Genetic Mechanisms Underlying the Baldwin Effect Are Evident in Natural Antibodies

J.M. Baldwin theorized that individual learning allows an organism to exploit genetic variations that only partially determine a physiological structure; consequently, useful genetic variations are increased in subsequent generations. Theoretical studies have demonstrated the Baldwin effect in the evolution of simulated neural networks and in quantitative genetics models. Heretofore, it has not been shown how the Baldwin effect is manifested in the genetics of a specific biological system. The adaptive antibody population has all the requisite elements of a learning system, and as theorized by Baldwin, this ability to learn can facilitate the evolution of other structures. I show how the adaptive antibody population facilitates the evolution of a separate, genetically-determinant antibody population, responsible for natural antibodies. Both natural and adaptive antibodies are constructed from a common library of gene segments. Natural antibodies, however, express a restricted set of the gene segment libraries. There are two competing theories for the mechanisms of biased gene usage: the “proximal usage” hypothesis and “preferential expression” hypothesis. The genetic manifestation of the Baldwin effect in the 1g genes depends on the mechanism of gene expression. Under the proximal usage hypothesis, the Baldwin effect is a direct consequence of quantitative genetics. Under the preferential expression hypothesis, gene segments in the parental genes can become marked for preferential expression in the natural antibody population of their offspring. This system is ideal for experimental and modeling studies of the interactions between learning and evolution.