Sea Snacks from DNA Tracks: Using DNA Metabarcoding to Characterize the Diet of Green Turtles (Chelonia Mydas)

Synopsis The green turtle (Chelonia mydas) is a circumglobal species with a wide dietary breadth that varies among regions and life history stages. Comprehensive understanding of foraging ecology over space and time is critical to inform conservation and management of this species and its habitats. Here, we used DNA metabarcoding to test candidate primer sets with 39 gut content homogenates from stranded green turtles (FL, USA) to identify primer sets that maximize detection of food items and specificity of taxonomic classifications. We tested six existing universal primer sets to detect plants, animals, and eukaryotes more broadly (CO1, 18SV1-V3, 18SV4, rbcL, UPA, ITS). The CO1 and 18SV4 primer sets produced the greatest number of dietary amplicon sequence variants (ASVs) and unique taxonomic classifications, and they were the only primer sets to amplify taxa from all three kingdoms relevant to green turtle diet (Animalia, Chromista, and Plantae). Even though the majority of CO1-derived reads were of host origin (>90%), this primer set still produced the largest number of dietary ASVs classified to species among the six primer sets. However, because the CO1 primer set failed to detect both vascular plants and green algae, we do not recommend the use of this primer set on its own to characterize green turtle diet. Instead, our findings support previous research highlighting the utility of using multiple primer sets, specifically targeting CO1 and the V4 region of the 18S gene, as doing so will provide the most comprehensive understanding of green turtle diet. More generally, our results highlight the importance of primer and loci selection and the need to validate primer sets against the study system of interest. The addition of DNA metabarcoding with optimized primer sets to the sea turtle researcher's toolbox will both increase our understanding of foraging ecology and better inform science-based conservation and ecosystem management.