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464 results for “high density”
Designer high-density lipoprotein particles enhance endothelial barrier function and suppress inflammation
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Mapping of the QTLs governing grain micronutrients and thousand kernel weight in wheat (Triticum aestivum L.) using high density SNP markers
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Timing is everything: survival of Atlantic salmon (Salmo salar) postsmolts during events of high salmon lice densities
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High-density single-unit human cortical recordings using the Neuropixels probe
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FAB 1 Leaf Herbivory:FAB 1 : Forests and Biodiversity Experiment - High density diversity
A forest biodiversity experiment (FAB) focused on trees of our region investigates the consequences of multiple dimensions of tree diversity for soil, food webs, plant communities and ecosystems. FAB is designed to unravel effects of three forms of biological diversity: species richness (SR), functional diversity (FD), and phylogenetic diversity (PD). We define FD as the representation of multiple traits of leaves, roots, seeds, and the whole organism that are correlated with species positions along gradients of resource supply, growth, and decomposition. PD is the representation of evolutionary lineages measured as the genetic distances between species. While PD and FD are often correlated, convergent evolution and adaptive differentiation can decouple them. When functional traits that drive specific ecosystem functions are not phylogenetically conserved, PD and FD may give contrasting predictions. SR, PD, and FD are not independent, and we posit that PD may help explain SR effects, and FD may help explain both PD and SR effects. Thus FAB is designed to examine the separate and combined effects of all three components of diversity for multiple ecosystem functions and to distinguish between ???sampling??? and ???complementarity??? effects of biodiversity. Due to the long lag between planting tree seedlings and determining effects of tree composition and diversity on ecosystem functioning, fewer experiments have been established to elucidate the role of biodiversity in the functioning of forest ecosystems than grassland experiments. FAB will contribute to this gap and is a member of the IDENT and TreeDiv network of forest biodiversity experiments (www.treedivnet.ugent.be). Hypotheses: 1. PD, FD, and SR will all contribute to increased productivity, stability, and diversity of other trophic levels (herbivores, predators, parasitoids, soil microbes, soil flora and fauna) as well as to greater soil C sequestration. 2. Because PD incorporates both the number of species a
Tilia americana leaf senescence phenology:FAB 1 : Forests and Biodiversity Experiment - High density diversity
A forest biodiversity experiment (FAB) focused on trees of our region investigates the consequences of multiple dimensions of tree diversity for soil, food webs, plant communities and ecosystems. FAB is designed to unravel effects of three forms of biological diversity: species richness (SR), functional diversity (FD), and phylogenetic diversity (PD). We define FD as the representation of multiple traits of leaves, roots, seeds, and the whole organism that are correlated with species positions along gradients of resource supply, growth, and decomposition. PD is the representation of evolutionary lineages measured as the genetic distances between species. While PD and FD are often correlated, convergent evolution and adaptive differentiation can decouple them. When functional traits that drive specific ecosystem functions are not phylogenetically conserved, PD and FD may give contrasting predictions. SR, PD, and FD are not independent, and we posit that PD may help explain SR effects, and FD may help explain both PD and SR effects. Thus FAB is designed to examine the separate and combined effects of all three components of diversity for multiple ecosystem functions and to distinguish between ???sampling??? and ???complementarity??? effects of biodiversity. Due to the long lag between planting tree seedlings and determining effects of tree composition and diversity on ecosystem functioning, fewer experiments have been established to elucidate the role of biodiversity in the functioning of forest ecosystems than grassland experiments. FAB will contribute to this gap and is a member of the IDENT and TreeDiv network of forest biodiversity experiments (www.treedivnet.ugent.be). Hypotheses: 1. PD, FD, and SR will all contribute to increased productivity, stability, and diversity of other trophic levels (herbivores, predators, parasitoids, soil microbes, soil flora and fauna) as well as to greater soil C sequestration. 2. Because PD incorporates both the number of species a
Photosynthetic light-response curves:FAB 1 : Forests and Biodiversity Experiment - High density diversity
A forest biodiversity experiment (FAB) focused on trees of our region investigates the consequences of multiple dimensions of tree diversity for soil, food webs, plant communities and ecosystems. FAB is designed to unravel effects of three forms of biological diversity: species richness (SR), functional diversity (FD), and phylogenetic diversity (PD). We define FD as the representation of multiple traits of leaves, roots, seeds, and the whole organism that are correlated with species positions along gradients of resource supply, growth, and decomposition. PD is the representation of evolutionary lineages measured as the genetic distances between species. While PD and FD are often correlated, convergent evolution and adaptive differentiation can decouple them. When functional traits that drive specific ecosystem functions are not phylogenetically conserved, PD and FD may give contrasting predictions. SR, PD, and FD are not independent, and we posit that PD may help explain SR effects, and FD may help explain both PD and SR effects. Thus FAB is designed to examine the separate and combined effects of all three components of diversity for multiple ecosystem functions and to distinguish between ???sampling??? and ???complementarity??? effects of biodiversity. Due to the long lag between planting tree seedlings and determining effects of tree composition and diversity on ecosystem functioning, fewer experiments have been established to elucidate the role of biodiversity in the functioning of forest ecosystems than grassland experiments. FAB will contribute to this gap and is a member of the IDENT and TreeDiv network of forest biodiversity experiments (www.treedivnet.ugent.be). Hypotheses: 1. PD, FD, and SR will all contribute to increased productivity, stability, and diversity of other trophic levels (herbivores, predators, parasitoids, soil microbes, soil flora and fauna) as well as to greater soil C sequestration. 2. Because PD incorporates both the number of species a
Data file for paper:Zalitis, Christopher; Kucernak, Anthony; Lin, Xiaoqian; Sharman, Jonathan, "Electrochemical Measurement of Intrinsic Oxygen Reduction Reaction Activity at High Current Densities as a Function of Particle Size for Pt<sub>4-x</sub>Co<sub>x</sub> /C (x=0,1,3) Catalysts", ACS Catalysis, 2020 - https://doi.org/10.1021/acscatal.9b04750
<p>The data in this spreadsheet was used to produce the figures in the paper </p> <p>Authors: Zalitis, Christopher; Kucernak, Anthony; Lin, Xiaoqian; Sharman, Jonathan</p> <p>Title: Electrochemical Measurement of Intrinsic Oxygen Reduction Reaction Activity at High Current Densities as a Function of Particle Size for Pt<sub>4-x</sub>Co<sub>x</sub> /C (x=0,1,3) Catalysts</p> <p>Journal: ACS Catalysis</p> <p>Year: 2020</p>
Dataset of high-density EEG recordings with auditory and optogenetic stimulation in mice
<p>[Duplicated dataset from G-Node repository: <a href="https://gin.g-node.org/hiobeen/Mouse_hdEEG_ASSR_Hwang_et_al/">https://gin.g-node.org/hiobeen/Mouse_hdEEG_ASSR_Hwang_et_al/</a>]</p> <p>A set of high-density EEG (electroencephalogram) recording obtained from awake, freely-moving mice (mus musculus). Details of experimental method are described in the original research article using the same dataset [Hwang et al., 2019, Brain Structure and Function].</p>
Dataset of high-density EEG recordings with auditory and optogenetic stimulation in mice
<p>[Duplicated dataset from G-Node repository: <a href="https://gin.g-node.org/hiobeen/Mouse_hdEEG_ASSR_Hwang_et_al/">https://gin.g-node.org/hiobeen/Mouse_hdEEG_ASSR_Hwang_et_al/</a>]</p> <p>A set of high-density EEG (electroencephalogram) recording obtained from awake, freely-moving mice (mus musculus). Details of experimental method are described in the original research article using the same dataset [Hwang et al., 2019, Brain Structure and Function].</p>
Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis
<p>Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (<i>F</i><sub>ST</sub>) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.</p>
Data from: Pacman profiling: a simple procedure to identify stratigraphic outliers in high-density deep-sea microfossil data
The deep-sea microfossil record is characterized by an extraordinarily high density and abundance of fossil specimens, and by a very high degree of spatial and temporal continuity of sedimentation. This record provides a unique opportunity to study evolution at the species level for entire clades of organisms. Compilations of deep-sea microfossil species occurrences are, however, affected by reworking of material, age model errors, and taxonomic uncertainties, all of which combine to displace a small fraction of the recorded occurrence data both forward and backwards in time, extending total stratigraphic ranges for taxa. These data outliers introduce substantial errors into both biostratigraphic and evolutionary analyses of species occurrences over time. We propose a simple method—Pacman—to identify and remove outliers from such data, and to identify problematic samples or sections from which the outlier data have derived. The method consists of, for a large group of species, compiling species occurrences by time and marking as outliers calibrated fractions of the youngest and oldest occurrence data for each species. A subset of biostratigraphic marker species whose ranges have been previously documented is used to calibrate the fraction of occurrences to mark as outliers. These outlier occurrences are compiled for samples, and profiles of outlier frequency are made from the sections used to compile the data; the profiles can then identify samples and sections with problematic data caused, for example, by taxonomic errors, incorrect age models, or reworking of sediment. These samples/sections can then be targeted for re-study.
Data from: A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata
Development of genome-wide resources for application in genomic selection or genome-wide association studies, in the absences of full reference genomes, present a challenge to the forestry industry, where longer breeding cycles could benefit from the accelerated selection possible through marker-based breeding value predictions. In particular, large conifer megagenomes require a strategy to reduce complexity, whilst ensuring genome-wide coverage is achieved. Using a transcriptome-based reference template, we have successfully developed a high density exome capture genotype-by-sequencing panel for radiata pine (Pinus radiata D.Don), capable of capturing in excess of 80,000 single nucleotide polymorphism (SNP) markers with a minor allele frequency above 0.03 in the population tested. This represents approximately 29,000 gene models from a core set of 48,914 probes. A set of 704 SMP markers capable of pedigree reconstruction and differentiating individual genotypes were tested within two full-sib mapping populations. While as few as 70 markers could reconstruct parentage in almost all cases, the impact of missing genotypes was noticeable in several offspring. Therefore, sets of 60 sets of 110 randomly selected SNP markers were compared for both parentage reconstruction and clone differentiation. The performance in parentage reconstruction showed little variation over 60 iterations. However, there was notable variation in discriminatory power between closely related individuals, indicating a higher density SNP marker panel may be required to elucidate hidden relationships in complex pedigrees.
Data from: Incidence of multiple paternity and inbreeding in high-density brown bear populations on the Shiretoko Peninsula, Hokkaido, Japan
Understanding the breeding ecology of a species is essential for the appropriate conservation and management of wildlife. In brown bears, females occasionally copulate with multiple males in one breeding season, which may lead to multiple paternity in a single litter. In contrast, inbreeding, a potential factor in the reduction of genetic diversity, may occur, particularly in threatened populations. However, few studies have reported the frequency of these phenomena in brown bear populations. Here, we investigated the incidence of multiple paternity and inbreeding in a high-density brown bear population on the Shiretoko Peninsula in Hokkaido, Japan. A total of 837 individuals collected from 1998 to 2017 were genotyped at 21 microsatellite loci, and parentage analysis was performed. Out of 70–82 litters with ≥2 offspring, 14.6–17.1% of litters were sired by multiple males. This was comparable to the rate reported in a Scandinavian population, although population density and litter size, factors that potentially affect the incidence of multiple paternity, differed between the two populations. Out of 222 mother-father mating pairs, six litters (2.7%) resulted from matings between fathers and daughters. Additionally, one (0.5%) and four (1.8%) cases of mating between maternal half-siblings and between paternal half-siblings, respectively, were observed; however, no cases of mating between mothers and sons or between full-siblings were observed. Our results suggest that male-biased natal dispersal effectively limits mating between closely related individuals (aside from fathers and daughters) in brown bears.
Data from: A high density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour
High density SNP microarrays ('SNP chips') are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this paper we describe the development and application of a high density Affymetrix Axiom chip with around 500 000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation (CNVs). The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genome-wide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays, (ii) detecting SNPs by more than one pipeline, and in independent datasets, ensures a high proportion of working assays, (iii) allele frequency ascertainment bias is minimised by performing SNP discovery in individuals from multiple populations and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.
Data from: A high-density linkage map for Astyanax mexicanus using genotyping-by-sequencing technology
The Mexican tetra, Astyanax mexicanus, is a unique model system consisting of cave-adapted and surface-dwelling morphotypes which diverged >1My ago. This remarkable natural experiment has enabled powerful genetic analyses of cave adaptation. Here, we describe the application of next-generation sequencing technology to the creation of a high-density linkage map. Our map comprises over 2200 markers populating 25 linkage groups constructed from genotypic data generated from a single genotyping-by-sequencing project. We leveraged emergent genomic and transcriptomic resources to anchor hundreds of anonymous Astyanax markers to the genome of the zebrafish (Danio rerio), the most closely related model organism to our study species. This facilitated the identification of 784 distinct connections between our linkage map and the Danio rerio genome, highlighting several regions of conserved genomic architecture between the two species despite ~150My of divergence. Using a Mendelian cave-associated trait as a proof-of-principle, we successfully recovered the genomic position of the albinism locus near the gene Oca2. Further, our map successfully informed the positions of unplaced Astyanax genomic scaffolds within particular linkage groups. This ability to identify the relative location, orientation and linear order of unaligned genomic scaffolds will facilitate ongoing efforts to improve upon the current early draft and assemble future versions of the Astyanax physical genome. Moreover, this improved linkage map will enable higher resolution genetic analyses and catalyze the discovery of the genetic basis for cave-associated phenotypes.
High-density 3-D coordinate data of avian and non-avian dinosaur endocasts
<p><span><span><span><span><span><span><span><span><span><span><span>How do large and unique brains evolve? Historically, comparative neuroanatomical studies have attributed the evolutionary genesis of highly encephalized brains to deviations along, as well as from, conserved scaling relationships among brain regions. However, the relative contributions of these concerted (integrated) and mosaic (modular) processes as drivers of brain evolution remain unclear, especially in non-mammalian groups. While proportional brain sizes have been the predominant metric used to characterize brain morphology to date, we perform a high-density geometric morphometric analysis on the encephalized brains of crown birds (Neornithes or Aves) compared to their stem taxa—the non-avialan coelurosaurian dinosaurs. When analyzed together with developmental neuroanatomical data of model archosaurs (<i>Gallus</i>, <i>Alligator</i>), crown birds exhibit a distinct allometric relationship that dictates their brain evolution and development. Furthermore, analyses by neuroanatomical regions reveal that the acquisition of this derived shape-to-size scaling relationship occurred in a mosaic pattern, where the 'avian'-grade optic lobe and cerebellum evolved first among non-avialan dinosaurs, followed by major changes to the evolutionary and developmental dynamics of cerebrum shape after the origin of Avialae. Notably, the brain of crown birds is a more integrated structure than non-avialan archosaurs, implying that diversification of brain morphologies within Neornithes proceeded in a more coordinated manner, perhaps due to spatial constraints and abbreviated growth period. Collectively, these patterns demonstrate a plurality in evolutionary processes that generate encephalized brains in archosaurs and across vertebrates.</span></span></span></span></span></span></span></span></span></span></span></p>
Pressure-induced amorphisation and a new high density amorphous metallic phase in matrix-free Ge nanoparticles: simulation data
<p>The folder contains:</p> <p>-Pseudopotential files for Ge and H in the .recpot format used in all calculations.</p> <p>-Input and output files for constant enthalpy geometry relaxations of hydrogenated Ge nanocrystals using the electronic enthalpy method within ONETEP (version 3.3).</p> <p>-Input and output files for the DFPT calculations performed with CASTEP (version 6.01).</p>
Data_PlosOne_Too many is too bad: Long-term net negative effects of high density ungulate populations on a dominant Mediterranean shrub
<p>Dataset for Plos One Publication (2016): Too many is too bad: Long-term net negative effects of high density ungulate populations on a dominant Mediterranean shrub</p>
FIG. 1 in Foraging by the flower-dwelling spider, Misumenops argenteus (Thomisidae), at high prey density sites
FIG. 1. Manly's index of habitat preference for (A) M. argenteus and of (B) potential prey for each phase of T. adenantha flowerheads (F1 to F5, see Methods) along the Mirante track, during the rainy season. Values above and below 0.20 (1/total number of flowerhead phases) indicate a preference for and avoidance of flowerhead types by the spiders, respectively. The distribution of the spiders in the dry season was not assessed because of the low number of animals encountered. In the dry season the prey and adult females were not considered because their distribution among the different flowerheads was not significant (see Results).
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
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.