Abstracts (first author)

Poster 

Genetic changes underlying host plant resistance in Drosophila sechellia

Author(s): Bolivar Balbas P, Matute DR, Hartl DL, Ayroles JF

Summary:

The genetic basis of adaptation is a major question in evolutionary biology. In particular, ecological specialization can result from rapid host shifts and strong selective forces. Although most Drosophila species are generalists, D. sechellia a species endemic to the Seychelles archipelago is one such specialist species. D. sechellia feeds and breed almost exclusively on Morinda citrifolia, and its fruit commonly known as noni. M. citrifolia produces several volatile compounds which are toxic for most arthropod species and all closely related Drosophila species. Nonetheless, D. sechellia has evolved resistance and host preferences that include stimulation of egg production, oviposition site preference and chemotaxis. To understand how this suite of host specialization traits evolved, it is important to dissect the underlying genetic basis of these phenotypes. QTL mapping is an important tool for the study of such complex traits. In order to detect and localize loci that influence resistance to M. Citrifolia, we use bulk segregant mapping approaches, based on backcrosses between D. sechellia and its sister species D. simulans (which is sensitive to Noni) and use by deep sequencing to identify QTL regions. We combine this approach with genome scans, based on light coverage sequencing of over 250 isofemale lines of D. Sechellia and D. Simulans derived from recent field collections in the Seychelles. This approach allows us to unravel the genetic characteristics that allow D. sechellia to contend with the toxic compounds that are otherwise lethal to close relatives.



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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