Development and testing of species-specific quantitative PCR assays for environmental DNA applications
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Abstract
New, non-invasive methods for detecting and monitoring species presence are being developed to aid in fisheries and wildlife conservation management. The use of environmental DNA (eDNA) samples for detecting macrobiota is one such group of methods that is rapidly becoming popular and being implemented in national management programs. Here we focus on the development of species-specific targeted assays for probe-based quantitative PCR (qPCR) applications. Using probe-based qPCR offers greater specificity than is possible with primers alone. Furthermore, the ability to quantify the amount of DNA in a sample can be useful in our understanding of the ecology of eDNA and the interpretation of eDNA detection patterns in the field. Careful consideration is needed in the development and testing of these assays to ensure the sensitivity and specificity of detecting the target species from an environmental sample. In this protocol we will delineate the steps needed to design and test probe-based assays for the detection of a target species; including creation of sequence databases, assay design, assay selection and optimization, testing assay performance, and field validation. Following these steps will help achieve an efficient, sensitive, and specific assay that can be used with confidence. We demonstrate this process with our assay designed for populations of the mucket (Actinonaias ligamentina), a freshwater mussel species found in the Clinch River, USA.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Development and testing of species-specific quantitative PCR assays for environmental DNA applications |
| Series title | JOVE Journal Of Visualized Experiments |
| DOI | 10.3791/61825 |
| Volume | 165 |
| Year Published | 2020 |
| Language | English |
| Publisher | JoVE Journal |
| Contributing office(s) | Columbia Environmental Research Center |
| Description | e61825, 25 p. |
| Google Analytic Metrics | Metrics page |