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L of the population does not mutate, and of these, a group described by p't(x,y) survives to contribute to the next generation. L that mutates, individuals will have phenotypes (x,y) if they started with phenotype (u,v), survived selection, and mutated from (u,v) to (x,y). Stating the model in this way, it is clear that the distribution of allelic effects, which is described as the genetic covariance matrix in a Gaussian setting, is a mixture distribution of bivariate distributions. Although approximations can be made to obtain a bivariate Gaussian distribution from this, Turelli (1986) provides compelling Feasons to attempt analyses without a Gaussian assumption.

A typ- I Department of Biology, Pennsylvania State University, University Park, PA 16802, USA Genetic Constraints on Adaptive Evolution Ed. by V. G. Clark ical quantitative genetic study will manifest the effects of this type of linkage or pleiotropy as a genetic correlation. A simple sib analysis or artificial selection experiment will not reveal whether the genetic correlation is due to linkage or pleiotropy, but the consequences of these two mechanistically distinct genetic constraints could be quite different.

8) Wt The first term on the right is the distribution of non-mutants after selection, and g(x) is the distribution of allelic effects of mutants. It is clear that g(x) is independent of the premutation state. After a number of approximations, Turelli (1984) derives the result that the equilibrium genetic variance in the n-Iocus house-of-cards model is (9) This result is also obtained for the n-diallelic locus approximation to the Gaussian model (Latter 1960; Bulmer 1972), and in both cases it is assumed that the n loci are equally mutable and are in global linkage equilibrium.

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