科研之友
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摘要
The breeder's equation is a cornerstone of quantitative genetics, widely used in evolutionary modeling. Noting the mean phenotype in parental, selected parents, and the progeny by E(Z(0)), E(Z(W)), and E(Z(1)), this equation relates response to selection R = E(Z(1)) - E(Z(0)) to the selection differential S = E(Z(W)) - E(Z(0)) through a simple proportionality relation R = h(2)S, where the heritability coefficient h(2) is a simple function of genotype and environment factors variance. The validity of this relation relies strongly on the normal (Gaussian) distribution of the parent genotype, which is an unobservable quantity and cannot be ascertained. In contrast, we show here that if the fitness (or selection) function is Gaussian with mean mu, an alternative, exact linear equation of the form R ' = j(2)S ' can be derived, regardless of the parental genotype distribution. Here R ' = E(Z(1)) - mu and S ' = E(Z(W)) - mu stand for the mean phenotypic lag with respect to the mean of the fitness function in the offspring and selected populations. The proportionality coefficient j(2) is a simple function of selection function and environment factors variance, but does not contain the genotype variance. To demonstrate this, we derive the exact functional relation between the mean phenotype in the selected and the offspring population and deduce all cases that lead to a linear relation between them. These results generalize naturally to the concept of G matrix and the multivariate Lande's equation Delta z over bar =GP-1S. The linearity coefficient of the alternative equation are not changed by Gaussian selection.
- 出版日期2014-1
