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. 2007 Jul;176(3):1663-78.
doi: 10.1534/genetics.107.073080. Epub 2007 May 4.

Genetic load in sexual and asexual diploids: segregation, dominance and genetic drift

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Genetic load in sexual and asexual diploids: segregation, dominance and genetic drift

Christoph R Haag et al. Genetics. 2007 Jul.

Abstract

In diploid organisms, sexual reproduction rearranges allelic combinations between loci (recombination) as well as within loci (segregation). Several studies have analyzed the effect of segregation on the genetic load due to recurrent deleterious mutations, but considered infinite populations, thus neglecting the effects of genetic drift. Here, we use single-locus models to explore the combined effects of segregation, selection, and drift. We find that, for partly recessive deleterious alleles, segregation affects both the deterministic component of the change in allele frequencies and the stochastic component due to drift. As a result, we find that the mutation load may be far greater in asexuals than in sexuals in finite and/or subdivided populations. In finite populations, this effect arises primarily because, in the absence of segregation, heterozygotes may reach high frequencies due to drift, while homozygotes are still efficiently selected against; this is not possible with segregation, as matings between heterozygotes constantly produce new homozygotes. If deleterious alleles are partly, but not fully recessive, this causes an excess load in asexuals at intermediate population sizes. In subdivided populations without extinction, drift mostly occurs locally, which reduces the efficiency of selection in both sexuals and asexuals, but does not lead to global fixation. Yet, local drift is stronger in asexuals than in sexuals, leading to a higher mutation load in asexuals. In metapopulations with turnover, global drift becomes again important, leading to similar results as in finite, unstructured populations. Overall, the mutation load that arises through the absence of segregation in asexuals may greatly exceed previous predictions that ignored genetic drift.

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Figures

F<sc>igure</sc> 1.—
Figure 1.—
Mean frequency p (A) of a partly recessive deleterious allele (h = 0.1, s = 0.05), mean load L (B), and relative fitness wsex/wasex (C). Solid lines in A and B represent sexual populations and dashed lines represent asexual populations. Triangles on the left and right (A and B) indicate expected values for very small and infinite populations, respectively, and ×'s (B) indicate Nlim. In A, solid circles (sexuals) and open circles (asexuals) are simulation results for selected values of N. Mutation parameters: u = 10−5, v = 10−7.
F<sc>igure</sc> 2.—
Figure 2.—
Expected average genotype frequencies in sexual (A) and asexual (B) populations. a is a deleterious allele with h = 0.01, s = 0.01, u = 10−5, and v = 10−7. Note that the plotted frequencies are averages over many populations of a given size. For instance, sexual populations of the size indicated with an arrow in A have equal frequencies of aa and AA genotypes, on average, in the near absence of Aa. However, this does not imply heterozygote deficit within populations, but rather that most populations are fixed for AA or aa (with equal probability).
F<sc>igure</sc> 3.—
Figure 3.—
(A) Mean frequency, p, of a deleterious allele under multiplicative selection (s = 0.05, formula image) in sexual (solid line) and asexual (dashed line) populations. The circles (solid for sexuals, open for asexuals) represent simulation results, and in each pair of horizontally adjacent circles, Nasex = 2Nsex. Mutation parameters: u = 10−5, v = 10−7. (B) Simulation results showing the mean intralocus association formula image as a function of formula image, in asexual populations (same parameter values as in A). For comparison, at formula image, formula image at a neutral locus with the same mutation parameters is −0.005 in asexuals and formula image in sexuals.
F<sc>igure</sc> 4.—
Figure 4.—
Mean genetic load, L, in sexuals (solid lines) and asexuals (dashed lines) for mutations of different h and s. Simulation results (solid circles for sexuals, open circles for asexuals) are given for three selected parameter combinations of h and s. No graph is shown for h = 0.01, s = 0.001, because our model assumes hs > u. ×'s indicate Nlim. Mutation parameters: u = 10−5, v = 10−7.
F<sc>igure</sc> 5.—
Figure 5.—
Effect of selection coefficients s and dominance coefficients h on the limiting population size Nlim, below which genetic load L > 0.0001. Open (asexuals) and solid (sexuals) squares indicate different values of Nlim obtained from our model. The lines indicate the approximations, Nlim = 4/s (sexuals, solid line) and Nlim = 4/hs (asexuals, dashed lines). In sexuals, Nlim depends only minimally on h (Figure 4). Mutation parameters: u = 10−5, v = 10−7.
F<sc>igure</sc> 6.—
Figure 6.—
Fitness of sexuals relative to asexuals for different values of h (A), s (B), and U (C). (A and B) U = 0.02; (C) h = s = 0.01. Per-locus mutation rates, u = 10−5 and v = 10−7; the number of loci, n = 2000 for U = nu = 0.02 and n = 20,000 for U = 0.2.
F<sc>igure</sc> 7.—
Figure 7.—
Genetic load L as a function of deme size N in sexual (solid lines) and asexual (dashed lines) metapopulations without turnover (e = 0). Thick lines show diffusion results for sexuals (solid line) and asexuals (dashed line), while the open (asexuals) and solid (sexuals) circles show simulation results for N = 2, 5, 10, 20, 40, 100, 1000, and 10,000 (average load over formula image generations). The thin lines correspond to approximations (10) and (11), while the dashed-dotted line shows the sexual load in Agrawal and Chasnov's (2001) model, with no local competition. Parameters: formula image, formula image, formula image, formula image, formula image, formula image.
F<sc>igure</sc> 8.—
Figure 8.—
Genetic load in sexual (solid lines) and asexual (dashed lines) metapopulations, as a function of the extinction rate e, for the migrant pool model of recolonization (A) and the propagule model (B). Solid (sexuals) and open (asexuals) circles show simulation results. Parameters: formula image, formula image, formula image, formula image, formula image, formula image, formula image, formula image.

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