Optimizing a metabarcoding marker portfolio for species detection from complex mixtures of globally diverse fishes

Author:

Baetscher Diana S.1ORCID,Locatelli Nicolas S.1,Won Eugene2,Fitzgerald Timothy3,McIntyre Peter B.1,Therkildsen Nina Overgaard1

Affiliation:

1. Department of Natural Resources and the Environment Cornell University Ithaca New York USA

2. Department of Animal Science Cornell University Ithaca New York USA

3. Environmental Defense Fund Washington District of Columbia USA

Abstract

AbstractDNA metabarcoding is used to enumerate and identify taxa in both environmental samples and tissue mixtures, but the effectiveness of particular markers depends on their sensitivity to the taxa involved. Using multiple primer sets that amplify different genes can mitigate biases in amplification efficiency, sequence resolution, and reference data availability, but few empirical studies have evaluated markers for complementary performance. Here, we assess the individual and joint performance of 22 markers for detecting species in a DNA pool of 98 species of marine and freshwater bony fishes from geographically and phylogenetically diverse origins. We find that a portfolio of four markers targeting 12S, 16S, and two regions of COI identifies 100% of reference taxa to family and nearly 60% to species. We then use these four markers to evaluate metabarcoding of heterogeneous tissue mixtures, using experimental fishmeal to test: (1) the tissue input threshold to ensure detection; (2) how read depth scales with tissue abundance; and (3) the effect of non‐target material in the mixture on recovery of target taxa. We consistently detect taxa that makeup >1% of fishmeal mixtures and can detect taxa at the lowest input level of 0.01%, but rare taxa (<1%) were detected inconsistently across markers and replicates. Read counts showed only a weak correlation with tissue input, suggesting they are not a reliable quantitative proxy for relative abundance. Despite the limitations arising from primer specificity and reference data availability, our results demonstrate that a modest portfolio of markers can perform well in detecting and identifying aquatic species in complex mixtures despite heterogeneity in tissue representation, phylogenetic affinities, and from a broad geographic range.

Funder

Cornell Atkinson Center for Sustainability, Cornell University

David and Lucile Packard Foundation

Publisher

Wiley

Subject

Genetics,Ecology,Ecology, Evolution, Behavior and Systematics

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