Format

Send to

Choose Destination
Evolution. 2018 Oct;72(10):2167-2180. doi: 10.1111/evo.13585. Epub 2018 Sep 5.

Bayesian updating during development predicts genotypic differences in plasticity.

Author information

1
Department of Evolution and Ecology, University of California, Davis, California 95616.
2
Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria 3216, Australia.
3
Department of BioSciences, Rice University, Houston, Texas 77005.

Abstract

Interactions between genotypes and environments are central to evolutionary genetics, but such interactions are typically described, rather than predicted from theory. Recent Bayesian models of development generate specific predictions about genotypic differences in developmental plasticity (changes in the value of a given trait as a result of a given experience) based on genotypic differences in the value of the trait that is expressed by naïve subjects. We used these models to make a priori predictions about the effects of an aversive olfactory conditioning regime on the response of Drosophila melanogaster larvae to the odor of ethyl acetate. As predicted, across 116 genotypes initial trait values were related to plasticity. Genotypes most strongly attracted to the odor of ethyl acetate when naïve reduced their attraction scores more as a result of the aversive training regime than those less attracted to the same odor when naïve. Thus, as predicted, the variance across genotypes in attraction scores was higher before than after the shared experience. These results support predictions generated by Bayesian models of development and indicate that such models can be successfully used to investigate how variation across genotypes in information derived from ancestors combines with personal experience to differentially affect developmental plasticity in response to specific types of experience.

KEYWORDS:

Aversive conditioning; Drosophila melanogaster; GxE; developmental plasticity; learning

PMID:
30133698
DOI:
10.1111/evo.13585

Supplemental Content

Loading ...
Support Center