Abstracts (first author)


The information value of non-genetic inheritance in heterogeneous environments

Author(s): English S, Shea N, Pen I, Uller T


Parents contribute a variety of inputs to the development and fitness of their offspring beyond the transmission of DNA, including epigenetic marks, transfer of nutrients, antibodies and hormones, and behavioural interactions after birth. The evolutionary consequences of such non-genetic inheritance have been explored recently. By disconnecting what is selected from what is inherited, non-genetic inheritance can modify the course of evolution and selection on future generations. Less is known, however, about how mechanisms of non-genetic inheritance have themselves evolved. Here, we present a simple model to explore the adaptive evolution of non-genetic inheritance under different regimes of environmental change. Our model is based on a developmental switch that can evolve to produce different phenotypes in response to different levels of input. We consider genetic and non-genetic inputs as potential cues containing correlational information about coming selective conditions. Differential use of these cues is manifested as different degrees of genetic, parental or environmental morph determination. By exploring a range of temporal and spatial environmental fluctuation scenarios (cyclic and stochastic, of varying frequency), we evaluate the conditions that favour non-genetic inheritance as opposed to genetic determination of phenotype or within-generation plasticity. Finally, we use the model to exemplify three case studies which have provided hallmark examples of non-genetic inheritance: maternal effects on seed germination in plants, transgenerational phase shift in desert locusts and grandparental effects on dispersal polymorphisms in aphids.


Chairman: Octávio S. Paulo
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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group