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1,076 results for “Metabarcoding”
Figure 1 from: Gueidan C, Li L (2022) A long-read amplicon approach to scaling up the metabarcoding of lichen herbarium specimens. MycoKeys 86: 195-212. https://doi.org/10.3897/mycokeys.86.77431
Figure 1 Examples of lichen herbarium specimens used for this study AParmotrema perlatum, specimen J.A. Elix 43686 (CANB790817) BEndocarpon pusillum, specimen H. Streiman 45100 (CBG9011273) CBuellia albula, specimen J.A. Elix 45138 (CANB810791) DCatillaria sp., specimen J.A Elix 37142 (CANB872684). Scale bar: 1 cm. Photos C. Gueidan.
Figure 2 from: Gueidan C, Li L (2022) A long-read amplicon approach to scaling up the metabarcoding of lichen herbarium specimens. MycoKeys 86: 195-212. https://doi.org/10.3897/mycokeys.86.77431
Figure 2 Sequencing success for different morphological groups of taxa included in this study. Specimens were grouped into three main morphological categories: 1Buellia, Catillaria and other crustose saxicolous taxa 2Endocarpon and other squamulose terricolous taxa 3 the foliose corticolous genus Parmotrema. In the graph, stalked columns show successful samples (sequence generated for the target species) in dark grey and unsuccessful samples (no sequence generated or generated sequences not from the target species) in light grey. The total number of samples (N) is indicated below each corresponding column.
Figure 3 from: Gueidan C, Li L (2022) A long-read amplicon approach to scaling up the metabarcoding of lichen herbarium specimens. MycoKeys 86: 195-212. https://doi.org/10.3897/mycokeys.86.77431
Figure 3 Sequencing success for different ages of specimens included in this study. Specimens were grouped in five categories: 1966–1980, 1981–1990, 1991–2000, 2001–2010, 2011–2020. In the graph, stalked columns show successful samples (sequence generated for the target species) in dark grey and unsuccessful samples (no sequence generated or generated sequences not from the target species) in light grey. The total number of samples (N) is indicated below each corresponding column.
DNA metabarcoding reveals broad woodpecker diets in fire-maintained forests
<p class="MsoNoSpacing">Ecological disturbance is a key agent shaping the spatial and temporal landscape of food availability. In forests of western North America, disturbance from fire can lead to resource pulses of deadwood-associated arthropods that provide important prey for woodpeckers. Although the foraging strategies among woodpecker species often demonstrate pronounced differences, little is known about the ways in which woodpeckers exploit and partition prey in disturbed areas. In this study, we employed DNA metabarcoding to characterize and compare the arthropod diets of four woodpecker species in Washington and California, USA – Black-backed Woodpecker (<i>Picoides arcticus</i>), Hairy Woodpecker (<i>Dryobates villosus</i>), Northern Flicker (<i>Colaptes auratus</i>), and White-headed Woodpecker (<i>D. albolarvatus</i>) – primarily using nestling fecal samples from burned forests 1–13 years post-fire. Successful sequencing from 78 samples revealed the presence of over 600 <a name="_Hlk73784549">operational taxonomic units (OTUs) </a>spanning 32 arthropod orders. <a name="_Hlk87260574">The nestling diets of two species in particular</a> – Northern Flicker and Black-backed Woodpecker – proved to be much broader than previous observational studies suggest. <a name="_Hlk87260757">Northern Flicker nestlings demonstrated</a> significantly higher diet diversity compared to other focal species, all of which displayed considerable overlap in diversity. Wood-boring beetles, which colonize dead and dying trees after fire, were particularly important diet items for Black-backed, Hairy, and White-headed woodpeckers. Diet composition differed among species, and diets showed limited differences between newer (≤5 yr) and older (>5 yr) post-fire forests. Our results show mixed evidence for dietary resource partitioning, with three of the four focal species exhibiting relatively high diet overlap, perhaps due to the pulsed subsidy of deadwood-associated arthropods in burned forests. Woodpeckers are frequently used as management indicator species for forest health, and our study provides one of the first applications of DNA metabarcoding to build a more complete picture of woodpecker diets.</p>
Data from: Seasonal progression and differences in major floral resource use by bees and hoverflies in a diverse horticultural and agricultural landscape revealed by DNA metabarcoding
<p>Gardens are important habitats for pollinators, providing floral resources and nesting sites. There are high levels of public support for growing 'pollinator-friendly' plants but whilst plant recommendation lists are available, they are usually inconsistent, poorly supported by scientific research and target a narrow group of pollinators. In order to supply the most appropriate resources, there is a clear need to understand foraging preferences, for a range of pollinators, across the season within horticultural landscapes.</p> <p>Using an innovative DNA metabarcoding approach, we investigated foraging preferences of four groups of pollinators in a large and diverse, horticultural, and agricultural landscape, across the flowering season and over two years, significantly improving on the spatial and temporal scale that can be achieved using observational studies.</p> <p>Bumblebees, honeybees, non-corbiculate bees, and hoverflies visited 191 plant taxa. Overall floral resources were shared between the different types of pollinators, but significant differences were seen between the plants used most abundantly by bees (Hymenoptera) and hoverflies (Diptera).</p> <p>Floral resource use by pollinators is strongly associated with seasonal changes in flowering plants, with pollinators relying on dominant plants found within each season, with preferences consistent across both years.</p> <p>The plants identified were categorised according to their native status to investigate the value of native and non-native plants. The majority of floral resources used were of native and near-native origin, but the proportion of horticultural and naturalised plants increased during late summer and autumn.</p> <p><em>Synthesis and applications: </em>We recommend that plant lists should distinguish between bees and hoverflies and provide evidence-based floral recommendations throughout the year that include native as well as non-native plants for use in the UK and Northern Europe. Specific management recommendations include reducing mowing to encourage plants such as dandelion <em>Taraxacum officinale</em>, buttercups <em>Ranunculus spp.</em>, and reducing scrub management to encourage bramble <em>Rubus fruticosus</em>.</p>
Supplementary material 1 from: Nagai S, Sildever S, Nishi N, Tazawa S, Basti L, Kobayashi T, Ishino Y (2022) Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding. Metabarcoding and Metagenomics 6: e77704. https://doi.org/10.3897/mbmg.6.77704
Table S1–S3
Supplementary material 3 from: Nagai S, Sildever S, Nishi N, Tazawa S, Basti L, Kobayashi T, Ishino Y (2022) Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding. Metabarcoding and Metagenomics 6: e77704. https://doi.org/10.3897/mbmg.6.77704
same_tophit_count_merge.pl
Supplementary material 2 from: Nagai S, Sildever S, Nishi N, Tazawa S, Basti L, Kobayashi T, Ishino Y (2022) Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding. Metabarcoding and Metagenomics 6: e77704. https://doi.org/10.3897/mbmg.6.77704
merge_tophit_count.pl
Supplementary material 1 from: Sakata MK, Kawata MU, Kurabayashi A, Kurita T, Nakamura M, Shirako T, Kakehashi R, Nishikawa K, Hossman MY, Nishijima T, Kabamoto J, Miya M, Minamoto T (2022) Development and evaluation of PCR primers for environmental DNA (eDNA) metabarcoding of Amphibia. Metabarcoding and Metagenomics 6: e76534. https://doi.org/10.3897/mbmg.6.76534
Supporting Information
Supplementary material 4 from: Nagai S, Sildever S, Nishi N, Tazawa S, Basti L, Kobayashi T, Ishino Y (2022) Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding. Metabarcoding and Metagenomics 6: e77704. https://doi.org/10.3897/mbmg.6.77704
blastxml_parser
Supplementary material 1 from: Sogawa S, Tsuchiya K, Nagai S, Shimode S, Kuwahara VS (2022) Annual dynamics of eukaryotic and bacterial communities revealed by 18S and 16S rRNA metabarcoding in the coastal ecosystem of Sagami Bay, Japan. Metabarcoding and Metagenomics 6: e78181. https://doi.org/10.3897/mbmg.6.78181
Figures S1–S8
Figure 4 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 4 Heatmap using Pearson's correlation coefficient between the OTUs generated from the ITS2 and LSU D1-D2 metabarcodes and the analysed beetle species and forest types. Rectangles indicate the strength of association between an OTU and beetle/forest (strongly negative, grey, to strongly positive, red). Fungal OTUs (on the horizontal axis) were classified to genus or species level where possible; they are shown in random order and cannot be linked taxonomically between both markers.
Supplementary material 1 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure S1. Length distribution of the ITS (grey) and LSU (orange) OTUs
Figure 7 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 7 Closed reference clustering of OTUs and phylogenetic trees at different thresholds A results from the closed reference clustering of OTUs at each clustering threshold against composite LSU/ITS2 reference sequences. LSU matches in green, ITS2 matches in blue, linked matches (for which both an ITS2 and LSUOTU were matched to a reference sequence of the same species) in yellow. Underlined taxa indicate new matches at each clustering threshold B phylogenetic tree of LSUOTUs under increasingly stringent clustering thresholds, with arrows marking newly added taxa as threshold values are increased.
Figure 3 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 3 NMDS ordination plot of all specimens sampled with ITS2 and LSU D1-D2, based on the fungal community composition of the individual beetles. Shapes represent forest types and colours represent beetle species. Stress for this graph fell within acceptable ranges (<0.2).
Figure 2 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 2 Top panel: The proportion of OTUs identified as members of a fungal Class determined by the ITS2 and LSU D1-D2 regions. For the spruce forest, only nine X. germanus and four X. saxesenii specimens were retained after rarefaction. Lower panel: The number of fungal OTUs per beetle specimen, separate for each beetle species and forest type, for ITS2 and LSU.
Figure 6 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 6 Order-level trees and splitting/lumping of OTUs at clustering A order-level ML trees with mixed OTU clustering thresholds (99% LSU D1-D2, 98% ITS2). Full tree in supplementary materials. Leotia lubrica was used as the outgroup (not pictured). Brackets indicate reference taxa linked to an ITS2 and/or LSUOTU, with colours indicating potential splitting/lumping (blue, splitting; green, lumping; orange, 1:1) B diagram illustrating the effects of splitting and lumping of an OTU in the fungal community on the tree inference. Four hypothetical species (A to D) in a community are treated under uniform clustering thresholds for ITS2 and LSU. This may result in deviation from the 1:1 ratio of OTUs expected if each species in the community is represented equally by both markers (species A). Threshold values may be too high, resulting in splitting of species into multiples OTUs, which is likely to affect the more variable ITS2 region (species B) or may be too low, resulting in lumping of multiple species into a single OTU, likely to affect the conservative LSU region (species C and D).
Supplementary material 4 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure S4. Binding site of ITS86 primer showing mismatched base pairs in Ophiostomatales
Figure 1 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 1 The proportion of fungi classified with IDTAXA, Protax-fungi and RDP from class to species level. "All" refers to the proportion of OTUs for which the three classifiers agreed in their classification.
Supplementary material 7 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Table S3. Number of OTUs assigned to each order based on RDP Bayesian classifier
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