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1,076 results for “Metabarcoding”
Supplementary material 4 from: Macher T-H, Schütz R, Arle J, Beermann AJ, Koschorreck J, Leese F (2021) Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species. Metabarcoding and Metagenomics 5: e66557. https://doi.org/10.3897/mbmg.5.66557
Figure S1
Capabilities and limitations of using DNA metabarcoding to study plant-pollinator interactions
<p>Many pollinator populations are experiencing declines, emphasizing the need for a better understanding of the complex relationship between bees and flowering plants. Using DNA metabarcoding to describe plant-pollinator interactions eliminates many challenges associated with traditional methods and has the potential to reveal a more comprehensive understanding of foraging behavior and pollinator life history. Here we use DNA metabarcoding of ITS2 and<i> rbcL</i> gene regions to identify plant species present in pollen loads of 404 bees from three habitats in eastern Oregon. Our specific objectives were to 1) determine whether plant species identified using DNA metabarcoding are consistent with plant species identified using observations, 2) compare characterizations of diet breadth derived from foraging observations to those based on plant species assignments obtained using DNA metabarcoding, and 3) compare plant species assignments produced by DNA metabarcoding using a "regional" reference database to those produced using a "local" database. At the three locations, 31-86% of foraging observations were consistent with DNA metabarcoding data, 8-50% of diet breadth characterizations based on observations differed from those based on DNA metabarcoding data, and 22-25% of plant species detected using the regional database were not known to occur in the study area in question. Plant-pollinator networks produced from DNA metabarcoding data had higher sampling completeness and significantly lower specialization than networks based on observations. Here, we examine some strengths and limitations of using DNA metabarcoding to identify plant species present in bee pollen loads, make ecological inferences about foraging behavior, and provide guidance for future research.</p>
Revealing cryptic interactions between large mammalian herbivores and plant-dwelling arthropods via DNA metabarcoding
<p><span>In the past decade, it has become clear that omnivory, feeding on more than one trophic level, is important in natural and agricultural systems. Large mammalian herbivores (LMH) frequently encounter plant-dwelling arthropods (PDA) on their food plants. Yet, ingestion of PDA by LMH is only rarely addressed and the extent of this direct trophic interaction, especially at the PDA community level, remains unknown. Using a DNA metabarcoding analysis on feces of free-ranging cattle from a replicated field experiment of heavily and moderately grazed paddocks, we reveal that feeding cattle (incidentally) ingest an entire food-chain of PDA including herbivores, predators and parasites. Overall, 25 families of insects and 4 families of arachnids were ingested, a pattern that varied over the season, but not with grazing intensity. We identified the functional groups of PDA vulnerable to ingestion, such as sessile species and immature life stages. Most of the fecal samples (76%) contained sequences belonging to PDA, indicating that direct interactions are frequent. This study highlights the complex trophic connections between LMH and PDA. It may even be appropriate to consider LMH as omnivorous enemies of PDA. </span></p>
Supplementary material 4 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Table S3
Supplementary material 6 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Figure S1. Pictures were taken with a digital microscope (Keyence VHX-6000, Keyence, Osaka, Japan)
Supplementary material 1 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Protocol 1 – DIY-DS
Supplementary material 3 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Table S2. Raw read table
Supplementary material 2 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Table S1. PCR primers used in this study
Supplementary material 8 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Figure S3
Supplementary material 5 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Script 1
Supplementary material 3 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S3
Supplementary material 5 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S5
Supplementary material 2 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S2
Supplementary material 4 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S4
Supplementary material 6 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Scripts S1
Supplementary material 1 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S1
Supplementary material 1 from: Pissaridou P, Cantonati M, Bouchez A, Tziortzis I, Dörflinger G, Vasquez MI (2021) How can integrated morphotaxonomy- and metabarcoding-based diatom assemblage analyses best contribute to the ecological assessment of streams? Metabarcoding and Metagenomics 5: e68438. https://doi.org/10.3897/mbmg.5.68438
Table S1
Supplementary material 2 from: Pissaridou P, Cantonati M, Bouchez A, Tziortzis I, Dörflinger G, Vasquez MI (2021) How can integrated morphotaxonomy- and metabarcoding-based diatom assemblage analyses best contribute to the ecological assessment of streams? Metabarcoding and Metagenomics 5: e68438. https://doi.org/10.3897/mbmg.5.68438
Figure S1
Supplementary material 3 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S3
Supplementary material 9 from: Rajter Ľ, Dunthorn M (2021) Ciliate SSU-rDNA reference alignments and trees for phylogenetic placements of metabarcoding data. Metabarcoding and Metagenomics 5: e69602. https://doi.org/10.3897/mbmg.5.69602
File S9
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
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DANDI Archive for NWB datasets
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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.