Abstracts (first author)


Multifunctional vitellogenin – Can the evolution of a pleiotropic gene be linked to the domain architecture of its protein product?

Author(s): Havukainen H, Amdam GV


How do single proteins perform a broad range of tasks, and how can evolution act on pleiotropic genes/proteins? Vitellogenin is a multitask protein mostly associated with its egg-yolk function. It transports lipids to the egg and provides a source of amino acids for the embryo, and this function is conserved across several taxa. However, in the honey bee workers, vitellogenin is also a central life-history regulator that supports immune cell viability, protects against oxidative stress, and suppresses risky foraging behavior. It is expressed in queens, workers and males. In fish, this egg-yolk protein has bactericidal effects and is overexpressed in infected females and males. The key to this multifunctionality may lie in the evolution and diversity of specific structural domains. Typical structural elements of vitellogenins are, among others, N-sheet, alpha-helical and the vertebrate phosvitin domain. The latter has been pinpointed as the bactericidal actor in fish. In the honeybee, it is known that different vitellogenin domains are evolving under differing selection pressure, the putative receptor-binding N-sheet being more conserved than the other parts of the sequence. Furthermore, honeybee vitellogenin is a structurally adjustable protein that can shed the N-sheet domain. We have identified the alpha-helical domain as a membrane-binding region. Using the methods of cell and molecular biology, we show that the membrane-binding can be linked to vitellogenin’s antioxidative and putative anti-inflammatory functions in the honey bee. Thus, research on protein domains can facilitate understanding the evolution of pleiotropic genes such as vitellogenin.


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