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Efficacy of metabarcoding for identification of fish eggs evaluated with mock communities

TitleEfficacy of metabarcoding for identification of fish eggs evaluated with mock communities
Publication TypeJournal Article
Year of Publication2020
AuthorsDuke E.M, Burton RS
Date Published2020/03
Type of ArticleArticle; Early Access
ISBN Number2045-7758
Accession NumberWOS:000517753600001
Keywords16S; bias; cytochrome oxidase subunit I; DNA; Environmental Sciences & Ecology; Evolutionary Biology; fish egg surveys; ichthyoplankton; metabarcoding; san-diego

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative than that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study, we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition, we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions; however, levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however, the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management.

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