You are here:
DNA metabarcoding-based identification of fish larvae for invasive species early detection
Citation:
Hoffman, J., C. Meredith, E. Pilgrim, A. Trebitz, C. Hatzenbuhler, J. Kelly, G. Peterson, J. Lietz, S. Okum, AND J. Martinson. DNA metabarcoding-based identification of fish larvae for invasive species early detection. Upper Midwest Invasive Species Conference, Duluth, MN, November 02 - 06, 2020. https://doi.org/10.23645/epacomptox.13231910
Impact/Purpose:
Under the Great Lakes Water Quality Agreement, there is a commitment for a bi-national program for aquatic invasive species early detection surveillance Great Lakes-wide. When initially introduced, invasive species typically evade detection because they are present at low density and occupy a small area; DNA metabarcoding (i.e., DNA barcoding coupled with high-throughput sequencing, or HTS) may be both more sensitive and accurate than morphology-based taxonomy, and thus has the potential to increase detection of rare or invasive species. We quantified the relative error of species presence results between morphology-based and HTS-based taxonomic identification of ichthyoplankton collections from the Port of Duluth, Minnesota, an aquatic non-native species introduction ‘hot-spot’ in the Laurentian Great Lakes, and compared HTS-based detection to existing early detection surveys. The study demonstrates the importance of formal benchmarking novel taxonomic methods for large-scale biodiversity surveys.
Description:
When initially introduced, invasive species typically evade detection because they are present at low density and occupy a small area; DNA metabarcoding (i.e., DNA barcoding coupled with high-throughput sequencing, or HTS) may be both more sensitive and accurate than morphology-based taxonomy, and thus has the potential to increase detection of rare or invasive species. We quantified the relative error of species presence results between morphology-based and HTS-based taxonomic identification of ichthyoplankton collections from the Port of Duluth, Minnesota, an aquatic non-native species introduction ‘hot-spot’ in the Laurentian Great Lakes, and compared HTS-based detection to existing early detection surveys. We found high agreement between methods at the system scale; HTS-based taxonomy identified 28 species, morphology-based taxonomy 30 species, and 27 of those were common to both. Among samples, 76% of family-level taxonomic assignments agreed; however, only 42% of species assignments agreed. Most errors were attributed to morphology-based taxonomy limitations (yielding false negatives, 9%) and species misidentification (which yields false positives, 20%, and false negatives, 21%), whereas HTS-based taxonomy error was low (5%). Further, the probability of detecting most of the non-native fishes as larvae in a randomized survey was roughly similar to the probability of detecting them as juveniles or adults in a survey optimized for non-native species early detection. We conclude that as a first step toward incorporating HTS-based taxonomy into large-scale surveys for non-native species early detection, benchmarking HTS results against traditional, morphology-based taxonomy is important to quantify error rates and determine error sources.
URLs/Downloads:
DOI: DNA metabarcoding-based identification of fish larvae for invasive species early detection