Date of Award

Fall 2021

Publication Type

Thesis

Degree Name

M.Sc.

Department

Great Lakes Institute for Environmental Research

First Advisor

H.J. MacIsaac

Second Advisor

G.D. Haffner

Third Advisor

D.D. Heath

Keywords

Targeted eDN, metabarcoding, Freshwater and marine aquatic invasive species

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Species invasions are of critical concern due to their significant impacts on ecosystems and social economies, of which aquatic invasive species (AIS) often pose significant challenges in their control and management, notably because of difficulties in early detection. Environmental DNA (eDNA) provides a promising tool in advancing the detection of newly introduced aquatic organisms because of its high sensitivity and ease of use compared to traditional capture-based methods. Although eDNA-based methods are increasingly used worldwide, especially in aquatic ecosystems, most studies focus on a limited number of target species despite a pressing need for broad taxonomic monitoring for conservation and management. In this thesis, I developed and applied an approach that capitalizes on a combination of high-sensitivity PCR primer sets and high-throughput sequencing (HTS) to detect 69 aquatic invasive species. This hybrid approach is defined as “targeted metabarcoding”. The sensitivity of the 128 primer sets ranged between 2.8 × 10–4 ng and 4.8 ng, and the inclusion of interfering plankton eDNA reduced the sensitivity by an average of approximately an order of magnitude. My targeted metabarcoding resulted in the detection of > 97% of the AIS spiked into eDNA samples, and the number of HTS reads had a significantly (P < 0.002) positive relationship with the amount of spiked DNA. I then applied this approach to eDNA collected at eight Canadian ports or harbors to detect potential invaders; 38.6% of anticipated species from our 69 were detected. This fast, high-sensitive, and relative cost-saving approach can be used to detect AIS at early invasion stages, which will contribute to routine aquatic invasive species detection globally.

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