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Journal Article

Quantitative Genetics in Natural Plant Populations: A Review of the Theory

Thomas Mitchell-Olds and J. J. Rutledge
The American Naturalist
Vol. 127, No. 3 (Mar., 1986), pp. 379-402
Stable URL: http://www.jstor.org/stable/2461406
Page Count: 24
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Quantitative Genetics in Natural Plant Populations: A Review of the Theory
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Abstract

The methods of quantitative genetics may be useful for quantifying constraints on the rate and direction of response to selection in natural plant populations. We review the assumptions necessary for accurate estimation and significance testing of quantitative-genetic parameters, and consider when such estimates may accurately predict a response to selection. Estimates of heritabilities and genetic correlations can provide good predictions of a long-term response to selection if (1) such estimates are reasonably accurate; (2) many genes contribute to genetic variances and covariances; (3) genetic variance-covariance matrices remain approximately constant through time (when major genes are important sources of variation, when selection is strong, or when populations are small, then rapid alterations in gene frequencies may occur, with consequent changes in the quantitative-genetic parameters); (4) genotype-environment interaction does not alter genetic parameters in new or unmeasured environments; and (5) populations are not inbred. The importance of these assumptions depends on the evolutionary scale of the questions we wish to ask. We discuss evolutionary interpretations of heritabilities and genetic correlations, emphasizing that the plasticity of quantitative-genetic parameters and the imprecision of their estimates are serious problems in the study of natural plant populations. It is important to separate the fundamental, long-term genetic constraints, which limit species evolution, from the transient genetic correlations that may be found in a particular population. It is unclear whether natural populations ever reach equilibrium conditions, in which the additive genetic variance for fitness is depleted. Under many circumstances it is difficult to deduce the past history of selection from the genetic architecture of metrical traits.

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