polygenic adaptation - senecio7の日記

Matuszewski S, Hermisson J & Kopp M 2015 Catch me if you can: adaptation from standing genetic variation to a moving phenotypic optimum. Genetics 200:1255-1274.

adaptive-walk models consider adaptation from the successive fixation of de novo mutations only
quantitative genetic models assume that adaptation proceeds exclusively from preexisting standing genetic variation
the latter approach, however, has focused on short-term evolution of population means and variances

we derive the distribution of adaptive substitutions from standing genetic variation
that is, the distribution of the phenotypic effects of those alleles from the standing variation that become fixed during adaptation
(i) adaptation from standing variation proceeds by the fixation of more alleles of small effect
(ii) populations that adapt from standing genetic variation can traverse larger distances in phenotype space and, thus, have a higher potential for adaptation if the rate of environmental change is fast rather than slow

in contrast to what has been claimed by the neutral theory (Kimura 1983), adaptive evolution at the molecular level is widespread
selection following a change in the environmental conditions may act either on de novo mutations or on alleles already present in the population, also known as standing genetic variation

the origins of quantitative genetics lie in the design of plant and animal breeding schemes
the traditional focus of these models was on predicting short-term changes in the population mean phenotype (often assuming constant genetic variances and covariances) and not on the fate and effect of individual alleles
it is only in the past decade that population geneticists have thoroughly addressed adaptation from standing genetic variation at the level of individual substitutions
Hermisson and Pennings (2005) calculated the probability of adaptation from standing genetic variation following a sudden change in the selection regime
for small-effect alleles, the fixation probability is considerably increased relative to that from new mutations
Chevin and Hospital (2008) showed that the selective dynamics at a focal locus are substantially affected by genetic background variation
the selective advantage of a mutation plays only a limited role in determining its ultimate fate
instead, fixation or loss is largely determined by variation in the genetic background—which need not to be preexisting, but could quickly be generated by a large number of new mutations
predictions beyond these single-locus results have been verbal at best

when standing genetic variation is the sole source for adaptation, faster environmental change can enable the population to remain better adapted and to traverse larger distances in phenotype space

all mutations that are segregating in the population at the time the environment starts changing are considered as standing genetic variants
all mutations introduced after that point are considered as de novo mutations

genetic assumptions and simulation model
we do not fix the number of loci a priori, but instead assume that each mutation creates a unique polymorphic locus, whose position is drawn randomly from a uniform distribution over the entire genome
each locus contains only a wild-type allele with phenotypic effect 0 and a mutant allele with phenotypic effect α
the simulation was stopped once all alleles from the standing genetic variation were either fixed or lost
i.e., when σ_{sgv² = 0}

alleles at different loci influencing the same trait segregate as standing genetic variation
the selective dynamics of any individual allele are critically affected by the collective evolutionary response at other loci

when comparing adaptation from standing genetic variation to that from de novo mutations, the former proceeds, on average, by the fixation of more alleles of small effect

in the absence of continued environmental change, establishment does not guarantee fixation
alleles need to "race for fixation" before other competing alleles get fixed and they become deleterious
the dynamics of a mutation along its trajectory should therefore be even more complex than in the moving-optimum model and show an even stronger dependence on the genetic background