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143 results for “eDNA metabarcoding”
F I G U R E 3 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 3 Comparison of trait-based metrics expressed in relative number of individuals computed from eDNA () and traditional electro-fishing (TEF;) samples in the five river stretches (RS), A, B, C, D and E. Trait categories: BEN, benthic; EUR, eurytopic; INS, insectivorous; OMN, omnivorous; PHY, phytophilic; POT, potamodromous; RHE, rheophilic; TOL, tolerant; PEL pelagic. Significance of the differences between eDNA and TEF metrics are shown: ns, not significant (P> 0.05)
F I G U R E 4 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 4 Boxplots (, median value;, interquartile range;, full range;, outliers) showing the variability in the eDNAadapted fish index (six metrics) computed at three sites (Brangues, Rhins and Usses) where 10 eDNA water samples were collected once. At each site, the eDNA-based six-metric fish index was computed for each of the 45 possible pairs of samples
F I G U R E 2 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 2 Comparison of trait-based metrics expressed in number of species computed from eDNA () and traditional electrofishing (TEF;) samples in the five river stretches (RS), A, B, C, D and E. Trait categories: BEN, benthic; EUR, eurytopic; INS, insectivorous; OMN, omnivorous; PHY, phytophilic; POT, potamodromous; RHE, rheophilic; TOL, tolerant; PEL pelagic. Significance of the differences between eDNA and TEF metrics are shown: P <0.05; P <0.01; ns, not significant (P> 0.05)
F I G U R E 1 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 1 Sampling locations along river stretches (RS) A to E () of the main channel of the Rhône River, France, using both traditional electro-fishing (TEF) and eDNA., Sites sampled every 2 months (September 2015– August 2016);, sites where ten eDNA water samples (filtration capsules) were collected once;, sites located on the tributaries or the Rhône River itself sampled once for eDNA. The 10 metric fish index and the adapted six-metric fish index were computed at all sites with a black filled symbol within natural water bodies
Data from: eDNA metabarcoding of log hollow sediments and soils highlights the importance of substrate type, frequency of sampling and animal size, for vertebrate species detection
<p>Fauna monitoring often relies on visual monitoring techniques such as camera trappings, which have biases leading to underestimates of vertebrate species diversity. Environmental DNA (eDNA) has emerged as a new source of biodiversity data that may improve biomonitoring; however, eDNA based assessments of species richness remain relatively untested in terrestrial environments. We investigated the suitability of fallen log hollow sediment as a source of vertebrate eDNA, across two sites in south-western Australia - one with a Mediterranean climate and the other semi-arid. We compared two different approaches (camera trapping and eDNA metabarcoding) for monitoring of vertebrate species, and investigated the effect of other factors (frequency of species, timing of visits, frequency of sampling, body size) on vertebrate species detectability. Metabarcoding of hollow sediments resulted in the detection of higher species richness in comparison Hollow sediment detected higher species richness (29 taxa: six birds, three reptiles and 20 mammals) to metabarcoding of soil at the entrance of the hollow (13 taxa: three birds, two reptiles and eight mammals). We detected 31 taxa in total with eDNA metabarcoding and 47 with camera traps, with 14 taxa detected by both (12 mammals and two birds). By comparing camera trap data with eDNA read abundance, we were able to detect vertebrates through eDNA metabarcoding that had visited the area up to two months prior to sample collection. Larger animals were more likely to be detected, and so were vertebrates that were identified multiple times in the camera traps. These findings demonstrate the importance of substrate selection, frequency of sampling, and animal size, on eDNA based monitoring. Future eDNA experimental design should consider all these factors as they affect detection of target taxa. </p>
Data from: Reduced sampling intensity through key sampling site selection for optimal characterization of riverine fish communities by eDNA metabarcoding
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Data from: Testing multiple substrates for terrestrial biodiversity monitoring using environmental DNA (eDNA) metabarcoding
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Data from: eDNA metabarcoding of log hollow sediments and soils highlights the importance of substrate type, frequency of sampling and animal size, for vertebrate species detection
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A manager’s guide to using eDNA metabarcoding in marine ecosystems
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Data from: Biodiversity assessment of tropical shelf eukaryotic communities via pelagic eDNA metabarcoding
<p>Our understanding of marine communities and their functions in an ecosystem relies on the ability to detect and monitor species distributions and abundances. Currently, the use of environmental DNA (eDNA) metabarcoding is increasingly being applied for the rapid assessment and monitoring of aquatic species. Most eDNA metabarcoding studies have either focused on the simultaneous identification of a few specific taxa/groups or have been limited in geographical scope. Here we employed eDNA metabarcoding to compare beta diversity patterns of complex pelagic marine communities in tropical coastal shelf habitats spanning the whole Caribbean Sea. We screened 68 water samples using a universal eukaryotic COI barcode region and detected highly diverse communities, which varied significantly among locations, and proved good descriptors of habitat type and environmental conditions. Less than 15% of eukaryotic taxa were assigned to metazoans, most DNA sequences belonged to a variety of planktonic 'protists', with over 50% of taxa unassigned at the phylum level, suggesting that the sampled communities host an astonishing amount of micro-eukaryotic diversity yet undescribed or absent from COI reference databases. Although such a predominance of micro-eukaryotes severely reduces the efficiency of universal COI markers to investigate vertebrate and other metazoans from aqueous eDNA, the study contributes to the advancement of rapid biomonitoring methods, and brings us closer to a full inventory of extant marine biodiversity.</p>
eDNA metabarcoding of avocado flowers: 'Hass' it got potential to survey arthropods in food production systems?
<p>In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection managed and unmanaged arthropod taxa (e.g. flower-visiting insects and potential pollinators). Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (<em>Persea americana </em>- 'Hass' avocado), with two conventional survey techniques; Digital Video Recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 hours of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. This study demonstrates that eDNA metabarcoding of flowers to detect visiting arthropods, although in a developmental stage, can complement traditional survey methods and increase the diversity of taxa detected with implications for both natural and agro-ecosystems.</p>
The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (metazoa data)
<p>This dataset is associated to the following publication: <strong>Macé, B.</strong>, Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (<strong>2024</strong>). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. <em>Molecular Ecology</em>, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a></p> <p>It contains the data obtained with the <strong>metazoa</strong> marker:</p> <ul> <li><em>fastq</em> files are the raw NGS eDNA sequencing outputs</li> <li><em>dat</em> file records the adapters names and oligos used for sequencing</li> </ul> <p>Metadata associated to each eDNA sample are also provided.</p> <p> </p> <p><strong>Methods</strong></p> <blockquote> <p>eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France).</p> </blockquote> <p> </p> <p><strong>References</strong></p> <p>Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. <em>PLOS ONE</em>, <em>10</em>(10), e0139633. https://doi.org/10.1371/journal.pone.0139633</p> <p>Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. <em>PeerJ</em>, <em>4</em>, e2444. https://doi.org/10.7717/peerj.2444</p> <p>Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. <em>Environmental DNA</em>, <em>3</em>(1), 142–156. https://doi.org/10.1002/edn3.140</p> <p>Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). <em>Environmental DNA: For Biodiversity Research and Monitoring</em>. Oxford University Press.</p> <p>Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. <em>Molecular Ecology</em>, <em>25</em>(4), 929–942. https://doi.org/10.1111/mec.13428</p>
The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (bact2 data)
<p>This dataset is associated to the following publication: <strong>Macé, B.</strong>, Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (<strong>2024</strong>). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. <em>Molecular Ecology</em>, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a></p> <p>It contains the data obtained with the <strong>bact2</strong> marker:</p> <ul> <li><em>fastq</em> files are the raw NGS eDNA sequencing outputs</li> <li><em>dat</em> file records the adapters names and oligos used for sequencing</li> </ul> <p>Metadata associated to each eDNA sample are also provided.</p> <p> </p> <p><strong>Methods</strong></p> <blockquote> <p>eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France).</p> </blockquote> <p> </p> <p><strong>References</strong></p> <p>Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. <em>PLOS ONE</em>, <em>10</em>(10), e0139633. https://doi.org/10.1371/journal.pone.0139633</p> <p>Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. <em>PeerJ</em>, <em>4</em>, e2444. https://doi.org/10.7717/peerj.2444</p> <p>Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. <em>Environmental DNA</em>, <em>3</em>(1), 142–156. https://doi.org/10.1002/edn3.140</p> <p>Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). <em>Environmental DNA: For Biodiversity Research and Monitoring</em>. Oxford University Press.</p> <p>Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. <em>Molecular Ecology</em>, <em>25</em>(4), 929–942. https://doi.org/10.1111/mec.13428</p>
The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (euka2 data)
<p>This dataset is associated to the following publication: <strong>Macé, B.</strong>, Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (<strong>2024</strong>). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. <em>Molecular Ecology</em>, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a></p> <p>It contains the data obtained with the <strong>euka2</strong> marker:</p> <ul> <li><em>fastq</em> files are the raw NGS eDNA sequencing outputs</li> <li><em>dat</em> file records the adapters names and oligos used for sequencing</li> </ul> <p>Metadata associated to each eDNA sample are also provided.</p> <p> </p> <p><strong>Methods</strong></p> <blockquote> <p>eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France).</p> </blockquote> <p> </p> <p><strong>References</strong></p> <p>Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. <em>PLOS ONE</em>, <em>10</em>(10), e0139633. https://doi.org/10.1371/journal.pone.0139633</p> <p>Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. <em>PeerJ</em>, <em>4</em>, e2444. https://doi.org/10.7717/peerj.2444</p> <p>Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. <em>Environmental DNA</em>, <em>3</em>(1), 142–156. https://doi.org/10.1002/edn3.140</p> <p>Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). <em>Environmental DNA: For Biodiversity Research and Monitoring</em>. Oxford University Press.</p> <p>Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. <em>Molecular Ecology</em>, <em>25</em>(4), 929–942. https://doi.org/10.1111/mec.13428</p>
The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves (teleo data)
<p>This dataset is associated to the following publication: <strong>Macé, B.</strong>, Mouillot, D., Dalongeville, A., Bruno, M., Deter, J., Varenne, A., Gudefin, A., Boissery, P., & Manel, S. (<strong>2024</strong>). The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves. <em>Molecular Ecology</em>, e17373. <a href="https://doi.org/10.1111/mec.17373">https://doi.org/10.1111/mec.17373</a></p> <p>It contains the data obtained with the <strong>teleo</strong> marker:</p> <ul> <li><em>fastq</em> files are the raw NGS eDNA sequencing outputs</li> <li><em>dat</em> file records the adapters names and oligos used for sequencing</li> </ul> <p>Metadata associated to each eDNA sample are also provided.</p> <p> </p> <p><strong>Methods</strong></p> <blockquote> <p>eDNA extractions were performed in a BSL-2 lab dedicated for eDNA samples following the protocol described in Polanco Fernández et al. (2021). Four PCR amplifications were conducted with different assays covering the whole tree of life. The teleo primer pair (Valentini et al., 2016) targets a 12S mitochondrial DNA marker from teleosts and elasmobranchs; the metazoa primer pair (Kelly et al., 2016) targets a 16S mitochondrial DNA marker from metazoans; the euka2 primer pair (Guardiola et al., 2015) targets a marker from eukaryotes located on the V7 region of the 18S ribosomal RNA; and the bact2 primer pair (Taberlet et al., 2018) targets a marker from prokaryotes located on the V4 region of the 16S ribosomal RNA. The idea of this experimental design is to give a holistic overview of communities, with a nested hierarchy euka2-metazoa-teleo to obtain a finer taxonomic resolution over animal communities, and particularly fish. Twelve PCR replicates per sample were run, with negative extractions and PCR positive and negative controls analyzed in parallel. Unique tags were used for each PCR replicate amplified with the teleo primers only, allowing to differentiate them in the bioinformatic analysis (see after). NGS library preparation and MiSeq paired-end sequencing (2 × 150 bp) were performed at DNA Gensee (Le Bourget-du-Lac, France).</p> </blockquote> <p> </p> <p><strong>References</strong></p> <p>Guardiola, M., Uriz, M. J., Taberlet, P., Coissac, E., Wangensteen, O. S., & Turon, X. (2015). Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. <em>PLOS ONE</em>, <em>10</em>(10), e0139633. https://doi.org/10.1371/journal.pone.0139633</p> <p>Kelly, R. P., O’Donnell, J. L., Lowell, N. C., Shelton, A. O., Samhouri, J. F., Hennessey, S. M., Feist, B. E., & Williams, G. D. (2016). Genetic signatures of ecological diversity along an urbanization gradient. <em>PeerJ</em>, <em>4</em>, e2444. https://doi.org/10.7717/peerj.2444</p> <p>Polanco Fernández, A., Marques, V., Fopp, F., Juhel, J.-B., Borrero-Pérez, G. H., Cheutin, M.-C., Dejean, T., González Corredor, J. D., Acosta-Chaparro, A., Hocdé, R., Eme, D., Maire, E., Spescha, M., Valentini, A., Manel, S., Mouillot, D., Albouy, C., & Pellissier, L. (2021). Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes. <em>Environmental DNA</em>, <em>3</em>(1), 142–156. https://doi.org/10.1002/edn3.140</p> <p>Taberlet, P., Bonin, A., Zinger, L., & Coissac, E. (2018). <em>Environmental DNA: For Biodiversity Research and Monitoring</em>. Oxford University Press.</p> <p>Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F., Bellemain, E., Besnard, A., Coissac, E., Boyer, F., Gaboriaud, C., Jean, P., Poulet, N., Roset, N., Copp, G. H., Geniez, P., Pont, D., Argillier, C., Baudoin, J.-M., … Dejean, T. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. <em>Molecular Ecology</em>, <em>25</em>(4), 929–942. https://doi.org/10.1111/mec.13428</p> <p> </p>
Large-scale eDNA metabarcoding survey reveals marine biogeographic break and transitions over tropical north-western Australia
<p><b>Aim:</b> Environmental DNA (eDNA) metabarcoding has demonstrated its applicability as a highly sensitive biomonitoring tool across small spatial and temporal scales in marine ecosystems. However, it has rarely been tested across large spatial scales, or biogeographical barriers. Here, we scale up marine eDNA metabarcoding, test its ability to detect a major marine biogeographic break, and evaluate its use as a regional biomonitoring tool in Australia.</p> <p><b>Location:</b> North-western Australia (NWA)</p> <p><b>Methods:</b> We applied metabarcoding assays targeting the mitochondrial 16S rRNA and CO1 genes to 284 surface seawater eDNA samples collected from 71 mid-shelf, inshore, coastal and nearshore estuarine sites over 700 km of the NWA coastline.</p> <p><b>Results:</b> Metabarcoding detected a wide range of bony fish (404 taxa), elasmobranchs (44) and aquatic reptiles (5). We detected bioregional and depth differentiation within inshore bony fish communities. These findings support the presence of a marine biogeographic break, which is purported to occur in the vicinity of Cape Leveque, demarcating the border between the Kimberley and Canning bioregions. Inshore bony fish and elasmobranch communities, as well as coastal bony assemblages, were additionally found to differ between the South and North Kimberley regions <span><span>suggesting</span></span> previously unrecognised subregional differentiation among these taxa. The overall compositional data has been used to update distribution information for a number of endangered, elusive and data-deficient taxa, including sawfish (family: Pristidae), northern river shark (<i>Glyphis garricki</i>) and wedgefish (genus: <i>Rhynchobatus</i>).</p> <p><b>Main conclusions</b>: eDNA metabarcoding demonstrated a high level of sensitivity that was able to discern fine-scale patterns across the large-scale, remote and oceanographically complex region of North-western Australia. Importantly, this study highlights the potential of integrating broad-scale eDNA metabarcoding alongside other baseline surveys and long-term monitoring approaches, which are crucial for the sustainable management and conservation of marine biodiversity in this unique marine region.</p>
Niche overlap between two large herbivores across landscape variability using dietary eDNA metabarcoding: Raw sequences of European bison and red deer – Bialowieza
<p><span>Understanding the trophic ecology of herbivore species is key to assess their environmental requirements and to improve management policies, but measuring their trophic interactions remains challenging. Among the methods available, quantifying the plant composition of a species' diet provides a detailed picture of how species exploit the resources in their environment and their associated niche overlap. Yet, most studies focusing on herbivore trophic ecology ignore the influence that landscape variability may have. Here, we studied how landscape variability influences trophic interactions through niche partitioning. We used eDNA metabarcoding to quantify the diet composition of two large herbivores of the Bialowieza Forest, red deer (<em>Cervus elaphus</em>) and European bison (<em>Bison bonasus</em>, hereafter referred to as bison) to investigate how increasing habitat quality and predation risk in their environment influence their diet composition and niche partitioning. We found red deer to have an overall greater diet variability and lower niche overlap within species compared to bison. Moreover, our findings indicate herbivore interactions are non-homogeneous across the landscape. Higher habitat quality was associated with higher niche overlap only within bison. We also detected an increase in niche overlap with increasing predation risk within red deer, indicating they modify their diet choice as a reaction to wolf predation risk. This study provides evidence of eDNA dietary metabarcoding as a useful tool for wildlife management to assess the status of species in an ecosystem based on known environmental factors. We suggest future studies to integrate the environments' variability when studying trophic ecology of herbivores to capture the whole extent of species interaction in order to improve conservation and management guidelines. </span></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 from: Community ecology in a bottle: Leveraging eDNA metabarcoding data to predict occupancy of co-occurring species
<p>Detecting environmental DNA (eDNA) of numerous organisms from the same samples has been revolutionized by metabarcoding. However, utilizing the vast amounts of data generated from metabarcoding to predict occupancy probabilities for co-occurring species is currently rare. Here, we demonstrate how metabarcoding data can be used to advance community ecology research through a case study using replicate stream water samples and Bayesian occupancy models to test hypotheses of eDNA occurrence for a native fish (brook trout, Salvelinus fontinalis), its major ectoparasite (gill lice, Salmincola edwardsii), and an introduced potential competitor (brown trout, Salmo trutta). Gill lice DNA occupancy was positively associated with brook trout biomass determined via electrofishing conducted near eDNA sampling sites, suggesting gill lice occupancy is dependent on host density. Leveraging site-specific molecular operational taxonomic units identified from metabarcoding, DNA occupancy of trout and gill lice was often positively predicted by species richness of aquatic insect orders trout commonly feed on, which are also environmental quality indicators. Thus, high-quality habitat that environmentally sensitive salmonids and their primary prey rely on may promote higher fish occupancy rates, further facilitating the spread of fish parasites. An increasing amount of community-level data is being generated from global metabarcoding efforts, and we suggest our framework could be broadly implemented to enhance understanding of factors impacting distributions of co-occurring species, reveal new ecological phenomena, and support management and conservation efforts.</p>
Data from: Primer sets evaluation and sampling method assessment for the monitoring of fish communities in the North-western part of the Mediterranean Sea through eDNA metabarcoding
<p>Environmental DNA (eDNA) metabarcoding appears to be a promising tool for surveying fish communities. However, the effectiveness of this method relies on primer set performance and on a robust sampling strategy. While some studies have evaluated the efficiency of several primers for fish detection, it has not yet been assessed <em>in situ </em>for the Mediterranean Sea. In addition, mainly surface waters were sampled and no filter porosity testing was performed. In this pilot study, our aim was to evaluate the ability of six primer sets, targeting 12S rRNA (AcMDB07; MiFish; Tele04) or 16S rRNA (Fish16S; Fish16SFD; Vert16S) loci, to detect fish species in the Mediterranean Sea using a metabarcoding approach. We also assessed the influence of sampling depth and filter pore size (0.45 µm <em>versus</em> 5 µm filters). To achieve this, we developed a novel sampling strategy allowing simultaneous surface and bottom filtration of large water volumes along on-site the same transect. We found that 16S rRNA primer sets enabled more fish taxa to be detected across each taxonomic level. The best combination was Fish16S/Vert16S/AcMDB07, which recovered 95% of the 97 fish species detected in our study. There were highly significant differences in species composition between surface and bottom samples. Filters of 0.45 µm led to the detection of significantly more fish species. Therefore, to maximize fish detection in the studied area, we recommend to filter both surface and bottom waters through 0.45 µm filters and to use a combination of these three primer sets.</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.