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2,880 results for “Variant.”
Genome-wide analysis identified candidate variants and genes associated with heat stress adaptation in Egyptian sheep breeds
<p>The current study was conducted from 2009 to 2019 in three hot and dry agroecological zones in Egypt: Western Desert coastal zone, New Valley desert oasis, and hot-dry Upper Egypt. Within these zones, three local sheep breeds were studied: Barki (83 ewes), Wahati (55 ewes) and Saidi (68 ewes). During the study period, the animals exercised under natural heat stress (simulating summer grazing on poor pasture). Meteorological and physiological parameters were measured and recorded. The heat tolerance index of the animals was calculated to identify animals with high and low heat tolerance based on the animals' response to the five main physiological parameters (scale from 0 to 5). DNA samples were extracted for genomic analysis. The genetic diversity measurements showed a significant influence of breed and location on the populations. The influence of breed is more significant than that of location. The inbreeding analysis shows that the desert breeds (Wahati and Barki) have lower values than the urban breed (Saidi). The high rate of sub-clustering indicates the process of sub-population through inbreeding pressure. Wahati and Barki are very distinct breeds with strong identification, while Saidi breed has crosses with other breeds. The most significant SNPs associated with heat tolerance were found in MYO5A, PRKG1, GSTCD, and RTN1 genes (P < 0.0001). MYO5A had an effect of 0.74 on the trait heat tolerance in the studied population. It produces a protein that is widely distributed in the melanin-producing neural crest of the skin. Genetic association between genetic and phenotypic variations showed that OAR1 18300122.1, located in ST3GAL3, had the greatest positive effect on heat tolerance. GWAS analysis identified SNPs associated with heat tolerance in the PLCB1, STEAP3, KSR2, UNC13C , PEBP4, and GPAT2 genes.</p>
COCO BBOB-constrained Benchmark Results of Two Evolution Strategy Variants
<p>The three zip-files of this data set provide the performance data of the algorithms presented in the paper<strong> "Benchmarking 𝜖MAg-ES and BP-𝜖MAg-ES on the bbob-constrained Testbed"</strong> submitted to the GECCO 2022 Workshop "<a href="https://gecco-2022.sigevo.org/Workshops#BBOB 2022">BBOB 2022 — Black Box Optimization Benchmarking 2022</a>".</p> <ul> <li><em>coco2.6.2_bbob-constrained_epsMAg.zip</em> <-- results of the 𝜖MAg-ES on COCO version 2.6.2</li> <li><em>coco2.6.2_bbob-constrained_BPepsMAg.zip</em> <-- results of the BP-𝜖MAg-ES on COCO version 2.6.2</li> <li><em>coco2.6.2_bbob-constrained_fmincon</em><em>.zip</em> <-- results of FMINCON (Matlab 2021b) on COCO version 2.6.2</li> </ul> <p> </p>
Simulation of Receptor Binding Domain of SARS-CoV-2 spike protein (WT and variants) in complex with neutralizing antibodies.
<p>This repository contains the molecular dynamics trajectories of the SARS-CoV-2 Spike RBD bound to BD23 and B38 monoclonal antibodies. The simulations for the RBD only systems are also provided. The trajectories are available for the WT spike protein as well as for four different variants (alpha, beta, kappa and delta). The simulations of the RBD only system are propagated for 300 ns and for the RBD-Antibody complex for 500 ns. The trajectories are saved at 100 ps interval. The Steered MD simulation trajectories (WT_RBD_B38_SMD_1.dcd etc.) and collective variables files are also included (WT_RBD_B38_SMD_1.colvars.traj etc.). There are 5 SMD trajectories for each RBD antibody pair. The details of the simulation can be obtained from the preprint: https://doi.org/10.1101/2021.08.13.456317</p>
Supplementary Data: OpenCOVID model output underlaying Figures 1 and 2 of "Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden"
<p>Supplementary data files <strong>Figure_1.xlsx</strong> and <strong>Figure_2.xlsx</strong> contain the model simulation outcomes for Figures 1 and 2 of <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al</em></a> "<strong>Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden</strong>" (2022)</p> <ul> <li><strong>Figure 1</strong>: Peak daily hospital occupancy (number of beds per 100,000 population over the six-month simulation period) for three variant properties; infectivity (relative to Delta), immune evading capacity (%), and severity (relative to Delta)<br> </li> <li><strong>Figure 2</strong>: Percentage of COVID-19 infections and deaths averted by third-dose vaccines for adults and vaccinating 5-11-year-olds with doses one and two.<br> </li> <li>Open access source-codes of the associated plotting functions are published <a href="http://zenodo.org/record/6532404#.Yqw7cezMKdb">here</a> on Zenodo.<br> </li> <li>Open access source-codes for the OpenCOVID model of all analyses as presented in <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al.</em> (2022)</a> are publicly available at <a href="https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src">https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src</a>.<br> </li> <li>Detailed model descriptions and model equations of individual-based transmission model <strong>OpenCOVID</strong> are described in <a href="https://pubmed.ncbi.nlm.nih.gov/34923396/">Shattock <em>et al</em>. (2022)</a> and <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al.</em> (2022).</a></li> </ul>
Systematic analysis of disease-linked rare germline variants reveals new classes of cancer predisposing genes
<ul> <li>GEMs_Liver-HCC: 312 cancer patient-specific genome-scale metabolic models (GEMs) for Liver-HCC reconstructed using the RNA-seq data from PCAWG-TCGA Liver-HCC samples and generic human GEM 'Recon 2M.2'</li> <li>GEMs_Lung-SCC: 493 cancer patient-specific GEMs for Lung-SCC reconstructed using the RNA-Seq data from PCAWG-TCGA Lung-SCC samples and generic human GEM 'Recon 2M.2'</li> </ul> <p>All the patient-specific GEMs were generated using a previously developed method (i.e., tINIT algorithm with a rank-based weight function), which is available at <a href="https://bitbucket.org/kaistmbel/recon-manager">https://bitbucket.org/kaistmbel/recon-manager</a>.</p>
Outputs of molecular dynamics simulations of two NS1 ZIKV variants in the membrane presence
<p>Files corresponding to outputs obtained through Molecular Dynamics (MD) simulations of two Non-structural (NS) proteins 1 of the Zika virus from Uganda (ZIKV-UG) and Brazil (ZIKV-BR). Simulations were performed using GROMACS 5.1.5 or later versions. Systems were built based on atomistic models (https://zenodo.org/record/5608521#.YvDNZTlBzJw) and converted to a coarse-grained representation employing MARTINI 2.2p ElNeDyn. It was assumed to be NS1 systems in <em>apo</em> and <em>holo</em> forms (<em>i.e.</em>, in the absence and presence of a lipid bilayer, respectively). The membrane model tries to reproduce a lipid concentration of an endoplasmic reticulum lipid bilayer. <em>Holo</em> and <em>apo</em> systems were simulated until they reached 20 and 10 µs, respectively. Trajectories do not include water molecules. For the specific case of <em>holo</em> systems, frames were skipped every 5 frames, which means that processed trajectories are equivalent to simulations when it is recorded every 1000 ps. More details can be found at <a href="https://doi.org/10.1021/acs.jcim.2c01461">https://doi.org/10.1021/acs.jcim.2c01461</a></p> <p>Note: Some topology and index files important for MD analysis are also present.</p>
GWAS summary statistics and code for "Sequence variants affecting voice pitch in humans"
<p>Contents: GWAS summary statistics for voice pitch (median F0 in reading) and code for acoustic analysis</p> <p>Please refer to the corresponding publication:</p> <p>Gisladottir et al. Sequence variants affecting voice pitch in humans. <em>Science Advances</em></p> <p>The GWAS summary statistics is also available at: https://www.decode.com/summarydata/</p> <p>The code for acoustic analysis is also available at: https://github.com/cadia-lvl/deCODE</p> <p> </p> <p> </p> <p> </p>
Text-fig. 1. Modern vegetation proxies as delivered by the Drudge 1 and 2 tools for Parschlug. Left column results from KovarEder et al. (2021) based on the floristic spectrum published by Kovar-Eder et al. (2004). The other three columns result from three variants using the enlarged floristic spectrum herein. Differences between variants 1–3 from this study are caused by differences in assignment of some taxa and morphotypes (see Appendix 1). European vegetation formations: Formation C – Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation; Formation D – Mesophytic and hygromesophytic coniferous and mixed broad-leaved-coniferous forests; Formation F – Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation G – Thermophilous mixed deciduous broadleaved forests; Formation J – Mediterranean sclerophyllous forests and scrub; Formation K – Xerophytic coniferous forests, coniferous woodland and scrub. East Asian vegetation types: MCF China, Japan – Montane Coniferous Forests China, Honshu, Yakushima; BLDF N and NE Provinces, China – Broad-leaved Deciduous Forests of the Northern and Northeastern Provinces (China); BLDF Upper Yangtze, Honshu – Broad-leaved Deciduous Forest, Upper Yangtze Provinces, Mt. Emei, and Honshu; MMF China – Mixed Mesophytic Forest, Lower Yangtze Provinces; BLEF China, Japan – Broad-leaved Evergreen Forests, China, Japan; Meili Snow Mt. high altitude SCL and BLF, China – Meili Snow Mt., Sclerophyllous and broad-leaved forest zone (2,580-3,650 m alt.). (Designations of European vegetation formations follow Bohn et al. (2004) and Asian ones follow Kovar-Eder et al. (2021). in Floristic, Vegetation And Climate Assessment Of The Early/Middle Miocene Parschlug Flora Indicates A Distinctly Seasonal Climate
Text-fig. 1. Modern vegetation proxies as delivered by the Drudge 1 and 2 tools for Parschlug. Left column results from KovarEder et al. (2021) based on the floristic spectrum published by Kovar-Eder et al. (2004). The other three columns result from three variants using the enlarged floristic spectrum herein. Differences between variants 1–3 from this study are caused by differences in assignment of some taxa and morphotypes (see Appendix 1). European vegetation formations: Formation C – Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation; Formation D – Mesophytic and hygromesophytic coniferous and mixed broad-leaved-coniferous forests; Formation F – Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation G – Thermophilous mixed deciduous broadleaved forests; Formation J – Mediterranean sclerophyllous forests and scrub; Formation K – Xerophytic coniferous forests, coniferous woodland and scrub. East Asian vegetation types: MCF China, Japan – Montane Coniferous Forests China, Honshu, Yakushima; BLDF N and NE Provinces, China – Broad-leaved Deciduous Forests of the Northern and Northeastern Provinces (China); BLDF Upper Yangtze, Honshu – Broad-leaved Deciduous Forest, Upper Yangtze Provinces, Mt. Emei, and Honshu; MMF China – Mixed Mesophytic Forest, Lower Yangtze Provinces; BLEF China, Japan – Broad-leaved Evergreen Forests, China, Japan; Meili Snow Mt. high altitude SCL and BLF, China – Meili Snow Mt., Sclerophyllous and broad-leaved forest zone (2,580-3,650 m alt.). (Designations of European vegetation formations follow Bohn et al. (2004) and Asian ones follow Kovar-Eder et al. (2021).
Data for publication: A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components
<p>Raw and processed sequence data from Oxford Nanopore and BGI short read sequencing platforms used in the publication: "A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components".</p>
Canadian Arctic killer whale genomic variants
<p>This dataset contains resequencing data used in our killer whale genomics research exaiming population structure and demographic history, including unfiltered genomic variants and filtered SNPs. Source code for genomic analyses is available at <a href="http://github.com/edegreef/NBW-resequencing">github.com/edegreef/killerwhale-resequencing</a>. Data uploaded here contain:</p> <ul> <li><strong>orca_sample_info.csv</strong> - metadata for the killer whale samples</li> <li><strong>orca_unfiltered_diploid.vcf.gz</strong> - all variant calls, including indels and SNPs (n = 29)</li> <li><strong>orca_snps_q30_biallelic.vcf.gz </strong>- SNPs filtered for quality and bi-allelic sites (n = 29)</li> <li><strong>orca_snps_q30_biallelic_HWE0.005_miss0.4.vcf.gz</strong> - SNPs filtered for quality, bi-allelic sites, out of HWE, and missingness > 0.4 (n = 29).</li> <li><strong>orca_snps_q30_biallelic_HWE0.005_miss0.4_maf0.05_LDprunedr08_n24.vcf.gz</strong> - SNPs further filtered for MAF, LD-pruned, and removal of kin & duplicates (n = 24).</li> </ul>
Fig. 1 in A new subtype of Entamoeba gingivalis: BE. gingivalis ST2, kamaktli variant^
Fig. 1 Electrophoresis on 1.2% TBE agarose gel and ethidium bromide stained of amplicons obtained with different primer pairs (shown on the top of each line) and DNA from some clinical samples. Line 1, 100 bp DNA Ladder Molecular size Marker (MM) GeneDirex®, of 100 to 1500 bp. The primers used were GEI18SF/GE18SR (18/18) line 2, Entam1-Entam2 (E1/E2) line 3, GEI18SF-P2 (18/P2) lines 4, Entam1-RD3 (E1/RD3) lines 6 and 7, Entam1-GE18SR (E1/18) lines 8 and 9, and RD5/RD3 (RD5′-RD3′) lines 10 and 11. Lines 2, 4, and 6 did not show visible bands
Fig. 2 in Anticarsia gemmatalis nucleopolyhedrovirus from soybean crops in Tamaulipas, Mexico: diversity and insecticidal characteristics of individual variants and their co-occluded mixtures
Fig. 2. Mortality of second instar Anticarsia gemmatalis following inoculation with 2 × 105 occlusion bodies per mL of (A) genotypic variants compared with a mixture of 30 field isolates (30wt) and reference Brazilian variant AgMNPV-2D (Ag-2D), and (B) co-occluded mixtures of variants (M1–M4).
Fig. 4 in Anticarsia gemmatalis nucleopolyhedrovirus from soybean crops in Tamaulipas, Mexico: diversity and insecticidal characteristics of individual variants and their co-occluded mixtures
Fig. 4. Weibull estimates of mean time to death of fourth instar Anticarsia gemmatalis infected by (A) the individual genotypic variants compared with a mixture of 30 field isolates (30wt) and reference Brazilian variant AgMNPV-2D (Ag-2D) (shape parameter a = 6.776), and (B) co-occluded mixtures of variants (M1–M4) (shape parameter a = 7.509).
Fig. 1 in Anticarsia gemmatalis nucleopolyhedrovirus from soybean crops in Tamaulipas, Mexico: diversity and insecticidal characteristics of individual variants and their co-occluded mixtures
Fig. 1. (A) HindIII restriction endonuclease profiles of 5 individual genotypic variants (G1–G5) compared with a mixture of 30 field isolates (30wt) obtained from pooled field-collected larvae and the reference Brazilian variant AgMNPV-2D (Ag-2D). Arrows indicate the position of marker fragments for each of the variants. (B) Prevalence of plaque purified variants in pooled sample of 30 Anticarsia gemmatalis larvae that died from polyhedrosis during laboratory rearing (n indicates total number of plaques of each genotypic variant out of a total of 52 plaques).
Fig. 6 in A new vesselless angiosperm stem with a cambial variant from the Upper Cretaceous of Antarctica
Fig. 6. Simplified phylogenetic representation (modified from APG VI 2016), with the three main atypical morphological characters discussed: presence of AVES pattern, absence of vessels, and presence of transitional tracheid-vessel elements.
Fig. 5 in A new vesselless angiosperm stem with a cambial variant from the Upper Cretaceous of Antarctica
Fig. 5. World distribution of extant Chloranthaceae (red area) and sites where macro/meso fossils of the family were found (asterisks): Couperites USA), Chloranthistemon (Sweden and USA), Asteropollis plant and Canrightia (Portugal), Zlatkocarpus (Czech Republic), loose anthers Argentina), and Sarcandraxylon gen. nov. (Antarctic Peninsula).
Fig. 3 in A new vesselless angiosperm stem with a cambial variant from the Upper Cretaceous of Antarctica
Fig. 3. SEM images of the secondary xylem of the chloranthacean angiosperm Sarcandraxylon sanjosense gen. et sp. nov. (IAA-Pb 621), San José Pass, Antarctica, early–middle Campanian. A. Transverse section of the stem, showing one vascular bundle in the middle, pith toward the right, white arrows pointing uniseriate fascicular rays. B. Parenchymatic cells of an interfascicular ray in transverse section showing the main shape and piritization of the cell walls. C. Secondary xylem in longitudinal tangential section, showing fascicular xylem (fx) and interfascicular rays (ir). D. Longitudinal section of fascicular xylem; D1, showing tracheids and a two cells tall uniseriate ray (white arrow) with elongate upright cells; D2, detail showing cell walls partially replaced with framboidal pyrite (white arrow). Scale bars: A, D, 100 μm; B, 40 μm; C, 200 μm; E, 50 μm.
Fig. 2 in A new vesselless angiosperm stem with a cambial variant from the Upper Cretaceous of Antarctica
Fig. 2. Light micrographs of the stem of chloranthacean angiosperm Sarcandraxylon sanjosense gen. et sp. nov. (IAA-Pb 621), San José Pass, Antarctica, early–middle Campanian. A. Transverse section of the complete stem with pith, secondary xylem, phloem, and bark. B. Protoxylem (black arrow) and metaxylem (white arrow) in a vascular bundle. C. Secondary xylem in transverse section, pith in the left (white arrow), two interfascicular rays and fascicular secondary xylem (fx) intercalated. White arrow pointing uniseriate fascicular ray. D. Detail of bark and secondary phloem. Note phloem with AVES pattern as well. Phloem cells not preserved (p) and phloem fibers cap (black double head arrow) separated by interfascicular rays (ir). Bark (white double head arrow) with a continued thickened layer, forming shallow ribs. E. Tangential section of the stem, arrows pointing fascicular uniseriate rays; at both sides interfascicular rays (ir). Scale bars: 50 μm; except A, 1 mm.
Fig. 4 in A new vesselless angiosperm stem with a cambial variant from the Upper Cretaceous of Antarctica
Fig. 4. Light micrographs of the stem of extant chloranthacean angiosperm Sarcandra glabra (Thunberg, 1794) Nakai, 1930. Images taken from the database of Japanese woods of the Forestry and Forest Products Research Institute (http://db.ffpri.affrc.go.jp/WoodDB/JWDB-E/home.php; accessed in 2019). A. Transverse section of the stem, pith almost entirely missing, secondary xylem with growth rings, secondary phloem and bark. B. Secondary xylem in transverse section, two interfascicular rays (ir) and fascicular secondary xylem (fx) intercalated. White arrow pointing uniseriate fascicular ray. Black arrow pointing protoxylem. C. Detail of bark and secondary phloem. Note phloem with AVES pattern as well. Phloem cells preserved and phloem fibers cap (black double headed arrow) separated by interfascicular rays. Bark (white double headed arrow) with a continued thickened layer. D. Tangential section of the stem, arrows pointing fascicular uniseriate rays in fascicular xylem (fx). Interfascicular rays (ir) intercalated. Scale bars 50 μm, except A, 1 mm.
Fig. 3 in Anticarsia gemmatalis nucleopolyhedrovirus from soybean crops in Tamaulipas, Mexico: diversity and insecticidal characteristics of individual variants and their co-occluded mixtures
Fig. 3. Logarithm of mean occlusion body (OB) production in fourth instar Anticarsia gemmatalis infected by (A) the genotypic variants compared with a mixture of 30 field isolates (30wt) and reference Brazilian variant AgMNPV-2D (Ag-2D), and (B) co-occluded mixtures of variants (M1–M4).
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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.