Abstracts (first author)

Talk 

Understanding the relationship between natural and sexual selection using the evolve and resequence approach in a non-model insect

Author(s): Chenoweth S, Appleton N, Rundle H

Summary:

Sexual selection is a source of strong directional selection in nature that has received long-standing attention due to its role in the evolution of elaborate sexual ornaments and armaments. Although its contribution to the evolution of sexual traits is uncontroversial, the way in which sexual selection works alongside natural selection, specifically, whether the process favors similar or different allelic variants to natural selection, remains poorly understood. To address this question we assessed the genome-wide response from standing variation to natural and sexual selection using experimental evolution in a fly. RAD-seq sequencing was applied to replicate experimental populations of Drosophila serrata that were allowed to adapt to a novel environment over sixteen generations. Each line was randomly assigned to one of four experimental treatments that reflected a full factorial manipulation of the opportunity for natural and sexual selection. Our analysis of the genomic response suggests that the interaction between natural and sexual selection can lead to contrasting allele frequency trajectories compared to when either process operates alone. In the course of outlining our study I will address some of the statistical challenges posed by the analysis of “evolve and resequence” studies that are short-term and often involve highly polygenic responses. This will include our application of multivariate tools and generalised linear mixed effects models to experimental evolution data.



Contacts

Chairman: Octávio S. Paulo
Tel: 00 351 217500614 direct
Tel: 00 351 217500000 ext22359
Fax: 00 351 217500028
email: mail@eseb2013.com

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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