Reporting the limits of detection and quantification for environmental DNA assays

Authors

Katy E. Klymus, U.S. Geological Survey, Columbia Environmental Research CenterFollow
Christopher M. Merkes, U.S. Geological Survey, Upper Midwest Environmental Sciences Center,
Michael J. Allison, University of Victoria, Victoria, BC
Caren S. Goldberg, Washington State University
Caren C. Helbing, University of Victoria, Victoria, BC
Margaret E. Hunter, U.S. Geological Survey, Wetland and Aquatic Research Center, Gainesville, FLFollow
Craig A. Jackson, U.S. Geological Survey, Upper Midwest Environmental Sciences Center
Richard F. Lance, United States Army Engineer Research & Development Center, Vicksburg, MS
Anna M. Mangan, USDA APHIS NWRC
Emy M. Monroe, USFWS Midwest Fisheries Center
Antoinette J. Piaggio, USDA APHIS NWRCFollow
Joel P. Stokdyk, USGS Upper Midwest Water Science Center
Chris C. Wilson, Ontario Ministry of Natural Resources and Forestry, Peterborough, ON
Catherine A. Richter, U.S. Geological Survey, Columbia Environmental Research Center

ORCID IDs

Katy E. Klymus https://orcid.org/0000-0002-8843-6241

Christopher M. Merkes https://orcid.org/0000-0001-8191-627X

Caren C. Helbing https://orcid.org/0000-0002-8861-1070

Margaret E. Hunter https://orcid.org/0000-0002-4760-9302

Craig A. Jackson https://orcid.org/0000-0003-4023-0276

Antoinette J. Piaggio https://orcid.org/0000-0002-4701-0746

Catherine A. Richter https://orcid.org/0000-0001-7322-4206

Date of this Version

2020

Citation

Environmental DNA. 2020;2:271–282.

DOI: 10.1002/edn3.29

Comments

US gov't work

Abstract

Background: Environmental DNA (eDNA) analysis is increasingly being used to detect the presence and relative abundance of rare species, especially invasive or imperiled aquatic species. The rapid progress in the eDNA field has resulted in numerous studies impacting conservation and management actions. However, standardization of eDNA methods and reporting across the field is yet to be fully established, with one area being the calculation and interpretation of assay limit of detection (LOD) and limit of quantification (LOQ).

Aims: Here, we propose establishing consistent methods for determining and reporting of LOD and LOQ for single‐species quantitative PCR (qPCR) eDNA studies.

Materials & Methods/ Results: We utilize datasets from multiple cooperating laboratories to demonstrate both a discrete threshold approach and a curve‐fitting modeling approach for determining LODs and LOQs for eDNA qPCR assays. We also provide details of an R script developed and applied for the modeling method.

Discussion/Conclusions: Ultimately, standardization of how LOD and LOQ are determined, interpreted, and reported for eDNA assays will allow for more informed interpretation of assay results, more meaningful interlaboratory comparisons of experiments, and enhanced capacity for assessing the relative technical quality and performance of different eDNA qPCR assays.