five

Metabarcoding primers for Indo-Pacific fishes

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.dr7sqvbbf
下载链接
链接失效反馈
官方服务:
资源简介:
Environmental DNA (eDNA) metabarcoding offers an effective solution to determine fish species compositions in communities across diverse environments. However, it is not clear how different metabarcoding primers perform in terms of recovering fish species and community diversity in the Indo-Pacific bioregion. In this study, we compared the relative performance of five metabarcoding primers (Berry 16S, Riaz 12S, MiFish E 12S, MiFish U 12S, and Leray CO1) in recovering Indo-Pacific fish taxa. We tested the primers using template DNA from three different environments: (1) a controlled mock community composed of tissue-based DNA extractions from 96 species, (2) a semi-controlled Indo-Pacific reef fish community from a public aquarium tank, and (3) a natural tropical coral reef lagoon. In the mock community sample, each primer recovered a distinct subset of the community, and no single primer recovered all taxa. Of the 65 distinct genera included in the mock community, all but six were recovered by at least one primer, representing 91% of genera. Fifty-nine of the 96 included species (61%) were identified to species-level using at least one primer set. From the aquarium community, 17 of the 20 known genera were recovered (85%), and 13 out of 24 (54%) censused species were identified by at least one primer. In the coral reef lagoon 48 genera were identified, and 47 species-level identifications were made, including 87% endemic and established species. Overall, we find Riaz 12S performed better than other fish-specific markers although there were differences in the specific fish taxa recovered. While all markers performed well in the mock community in terms of the relative proportion of fish sequences recovered, this did not accurately predict how they would perform under natural conditions. Caution is therefore urged in using a mock community alone to evaluate metabarcoding primer performance for studies in natural environments.
创建时间:
2025-10-16
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作