You are here:
Evaluating the performance of DNA metabarcoding for assessment of zooplankton communities in Western Lake Superior using multiple markers
Citation:
Meredith, C., J. Hoffman, A. Trebitz, E. Pilgrim, S. Okum, AND J. Martinson. Evaluating the performance of DNA metabarcoding for assessment of zooplankton communities in Western Lake Superior using multiple markers. Metabarcoding and Metagenomics. Pensoft Publishers, Sofia, Bulgaria, 50:83-97, (2021). https://doi.org/10.3897/mbmg.5.64735
Impact/Purpose:
Developing the capability for using DNA metabarcoding to monitor biological communities and search for aquatic invasive species is a major EPA/ORD research emphasis under SSWR. This manuscript examines the ability to apply DNA metabarcoding for determining the composition of Great Lakes zooplankton. Key findings from comparing DNA-based results to morphological-ID based results are that multiple genetic markers need to be employed, that efforts to fill gaps in DNA barcode libraries need to continue, and that tandem DNA-based vs. morphologically-based taxonomy remain an effective learning path forward. This work was conducted under SSWR research area 3.01A-2.1 (the FY15-FY19 time period structure), and represents a continued research collaboration between the EPA/ORD Duluth lab (leading the field effort) and the EPA/ORD Cincinnati lab (leading the DNA sequencing effort). This work brings together a dataset collected from the R/V Lake Explorer II explicitly for that purpose and a dataset collected as part of a Great Lakes National Program Office (GLNPO) K-12 teacher training cruise.
Description:
In order for DNA metabarcoding to attain its potential as a community assessment tool, we need to better understand its performance versus traditional morphological identification and work to address any remaining performance gaps. Using 4 DNA loci -- the 18S, and 16S genetic markers and two regions of the COI marker -- we examined the use of DNA metabarcoding for understanding the diversity and composition of zooplankton at 42 sites across western Lake Superior. We identified 51 unique zooplankton taxa, of which 17 were identified using only morphological traits, 13 using only DNA, and 21 using both methods. The percent of zooplankton taxa identified was 35-41% with the two COI markers, 22% with 16S, 16% with 18S, and 69% when merging results from all DNA markers. The two COI loci performed best at identifying taxa at the species level whereas18S was the only marker whose family-level composition patterns matched those from morphological ID. Approximately 63%, 80%, and 74%, of the taxa that could not be identified for the COI, 16S, and 18S markers, respectively, had 0 (“no record”) or <2 records (“underrepresented record”) present in reference databases. The list of taxa found using only DNA metabarcoding included 4 species not known to occur in Lake Superior. Some taxa found using only DNA may be attributed to sequencing errors or the inability to distinguish among closely related taxa. Our results support that DNA metabarcoding can augment morphological ID for estimating broad trends in composition of zooplankton over space and time, as well as be used for detecting rare taxa, but may require multiple field and laboratory replicates and a synthesis of multiple genetic loci. Further addition of taxa to reference DNA databases, as well as a better understanding of the effects of laboratory and bioinformatics choices, will improve our ability to use DNA metabarcoding to identify zooplankton and other invertebrates in aquatic surveys.
URLs/Downloads:
DOI: Evaluating the performance of DNA metabarcoding for assessment of zooplankton communities in Western Lake Superior using multiple markers