Department of Biology, University of Central Florida, Genomics and Bioinformatics Cluster, Orlando, FL, United States of America.
PLoS One. 2022 Jun 17;17(6):e0266720. doi: 10.1371/journal.pone.0266720. eCollection 2022.
Metabarcoding of environmental DNA is increasingly used for biodiversity assessments in aquatic communities. The efficiency and outcome of these efforts are dependent upon either de novo primer design or selecting an appropriate primer set from the dozens that have already been published. Unfortunately, there is a lack of studies that have directly compared the efficacy of different metabarcoding primers in marine and estuarine systems. Here we evaluate five commonly used primer sets designed to amplify rRNA barcoding genes in fishes and compare their performance using water samples collected from estuarine sites in the highly biodiverse Indian River Lagoon in Florida. Three of the five primer sets amplify a portion of the mitochondrial 12S gene (MiFish_12S, 171bp; Riaz_12S, 106 bp; Valentini_12S, 63 bp), one amplifies 219 bp of the mitochondrial 16S gene (Berry_16S), and the other amplifies 271 bp of the nuclear 18S gene (MacDonald_18S). The vast majority of the metabarcoding reads (> 99%) generated using the 18S primer set assigned to non-target (non-fish) taxa and therefore this primer set was omitted from most analyses. Using a conservative 99% similarity threshold for species level assignments, we detected a comparable number of species (55 and 49, respectively) and similarly high Shannon's diversity values for the Riaz_12S and Berry_16S primer sets. Meanwhile, just 34 and 32 species were detected using the MiFish_12S and Valentini_12S primer sets, respectively. We were able to amplify both bony and cartilaginous fishes using the four primer sets with the vast majority of reads (>99%) assigned to the former. We detected the greatest number of elasmobranchs (six species) with the Riaz_12S primer set suggesting that it may be a suitable candidate set for the detection of sharks and rays. Of the total 76 fish species that were identified across all datasets, the combined three 12S primer sets detected 85.5% (65 species) while the combination of the Riaz_12S and Berry_16S primers detected 93.4% (71 species). These results highlight the importance of employing multiple primer sets as well as using primers that target different genomic regions. Moreover, our results suggest that the widely adopted MiFish_12S primers may not be the best choice, rather we found that the Riaz_12S primer set was the most effective for eDNA-based fish surveys in our system.
环境 DNA 的代谢条形码技术越来越多地用于水生生物群落的生物多样性评估。这些工作的效率和结果取决于从头设计引物或从已经发表的数十个引物中选择合适的引物。不幸的是，很少有研究直接比较不同代谢条形码引物在海洋和河口系统中的效果。在这里，我们评估了五个常用于扩增鱼类 rRNA 条形码基因的通用引物集，并使用从佛罗里达州高度生物多样性的印度河泻湖河口采集的水样比较它们的性能。五个引物集中的三个扩增了线粒体 12S 基因的一部分（MiFish_12S，171bp；Riaz_12S，106bp；Valentini_12S，63bp），一个扩增了线粒体 16S 基因的 219bp（Berry_16S），另一个扩增了核 18S 基因的 271bp（MacDonald_18S）。使用 18S 引物生成的绝大多数代谢条形码读数（>99%）分配给非目标（非鱼类）分类群，因此该引物集在大多数分析中被忽略。使用物种水平分配的保守 99%相似性阈值，我们检测到数量相当的物种（分别为 55 种和 49 种）和同样高的 Shannon 多样性值，对于 Riaz_12S 和 Berry_16S 引物集。同时，仅使用 MiFish_12S 和 Valentini_12S 引物集分别检测到 34 种和 32 种。我们能够使用四个引物集扩增硬骨鱼和软骨鱼，其中绝大多数读数（>99%）分配给前者。我们使用 Riaz_12S 引物集检测到的鲨鱼和鳐鱼数量最多（六种），这表明它可能是检测鲨鱼和鳐鱼的合适候选引物集。在所有数据集共鉴定的 76 种鱼类中，组合的三个 12S 引物集检测到 85.5%（65 种），而 Riaz_12S 和 Berry_16S 引物的组合检测到 93.4%（71 种）。这些结果强调了使用多个引物集以及使用靶向不同基因组区域的引物的重要性。此外，我们的结果表明，广泛采用的 MiFish_12S 引物可能不是最佳选择，相反，我们发现 Riaz_12S 引物集是我们系统中基于 eDNA 的鱼类调查最有效的引物。
