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Steven Winters-Hilt

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As a candidate species for aquaculture in Southern California, genomic resources are necessary to accelerate the development of Seriola dorsalis aquaculture. With knowledge of genetic basis behind locally adapted traits between wild populations of important aquaculture species, individuals that possess these valuable phenotypes can be used for selective breeding in aquaculture. In this study, a population genomic tool, Bayescan version 2.1, was implemented on a dataset of 76,974 loci of SNPs found within the genome of S. dorsalis, in order to search for loci being selected for based on allele frequencies between the three populations. No loci were found to have a probability of being naturally selected for higher than 11.042%, which does not provide any evidence of locally adapted, population specific traits that could be exploited through selective breeding in aquaculture. Based on these results, any fish taken from the region surrounding the three sample locations would possess similar traits, and the three populations can be managed as one.



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