An understanding of the mechanisms that generate and maintain biodiversity is fundamental in current biological research, both from a fundamental and an applied viewpoint. In this project, we address how the interplay between environmental heterogeneity and breeding system variation affect diversity at multiple levels of biological organization. Using the model organism Caenorabditis elegans and the powerful tool of experimental evolution, we propose to test hypotheses concerning the maintenance of polymorphisms in environments where resources are spatially heterogenous.
Specifically, we will investigate:
(1) whether adaptation to different resources entails fitness trade-offs;
(2) how density regulation at different levels affect the maintenance of genetic diversity and
(3) whether the occurrence of an out-crossing mode of reproduction hampers the maintenance of polymorphisms due to recombination among locally-adapted populations.
Moreover, we aim at tackling the genetics underlying the process, using the molecular biology technology available for studying this organism. We will follow the evolution of replicate populations during fifty generations for characters related to fitness and also gene diversity at the molecular level. Predominantly selfing and exclusively out-crossing populations of C. elegans are already established at the host institution. This project comes as a follow-up of the research carried out by the candidate during her post-doctoral studies, and matches perfectly with the research of the host institution as well as with its long-term aims. We expect that the results from this project will contribute decisively to evolutionary theory epical verification. The fellow will take this opportunity to return to her country of origin and set paths for an independent research career in Portugal.
Field of science
- /natural sciences/biological sciences/molecular biology
- /medical and health sciences/basic medicine/pharmacology and pharmacy/drug resistance
- /natural sciences/computer and information sciences/artificial intelligence/computational intelligence
Call for proposal
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