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132 results for “environmental detection”
Environmental DNA-based detection of Batrachochytrium salamandrivorans in captive settings
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Data from: Environmental change, if unaccounted, prevents detection of cryptic evolution in a wild population
Detecting contemporary evolution requires demonstrating that genetic change has occurred. Mixed-effects models allow estimation of quantitative genetic parameters and are widely used to study evolution in wild populations. However, predictions of evolution based on these parameters frequently fail to match observations. Furthermore, such studies often lack an independent measure of evolutionary change against which to verify predictions. Here, we applied three commonly used quantitative genetic approaches to predict the evolution of size at maturity in a wild population of Trinidadian guppies. Crucially, we tested our predictions against evolutionary change observed in common garden experiments performed on samples from the same population. We show that standard quantitative genetic models underestimated or failed to detect the cryptic evolution of this trait as demonstrated by the common garden experiments. The models failed because: 1) size at maturity and fitness both decreased with increases in population density, 2) offspring experienced higher population densities than their parents, and 3) selection on size was strongest at high densities. When we accounted for environmental change, predictions better matched observations in the common garden experiments, although substantial uncertainty remained. Our results demonstrate that predictions of evolution are unreliable if environmental change is not appropriately captured in models.
Data from: Spatial and temporal patterns of environmental DNA detection to inform sampling protocols in lentic and lotic systems.
<p>The development of efficient sampling protocols for the capture of environmental DNA (eDNA) could greatly help improve accuracy of occupancy monitoring for species that are difficult to detect. However, the process of developing a protocol in situ is complicated for rare species by the fact that animal locations are often unknown. We tested sampling designs in lake and stream systems to determine the most effective eDNA sampling protocols for two rare species: the Sierra Nevada yellow-legged frog (<i>Rana sierrae</i>) and the foothill yellow-legged frog (<i>R. boylii</i>). We varied water volume, spatial sampling, and seasonal timing in lakes and streams; in lakes we also tested multiple filter types. We found that filtering 2 L versus 1 L increased the odds of detection in streams 5.42X (95% CI: 3.2-9.19X) in our protocol, from a probability of 0.51 to 0.85 per technical replicate. Lake sample volumes were limited by filter clogging and we found no effect of volume or filter type. Sampling later in the season increased the odds of detection in streams by 1.96X for every 30 days (95% CI: 1.3 - 2.97X) but there was no effect for lakes. Spatial autocorrelation of the quantity of yellow-legged frog eDNA captured in streams between 100 and 200 m, indicating that sampling at close intervals is important.</p>
Supplementary data for: simultaneous species detection and discovery with environmental DNA metabarcoding: a freshwater mollusk case study
<p>Environmental DNA (eDNA) sampling is a powerful tool for rapidly characterizing biodiversity patterns for specious, cryptic taxa with incomplete taxonomies. One such group that are also of high conservation concern are North American freshwater gastropods. In particular, springsnails of the genus <em>Pyrgulopsis</em> (Family: Hydrobiidae) are prevalent throughout the western United States where >140 species have been described. Many of the described species are narrow endemics known from a single spring or locality and it is believed that there are likely many additional species which have yet to be described. The distribution of these species across the landscape is of interest because habitat loss and degradation, climate change, groundwater mining, and pollution have resulted in springsnail imperilment rates as high as 92%. Determining distributions with conventional sampling methods is limited by the fact that these snails are often <5 mm in length with few distinguishing morphological characters, making them both difficult to detect and to identify. In order to facilitate detection of <em>Pyrgulopsis</em> we developed an eDNA metabarcoding protocol that is both inexpensive and capable of rapid, accurate detection of all known <em>Pyrgulopsis</em> species. When compared with conventional collection techniques, our pipeline consistently resulted in detection at sites previously known to contain <em>Pyrgulopsis </em>springsnails and at a cost per site that is likely to be substantially less than the conventional sampling and individual barcoding that has been done historically. Additionally, because our method uses eDNA extracted from filtered water it is non-destructive and suitable for the detection of endangered species where "no take" restrictions may be in effect. This effort represents both a tool which is immediately applicable to a group of high conservation concern across western North America and a case study in the broader application of eDNA sampling for landscape assessments of cryptic taxa of conservation concern.</p>
Fig. 1 in First report of successful Naegleria detection from environmental resources of some selected areas of Rawlakot, Azad Jammu and Kashmir, Pakistan
Fig. 1. Sampling sites in the targeted area of Rawlakot, Azad Jammu and Kashmir, Pakistan
Detection of black rat inhabitation using environmental DNA
<p>The all raw data of this study including expeirment 1, 2 and primer specificitiy as well as LOD.</p> <p> </p> <p>Pest management is essential for safeguarding agricultural productivity, public health, and ecological balance, especially as the global demand for sustainable pest control strategies rises with population growth. Among emerging technologies, environmental DNA (eDNA) analysis has gained prominence as a powerful tool, enabling the detection of pest species by isolating their genetic material from environmental samples. This study explores the innovative application of eDNA analysis in black rat (<a name="_Hlk184139956"></a><em>Rattus</em><em> rattus</em>) management, utilizing wipe sampling to recover eDNA from the air. Key experiments were found to determine the minimum surface area (~5 inch area) required for effective eDNA collection and to analyze the temporal persistence of black rat eDNA over two months. Our findings demonstrate the potential of eDNA techniques to transform pest management strategies, offering a highly efficient, cost-effective, and environmentally sustainable approach to monitoring and controlling black rat populations. This work represents a significant advancement in integrating molecular tools into pest control practices.</p> <p> </p>
Environmental differences explain subtle yet detectable genetic structure in a widespread pollinator
<p><strong>Background</strong><br>The environment is a strong driver of genetic structure in many natural populations, yet often neglected in population genetic studies. This may be a particular problem in vagile species, where subtle structure cannot be explained by limitations to dispersal. Consequently, these species might falsely be considered quasi-panmictic and hence potentially mismanaged. A species this might apply to, is the buff-tailed bumble bee (<em>Bombus terrestris</em>), an economically important and widespread pollinator, which is considered to be quasi-panmictic at mainland continental scales. Here we aimed to (i) quantify genetic structure in 21+ populations of the buff-tailed bumble bee, sampled throughout two Eastern European countries, and (ii) analyse the degree to which structure is explained by environmental differences, habitat permeability and geographic distance. Using 12 microsatellite loci, we characterised populations of this species with Fst analyses, complemented by discriminant analysis of principal components and Bayesian clustering approaches. We then applied generalized dissimilarity modelling to simultaneously assess the informativeness of geographic distance, habitat permeability and environmental differences among populations in explaining divergence.</p> <p><br><strong>Results</strong><br>Genetic structure of the buff-tailed bumble bee quantified by means of Fst was subtle and not detected by Bayesian clustering. Discriminant analysis of principal components suggested insignificant but still noticeable structure that slightly exceeded estimates obtained through Fst analyses. As expected, geographic distance and habitat permeability were not informative in explaining the spatial pattern of genetic divergence. Yet, environmental variables related to temperature, vegetation and topography were highly informative, explaining between 33 and 39% of the genetic variation observed.</p> <p><br><strong>Conclusions</strong><br>In contrast to previous studies reporting quasi-panmixia in continental populations of this species, we demonstrated the presence of subtle population structure related to environmental heterogeneity. Environmental data proved to be highly useful in unravelling the drivers of genetic structure in this vagile and opportunistic species. We highlight the potential of including these data to obtain a better understanding of population structure and the processes driving it in species considered to be quasi-panmictic.</p>
Improved biodiversity detection using a large-volume environmental DNA sampler with in situ filtration and implications for marine eDNA sampling strategies
<p>Metabarcoding analysis of environmental DNA samples is a promising new tool for marine biodiversity and conservation. Typically, seawater samples are obtained using Niskin bottles and filtered to collect eDNA. However, standard sample volumes are small relative to the scale of the environment, conventional collection strategies are limited, and the filtration process is time consuming. To overcome these limitations, we developed a new large – volume eDNA sampler with in situ filtration, capable of taking up to 12 samples per deployment. We conducted three deployments of our sampler on the robotic vehicle <em>Mesobot</em> in the Flower Garden Banks National Marine Sanctuary in the northwestern Gulf of Mexico and collected samples from 20 to 400 m depth. We compared the large volume (~40 – 60 liters) samples collected by <em>Mesobot</em> with small volume (~2 liters) samples collected using the conventional CTD rosette – mounted Niskin bottle approach. We sequenced the V9 region of 18S rRNA, which detects a broad range of invertebrate taxa, and found that while both methods detected biodiversity changes associated with depth, our large volume samples detected approximately 66% more taxa than the CTD small volume samples. We found that the fraction of the eDNA signal originating from metazoans relative to the total eDNA signal decreased with sampling depth, indicating that larger volume samples may be especially important for detecting metazoans in mesopelagic and deep ocean environments. We also noted substantial variability in biological replicates from both the large volume <em>Mesobot</em> and small volume CTD sample sets. Both of the sample sets also identified taxa that the other did not – although the number of unique taxa associated with the <em>Mesobot</em> samples was almost four times larger than those from the CTD samples. Large volume eDNA sampling with in situ filtration, particularly when coupled with robotic platforms, has great potential for marine biodiversity surveys, and we discuss practical methodological and sampling considerations for future applications.</p>
Data from: Development and validation of targeted environmental DNA (eDNA) metabarcoding for early detection of 69 invasive fishes and aquatic invertebrates
<p>Invasive species are of concern due to their impacts on ecosystems and economies, but they pose significant control challenges. Environmental DNA (eDNA) is a powerful tool in the detection of aquatic organisms at low densities due to high sensitivity and ease of collection. Aquatic eDNA analyses have increased worldwide and are generally either applied to a few target species (quantitative PCR) or for broad taxonomic applications (metabarcoding). Here we describe the development and testing of a hybrid approach that utilized high sensitivity PCR primer sets and high-throughput sequencing (HTS), referred to as <em>targeted metabarcoding</em>, to detect 69 fishes and invertebrates. We identified target species based on reports of globally important invasive species and developed two independent PCR primers for each species (CO1 and a second mtDNA region). We assessed sensitivity and eDNA interference for all 138 primers (2 per species, 69 species) using standard end-point PCR and tested them on 10 eDNA samples spiked with various amounts of one or more of the target species' DNA. The sensitivity of the 138 primer sets ranged between 1.5×10<sup>-5</sup> and 2.64 ng template DNA (mean = 0.069 ng). Primers were also tested for interference effects using plankton eDNA to simulate field conditions. The inclusion of interfering plankton DNA reduced the sensitivity for most primer sets by one or more orders of magnitude (range 0 to 3). Overall, our targeted metabarcoding resulted in the detection of ~ 98% of species in the DNA spiked samples, and, perhaps more importantly, the HTS read count was positively related to the quantity of spiked DNA (P < 0.002). We envision this technique being particularly useful for the early detection of species at low population densities; however, there are diverse applications of targeted metabarcoding for monitoring aquatic community composition and quantifying ecosystem change and health.</p>
Data for: Environmental DNA storage and extraction method affects detectability for multiple aquatic invasive species
<p>Environmental DNA (eDNA) refers to genetic material released by organisms into their surrounding environment. Collecting and identifying eDNA has gained popularity for monitoring and surveillance of aquatic invasive species. Invasive species management is most successful when an invasion is identified early while population size is likely to be low, highlighting the importance of eDNA detection sensitivity. Various factors influence DNA yield recovered from environmental samples. Environmental DNA storage and extraction methods, for example, can be adjusted to maximize DNA yield, thereby improving detectability. In this study, we compared the performance of two eDNA storage and extraction methods in detecting three common aquatic invasive species (<em>Bythotrephes longimanus</em>, <em>Dreissena polymorpha</em>, and <em>Faxonius rusticus</em>) across five natural ecosystems of Minnesota, United States. One method involved storing filters in 95% ethanol (EtOH) and extracting DNA using a DNeasy PowerSoil Pro Kit (Qiagen, Hilden, Germany), whereas the other method used cetyl trimethylammonium bromide (CTAB) for storage and a phenol–chloroform–isoamyl (PCI) procedure for DNA extraction. We also investigated the effect of DNA extract volume (1 μL relative to 3 μL) in qPCR reactions on eDNA detections for the commercial kit method. The CTAB‐PCI method yielded significantly more positive detections, across all three species, compared to the EtOH‐Qiagen method. Moreover, we found that using 1 μL of DNA extract in qPCR reactions was equally effective as using 3 μL. To improve detections of aquatic invasive species, we recommend that researchers store eDNA sample filters in CTAB or a similar lysis buffer such as Longmire's solution and extract with PCI when feasible, but note that lower extract volumes might be used without negative effect when either increasing technical replicates or repurposing samples for the detection of multiple species.</p>
Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga
<p>Early detection of nuisance species is crucial for the conservation and management of threatened ecosystems, reducing the risk of widespread establishment. Environmental DNA (eDNA) data can increase the sensitivity of biomonitoring programs, oftentimes with minimal cost and effort. However, eDNA analyses have inherent errors that can complicate the integration of molecular survey methods into existing management frameworks. Therefore, it is crucial for eDNA studies to consider imperfect detections and estimate error rates accordingly. Detecting nuisance species in low abundance with minimal uncertainty is vital to increase the chance of containment and eradication. We developed a novel eDNA assay to detect a nuisance marine macroalga across its colonization front using surface seawater samples from Papahānaumokuākea Marine National Monument (PMNM), one of the world's largest marine reserves. <em>Chondria tumulosa</em>, a cryptogenic red alga with invasive characteristics, has been documented forming dense mats that overgrow coral reefs and smother native flora and fauna in PMNM. We verified the eDNA assay using site-occupancy detection modeling from quantification polymerase chain reaction (qPCR) data, calibrated with visual estimates of benthic cover of <em>C. tumulosa </em>that ranged from < 1% to 95%. Results were subsequently validated with high-throughput sequencing of amplified eDNA and negative control samples. Overall, the probability of detecting <em>C. tumulosa </em>at occupied sites was at least 92% when multiple qPCR replicates were positive. Modeled false-positive inferences were 3% or less and false-negative errors were 11% or less. The developed assay is suitable for routine monitoring at shallow sites (less than 10 m), even when <em>C. tumulosa </em>abundance was less than 1%. Successful implementation of eDNA tools in conservation decision-making relies on balancing uncertainties in both visual and molecular detection methods. Our results and modeling demonstrated the assay's sensitivity to <em>C. tumulosa</em>, and we outline the necessary steps to infer ecological presence-absence from molecular detection data. By providing a reliable, cost-effective tool for detecting low-abundance species, eDNA analyses have the potential to enhance the surveillance of nuisance species and inform timely management interventions.</p>
Table 1 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA
<p><b>Table 1.</b> Number of field samples (including controls) for each qPCR assay at each site sampled for eDNA in 2018 and 2019 in western Lake Erie. DR = Detroit River, HP = Hot Ponds, MB = Maumee Bay. Note that samples are site-specific.</p><table><tbody><tr><th>Site</th><th>Year</th></tr><tr><th>2018</th><th>2019</th></tr><tr><th>Assay</th><th>Samples</th><th>Assay</th><th>Samples</th></tr></tbody><tbody><tr><th>DR</th><td>GCTM10 GCTM22 GCTM32</td><td>78 78 78</td><td>GCTM10 GCTM22 GCTM32</td><td>81 81 81</td></tr><tr><th>HP</th><td>GCTM10 GCTM22 GCTM32</td><td>77 77 77</td><td>GCTM10 GCTM22 GCTM32</td><td>82 82 82</td></tr><tr><th>MB</th><td>GCTM10 GCTM22 GCTM32</td><td>78 78 78</td><td>GCTM10 GCTM22 GCTM32</td><td>80 80 80</td></tr></tbody></table>
Table 4 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA
<p><b>Table 4.</b> Percentage of positive eDNA replicate detections in each month and site in 2018 and 2019 in western Lake Erie (based on at least one positive detection on at least one marker and one replicate). All markers (GCTM10, GCTM 22, GCTM32) were used to calculate these proportions. Samples were collected monthly from June to November for each site. The number of telemetered grass carp detected within 7 days before sampling for eDNA is denoted in parentheses. Acoustic telemetry receivers in MB in 2018 were not available. DR = Detroit River, HP = Hot Ponds, and MB = Maumee Bay. NA denotes when acoustic telemetry receivers were not in operation.</p><table><tbody><tr><th>Year</th></tr><tr><th>Site</th><th>2018</th><th>2019</th></tr><tr><th></th><th>June</th><th>July</th><th>Aug</th><th>Sept</th><th>Oct</th><th>Nov</th><th>May</th><th>June</th><th>July</th><th>August</th><th>Oct</th><th>Nov</th></tr></tbody><tbody><tr><th>DR</th><td>0.0%</td><td>2.3%</td><td>2.3%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>4.5%</td><td>10.6</td><td>14.1</td><td>17.4%</td><td>14.1%</td><td>2.2%</td></tr><tr><td>(1)</td><td>(1)</td><td>(2)</td><td>(1)</td><td>(2)</td><td>(0)</td><td>(1)</td><td>% (1)</td><td>% (1)</td><td>(2)</td><td>(2)</td><td>(0)</td></tr><tr><th>HP</th><td>0.0%</td><td>0.1%</td><td>4.1%</td><td>2.2%</td><td>15.8%</td><td>0.0%</td><td>9.0%</td><td>1.5%</td><td>34.8</td><td>1.5%</td><td>15.8%</td><td>22.7%</td></tr><tr><td>(1)</td><td>(1)</td><td>(2)</td><td>(2)</td><td>(3)</td><td>(NA)</td><td>(2)</td><td>(2)</td><td>% (2)</td><td>(3)</td><td>(2)</td><td>(2)</td></tr><tr><th>MB</th><td>12.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>6.1%</td><td>37.1</td><td>8.3%</td><td>8.3%</td><td>0.0%</td></tr><tr><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(0)</td><td>(0)</td><td>% (0)</td><td>(0)</td><td>(0)</td><td>(0)</td></tr></tbody></table>
Table 3 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA
<p><b>Table 3.</b> Candidate set of hierarchical occupancy models used to estimate probability of grass carp eDNA occurrence among sites (ψ), the conditional probability of grass carp eDNA occurrence at a sampling locality within a site given that grass carp were present at the site (Θ), and the conditional probability of eDNA detection on replicate filters collected at a sampling locality given that the species is present at the sampling locality <i>(p</i>) from three sites in western Lake Erie sampled in 2018 and 2019. Covariates included location (site), time (Month) and probe type (GCTM10, GCTM22, GCTM32). Model comparison was evaluated with the Widely Applicable Information Criterion (WAIC).</p><table><tbody><tr><th>Model</th><th>WAIC</th><th>Δ WAIC</th><th>Lack of fit</th><th>Predicted Variance</th></tr></tbody><tbody><tr><th>ψ(Site)Θ(Site)p(.)</th><td>309.44</td><td>-</td><td>298.70</td><td>18.63</td></tr><tr><th>ψ(.)Θ(Site)p(.)</th><td>309.50</td><td>0.06</td><td>298.99</td><td>10.73</td></tr><tr><th>ψ(.)Θ(Month)p(.)</th><td>317.61</td><td>8.18</td><td>299.05</td><td>18.56</td></tr><tr><th>ψ(Season)Θ(.)p(.)</th><td>317.67</td><td>8.24</td><td>299.01</td><td>18.65</td></tr><tr><th>ψ(Month)Θ(.)p(.)</th><td>317.72</td><td>8.28</td><td>299.04</td><td>18.67</td></tr><tr><th>ψ(Season)Θ(Season)p(.)</th><td>317.84</td><td>8.40</td><td>299.04</td><td>18.79</td></tr><tr><th>ψ(.)Θ(Season)p(.)</th><td>317.74</td><td>8.31</td><td>299.07</td><td>18.66</td></tr><tr><th>ψ(Site)Θ(.)p(.)</th><td>317.94</td><td>8.51</td><td>299.04</td><td>18.90</td></tr><tr><th>ψ(.)Θ(.)p(.)</th><td>325.00</td><td>15.57</td><td>305.50</td><td>20.21</td></tr><tr><th>ψ(Season)Θ(Site)p(.)</th><td>325.41</td><td>15.98</td><td>305.49</td><td>19.91</td></tr><tr><th>ψ(Site + Season)Θ(.)p(.)</th><td>325.59</td><td>16.16</td><td>305.44</td><td>20.15</td></tr><tr><th>ψ(Site)Θ(Season)p(.)</th><td>325.72</td><td>16.29</td><td>305.48</td><td>20.23</td></tr><tr><th>ψ(Site + Season)Θ(Site + Season)p(.)</th><td>325.92</td><td>16.49</td><td>305.49</td><td>20.43</td></tr><tr><th>ψ(.)Θ(Site + Season)p(.)</th><td>326.37</td><td>16.94</td><td>305.52</td><td>20.84</td></tr><tr><th>ψ(Site)Θ(Month)p(.)</th><td>329.57</td><td>20.14</td><td>308.65</td><td>20.92</td></tr><tr><th>ψ(Month)Θ(Month)p(.)</th><td>330.14</td><td>20.71</td><td>308.66</td><td>21.84</td></tr><tr><th>ψ(Site + Season)Θ(Site)p(Probe)</th><td>377.63</td><td>68.20</td><td>276.90</td><td>100.72</td></tr><tr><th>ψ(Site + Season)Θ(.)p(Probe)</th><td>378.35</td><td>68.92</td><td>277.00</td><td>101.34</td></tr><tr><th>ψ(Site + Season)Θ(Site + Season)p(Probe)</th><td>378.42</td><td>68.99</td><td>277.00</td><td>101.41</td></tr><tr><th>ψ(Site + Season)Θ(Season)p(Probe)</th><td>378.55</td><td>69.12</td><td>277.09</td><td>101.46</td></tr><tr><th>ψ(Season)Θ(Site + Season)p(Probe)</th><td>379.41</td><td>69.98</td><td>277.28</td><td>102.10</td></tr><tr><th>ψ(Site)Θ(Site + Season)p(Probe)</th><td>379.62</td><td>70.19</td><td>277.40</td><td>102.21</td></tr><tr><th>ψ(.)Θ(Site + Season)p(Probe)</th><td>379.88</td><td>70.45</td><td>277.31</td><td>102.57</td></tr><tr><th>ψ(Site + Month)Θ(.)p(.)</th><td>383.56</td><td>74.13</td><td>282.86</td><td>100.69</td></tr><tr><th>ψ(Site + Month)Θ(Site + Month)p(.)</th><td>385.47</td><td>76.04</td><td>283.38</td><td>102.09</td></tr><tr><th>ψ(Site + Month)Θ(Site + Month)p(Probe)</th><td>386.95</td><td>77.52</td><td>282.90</td><td>104.05</td></tr><tr><th>ψ(.)Θ(Site + Month)p(.)</th><td>396.44</td><td>87.01</td><td>292.14</td><td>104.29</td></tr><tr><th>ψ(.)Θ(.)p(Probe)</th><td>396.45</td><td>87.01</td><td>292.14</td><td>104.29</td></tr></tbody></table>
Table 2 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA
<p><b>Table 2.</b> Gene region, primer, and probe sequences used to amplify GCTM10,GCTM22, and GCTM32 for grass carp.</p><table><tbody><tr><th>Gene</th><th>Primers and Probes</th><th>Sequence</th></tr></tbody><tbody><tr><th>ND2</th><td>Forward</td><td>5′- CCYTACGTACTCGCAATTCTAC -3′</td></tr><tr><th>ND2</th><td>Reverse</td><td>5′- GTGGTGGTGTTGGGCTATTA -3′</td></tr><tr><th>ND2</th><td>Probe</td><td>5′- VIC- ACCCTAACCTTTGCTAGCTCCCAC -MGBNFQ-3′</td></tr><tr><th>COII</th><td>Forward</td><td>5′- CCGACTCCTAGAAACAGATCAC -3′</td></tr><tr><th>COII</th><td>Reverse</td><td>5′- GGGACAGCTCAGGAATGTAATA -3′</td></tr><tr><th>COII</th><td>Probe</td><td>5′- 56-FAM- CCAGTTCGT/ZEN/GTCCTAGTATCTGCCGA -3IABkFQ -3′</td></tr><tr><th>COIII</th><td>Forward</td><td>5′- CCACGGACTACACGTCATTATT -3′</td></tr><tr><th>COIII</th><td>Reverse</td><td>5′-GATGTTCGGATGTAAAGTGGTATTG -3′</td></tr><tr><th>COIII</th><td>Probe</td><td>5′-NED- TTCCTAGCTGTTTGCCTTCTCCGT -MGBNFQ-3′</td></tr></tbody></table>
DNA sequences of transgenes detected via environmental DNA (raw ABI files, processed FASTA files, and reference alignments)
We demonstrate that simple, non-invasive environmental DNA (eDNA) methods can detect transgenes of genetically modified (GM) animals from terrestrial and aquatic sources in invertebrate and vertebrate systems. We detected transgenic fragments between 82-234 bp through targeted PCR amplification of environmental DNA extracted from food media of GM fruit flies (<i>Drosophila melanogaster</i>), feces, urine, and saliva of GM laboratory mice (<i>Mus musculus</i>), and aquarium water of GM tetra fish (<i>Gymnocorymbus ternetzi</i>). With rapidly growing accessibility of genome-editing technologies such as CRISPR, the prevalence and diversity of GM animals will increase dramatically. GM animals have already been released into the wild with more releases planned in the future. eDNA methods have the potential to address the critical need for sensitive, accurate, and cost-effective detection and monitoring of GM animals and their transgenes in nature.
Data for the detection of the boreal chorus frog (Pseudacris maculata) using environmental DNA and call surveys at 180 ponds sampled in 2017-2018 in southeastern Québec, Canada
<p>The boreal chorus frog (<em>Pseudacris maculata</em>) is at risk of extinction in parts of its range in Canada. Our objectives were to quantify the influence of local and landscape characteristics on the occurrence of the species in wetlands in southern Québec. We hypothesized that site occupancy depends on local characteristics and landscape characteristics contributing to site connectivity. We developed an environmental DNA (eDNA) method to detect the species and compared the detection probability of this method to traditional call surveys. We collected water samples at a total of 180 sites (90 in 2017, 110 in 2018), whereas we surveyed a subset of 63 sites using both eDNA and call surveys in 2018. Site occupancy varied across years, but was higher in sites where the species had been previously detected during the last 12 years by other studies. Site occupancy did not vary with other local and landscape characteristics, in part due to an apparent decrease in the number of sites occupied by the species since the last 12 years. Detection probability via eDNA (0.81; 95% CI: [0.31; 0.98]) did not differ from that of call surveys (0.62; 95% CI: [0.25; 0.89]). To identify the optimal sampling period for the boreal chorus frog, future studies should estimate the detection probability of eDNA during the breeding season and the larval development period of the species.</p>
Distinct latitudinal community patterns of Arctic marine vertebrates along the East Greenlandic coast detected by environmental DNA
<p><strong><span>Aim: </span></strong><span>Greenland is one of the places on Earth where the effects of climate change are most evident. The retreat of sea ice has made East Greenland more accessible for longer periods during the year. East Greenland fjords have been notoriously difficult to study due to their remoteness, dense sea ice conditions and lack of infrastructure. As a result, biological monitoring across latitudinal gradients is scarce in East Greenland and relies on sporadic research cruises and trawl data from commercial vessels. We here aim to investigate the transition in fish and marine mammal communities from South to Northeast Greenland using environmental DNA (eDNA).</span></p> <p><strong><span>Location: </span></strong><span>South to Northeast Greenland.</span></p> <p><strong><span>Methods: </span></strong><span>We investigated the transition in fish and marine mammal communities from South to Northeast Greenland using eDNA metabarcoding of seawater samples. We included both surface and mesopelagic samples, collected over approximately 2400 km waterway distance, by sampling from Cape Farewell to Ella Island in August 2021.</span></p> <p><strong><span>Results:</span></strong><span> We demonstrate a clear transition in biological communities from south to northeast, with detected fish and mammal species matching known distributions. Samples from the southern areas were dominated by capelin (<em>Mallotus villotus</em>) and redfish (<em>Sebastes</em>), whereas northeastern samples were dominated by polar cod (<em>Boreogadus saida</em>), sculpins (<em>Myoxocephalus</em>) and ringed seal (<em>Pusa hispida</em>). We provide newly generated 12S rRNA barcodes from 72 fish species, bringing the public DNA database closer to full taxonomic coverage for Greenlandic fish species for this locus.</span></p> <p><strong><span>Main conclusions: </span></strong><span>Our results demonstrate that eDNA sampling can detect latitudinal shifts in marine biological communities of the Arctic region, which can supplement traditional fish surveys in understanding species distributions and community compositions of marine vertebrates. Importantly, sampling of eDNA can be a feasible approach for detecting northward range expansions in remote areas as climate change progresses.</span></p>
Environmental DNA detection range for Hydrilla
<p>Dataset associated with publication of the same name including qPCR results, measured variables, and other supplemental data.</p>
Multi‐species occupancy modeling reveals methodological and environmental effects on eDNA detection of amphibians in temporary ponds
<p>Aquatic environmental DNA is increasingly used for biodiversity monitoring, such as surveying threatened and invasive species. Mainstreaming these methods in practical applications, however, still requires significant standardisation and optimisation, namely regarding DNA capture methods. Here we evaluated how filter type (standard disc filters vs high-capacity capsules), number of sampling sites, volume of water filtered and environmental factors affected amphibian detection in Mediterranean temporary ponds. The study involved water filtering until clogging at one (capsules) and five (discs) sites from 16 small and shallow ponds, where three urodele and seven anuran species were recorded through sweep-netting and adult observations. Detection probabilities were estimated from site occupancy models based on replicate sampling and from an adaptation of time-to-detection models relating detection probability to volume of water filtered. Discs filtered relatively small volumes (15–1250 mL), with detection probabilities of the two abundant species (<em>Pelobates</em> <em>cultripes</em>, <em>Hyla</em> <em>meridionalis</em>) increasing rapidly with sample size and water volume, reaching almost perfect detection (0.95) at four and seven discs, and 420 mL and 1860 mL, respectively. However, reaching high detection probabilities for rare species (<em>Pelodytes</em> <em>atlanticus</em>, <em>Pleurodeles</em> <em>waltl</em>, <em>Triturus</em> <em>pygmaeus</em>) would require larger sampling effort than that used in our study. Despite filtering much larger volumes (600–5300 mL), filtering with capsules at a single site per pond provided lower detection probabilities for abundant species than filtering with discs at five sites. Rarer species showed no difference between methods, which may be due to small sample sizes and reduced statistical power for species with few detection. The effect of conductivity on species detectability was largely negative, while the influence of water clarity varied across species, and pH had no effects. Overall, our results suggest that eDNA amphibian surveys in Mediterranean temporary ponds need to consider filter clogging, heterogeneous DNA distribution, and highly conductive waters.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.