Department of Biology, University of Central Florida, Orlando, FL, USA.
Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Integr Comp Biol. 2022 Aug 25;62(2):223-236. doi: 10.1093/icb/icac080.
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.
绿海龟（Chelonia mydas）是一种分布广泛的物种，其食性范围很广，因地区和生活史阶段而异。全面了解其空间和时间觅食生态学对于指导该物种及其栖息地的保护和管理至关重要。在这里，我们使用 DNA 代谢组学对来自搁浅绿海龟（佛罗里达州，美国）的 39 个肠道内容物匀浆进行了 39 个候选引物组合的测试，以确定能够最大程度检测食物的引物组合，并提高分类学分类的特异性。我们测试了六个现有的通用引物组合，以更广泛地检测植物、动物和真核生物（CO1、18SV1-V3、18SV4、rbcL、UPA、ITS）。CO1 和 18SV4 引物组合产生了最多的饮食扩增子序列变异（ASVs）和独特的分类学分类，它们是唯一能够扩增与绿海龟饮食相关的所有三个领域（动物界、Chromista 和植物界）的分类群的引物组合。尽管大多数 CO1 衍生的读数来自宿主（>90%），但该引物组合在六个引物组合中仍然产生了最多被分类为物种的饮食 ASVs。然而，由于 CO1 引物组合未能检测到维管束植物和绿藻，因此我们不建议单独使用该引物组合来描述绿海龟的饮食。相反，我们的研究结果支持了先前的研究，强调了使用多个引物组合的实用性，特别是针对 CO1 和 18S 基因 V4 区域，因为这样做将提供对绿海龟饮食最全面的了解。更普遍地说，我们的研究结果强调了引物和基因座选择的重要性，以及需要针对研究系统验证引物组合。将优化引物组合的 DNA 代谢组学添加到海龟研究人员的工具包中，将增加我们对觅食生态学的了解，并更好地为基于科学的保护和生态系统管理提供信息。
