Biology Faculty Articles


Come together: calibration of tiger shark (Galeocerdo cuvier) microsatellite databases for investigating global population structure and assignment of historical specimens

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Conservation Genetics Resources


Population genetics, Tiger sharks, Microsattelite data, Calibration, Global conservation, Archived DNA



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This study provides the first standardized global microsatellite database for a shark species, the tiger shark (Galeocerdo cuvier). Genotyping of reference individuals was used to develop and apply a calibration key for data from eight microsatellite loci data produced by three different laboratories, thereby allowing merging of genotypes into a single dataset. The unified data helped to elucidate the global population structure of the species and provided improved statistical power, through allowing a higher number of samples per location compared to the original studies from which the samples were obtained. Pairwise FST estimates and PCA plots showed significant genetic differentiation between Atlantic and Indo-Pacific samples, confirming previous findings by identifying the presence of a strong genetic break between tiger sharks inhabiting the two ocean basins. In turn, the standardized database (n = 799) also allowed archived historical samples to be genotyped and assigned back to their population (ocean basin) of origin. We demonstrate how calibration tests in population structure studies using microsatellite data is important as it simply provides more data to single studies. Importance factors for successful assignment analysis is discussed, as well as how the possibility of assigning historical samples of unknown origin back to the population, increases sample value. Our results demonstrate that global calibration of microsatellite and other genetic datasets can improve the statistical power and resolution of population structure analysis; an approach applicable not only when working with highly mobile globally distributed species such as the tiger shark, but with any species for which multiple genetic datasets exist.


We wish to thank all the researchers, institutes and museums that provided us with samples that were crucial for the completion of this study: Smithsonian Institution National Museum of Natural History, Florida Museum of Natural History, Virginia Institute of Marine Science, National Oceanic and Atmospheric Administration (NOAA, Rhode Island), Harvard Museum of Comparative Zoology, Dr. Austin Gallagher (Beneath the Waves), Dr. Javier Quesada (Natural Sciences Museum of Barcelona), Dr. Peter Rask Møller (Natural History Museum of Denmark), and Dr. Stefan Merker (State Museum of Natural History Stuttgart). We also wish to thank Romina Henriques for valuable comments on a previous draft. Finally, we are grateful to all of the laboratory technicians at DTU (Maj-Britt Jacobsen and Camilla Kristensen) for their help in carrying out the lab work.







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