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486 results for “DNA metabarcoding”
Multi-locus DNA metabarcoding of western spotted skunk diet in the McKenzie River Ranger District of the Willamette National Forest from 2017-2019
There are increasing concerns about the declining population trends of small mammalian carnivores around the world. Their conservation and management is often challenging due to limited knowledge about their ecology and natural history. To address one of these deficiencies for western spotted skunks (Spilogale gracilis), we investigated their diet in the Oregon Cascades of the Pacific Northwest during 2017 –2019. We collected 130 spotted skunk scats opportunistically and with detection dog teams and identified prey items using DNA metabarcoding and mechanical sorting. Western spotted skunk diet consisted of invertebrates such as wasps, millipedes, and gastropods, vertebrates such as small mammals, amphibians, and birds, and plants such as Gaultheria, Rubus, and Vaccinium. Diet also consisted of items such as black-tailed deer that were likely scavenged. Comparison in diet by season revealed that spotted skunks consumed more insects during the dry season (June –August), particularly wasps (75% of scats in the dry season), and marginally more mammals during the wet season(September –May). We observed similar diet in areas with no record of human disturbance and areas with a history of logging at most spatial scales, but scats collected in areas with older forest within a skunk’s home range (1 km buffer) were more likely to contain insects. Western spotted skunks provide food web linkages between aquatic, terrestrial, and arboreal systems and serve functional roles of seed dispersal and scavenging. Due to their diverse diet and prey-switching, western spotted skunks may dampen the effects of irruptions of prey, such as wasps during dry springs and summers. By studying the natural history of western spotted skunks in the Pacific Northwest forests while they are still abundant, we provide key information necessary to achieve the conservation goal of keeping this common species common.
Arctic-boreal bryophyte dynamics since the last glacial from ancient DNA metabarcoding
<p>A total of 26 lake-sediment cores collected from 26 study sites spanning the glacial and interglacial transition are used in this study. These sites are distributed across Siberia, Beringia, and Alaska regions, with a gradient of vegetation types dominated by tundra in the northern region and transitioning to boreal forest in the southern extents. DNA samples from the sediment core were analysed with a standard sedimentary ancient DNA metabarcoding pipeline (see additional description), which resulted in a raw dataset of all DNA plant sequences, which were then filtered for Bryophytes (Bryophyte DNA dataset). The Bryophyte DNA dataset contains 120 unique ASV. Samples in the Bryophyte DNA dataset are then grouped into 1000-year time slices and are subsequently resampled to a base count of 500 read counts for each time slice. After that, a Bryophyte trait datastet is assigned to the Bryophyte DNA dataset. </p> <p> </p> <h3>Input files</h3> <ul> <li><strong>Excel file with all data used in the R-Script:</strong> "Bryophytes_data.xlsx"</li> <li><strong>WorldClim 2.0 dataset with mean temperatures of Warmest Quarter</strong> (https://www.worldclim.org/; Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. <a href="https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5086">International Journal of Climatology 37 (12): 4302-4315</a>): "wc2.1_30s_bio_10.tif"</li> </ul> <h3>R script</h3> <ul> <li><strong>R-Script:</strong> "2025-01-14_R-Script_ arctic_boreal_bryophyte_dynamics_DNA_metabarcoding.R"</li> </ul> <h3>R outputs</h3> <ul> <li><strong>resampled Bryophyte metabarcoding percentage dataset with ASV:</strong> "2025-01-14_bryophyta_resampled_percentages_mean_100runs_sequences.csv"</li> <li><strong>resampled Bryophyte metabarcoding percentage dataset with unique scientific names: </strong>"2025-01-14_bryophyta_resampled_percentages_mean_100runs_scientific_names.csv"</li> <li><strong>GBIF taxa occurrences with WorldClim temperature data: </strong>"2025-01-14_gbif_taxa_occurrences_seqtypes_climate.csv"</li> </ul> <p> </p>
The tpm metabarcoding DNA sequence database for taxonomic allocations using RDP classifier implemented in DADA2.
<p><strong>The </strong><em>tpm</em><strong> metabarcoding DNA sequence database for taxonomic allocations using the Mothur and DADA2 bio-informatic tools</strong></p> <p>A.C.M. Pozzi<sup>1</sup>, R. Bouchali<sup>1</sup>, L. Marjolet<sup>1</sup>, B. Cournoyer<sup>1</sup></p> <p><sup>1 </sup><em>University of Lyon, UMR Ecologie Microbienne Lyon (LEM), CNRS 5557, INRAE 1418, Université Claude Bernard Lyon 1, VetAgro Sup, Research Team “Bacterial Opportunistic Pathogens and Environment” (BPOE), 69280 Marcy L’Etoile, France.</em></p> <p><strong>Corresponding authors: </strong></p> <ul> <li>A.C.M. Pozzi, UMR Microbial Ecology, CNRS 5557, CNRS 1418, VetAgro Sup, Main building, aisle 3, 1st floor, 69280 Marcy-L’Etoile, France. Tel. (+33) 478 87 39 47. Fax. (+33) 472 43 12 23. Email: <a href="mailto:adrien.meynier_pozzi@vetagro-sup.fr">adrien.meynier_pozzi@vetagro-sup.fr</a></li> <li>B. Cournoyer, UMR Microbial Ecology, CNRS 5557, CNRS 1418, VetAgro Sup, Main building, aisle 3, 1st floor, 69280 Marcy-L’Etoile, France. Tel. (+33) 478 87 56 47. Fax. (+33) 472 43 12 23. Email: and <a href="mailto:benoit.cournoyer@vetagro-sup.fr">benoit.cournoyer@vetagro-sup.fr</a></li> </ul> <p><strong>Keywords:</strong></p> <p>BACtpm, Bacteria, <em>tpm</em>, thiopurine-<em>S</em>-methyltransferase EC:2.1.1.67, Nucleotide sequences, PCR products, Next-Generation-Sequencing, OTHU</p> <p><strong>Description:</strong></p> <ul> <li>The <em>tpm</em> gene codes for the thiopurine-<em>S</em>-methyltransferase (TPMT), an enzyme that can detoxify metalloid-containing oxyanions and xenobiotics (Cournoyer et al., 1998). Bacterial TPMTs radiated apart from human and animal TPMTs, and showed a vertical evolution in line with the 16S rRNA gene molecular phylogeny (Favre‐Bonté et al., 2005).</li> <li>The <em>tpm</em> database, named BACtpm, was designed to apply the <em>tpm</em>-metabarcoding analytical scheme published in Aigle et al. (2021). It includes the full <em>tpm</em> identifiers, GenBank accession numbers, complete taxonomic records (domain down to strain code) of about 215 nucleotide-long <em>tpm</em> sequences of 840 unique taxa belonging to 139 genera.</li> <li>Nucleotide sequences of <em>tpm</em> (range: 190-233 nucleotides) were either retrieved from public repositories (GenBank) or made available by B. Cournoyer’s research group. Colin et al. (2020) described the PCR and high throughput Illumina Miseq DNA sequencing procedures used to produce <em>tpm</em> sequences.</li> <li>BACtpm v.2.0.1 (June 2021 release) is made available under the Creative Commons Attribution 4.0 International Licence. It can be used for the taxonomic allocations of <em>tpm </em>sequences down to the species and strain levels. Data is stored in the csv format enabling future user to reformat it to fit their specific needs.</li> </ul> <p><strong>Acknowledgments:</strong></p> <p>We thank the worldwide community of microbiologists who made contributions to public databases in the past decades, and made possible the elaboration of the BACtpm database. We also thank the Field Observatory in Urban Hydrology (OTHU, <a href="http://www.graie.org/othu/">www.graie.org/othu/</a>), Labex IMU (Intelligence des Mondes Urbains), the Greater Lyon Urban Community, the School of Integrated Watershed Sciences H2O'LYON, and the Lyon Urban School for their support in the development of this database. This work was funded by the French national research program for environmental and occupational health of ANSES under the terms of project “Iouqmer” EST 2016/1/120, l'Agence Nationale de la Recherche through ANR-16-CE32-0006, ANR-17-CE04-0010, ANR-17-EURE-0018 and ANR-17-CONV-0004, by the MITI CNRS project named Urbamic, and the French water agency for the Rhône, Mediterranean and Corsica areas through the Desir and DOmic projects. We thank former BPOE lab members who contributed to start and expand the BACtpm database: Céline COLINON, Romain MARTI, Emilie BOURGEOIS, Sébastien RIBUN and Yannick COLIN.</p> <p><strong>References:</strong></p> <p>Aigle, A., Colin, Y., Bouchali, R., Bourgeois, E., Marti, R., Ribun, S., Marjolet, L., Pozzi, A.C.M., Misery, B., Colinon, C., Bernardin-Souibgui, C., Wiest, L., Blaha, D., Galia, W., Cournoyer, B., 2021. Spatio-temporal variations in chemical pollutants found among urban deposits match changes in thiopurine S-methyltransferase-harboring bacteria tracked by the tpm metabarcoding approach. Sci. Total Environ. 767, 145425. https://doi.org/10.1016/j.scitotenv.2021.145425</p> <p>Colin, Y., Bouchali, R., Marjolet, L., Marti, R., Vautrin, F., Voisin, J., Bourgeois, E., Rodriguez-Nava, V., Blaha, D., Winiarski, T., Mermillod-Blondin, F., Cournoyer, B., 2020. Coalescence of bacterial groups originating from urban runoffs and artificial infiltration systems among aquifer microbiomes. Hydrol. Earth Syst. Sci. 24, 4257–4273. https://doi.org/10.5194/hess-24-4257-2020</p> <p>Cournoyer, B., Watanabe, S., Vivian, A., 1998. A tellurite-resistance genetic determinant from phytopathogenic pseudomonads encodes a thiopurine methyltransferase: evidence of a widely-conserved family of methyltransferases1The International Collaboration (IC) accession number of the DNA sequence is L49178.1. Biochim. Biophys. Acta BBA - Gene Struct. Expr. 1397, 161–168. https://doi.org/10.1016/S0167-4781(98)00020-7</p> <p>Favre‐Bonté, S., Ranjard, L., Colinon, C., Prigent‐Combaret, C., Nazaret, S., Cournoyer, B., 2005. Freshwater selenium-methylating bacterial thiopurine methyltransferases: diversity and molecular phylogeny. Environ. Microbiol. 7, 153–164. https://doi.org/10.1111/j.1462-2920.2004.00670.x</p>
Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: datasets collected using light microscopy and DNA metabarcoding
<p>This dataset contains all data required to reproduce the analyses conducted in Macgregor <em>et al. </em>(2018), using the R Notebook archived at doi: <a href="https://dx.doi.org/10.5281/zenodo.1322712">10.5281/zenodo.1322712</a>.</p> <p>Specifically, the dataset contains details of pollen transport detected on two matched samples, each containing 311 moths of 41 species, using two methods: a traditional light microscopy approach and a novel DNA metabarcoding approach. Both raw and manually-curated versions of each dataset are archived for full clarity. The dataset additionally contains all metadata required to fully interpret these data, including the RGB tables used to prepare Fig 4 in Macgregor <em>et al. </em>(2018).</p> <p>Macgregor <em>et al. </em>(2018) Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using light microscopy and DNA metabarcoding. <em>Ecological Entomology</em>, doi: <a href="https://dx.doi.org/10.1111/een.12674">10.1111/een.12674</a>.</p>
Spineless and overlooked: DNA metabarcoding of autonomous reef monitoring structures reveals intra- and interspecific genetic diversity in Mediterranean invertebrates
<p>Sequence data and stepwise pipeline outputs associated with the article "Spineless and overlooked: DNA metabarcoding of autonomous reef monitoring structures reveals intra- and interspecific genetic diversity in Mediterranean invertebrates".</p> <p>Preprint available here: <a href="https://doi.org/10.22541/au.167085544.47638352/v1">10.22541/au.167085544.47638352/v1</a></p> <p>Sequence data is deposited in fastq-format in folders by region (Palinuro.tar.gz, Livorno.tar.gz, and Rovinj.tar.gz) and a separate folder for controls (Controls.tar.gz). Each fastq-file contains sequences for a single PCR replicate named by sample and replicate number. Sample names are described in spineless_sample_names.csv. Positive control sequences are described in SM1_positive_controls.csv. Stepwise pipeline outputs are available in the folder Pipeline_outputs_stepwise.zip</p> <p>Scripts used to generate pipeline outputs as well as other aspects of the final article are available at <a href="https://github.com/thomasdotter/spineless-haplotypes">https://github.com/thomasdotter/spineless-haplotypes</a>.</p> <p> </p>
Data from: Deciphering host-parasitoid interactions and parasitism rates of crop pests using DNA metabarcoding
Open the record for dataset details and reuse information.
DNA metabarcoding and spatial modelling link diet diversification with distribution homogeneity in European bats
<p>Inferences of the interactions between species’ ecological niches and spatial distribution have been historically based on simple metrics such as low-resolution dietary breadth and range size, which might have impeded the identification of meaningful links between niche features and spatial patterns. We analysed the relationship between dietary niche breadth and spatial distribution features of European bats, by combining continent-wide DNA metabarcoding of faecal samples with species distribution modelling. Our results show that while range size is not correlated with dietary features of bats, the homogeneity of the spatial distribution of species exhibits a strong correlation with dietary breadth. We also found that dietary breadth is correlated with bats’ hunting flexibility. However, these two patterns only stand when the phylogenetic relations between prey are accounted for when measuring dietary breadth. Our results suggest that the capacity to exploit different prey types enables species to thrive in more distinct environments and therefore exhibit more homogeneous distributions within their ranges.</p>
Data from: DNA metabarcoding for biodiversity monitoring in a national park: screening for invasive and pest species
<ol> <li><span>DNA metabarcoding was utilized for a large-scale, multi-year assessment of biodiversity in Malaise trap collections from the Bavarian Forest National Park (Germany, Bavaria). </span></li> <li><span>Principal Component Analysis of read count-based biodiversities revealed clustering in concordance with whether collection sites were located inside or outside of the National Park.</span></li> <li><span>Jaccard distance matrices of the presences of BINs at collection sites in the two survey years (2016 and 2018) were significantly correlated.</span></li> <li><span>Overall similar patterns in the presence of total arthropod BINs, as well as BINs belonging to four major arthropod orders across the study area, were observed in both survey years, and are also comparable with results of a previous study based on DNA barcoding of Sanger-sequenced specimens.</span></li> <li><span>A custom reference sequence library was assembled from publicly available data to screen for pest or invasive arthropods among the specimens or from the preservative ethanol.</span></li> <li> <span>A single 98.6% match to the invasive bark beetle </span><span>Ips duplicatus</span><span> was detected in an ethanol sample. This species has not previously been detected in the National Park.</span> </li> </ol>
Trait-based sensitivity of large mammals to a catastrophic tropical cyclone: DNA metabarcoding data
<p>Extreme weather events perturb ecosystems and increasingly threaten biodiversity<sup>1</sup>. Ecologists emphasize the need to forecast and mitigate the impacts of these incidents, which requires knowledge of how risk is distributed among species and environments, but the scale and unpredictability of extreme events complicates assessment<sup>1</sup><sup>–4</sup>. These challenges are compounded for large animals ('megafauna'), which play crucial ecological roles but are hard to study<sup>5</sup>. Traits such as body size, dispersal ability, and habitat affiliation are among the hypothesized determinants of animals' vulnerability to natural hazards<sup>1,6,7</sup>. However, it has rarely been possible to test these propositions or, more generally, to link short- and longer-term effects of weather-related disturbance<sup>8,9</sup>. Here, we show how large herbivores and carnivores in Mozambique responded to Intense Tropical Cyclone Idai, the deadliest storm on record in Africa, across scales ranging from individual decisions in the hours after landfall to community-level responses nearly 20 months later. Animals occupying low-elevation habitats exhibited strong spatial responses to rising floodwaters. Body size predicted species' subsequent numerical responses: small-bodied species exhibited the greatest population declines. We trace this sensitivity to limited mobility, which increased likelihood of death during the flood and constrained animals' capacity to withstand food shortages afterward. Our results identify potentially general trait-based mechanisms underlying animal responses to severe weather and may help to inform strategies for wildlife conservation in a volatile climate.</p> <ol> <li><span><em><span>Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change</span></em><span> [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press. Cambridge University Press, Cambridge, UK and New York, NY, USA, (2022).</span></span></li> <li><span><span>Smith, M. An ecological perspective on extreme climatic events: A synthetic definition and framework to guide future research. <em>J. Ecol.</em> <strong>99</strong>, 656-663 (2011).</span></span></li> <li><span><span>Ummenhofer, C. C., & Meehl, G. A. Extreme weather and climate events with ecological relevance: a review, <em>Phil. Trans. R. Soc. B. </em><strong>372</strong>, 20160135 (2017).</span></span></li> <li><span><span>Jentsch, A., Kreyling, J., & Beierkuhnlein, C. A new generation of climate-change experiments: events, not trends. <em>Front. Ecol. Environ. </em><strong>5</strong>, 365-374 (2007).</span></span></li> <li><span><span>Pringle, R. M., et. al. Impacts of large herbivores on terrestrial ecosystems. <em>Current Biology</em> <strong>33</strong>, R584-R610 (2023).</span></span></li> <li><span><span>Spiller, D. A., Losos, J. B., & Schoener, T. W. Impact of a catastrophic hurricane on island populations. <em>Science </em><strong>281</strong>, 695-697 (1998). </span></span></li> <li><span><span>Schoener, T. W., & Spiller, D. A. Nonsynchronous recovery of community characteristics in island spiders after a catastrophic hurricane. <em>PNAS </em><strong>103</strong>, 2220-2225 (2006).</span></span></li> <li><span><span>Pruitt, N., Little, A. G., Majumdar, S. J., Schoener, T. W., & Fisher, D. N. Call-to-Action: A global consortium for tropical cyclone ecology. <em>TREE </em><strong>34</strong>, 588-590 (2019).</span></span></li> <li><span><span>Lin, T. C., Hogan, J. A., & Chang, C. T. Tropical cyclone ecology: a scale-link perspective. <em>TREE </em><strong>35</strong>, 594-604 (2020).</span></span></li> </ol>
Environmental DNA metabarcoding differentiates between micro-habitats within the rocky intertidal
<p>While the utility of environmental DNA (eDNA) metabarcoding surveys for biodiversity monitoring continues to be demonstrated, the spatial and temporal variability of eDNA, and thus the limits of the differentiability of an eDNA signal, remains under-characterized. In this study, we collected eDNA samples from distinct micro-habitats (~40 m apart) in a rocky intertidal ecosystem over their exposure period in a tidal cycle. During this period, the micro-habitats transitioned from being interconnected, to physically isolated, to interconnected again. Using a well-established eukaryotic (cytochrome oxidase subunit I) metabarcoding assay, we detected 415 species across 28 phyla. Across a variety of univariate and multivariate analyses, using exclusively taxonomically assigned data as well as all detected amplicon sequence variants (ASVs), we identified unique eDNA signals from the different micro-habitats sampled. This difference paralleled expected ecological gradients and increased as the sites became more physically disconnected. Our results demonstrate that eDNA biomonitoring can differentiate micro-habitats in the rocky intertidal only 40 m apart, that these differences reflect known ecology in the area, and that physical connectivity informs the degree of differentiation possible. These findings showcase the potential power of eDNA biomonitoring to increase the spatial and temporal resolution of marine biodiversity data, aiding research, conservation, and management efforts.</p>
Data from: European green crab predation in a Washington State estuary revealed with DNA metabarcoding
<p><strong>Fisher, MC, Grason, EW, Stote, A, Kelly, RP, Litle, K, & PS McDonald. (in review). <em>Invasive European green crab (</em>Carcinus maenas<em>) predation in a Washington State estuary revealed with DNA metabarcoding. </em></strong></p> <p>Sequencing data files produced for Fisher et al. (in review) on an Illumina MiSeq (2x300bp) targeting a 418bp DNA sequence in the mitochondrial cytochrome C oxidase subunit I gene (cox1 or COI) Folmer region. Data are demultiplexed but otherwise un-processed. Sample data sheets used to load each sequencing run are included as excel spreadsheets in the appropriate zipped folder. The metadata file contains sample (green crab stomach / mock community) metadata and corresponding MiSeq run number(s). </p> <p>Associated lab protocols are available on Github (<a href="https://github.com/mfisher5/Green-crab-dDNA/tree/main/doc" target="_blank" rel="noopener">Green-Crab-dDNA</a>)</p> <p>---</p> <p>Abstract: Predation by invasive species can threaten local ecosystems and economies. The European green crab (<em>Carcinus maenas</em>), one of the most widespread marine invasive species, is an effective predator associated with clam and crab population declines outside of its native range. In the U.S. Pacific Northwest, green crab has recently increased in abundance and expanded its distribution, generating concern for estuarine ecosystems and associated aquaculture production. However, regionally-specific information on the trophic impacts of invasive green crab is very limited. We compared the stomach contents of green crabs collected on shellfish aquaculture beds versus natural intertidal sloughs in Willapa Bay, Washington, to provide the first in-depth description of European green crab diet at a particularly crucial time for regional management. We first identified putative prey items using DNA metabarcoding of stomach content samples. We compared diet composition across sites using prey presence/absence and an index of species-specific relative abundance. For eight prey species, we also calibrated metabarcoding data to quantitatively compare DNA abundance between prey items, and to describe an ‘average’ green crab diet at an intertidal slough and an actively cultivated Manila clam bed. From the stomach contents of 61 green crabs, we identified 54 unique taxa belonging to nine phyla. The stomach contents of crabs collected from cultivated Manila clam beds were significantly different from the stomach contents of crabs collected at natural intertidal sloughs. Across all sites, arthropods were the most frequently detected prey, with the native hairy shore crab (<em>Hemigrapsus oregonensis</em>) the single most common prey item. Of the eight species included in the quantitative model, two ecologically-important native species – the sand shrimp (<em>Crangon franciscorum</em>) and the Pacific staghorn sculpin (<em>Leptocottus armatus</em>) – were the most abundant in crab stomach contents, when present. In addition to providing timely information on green crab diet, our research demonstrates the novel application of a recently developed model for more quantitative DNA metabarcoding. This represents another step in the ongoing evolution of DNA-based diet analysis towards producing the quantitative data necessary for modeling invasive species impacts.</p>
Github Repository for: European green crab predation in a Washington State estuary revealed with DNA metabarcoding
<p><strong>Fisher, MC, Grason, EW, Stote, A, Kelly, RP, Litle, K, & PS McDonald. (2024).<em> </em>Invasive European green crab (<em>Carcinus maenas</em>) predation in a Washington State estuary revealed with DNA metabarcoding. DOI:10.1371/journal.pone.0302518<em><br></em></strong></p> <p>Github release v1.1 of the repository for Fisher et al. 2024, "European green crab predation in a Washington State estuary revealed with DNA metabarcoding." For the most updated repository, see: <a href="https://github.com/mfisher5/Green-crab-dDNA/tree/main/doc">github.com/mfisher5/Green-crab-dDNA</a></p> <p>Contains the code and minimum dataset necessary to replicate study findings.</p> <p> </p> <p>---</p> <p>Abstract: Predation by invasive species can threaten local ecosystems and economies. The European green crab (<em>Carcinus maenas</em>), one of the most widespread marine invasive species, is an effective predator associated with clam and crab population declines outside of its native range. In the U.S. Pacific Northwest, green crab has recently increased in abundance and expanded its distribution, generating concern for estuarine ecosystems and associated aquaculture production. However, regionally-specific information on the trophic impacts of invasive green crab is very limited. We compared the stomach contents of green crabs collected on shellfish aquaculture beds versus natural intertidal sloughs in Willapa Bay, Washington, to provide the first in-depth description of European green crab diet at a particularly crucial time for regional management. We first identified putative prey items using DNA metabarcoding of stomach content samples. We compared diet composition across sites using prey presence/absence and an index of species-specific relative abundance. For eight prey species, we also calibrated metabarcoding data to quantitatively compare DNA abundance between prey items, and to describe an ‘average’ green crab diet at an intertidal slough and an actively cultivated Manila clam bed. From the stomach contents of 61 green crabs, we identified 54 unique taxa belonging to nine phyla. The stomach contents of crabs collected from cultivated Manila clam beds were significantly different from the stomach contents of crabs collected at natural intertidal sloughs. Across all sites, arthropods were the most frequently detected prey, with the native hairy shore crab (<em>Hemigrapsus oregonensis</em>) the single most common prey item. Of the eight species included in the quantitative model, two ecologically-important native species – the sand shrimp (<em>Crangon franciscorum</em>) and the Pacific staghorn sculpin (<em>Leptocottus armatus</em>) – were the most abundant in crab stomach contents, when present. In addition to providing timely information on green crab diet, our research demonstrates the novel application of a recently developed model for more quantitative DNA metabarcoding. This represents another step in the ongoing evolution of DNA-based diet analysis towards producing the quantitative data necessary for modeling invasive species impacts.</p>
Data from: Metabarcoding of soil environmental DNA replicates plant community variation but not specificity
<blockquote> <p>While metabarcoding of plant DNA from their environment is an exciting method that can supplement inventorying of live plant species, the accuracy and specificity has yet to be fully assessed over complex continuous landscapes. In this work, we evaluate plant community profiles produced via metabarcoding of soil by comparing them to a morphological survey. We assessed plant communities by metabarcoding of soil DNA in 130 sites along ecological gradients (nutrients, succession, moisture) in Denmark using chloroplast <i>trn</i>L region (10-143 bp) primer set and compared the resulting communities to communities produced with a longer nuclear ITS2 region (~216 bp) and a morphological survey. We found that the community variation observed within the morphological survey was well represented by molecular surveys, with significant correlation with both community composition and richness using both primer sets. While the majority of the ITS2 sequences could be assigned to species (over 80%), we had less success with the <i>trn</i>L sequences (70%), which was only possible after restricting the reference database to local species. We conclude that the community profiles produced by metabarcoding can be highly effective in performing large-scale macroecological studies. However, the discovery rates and taxonomic assignments produced via metabarcoding remained inferior to morphological surveys, but manual curation of databases improves the <i>specificity</i> of assignments made by the <i>trn</i>L primers, and improves the <i>accuracy</i> of the assignments made with the ITS2 primers. Finally, we suggest that a greater percentage of named diversity would be recovered by increasing soil sampling with the use of additional universal primer sets.</p> </blockquote>
Interspecific coprophagia by wild red foxes: DNA metabarcoding reveals a potentially widespread form of commensalism among animals
<p>Vertebrate animals are known to consume other species' faeces, yet the role of such coprophagy in species dynamics remains unknown, not least due to the methodological challenges of documenting it. In a large-scale metabarcoding study of red fox and pine marten scats, we document a high occurrence of domestic dog DNA in red fox scats and investigate if it can be attributed to interspecific coprophagia. We tested whether experimental artifacts or other sources of DNA could account for dog DNA, regressed dog occurrence in the diet of fox against that of the fox' main prey, short-tailed field voles, and consider whether predation or scavenging could explain the presence of dog DNA. Additionally, we determined the calorific value of dog faeces through calorimetric explosion. The high occurrence of dog DNA in the diet of fox, the timing of its increase, and the negative relationship between dog and the fox's main prey, point to dog faeces as the source of DNA in fox scats. Dog faeces being highly calorific, we found that foxes, but not pine martens, regularly exploit them, seemingly as an alternative resource to fluctuating prey. Scattered accounts from the literature may suggest that interspecific coprophagia is a potentially frequent and widespread form of interaction among vertebrates. However, further work should address its prevalence in other systems as well as the implications for ecological communities. Tools such as metabarcoding offer a way forward.</p>
Niche partitioning between planktivorous fish in the pelagic Baltic Sea assessed by DNA metabarcoding, qPCR and microscopy: Data and Analyses
<p class="MsoNormal"><span>Marine communities undergo rapid changes because of human-induced ecosystem pressures. The Baltic Sea pelagic food web has experienced several regime shifts during the past century, resulting in a system where competition between planktivorous mesopredators is assumed to be high. While the two clupeids sprat and herring reveal signs of competition, the stickleback population has increased drastically during the past decades. Here, we investigate diet overlap between the three dominating planktivorous fish in the Baltic Sea, utilizing DNA metabarcoding on the <em>18S rRNA</em> gene and the <em>COI </em>gene, targeted qPCR, and microscopy. Our results show niche differentiation between clupeids and stickleback and that rotifers play an important function in niche partitioning of stickleback, as a resource that is not being used, neither by the clupeids nor by other zooplankton. <span>We further show that all the diet assessment methods used in this study are consistent but DNA metabarcoding describes the plankton-fish link at the highest taxonomic resolution. </span>This study suggests that rotifers and other understudied soft-bodied prey may have an important function in the pelagic food web and that the growing population of pelagic stickleback is supported by the unutilized feeding niche offered by the rotifers.</span></p>
BeeDNA: microfluidic environmental DNA metabarcoding as a tool for connecting plant and pollinator communities
<p><strong>Data repository accompanying the paper 'BeeDNA: microfluidic environmental DNA metabarcoding as a tool for connecting plant and pollinator communities' by Harper et al. (2021).</strong></p> <p><br> <strong>1_Raw_Data.zip</strong><br> This zipped folder contains the raw sequence data (sorted by primer set and demultiplexed) for both sequencing runs (2019-10-24 and 2019-11-11). To decompress each file, run: </p> <pre><code>tar -xvf filename.bz2</code></pre> <p>This will create a folder for each primer set containing the raw reads for each sample/control.</p> <p><br> <strong>2_Anacapa_Bioinformatic_Processing.zip</strong></p> <p>This zipped folder contains all files needed to perform bioinformatic processing with Anacapa. Please process sequence data belonging to each primer set individually (i.e. do not process sequence data belonging to different primer sets together).</p> <p><br> <strong>3_metaBEAT_Bioinformatic_Processing.zip </strong></p> <p>This zipped folder contains the scripts and files needed to perform bioinformatic processing with metaBEAT. Before running the scripts, move the raw reads for each sample belonging to each primer set into the dedicated folder within metaBEAT_Bioinformatic_Processing, e.g. all .fastq files in Raw_Data > BF1_BR1 should be moved to metaBEAT_Bioinformatic_Processing > BF1-BR1 > raw_reads.</p> <p>To run metaBEAT, you will have to install Docker on your computer. Docker is compatible with all major operating systems, but see the Docker documentation for details. On Ubuntu, installing Docker should be as easy as:</p> <pre><code>sudo apt-get install docker.io</code></pre> <p>Once Docker is installed, you can enter the environment by typing:</p> <pre><code>sudo docker run -i -t --net=host --name metaBEAT -v $(pwd):/home/working chrishah/metabeat /bin/bash</code></pre> <p>This will download the metaBEAT image (if not yet present on your computer) and enter the 'container', i.e. the self contained environment (NB: sudo may be necessary in some cases). With the above command, the container's directory /home/working will be mounted to your current working directory (as instructed by $(pwd)). In other words, anything you do in the container's /home/working directory will be synced with your current working directory on your local machine.</p> <p>Please process sequence data belonging to each primer set individually (i.e. do not process sequence data belonging to different primer sets together). An example of expected outputs can be seen in the Jupyter Notebook for the BF1/BR1 primer set from the 2019-11-11 sequencing run.</p> <p><br> <strong>4_Illinois_Invert_Reference_Database.zip</strong></p> <p>This zipped folder contains all files that were used to generate the custom COI and 16S reference databases for invertebrates that occur in Illinois, U.S. You will need to have metaBEAT installed (see above) before you try to run any Jupyter Notebooks (.ipynb files).</p> <p><br> <strong>5_ecoPCR.zip</strong></p> <p>This zipped folder contains all files used to perform ecoPCR for each primer set evaluated for microfluidic eDNA metabarcoding. You will need to <a href="https://git.metabarcoding.org/obitools/ecopcr/wikis/home">install ecoPCR</a> before running any shell scripts.</p> <p><br> <strong>6_Tidied_Data.zip</strong></p> <p>This zipped folder contains the taxonomically assigned data for both sequencing runs produced by metaBEAT and Anacapa. These were copied over from the folders 2_Anacapa_Bioinformatic_Processing and 3_metaBEAT_Bioinformatic_Processing and rearranged into a more logical order. These files are used as the input for data analysis using R.</p> <p><br> <strong>7_Data_Analysis.zip</strong></p> <p>This zipped folder contains all scripts and metadata required to summarise and statistically analyse data in R.</p> <p> </p> <p><strong>Please contact Dr Lynsey Harper (lynsey.harper2@gmail.com) or Dr Mark Davis (davis63@illinois.edu) if you encounter any issues!</strong></p>
Figure 3 in Elasmobranch diversity across a remote coral reef atoll revealed through environmental DNA metabarcoding
Figure 3. Spatial variation in elasmobranch abundance and diversity inferred from eDNA metabarcoding of surface (A) and deep (40 m) (B) water samples collected around Diego Garcia. Negaprion acutidens is not visible in the charts as a result of low copy number, but was detected at site 8 in surface samples. Numbers correspond to the site numbers detailed in Figure 1.
Figure 4 in Elasmobranch diversity across a remote coral reef atoll revealed through environmental DNA metabarcoding
Figure 4. Venn diagram showing the overlap of shark species detected in previous UVC and BRUVS surveys in the MPA and the eDNA samples from around Diego Garcia analysed in this study.
Fig. 2 in Elucidating nematode diversity and prevalence in moose across a wide latitudinal gradient using DNA metabarcoding
Fig. 2. Nematode component community in winter with a) the number of nematode taxa detected at each study area and b) the number of nematode taxa shared among study areas.
Fig. 3 in Elucidating nematode diversity and prevalence in moose across a wide latitudinal gradient using DNA metabarcoding
Fig. 3. Prevalence in each study area of the six most common nematodes detected. Whiskers indicate 95% confidence intervals.
ScienceDex guides
Understand access before you commit
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.