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08:54 min
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November 5th, 2020
DOI :
November 5th, 2020
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Introduction
1:18
Generation of a Sequence Database of Mitochondrial DNA Sequences from Target and Non-target Species of Interest
2:03
Assay Design
3:56
Assay Screening and Optimization
6:21
Results: A. ligamentina qPCR Assay
8:23
Conclusion
Transcript
Well optimized assays are vital for the proper interpretation of environmental DNA data. This protocol describes the necessary design and testing steps to develop such an assay. In general, environmental DNA is a non-invasive method for detecting a particular species or suite of species.
It may reduce costs and be more sensitive compared to conventional survey methods. This method can aid conservation and wildlife management through the detection of DNA from a species of interest, allowing one to potentially infer that species presence in the sampled area. Because of the great sensitivity of quantitative PCR, contamination can happen easily, and negative controls are needed to identify steps at which contamination was introduced.
eDNA is a field littered with jargon and shorthand terms. For those not practiced in molecular biology or qPCR, visual demonstrations can aid the planning of an experimental design from conceptualization to data generation. Demonstrating the procedure will be Dannise Ruiz Ramos, a biologist from our laboratory, and Trudi Frost, a student laboratory aid.
To begin, search and download sequences from multiple gene regions for species of interest using NCBI's Nucleotide Database. Select all sequences that match the specifications, and select Send To.Choose Complete Record, File, Download Format as either GenBank or FASTA, then Create File. These sequences are now saved to the computer.
Repeat these steps for all the species of interest. Keep sequences for each gene region in a separate file, as they will be analyzed separately. To align the sequences from each gene region separately, import the downloaded sequence files into a sequence alignment program, such as Geneious Prime software.
Create separate folders for each gene region, then select all the sequences within a folder that contains sequences from one gene region. Use the Multiple Alignment tool to create a nucleotide alignment, such as Geneious or MUSCLE of the selected sequences. Choose promising regions for assay design through the visualization of aligned sequence data.
Select a region that has a lot of sequence data available for the species of interest, is highly divergent among species, and shows low within species variation. Next, design the assay primers and probe. Use qPCR assay design software to design five sets of qPCR assays.
Paste the selected sequence into the Sequence Entry box. If the alignment created spaces, delete those from the sequence. Select qPCR 2 primers probe in the Choose Your Design option, then download the recommended assays.
Copy the sequences from the forward primer of the first assay, and search for this primer sequence in the previously created alignment. If using Geneious Prime, use the Annotate Predict tool to add the primer region to the alignment. Do this for all the primer and probe combinations.
Inspect these regions of the alignment for variation within the target species, as well as within the co-occurring species. Test primers in silico through NCBI's Primer-BLAST. Paste primers to the use my own primer box under Primer Parameters.
In the Primer Pair Specificity Checking Parameters options, select NR as the Database and type the taxonomic order or family of the organism of interest in the Organism box. Ensure that the selected primers are not likely to amplify non-target species. Test assay efficiency in vitro by creating a standard curve and determine the curve's efficiency and linear range.
Test at least six ten-fold dilutions of a synthetic DNA standard containing the target sequence, at approximately one to a million copies per reaction. Use the qPCR software to plot the CQ value of each standard on the Y axis, and the log base 10 of the initial standard concentration in copies per reaction on the X axis. The qPCR software should automatically run a linear regression.
Calculate the efficiency from the slope of the regression. Visually inspect the standard curve for bias or for poor performance, as measured by efficiency and R squared values. Use an internal positive control to test for PCR inhibition of actual field samples, which can lead to a decrease in sensitivity and false negatives.
Determine the limits of detection and quantification for each assay. Test assays with non-target species to verify specificity, and make sure that the assay performs well with an IPC multiplexed. Assays with good sensitivity, specificity and efficiency can move on to the next steps.
To perform in situ testing of the assay, obtain multiple water samples and process them for qPCR. Run the quantitative PCR assay and compare eDNA concentration and detection frequency with known site differences in occurrence and abundance. Confirm all detections by sequencing.
Available sequences of all Unionidae species in the Clinch River were downloaded and aligned. After designing multiple assays, five sets of primers and probe were added to the alignment for visual assessment. The primer and probe sets were tested in silico and in vitro.
In the lab, all assays were tested using DNA extractions of 27 available species to verify specificity. One assay successfully amplified only the target species. A successful assay with good efficiency and R squared values is shown here.
The LOD and LOQ for the selected assay were both five copies per reaction. In contrast, assays that produced a standard curve with poor efficiency were discarded. In a quality qPCR, the standard dilutions amplify at evenly spaced cycle quantification values of approximately 3.3 cycles for each ten-fold difference in concentration.
In a poor qPCR, standards may exhibit uneven variation in cycle quantification values between dilutions. IPC amplification for unknown samples should be compared to the results of the negative template control IPC. If no inhibitors are present in the samples, all IPC amplification should have a tight grouping in the plot, with cycle quantification values nearly the same as the no template control.
For in situ testing of the assay, location sites included the bottom of the mussel bed in stream, bottom of the muscle bed near shore, 100 meters downstream of the bed in stream, 500 meters downstream of the bed in stream, and 500 meters downstream of the bed near shore. Quantitative PCR assays for environmental DNA can aid in the monitoring of both invasive and endangered species, as well as improve our understanding of the spatial and temporal changes in species detection without having to physically capture the individual organism.
Environmental DNA assays require rigorous design, testing, optimization and validation before the collection of field data can begin. Here, we present a protocol to take users through each step of designing a species-specific, probe-based qPCR assay for the detection and quantification of a target species DNA from environmental samples.
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