Abstracts (first author)

Poster 

Will kids be what grandparents ate? Transgenerational effects of different food quality revealed by Daphnia

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Author(s): Wojewodzic MW

Summary:

Daphnia are well known for their developmental plasticity, with phenotype modified as a consequence of parental environment, and this can be inherited through multiple generations despite clonal propagation. We examined whether multigenerational exposure of cladocerans to phosphorus (P) limitation alters the responses of the two next generations. Two clonal isolates, D.magna and D.pulex, were fed two standardized food quality (high and low carbon: phosphorus ratio) over 20 generations, resulting in four distinct lines. In reciprocal transplant experiment, we analysed a number of fitness-related traits for both daughters and grand-daughters of these lines. We focused on somatic growth rate, body RNA concentration (body growth rate marker), and the activity of alkaline phosphatase (phosphorus acquisition mechanism). As predicted by the Growth Rate Hypothesis, P-limitation had a strong negative effect on somatic growth rate, irrespectively of the species and line history. Here, we present evidence that food quality may have induced the transgenerational effects on somatic growth rate for one of the species used. The line origin for D.magna was highly significant for the diet response. Moreover, we found a significant interaction between diet type and line, which provides strong support for transgenerational effect. The responses were strong for D.magna but not for D.pulex, reflecting their different susceptibility to P-limitation. We also found a significant decrease in alkaline phosphatase activity related to multigenerational P-limitation stress. Currently RNA sequencing is performed to reveal the transcriptomic response underlying the observed responses.



Contacts

Chairman: Octávio S. Paulo
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Address

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
Portugal

Website

Computational Biology & Population Genomics Group 
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