Quantifying the Detection Sensitivity and Precision of qPCR and ddPCR Mechanisms for eDNA Samples
Permanent lenke
https://hdl.handle.net/10037/36085Dato
2024-12-11Type
Journal articleTidsskriftartikkel
Peer reviewed
Forfatter
Guri, Gledis; Ray, Jessica Louise; Shelton, Andrew Olaf; Kelly, Ryan P.; Præbel, Kim; Andruszkiewicz Allan, Elizabeth; Yoccoz, Nigel Gilles; Johansen, Torild; Wangensteen, Owen S.; Hanebrekke, Tanja Lexau; Westgaard, Jon-IvarSammendrag
Environmental DNA (eDNA) detection employing quantitative PCR (qPCR) and droplet digital PCR (ddPCR) offers a non-invasive and efficient approach for monitoring aquatic organisms. Accurate and sensitive quantification of eDNA is crucial for tracking rare and invasive species and understanding the biodiversity abundance and distribution of aquatic organisms. This study compares the sensitivity and quantification precision of qPCR and ddPCR for eDNA surveys through Bayesian inference using latent parameters from both known concentration (standards) and environmental samples across three teleost fish species assays. The results show that ddPCR offers higher sensitivity and quantification precision, particularly at low DNA concentrations (< 1 copy/μL reaction), than qPCR. These findings highlight the superior performance of ddPCR for eDNA detection at low concentrations, guiding researchers towards more reliable methods for effective species monitoring. Additionally, this study indicates that a two-step (detection and concentration) model increased the precision of qPCR results, useful for enhancing the robustness of eDNA quantification. Furthermore, we investigated the lower limit of quantification for ddPCR, providing insights on how such limit can be extended, which could also be applied to qPCR.
Forlag
WileySitering
Guri, Ray, Shelton, Kelly, Præbel, Andruszkiewicz Allan, Yoccoz, Johansen, Wangensteen, Hanebrekke, Westgaard. Quantifying the Detection Sensitivity and Precision of qPCR and ddPCR Mechanisms for eDNA Samples. Ecology and Evolution. 2024;14(12)Metadata
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