Genetics, Vol. 149, 2119-2133, August 1998, Copyright © 1998

Canalization, Genetic Assimilation and Preadaptation: A Quantitative Genetic Model

Ilan Eshela and Carlo Matessib
a Department of Statistics, School of Mathematics, Tel Aviv University, 69978 Tel Aviv, Israel
b Istituto di Genetica Biochimica ed Evoluzionistica, Consiglio Nazionale delle Ricerche, 27100 Pavia, Italy

Corresponding author: Carlo Matessi, Istituto di Genetica Biochimica ed Evoluzionistica, Consiglio Nazionale delle Ricerche, Via Abbiategrasso 207, 27100 Pavia, Italy., matessi{at}ipvgbe.igbe.pv.cnr.it (E-mail).

Communicating editor: M. K. UYENOYAMA

We propose a mathematical model to analyze the evolution of canalization for a trait under stabilizing selection, where each individual in the population is randomly exposed to different environmental conditions, independently of its genotype. Without canalization, our trait (primary phenotype) is affected by both genetic variation and environmental perturbations (morphogenic environment). Selection of the trait depends on individually varying environmental conditions (selecting environment). Assuming no plasticity initially, morphogenic effects are not correlated with the direction of selection in individual environments. Under quite plausible assumptions we show that natural selection favors a system of canalization that tends to repress deviations from the phenotype that is optimal in the most common selecting environment. However, many experimental results, dating back to WADDINGTON and others, indicate that natural canalization systems may fail under extreme environments. While this can be explained as an impossibility of the system to cope with extreme morphogenic pressure, we show that a canalization system that tends to be inactivated in extreme environments is even more advantageous than rigid canalization. Moreover, once this adaptive canalization is established, the resulting evolution of primary phenotype enables substantial preadaptation to permanent environmental changes resembling extreme niches of the previous environment.





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