Population structure and genetic stock identification in southeastern United States loggerhead sea turtles (Caretta caretta) using genome-wide SNPs

Abstract

Characterizing the genetic structure and connectivity between populations of endangered species can be used to inform management actions. In vagile species with high gene flow or recently established populations, such characterizations can be difficult to undertake using traditional genetic markers, and genetic stock identification (GSI) may be confounded by allele-sharing between populations. Loggerhead sea turtles ( Caretta caretta ) in the southeastern United States comprise seven management units (MUs) based on female philopatry inferred via mitochondrial DNA sequences, yet nuclear microsatellite data do not reflect divergence. Further, loci for accurate GSI are not currently known. To address this, we generated genome-wide single nucleotide polymorphism (SNP) data from 146 females nesting at individual sites representative of each southeastern United States MU. We found weak (F ST =0.001–0.003) but significant divergence among all MUs, with more notable divergence between the Gulf Coast and Atlantic Ocean MUs, and amongst the Atlantic Ocean MUs. We then used an iterative leave-one-out approach to identify candidate loci for GSI. This approach identified loci that could assign individuals to natal ocean basins (i.e., to the Gulf Coast or to the Atlantic Ocean), and to individual MUs within the Atlantic Ocean, with high (≥90%) success and accuracy. Analyses of genome-wide SNPs refined our understanding of the magnitude and scale of population connectivity in loggerhead turtles in the southeastern United States, and provided a foundation for the development of SNP panels for accurate, fine-scale GSI in sea turtles.

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