
  • Population Density
  • Population Dynamics
  • Reproducibility of Results