Abstracts (first author)


Characterizing and tracking MHC variation of chyrtridiomycosis affected Chiricahua leopard frogs over time in natural populations


Author(s): Mulder KP, Savage AE


The amphibian disease chytridiomycosis caused by the fungus Batrachochytrium dendrobatidis (Bd) has contributed to the decline and extirpation of numerous populations of Chiricahua leopard frogs (Lithobates chiricahuensis), an endangered species native to the Southwestern United States and Northern Mexico. Conservation efforts have focused on captive rearing of wild-caught egg masses and subsequent release following metamorphosis (called head-starting) to increase population sizes across the species range. The survival rate of released individuals is, however, heavily dependent on their ability to combat chytridiomycosis. In captivity, populations of other species of leopard frogs show differential survival to experimental Bd infections dependent on their genetic variation in the major histocompatability complex (MHC), a highly variable gene family in vertebrates known to be important in pathogen resistance. We used single locus 454 pyrosequencing to characterize MHC genetic variation in head-started Chiricahua leopard frogs that will be released and monitored for one year to determine survival rates and identify alleles that confer an advantage against Bd in a natural environment. This information will be used to identify candidate resistance alleles and add MHC-based marker assisted selection to captive breeding efforts, with the goal of increasing the success rate of head-starting efforts and mitigating the impact of Bd on natural populations of both Chiricahua leopard frogs as well as other amphibian species affected by chrytridiomycosis. This is a case study of how evolutionary genetic analyses of adaptive markers can assist conservation efforts in captive breeding.

Abstracts (coauthor)


Adaptive genetic variation is central to the survival of endangered populations, because it forms the evolutionary potential to respond to future challenges in a changing environment. Divergence in genetic variation among populations, however, has significant implications for conservation purposes. We here present a classical applied conservation biology question and base our answer on evolutionary concepts like selection, drift and adaptation: In Ireland, the Red grouse (Lagopus lagopus scoticus) is believed to be in risk of extinction, whereas it is rather abundant in Scotland and England. It has been proposed to restock the fragmented Irish populations with individuals from Scotland. We address the question whether Red grouse populations in Ireland and Scotland show significant divergence in adaptive genetic variation. If so, they should be recognized as separated evolutionary lineages for conservation purposes. Using 454-pyrosequencing we analysed immune genes of the MHC class II (Major histocompatibility complex), which are popular candidate genes to study adaptive genetic diversity due to their key role in many biological processes like pathogen resistance and mate choice. We compared the results with a study on neutral microsatellite variation to distinguish between genetic drift and selection. We found clear footprints of selection acting on the MHC genes, as well as variation in the number of gene copies, another classical feature of MHC evolution. The differentiation of adaptive genetic variation between Ireland and Scotland was strong with an Fst of 0.11, and significantly higher than differentiation based on neutral microsatellite variation with an Fst of 0.068. Thus, we conclude that these large differences in adaptive genetic variation are not due to drift and we advise against the introduction of Scottish Red grouse to supplement Irish populations. Instead we propose that efforts should be made to increase gene flow between Irish subpopulations.


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


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