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19,342 results for “Sequences”
Sequencing data and taxonomic assignments from: Biodiversity and vector-borne diseases: host dilution and vector amplification occur simultaneously for Amazonian leishmaniases
<p>This is the sequencing data used in the paper:<strong> "</strong>Biodiversity and vector-borne diseases: host dilution and vector amplification occur simultaneously for Amazonian leishmaniases" by Kocher et al. The study aims at assessing the effects of biodiversity changes on Leishmania transmission using molecular analyses of sand fly pools and blood-fed dipterans. The data is split in three files corresponding to the PCR amplicons used in the study (Ins16S for insect identifications, 12SV5 for vertebrate identifications and leishmini for Leishmania identifications). Each file combines output from different Illumina Miseq and Hiseq runs, after read demultiplexing and adapter trimming, dereplication and removal of reads present in less than 10 copies (but before further read filtering). The data is presented in tabular format (similar to the output of the obitab command from the obitools package), together with information on the corresponging sample, sequencing run, and taxonomic assignments (performed with ecotag from the obitools).</p>
FIGURE. Variable positions in the ITS2 secondary structure of some Coelastrella sensu lato species. The ITS2 model of Coelastrella striolata strain CAUP H 3602 (JX513881) was used to map sequence differences. Variable positions of analyzed strains (GenBank numbers can be found in Table 3, 4 are given next to the main structure and are marked in bold. Hemi- Compensatory Base Changes in conservative regions are circled and Compensatory Base Change is contoured. Sequences of strains with GenBank numbers JX513879 (C. aeroterrestrica), JX513882 (C. terrestris), JX513884 (C. rubescens), MH176120 (C. rubescens var. oocystiformis), JX513880 (C. multistriata), JX513887 (C. oocystiformis) were used as representatives of Coelastrella species. The strains analyzed in this study are underlined. in Morphological and phylogenetic relations of members of the genus Coelastrella (Scenedesmaceae, Chlorophyta) from the Ural and Khentii Mountains (Russia, Mongolia)
FIGURE. Variable positions in the ITS2 secondary structure of some Coelastrella sensu lato species. The ITS2 model of Coelastrella striolata strain CAUP H 3602 (JX513881) was used to map sequence differences. Variable positions of analyzed strains (GenBank numbers can be found in Table 3, 4 are given next to the main structure and are marked in bold. Hemi- Compensatory Base Changes in conservative regions are circled and Compensatory Base Change is contoured. Sequences of strains with GenBank numbers JX513879 (C. aeroterrestrica), JX513882 (C. terrestris), JX513884 (C. rubescens), MH176120 (C. rubescens var. oocystiformis), JX513880 (C. multistriata), JX513887 (C. oocystiformis) were used as representatives of Coelastrella species. The strains analyzed in this study are underlined.
Figure 1. A in Systematics and phylogeography of the Taiwanese endemic minnow Candidia barbatus (Pisces: Cyprinidae) based on DNA sequence, allozymic, and morphological analyses
Figure 1. A, image of Candidia barbatus; B, map of Taiwan showing the late Pleistocene (dashed line) shoreline, the current shoreline (solid line) (modified from Boggs et al., 1979 and Wu et al., 2007), the sampling sites of Candidia barbatus, the native species range (shaded area), and mtDNA lineages recovered. Geographical ranges of allozyme clusters are demarcated by arrows. Numerical codes for each sampling site: 1, Wulaokeng River (WL); 2, Shuangshi River (SS); 3, Masu River (MS); 4, Shandiaoling River (SD); 5, Sifen River (SF); 6, Waishuangshi River (WS); 7, Dahan River (DH); 8, Beishi River (BS); 9, Ayu River (AY); 10, Hapen River (HP); 11, Chingmei River (CM); 12, Fengshan River (FES); 13, Houlong River (HL); 14, Daan River (DA); 15, Dajia River (DJ); 16, Dadu River (DD); 17, Choshui River (CS); 18, Puzi River (PZ); 19, Tsengwen River (TW); 20, Nanzishan River (NZ); 21, Laonong River (LN); 22, Ailiao River (AL); 23, Lili River (LL); 24, Fanshan River (FAS); 25, Fengang River (FG); 26, Sichong River (SH) (also see Table 1).
Figure 4 in Systematics and phylogeography of the Taiwanese endemic minnow Candidia barbatus (Pisces: Cyprinidae) based on DNA sequence, allozymic, and morphological analyses
Figure 4. The marginal posterior probability distributions for the migration rate of Candidia barbatus between northern and central Taiwan.
Figure 3 in Systematics and phylogeography of the Taiwanese endemic minnow Candidia barbatus (Pisces: Cyprinidae) based on DNA sequence, allozymic, and morphological analyses
Figure 3. Detection of the number of groups by STRUCTURE. A, L(K) as a function of K; B, DK following Evanno et al. (2005) as a function of K.
Figure 2 in Systematics and phylogeography of the Taiwanese endemic minnow Candidia barbatus (Pisces: Cyprinidae) based on DNA sequence, allozymic, and morphological analyses
Figure 2. The neighbor-joining (NJ) tree corrected by the Hasegawa–Kishino–Yano (HKY) + Gamma (0.1719) model based on the complete mitochondrial cytochrome b sequence. The times to the most recent common ancestor for major splitting events are shown below branches with their 95% highest posterior density in parentheses. Numbers above the branches, from top to bottom, are bootstrap values derived from maximum likelihood, Bayesian, NJ, and maximum parsimony methods, respectively. Candidia sieboldii and Candidia temminckii were included as outgroups. H01–H05: lineage A, recovered from Masu River, Shandiaoling River, Sifen River, Waishuangshi River, Dahan River, Beishi River, Hapen River, and Chingmei River. H06, H07: Lineage B, recovered from Wulaokeng River, Shuangshi River, Masu River, Ayu River, Chingmei River, Fengshan River, Houlong River, and Daan River. H08: Lineage C, recovered from Masu River, Shandiaoling River, Sifen River, Beishi River, Ayu River, Dajia River, Dadu River, and Choshui River. H09–H11: Lineage D, recovered from Puzi River, Tsengwen River, and Nanzishan River. H12: Lineage E, recovered from Nanzishan River and Laonong River. H13–H19: Lineage F, recovered from Ailiao River, Lili River, Fanshan River, Fengang River, and Sichong River.
Integrative taxonomic analysis to reveal the species status of Bombus flavidus, combining COI and nuclear sequencing, wing morphometrics and secretions used for mate attraction as well as patterns of color polymorphism
<p>Bumble bees, due to their morphological monotony and color diversity, have presented difficulties with species delimitation. Recent bumble bee declines have made it ever more imperative to resolve the status of species to address conservation concerns. Some of the taxa found to be most threatened are the often-rare socially parasitic bumble bees, which have additional trophic requirements. Among the socially parasitic bumble bees,<i> Bombus flavidus</i> Eversmann has contentious species status. While multiple separate species allied with <i>Bombus flavidus</i> have been suggested, until recently, recognition of two species, a Nearctic <i>Bombus fernaldae</i> (Franklin) and Palearctic <i>B. flavidus,</i> was favoured. Limited genetic data, however, suggested that even these could be a single widespread species, <i>B. flavidus</i>. We addressed the species status of this lineage using an integrative taxonomic approach, combining <i>COI</i> and nuclear sequencing, wing morphometrics and secretions used for mate attraction. We also explore patterns of color polymorphism that have previously confounded taxonomy in this lineage. Our results support the conspecific status of <i>Bombus fernaldae</i> and <i>Bombus flavidus,</i> however, sampling specimens from across the range of these two taxa revealed a distinct population within this broader species confined to eastern North America. This makes the distribution of the social parasite <i>B. flavidus</i> the broadest of any bumble bee, broader than the known distribution of any non-parasitic bumble bee species. Analysis of color phenotypes revealed that color polymorphisms are retained across the range of the species, but may be influenced by local mimicry complexes. Following these results, <i>Bombus flavidus</i> Eversmann, 1852<i> </i>is synonymized with <i>Bombus fernaldae </i>(Franklin, 1911) <b>syn. nov.</b> and a subspecific status, <i>Bombus flavidus </i><i>appalachiensis</i> <b>ssp. nov.</b>, is assigned to the distinct lineage ranging from the Appalachians to the eastern boreal regions of the United States and far southeastern Canada.</p>
Magnetic bead epicPCR sequencing data, December 3 2021
<p>Samples:</p> <p>1. Chilomonas, 16S</p> <p>2. Rhodomonas, 16S</p> <p>3. Chilomonas+Rhodomonas, 16S</p> <p>4. Chilomonas+Rhodomonas+wastewater, 16S</p> <p>5. Wastewater, 16S</p> <p>6. Chilomonas, 18S</p> <p>7. Rhodomonas, 18S</p> <p>8. Chilomonas+Rhodomonas, 18S</p> <p>9. Chilomonas+Rhodomonas+wastewater, 18S</p> <p>10. Wastewater, 18S</p>
Hawksbill turtle ddRAD raw sequencing data
<p>Pleistocene environmental changes are generally assumed to have dramatically affected species' demography via changes in habitat availability, but this is challenging to investigate due to our limited knowledge of how Pleistocene ecosystems changed through time. Here, we tracked changes in shallow marine habitat availability resulting from Pleistocene sea level fluctuations throughout the last glacial cycle (120 – 14 thousand years ago; kya) and assessed correlations with past changes in genetic diversity inferred from genome-wide SNPs, obtained via ddRAD sequencing, in Caribbean hawksbill turtles, which feed in coral reefs commonly found in shallow tropical waters. We found sea level regression resulted in an average 75% reduction in shallow marine habitat availability during the last glacial cycle. Changes in shallow marine habitat availability correlated strongly with past changes in hawksbill turtle genetic diversity, which gradually declined to ~1/4th of present-day levels during the Last Glacial Maximum (LGM; 26 – 19 kya). Shallow marine habitat availability and genetic diversity rapidly increased after the LGM, signifying a population expansion in response to warming environmental conditions. Our results suggest a positive correlation between Pleistocene environmental changes, habitat availability and species' demography, and that demographic changes in hawksbill turtles were potentially driven by feeding habitat availability. However, we also identified challenges associated with disentangling the potential environmental drivers of past demographic changes, which highlight the need for integrative approaches. Our conclusions underline the role of habitat availability on species' demography and biodiversity, and that the consequences of ongoing habitat loss should not be underestimated.</p>
Data set for the paper "Temperatures and cooling rates recorded by the New Caledonia ophiolite: implications for cooling mechanisms in young forearc sequences"
<p>Data set for the paper "Temperatures and cooling rates recorded by the New Caledonia ophiolite: implications for cooling mechanisms in young forearc sequences" by Secchiari et al.</p>
Mitochondrial genome sequencing of marine leukemias reveals cancer contagion between clam species in the Seas of Southern Europe
<p>Clonally transmissible cancers are tumour lineages that are transmitted between individuals via the transfer of living cancer cells. In marine bivalves, leukemia-like transmissible cancers, called hemic neoplasias, have demonstrated the ability to infect individuals from different species. We performed whole-genome sequencing in eight <i>V. verrucosa</i> clams that were diagnosed with hemic neoplasia, from two sampling points located more than 1,000 nautical miles away in the Atlantic Ocean and the Mediterranean Sea Coasts of Spain. Mitochondrial genome sequencing of tumour tissues from neoplastic animals revealed the coexistence of haplotypes from two different clam species. Phylogenies estimated from mitochondrial and nuclear markers confirmed this leukemia originated in <i>C. gallina </i>(or a closely related taxa) and was later transmitted to <i>V. verrucosa</i>, in which it survived as a contagious cancer. The analysis of mitochondrial and nuclear gene sequences supports all the studied tumours belonging to a single neoplastic <i>C. gallina </i>lineage that spread in the Seas of Southern Europe.</p>
Long-read genome sequencing of bread wheat facilitates disease resistance gene cloning
<p>Cloning agronomically important genes from large, complex crop genomes remains challenging. Here, we generate a 14.7-gigabase chromosome-scale<i> </i>assembly of the South African bread wheat (<i>Triticum aestivum</i>) cultivar Kariega by combining high-fidelity long reads, optical mapping, and chromosome conformation capture. The resulting assembly is an order of magnitude more contiguous than previous wheat assemblies. Kariega shows durable resistance against the devastating fungal stripe rust disease. We identified the race-specific disease resistance gene <i>Yr27</i>, encoding an intracellular immune receptor, as a major contributor to this resistance. <i>Yr27</i> is allelic to the leaf rust resistance gene <i>Lr13,</i> with the Yr27 and Lr13 proteins sharing 97% sequence identity. Our results thus demonstrate the feasibility of generating chromosome-scale wheat assemblies to clone genes and also exemplify that highly similar alleles of a single-copy gene can confer resistance to different pathogens, which might provide a basis for engineering <i>Yr27</i> alleles with multiple recognition specificities in future.</p>
FIGURE. Maximum likelihood phylogram of Multiclavula spp. based on ITS sequences. Rooted to Clavulina cristata. Bar = estimated changes/nucleotide. Support values above or below branches: Bayesian posterior probability/maximum likelihood bootstrap. in New and interesting species of Agaricomycetes from Panama
FIGURE. Maximum likelihood phylogram of Multiclavula spp. based on ITS sequences. Rooted to Clavulina cristata. Bar = estimated changes/nucleotide. Support values above or below branches: Bayesian posterior probability/maximum likelihood bootstrap.
FIGURE. Maximum likelihood phylogram of Humidicutis spp. based on ITS sequences. Rooted to Humidicutis marginata. Bar = estimated changes/nucleotide. Support values above or below branches: Bayesian posterior probability/maximum likelihood bootstrap. in New and interesting species of Agaricomycetes from Panama
FIGURE. Maximum likelihood phylogram of Humidicutis spp. based on ITS sequences. Rooted to Humidicutis marginata. Bar = estimated changes/nucleotide. Support values above or below branches: Bayesian posterior probability/maximum likelihood bootstrap.
FIGURE. Bayesian MCMC phylogram of Gliophorus spp. based on ITS sequences. Rooted to Hygrophorus pudorinus. Bar = estimated changes/nucleotide. Support values above or below branches: Bayesian posterior probability/maximum likelihood bootstrap. in New and interesting species of Agaricomycetes from Panama
FIGURE. Bayesian MCMC phylogram of Gliophorus spp. based on ITS sequences. Rooted to Hygrophorus pudorinus. Bar = estimated changes/nucleotide. Support values above or below branches: Bayesian posterior probability/maximum likelihood bootstrap.
Raw mass-standardized ionomic data from seven fish species and raw transcriptome sequences for mosquitofish inhabiting the Tar Creek Superfund Site in OK, USA
<p>Our understanding of the mechanisms mediating the resilience of organisms to environmental change remains lacking. Heavy metals negatively affect processes at all biological scales, yet organisms inhabiting contaminated environments must maintain homeostasis to survive. Tar Creek in Oklahoma, USA, contains high concentrations of heavy metals and an abundance of Western mosquitofish (<em>Gambusia affinis)</em>, though several fish species persist at lower frequency. To test hypotheses about the mechanisms mediating the persistence and abundance of mosquitofish in Tar Creek, we integrated ionomic data from seven resident fish species and transcriptomic data from mosquitofish to test hypotheses about the mechanisms mediating the persistence of mosquitofish in Tar Creek. We predicted that mosquitofish minimize uptake of heavy metals more than other Tar Creek fish inhabitants and induce transcriptional responses to detoxify metals that enter the body, allowing them to persist in Tar Creek at higher density than species that may lack these responses. Tar Creek populations of all seven fish species accumulated heavy metals, suggesting mosquitofish cannot block uptake more efficiently than other species. We found population-level gene expression changes between mosquitofish in Tar Creek and nearby unpolluted sites. Gene expression differences primarily occurred in the gill, where we found upregulation of genes involved with lowering transfer of metal ions from the blood into cells and mitigating free radicals. However, many differentially expressed genes were not in known metal response pathways, suggesting multifarious selective regimes and/or previously undocumented pathways could impact tolerance in mosquitofish. Our systems-level study identified well characterized and putatively new mechanisms that enable mosquitofish to inhabit heavy metal-contaminated environments.</p>
Complete Genome Sequence of an Aeromonas rivuli Strain Isolated from Ready-to-Eat Food - Data Files
<p>This dataset contains input and intermediate files of the bcgTree analysis described in the Schwartz <em>et al</em>. MRA manuscript entitled “Complete Genome Sequence of an <em>Aeromonas rivuli</em> Strain Isolated from Ready-to-Eat Food”.</p> <table> <tbody> <tr> <td> <p><strong>File name</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>‘<em>Aeromonadaceae</em> identifier’.fa</p> </td> <td> <p>Amino acid FASTA file of the translated CDS sequences of a strain X (bcgTree input file)</p> </td> </tr> <tr> <td> <p>full_alignment.concat.fa</p> </td> <td> <p>Alignment of the concatenated amino acid sequences of 107 single-copy core genes that is used for phylogenetic tree calculation in bcgTree (bcgTree intermediate file)</p> </td> </tr> </tbody> </table> <p> </p> <p>In the bcgTree files, the <em>Aeromonadaceae</em> sequences were named/abbreviated as follows:</p> <table> <tbody> <tr> <td> <p><strong>Sequence name in the bcgTree file</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>AAZUK01-1</p> </td> <td> <p><em>Tolumonas lignilytica </em>BRL6-1</p> </td> </tr> <tr> <td> <p>Aeromonas-caviae</p> </td> <td> <p><em>Aeromonas caviae </em>NCTC 12244</p> </td> </tr> <tr> <td> <p>Aeromonas-dhakensis</p> </td> <td> <p><em>Aeromonas dhakensis </em>CIP 107500</p> </td> </tr> <tr> <td> <p>Aeromonas-hydrophila</p> </td> <td> <p><em>Aeromonas hydrophila </em>ATCC 7966</p> </td> </tr> <tr> <td> <p>Aeromonas-rivuli</p> </td> <td> <p><em>Aeromonas rivuli </em>DSM 22539</p> </td> </tr> <tr> <td> <p>Aeromonas-rivuli-20-VB00005</p> </td> <td> <p><em>Aeromonas rivuli </em>20-VB00005</p> </td> </tr> <tr> <td> <p>Aeromonas-veronii</p> </td> <td> <p><em>Aeromonas veronii </em>CECT 4257</p> </td> </tr> <tr> <td> <p>CP001616-1</p> </td> <td> <p><em>Tolumonas auensis </em>DSM 9187</p> </td> </tr> <tr> <td> <p>JACHGR01-1</p> </td> <td> <p><em>Tolumonas osonensis </em>DSM 22975</p> </td> </tr> </tbody> </table>
Neuromodulation of premotor and posterior parietal cortices for enhancing explicit motor sequence learning in healthy individuals: a randomized, sham-controlled crossover trial
<p>Data collected and analysed in the manuscript '<strong>Neuromodulation of premotor and posterior parietal cortices for enhancing explicit motor sequence learning in healthy individuals: a randomized, sham-controlled crossover trial', </strong>by Russo et al. PPCR. The Principles and Practice of Clinical Research, 2021</p>
Sequences of primers used for RT-qPCR assay
<p>the detailed sequences of the primers of tsRNAs and mRNAs used for RT-qPCR assay</p>
FIGURE. Phylogenetic tree of specimens on Poaceae and related host plants constructed by MP method based on ITS+28S regions of rDNA. Bootstrap values of MP and ML are followed by the Bayesian posterior probabilities (Bpp) on the nodes in the topology. Asterisk (*) represents bootstrap values or Bpp less than 50% in the topology. Sample data are shown with voucher specimen number or GenBank accession number, and host plant. Sequence data determined in this study are shown in color. Teliospore shapes are shown in each clade detected, and new species are shown by asterisk (*) on clades. 0, I: Spermogonial and aecial host genus. Asterisk (*) on host plants: Spermogonial and aecial host plants. in Phylogenetic approach for identification and life cycles of Puccinia (Pucciniaceae) species on Poaceae from northeastern China
FIGURE. Phylogenetic tree of specimens on Poaceae and related host plants constructed by MP method based on ITS+28S regions of rDNA. Bootstrap values of MP and ML are followed by the Bayesian posterior probabilities (Bpp) on the nodes in the topology. Asterisk (*) represents bootstrap values or Bpp less than 50% in the topology. Sample data are shown with voucher specimen number or GenBank accession number, and host plant. Sequence data determined in this study are shown in color. Teliospore shapes are shown in each clade detected, and new species are shown by asterisk (*) on clades. 0, I: Spermogonial and aecial host genus. Asterisk (*) on host plants: Spermogonial and aecial host plants.
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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
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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.