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4,144 results for “ITS barcode”
Fig. 5 in Lessons From a Museum's Cabinet: DNA Barcoding and Collections-Based Life Stage Associations Reveals a Hidden Diversity in the Puerto Rican Bank Paedomorphic
Fig. 5. Male adklt habiti of the Pkerto Ricac back Leptolycici—Cessator, Dracolycus acd Taicopteroc. A. Cessator luquillocis Kazactsev 2009. B. Cessator tortolecsis new species. C. Cessator obriecorum new species. D. Cessator crypticus new species. E. Dracolycus chupacabra new genus and new species.;.Dracolycus marshalli new genus and new species. G. Taicopteroc milleri Kazactsev 2009.
Fig. 4 in Lessons From a Museum's Cabinet: DNA Barcoding and Collections-Based Life Stage Associations Reveals a Hidden Diversity in the Puerto Rican Bank Paedomorphic
Fig. 4. Maximkm-likelihood topology of the gecerated COI seqkecces acd a maiclacd Calopteroc. Bracches ic color represect matches betweec adklt males acd larvae. Nkmbers represect KH-aLRT (left) acd Ultrafast Bootstrap (U;boot) (right).
Fig. 2 in Lessons From a Museum's Cabinet: DNA Barcoding and Collections-Based Life Stage Associations Reveals a Hidden Diversity in the Puerto Rican Bank Paedomorphic
Fig. 2. Ktkdy areas of the sampled material. A. Positioc of the Pkerto Ricac back ic the West Icdies. B. Locality of the El Verde;ield Ktatioc ic the El Ykcqke Natiocal;orest ic Pkerto Rico. C. The Virgic Islacds ic detail; camed islacds are the oces ic which Leptolycici specimecs were collected.
Fig. 3 in Lessons From a Museum's Cabinet: DNA Barcoding and Collections-Based Life Stage Associations Reveals a Hidden Diversity in the Puerto Rican Bank Paedomorphic
Fig. 3. Pkerto Rico collectioc site acd some of the ksed collecticg methods. A. Tropical raicforest ic the El Verde;ield Ktatioc. B.;light icterceptioc trap (;IT). C. Malaise trap. D. Leptolycici specimecs (above Leptolycus puellus acd to the right Cessator luquillocis) first collected by cet-sweepicg acd thec with ac aspirator.
Fig. 1. A. A in Lessons From a Museum's Cabinet: DNA Barcoding and Collections-Based Life Stage Associations Reveals a Hidden Diversity in the Puerto Rican Bank Paedomorphic
Fig. 1. A. A scheme showicg the hypothesized evolktiocary relatiocships of Lycidae (modified from Kksy et al. 2019). Red circles icdicate grokps ic which paedomorphosis has developed at least occe ic the skbfamilies. B. Distribktioc of Lycidae liceages across the differect zoogeographical zoces. Map of the differect ecozoces modified from Wikimedia commocs. Origically made by carol acd ksed kcder CC BY-KA 3.0.
FIGURES 7–11. C in Morphological description and DNA barcoding of Ceratophysella gracilimucronata sp. nov. (Collembola: Hypogastruridae) from China, with a key to species of the C. armata group of the Sino-Japanese Region
FIGURES 7–11. C. gracilimucronata sp. nov.: 7, furca; 8, chaetotaxy of Abd. V; 9, chaetotaxy of Abd. I–VI; 10, chaetotaxy of head; 11, chaetotaxy of Th. I–III.
FIGURES 1–6. C in Morphological description and DNA barcoding of Ceratophysella gracilimucronata sp. nov. (Collembola: Hypogastruridae) from China, with a key to species of the C. armata group of the Sino-Japanese Region
FIGURES 1–6. C. gracilimucronata sp. nov.: 1, chaetotaxy of Ant. I–IV, dorsal side; 2, chaetotaxy of Ant. III–IV, ventral side; 3, postantennal organ and ocelli; 4, labial palp; 5, claw I with empodial appendage; 6, labrum.
CRISPuRe-seq: pooled screening of barcoded ribonucleoprotein reporters reveals regulation of RNA polymerase III transcription by the Integrated Stress Response via mTOR
<p>NAR_Data_Package.zip contains the data required for generating figures, including original gel images for western blots and a step-by-step protocol for CRISPuRe-seq.</p> <p>SupplementaryData.xlsx contains all of the Supplemental Data directly referred to in the manuscript.</p> <p>Plasmid maps.zip contains plasmid maps for constructs used in the manuscript in genbank format.</p> <p>Scripts.zip contains the scripts used for screen processing with a text file explaining their usage.</p> <p>Look_Up_Table.zip contains the look-up-table for decoding barcode and sgRNA pairings.</p>
Data from: MetaBARFcoding: DNA-barcoding of regurgitated prey yields insights into Christmas Shearwater (Puffinus nativitatis) foraging ecology at Hōlanikū (Kure Atoll), Hawaiʻi
<p>Morphological identification of digested prey remains from a generalist predator can be challenging, especially when attempting to match degraded remains to taxonomic keys. DNA techniques, whereby prey is sequenced and matched to large public nucleotide sequence databases, are increasingly being used to augment morphological identification. We used "metaBARFcoding" (DNA metabarcoding) to target a region of the cytochrome <i><u>c</u></i> oxidase subunit I mitochondrial gene to identify prey in highly-digested regurgitations from Christmas Shearwaters <i>Puffinus nativitatis </i>at Hōlanikū (Kure Atoll). Metabarcoding was used to bulk-process 92 water samples from regurgitations collected from 2009-2017, providing an overview of the seabird's diet. We additionally Sanger sequenced 100 prey items from 50 randomly chosen regurgitations to verify that metabarcoding characterized key components of the diet. The metabarcoding technique identified 87 unique taxa from 29 families of fish and squid, spanning diverse taxa, including reef-associated, pelagic-oceanic, and mesopelagic species. Rare prey (frequency of occurrence <u><</u> 5% of samples) constituted 66% of the species richness, demonstrating the highly diverse diet of this generalist predator. Overall, 81% of the families detected in the contemporary diet were previously documented in Christmas Shearwater diets from the Northwestern Hawaiian Islands. Our results indicate that metabarcoding the cytochrome <i>c</i> oxidase subunit I (COI) region is useful in identifying a wide range of taxa from highly digested regurgitations, thus facilitating this approach to study seabird diets.</p>
FIGURE 2 in DNA barcodes for Cladocera and Copepoda from Mexico and Guatemala, highlights and new discoveries
FIGURE 2. Neighbour–joining tree of 440 COI sequences from 61 cladoceran species using K2P distances. The number of specimens sequenced, localities, and general distribution is in brackets. Abbreviations used: N = North; C = Center; S = South; CA = Canada; G = Guatemala; GE= Germany; MX = Mexico, ON = Ontario. Specimen details are available from BOLD (www.barcodinglife.org). * Sequences derive from cultured specimens; ** Sequences derive from cultured and wild specimens.
Assessing candidate DNA barcodes for Chinese and internationally traded timber species
<p>Accurate identification of species from timber is an essential step to help control illegal logging and forest loss. However, current approaches to timber identification based on morphological and anatomical characteristics have limited species resolution. DNA barcoding is a proven tool for plant species identification, but there is a need to build reliable reference data across broad taxonomic and spatial scales. Here, we construct a species barcoding library consisting of 1,550 taxonomically diverse timber species from 656 genera and 124 families, representing a comprehensive genetic reference data set for Chinese timber species and international commercial traded timber species, using four barcodes (<i>rbc</i>L, <i>mat</i>K, <i>trn</i>H–<i>psb</i>A, and ITS2). The ITS2 fragment was found to be the most efficient locus for Chinese timber species identification among the four barcodes tested, both at the species and genus level, despite its low recovery rate. Nevertheless, the barcode combination <i>mat</i>K+<i>trn</i>H–<i>psb</i>A+ITS2 was required as a complementary barcode to distinguish closely related species in complex datasets involving internationally traded timber species. Comparative analyses of family-level discrimination and species/genus ratios indicated that the inclusion of closely related species is an important factor affecting the resolution ability of barcodes for timber species verification. Our study indicates that although nuclear ITS2 is the most efficient single barcode for timber species authentication in China, complementary combinations like <i>mat</i>K+<i>trn</i>H–<i>psb</i>A+ITS2 are required to provide broader discrimination power. These newly-generated sequences enrich the existing publicly available databases, especially for tropical and subtropical evergreen timber trees and this current timber species barcode reference library can serve as an important genetic resource for forestry monitoring, illegal logging prosecution and biodiversity projects.</p>
Fig. 3 in Barcoding and interspecific relationships of Macaronesian Weevils (Coleoptera: Curculionoidea)
Fig. 3: The colour variants of Cionus griseus x variegatus in a single population on La Palma (Jedey). Is this a case of introgression
Figure 4 in Cytochrome c oxidase subunit I barcode species delineation methods imply critically underestimated diversity in 'common' Hermeuptychia butterflies (Lepidoptera: Nymphalidae: Satyrinae)
Figure 4. Percentage of pairwise comparisons within each class of genetic distances (p-distance) for Hermeuptychia sequences calculated between (black bars) and within (grey bars) species. Species delimitation was based on the recursive partitioning ABGD analysis.
Figure 3. A in Cytochrome c oxidase subunit I barcode species delineation methods imply critically underestimated diversity in 'common' Hermeuptychia butterflies (Lepidoptera: Nymphalidae: Satyrinae)
Figure 3. A, relationships from our phylogenetic analyses based on Bayesian inference. Support values> 50 are indicated with posterior probability values indicated above the branch and bootstrap values indicated below the branch. Names and morphology group symbols are as presented in Seraphim et al. (2014), 'ns' indicates new sequences, and numbers in parentheses indicate the number of species within clades as indicated by the ABGD (recursive partitioning) approach. B, relationships among Hermeuptychia species redrawn from the phylogeny presented in Seraphim et al. (2014), for comparison.
Figure 2 in Cytochrome c oxidase subunit I barcode species delineation methods imply critically underestimated diversity in 'common' Hermeuptychia butterflies (Lepidoptera: Nymphalidae: Satyrinae)
Figure 2. Bayesian inference (BEAST2) tree for Hermeuptychia COI barcode sequences with posterior probabilities (top)> 0.5 and bootstrap values (bottom)> 50 indicated. Sequences generated in this study have voucher numbers beginning 'LEP' or 'IN' and are highlighted in blue. Species boundaries as indicated by the three most plausible implementations of each approach, bPTP (ML) (black), ABGD (recursive partitioning) (green) and GMYC (multiple thresholds) (grey), are illustrated as coloured bars on the side. * indicates groups that were recovered as one putative species but appear separated owing to the underlying phylogeny. Red vertical bars denote putative species that do not include an previously published sequences. Horizontal coloured bars and symbols beside sample voucher names denote morphology groupings identified in Seraphim et al. (2014).
Supplementary material 9 from: Mahima K, Umapathy S, Sudhakar JV, Sathishkumar R (2021) Systematic reinstatement of highly sacred Ficus krishnae based on differences in morphology and DNA barcoding from Ficus benghalensis (Moraceae). PhytoKeys 186: 121-138. https://doi.org/10.3897/phytokeys.186.74086
Figure S4. Maximum Clade Credibility (MCC) tree from Bayesian analysis using the ITS2 DNA barcode marker with posterior probabilities values in percentage that are shown at nodes
Supplementary material 10 from: Mahima K, Umapathy S, Sudhakar JV, Sathishkumar R (2021) Systematic reinstatement of highly sacred Ficus krishnae based on differences in morphology and DNA barcoding from Ficus benghalensis (Moraceae). PhytoKeys 186: 121-138. https://doi.org/10.3897/phytokeys.186.74086
Figure S5. Maximum Clade Credibility (MCC) tree from Bayesian analysis using the trnH-psbA DNA barcode marker with posterior probabilities values in percentage that are shown at nodes.
Supplementary material 8 from: Mahima K, Umapathy S, Sudhakar JV, Sathishkumar R (2021) Systematic reinstatement of highly sacred Ficus krishnae based on differences in morphology and DNA barcoding from Ficus benghalensis (Moraceae). PhytoKeys 186: 121-138. https://doi.org/10.3897/phytokeys.186.74086
Figure S3. Parsimony distribution of the morphological characters and their status on the MCC Bayesian tree
FIGURE 6 in New records of water mites (Acari, Hydrachnidia) from Iran with the description of one new species based on morphology and DNA barcodes
FIGURE 6. Neighbor-joining tree based on studied Monatractides COI sequences. The optimal tree with the sum of branch length = 0.33301736 is shown. The analysis involved 9 nucleotide sequences. There were a total of 669 positions in the final dataset.
FIGURE 5 in New records of water mites (Acari, Hydrachnidia) from Iran with the description of one new species based on morphology and DNA barcodes
FIGURE 5. Partial NJ trees calculated with COI sequences of Sperchon papillosus and S. compactilis with BIN assignment. The optimal tree with the sum of branch length = 0.06613391 is shown. The analysis involved 7 nucleotide sequences. There were a total of 669 positions in the final dataset.
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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)
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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.