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4,529
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4,529 results for “drosophila”
Centripetal migration in Drosophila ovary VIII: E-cadherin null mitotic clones pt1
<p>Data supporting Figs. 6, 7, S6 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”</p> <p>DOI: 10.1242/dev.200492</p> <ul> <li><strong>“Immuno Shg LOF clonal analysis” 98 KB</strong></li> </ul> <p> Preliminary evaluation of sample image with clones of cells with E-Cadherin mutant or control mitotic clones</p> <ul> <li><strong>“Mixed control and shg mutant mitotic clones” 44.1Gb </strong></li> </ul> <p> Fixed sample image data for clones of cells with E-Cadherin mutant or control mitotic clones</p>
Centripetal migration in Drosophila ovary VII: E-cadherin RNAi clones in follicle cells timelapse
<p>Data supporting Figs. 5, S7, S8, S9, S10, S11, S12, S13, S14, S15 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”</p> <p>DOI: 10.1242/dev.200492</p> <ul> <li><strong>“FC RNAi flipout timelapse data complete” 43.53GB</strong></li> </ul> <p> Timelapse image data for clones of follicle cells with E-Cadherin knockdown</p> <ul> <li><strong>“Live FC RNAi Clonal Data prelim evaluation” 22.1 MB</strong></li> </ul> <p> Preliminary evaluation of follicle cell E-Cadherin knockdown samples</p> <ul> <li><strong>“RNAi clone M2-M3-M5 quant” 12 KB</strong></li> </ul> <p> Quantitative data from specific milestones for clones of follicle cells with E-Cadherin knockdown</p>
Analysis accompanying "Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the Drosophila larval brain"
<p>This repository documents the raw data processing and figure generation for the article “Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the <em>Drosophila </em>larval brain”, doi: 10.1261/rna.079552.122.</p>
DROP: Molecular voucher database for identification of Drosophila parasitoids
<p>A curated open-access molecular reference database for <em>Drosophila</em> parasitoids (DROP). Identifying <em>Drosophila</em> parasitoids is challenging and poses major impediment to realize the full potential of this model system in studies ranging from molecular mechanisms to food webs, and in biological control of <em>Drosophila suzukii</em>. In DROP, genetic data are linked to voucher specimens and, where possible, the voucher specimens are identified by taxonomists and vetted through direct comparison with primary type material. An updated taxonomic catalogue for the research community is also part of DROP. DROP offers accurate molecular identification and improves cross-referencing between individual studies that we hope will catalyze research on this diverse and fascinating model system. Our effort should also serve as an example for researchers facing similar molecular identification problems in other groups of organisms.</p>
Raw data for Kierdorf et al, "Muscle function and homeostasis require cytokine inhibition of AKT activity in Drosophila"
<p>This upload contains the raw data corresponding to the publication "Muscle function and homeostasis require cytokine inhibition of AKT activity in Drosophila" by Katrin Kierdorf et al., eLife 2020.</p>
Orthologs for Homo Sapiens and Drosophila Melanogaster from the Roundup Orthology Database Version 4
<p>This dataset contains orthologs for Homo sapiens and Drosophila melanogaster, computed with the Reciprocal Smallest Distance algorithm using a divergence threshold of 0.8 and an e-value threshold of 1e-5. The orthologs were downloaded from version 4 of the Roundup database, which is no longer available.</p>
Dataset 'Yeast facilitates the multiplication of Drosophila bacterial symbionts but has no effect on the form or parameters of Taylor's law'
<p>Dataset from the manuscript 'Yeast facilitates the multiplication of <em>Drosophila </em>bacterial symbionts but has no effect on the form or parameters of Taylor’s law' (2020)</p> <p>Each line corresponds to a single experimental unit.</p>
Raw diffraction images of Drosophila Piwi
<p>Crystal structure of Drosophila Piwi (PDB code: <a href="https://www.rcsb.org/structure/6KR6">6KR6</a>).</p> <p>28 mercury-bound data and 4 native data were included (see file_list.txt for details). Each dataset consists of 180° (except two 90° datasets) from single crystal and was collected using <a href="https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md">EIGER</a> X 9M detector at a wavelength of 1 Å with helical data collection scheme using 15×10 μm beam on BL32XU, SPring-8. </p> <p>All diffraction images were processed using DIALS 1.10.2 through <a href="https://github.com/keitaroyam/yamtbx/blob/master/doc/kamo-en.md">KAMO</a> pipeline, and merged using XSCALE from XDS package with kamo.multi_merge. The crystals belong to space group P2<sub>1</sub>2<sub>1</sub>2<sub>1</sub> with a=62.1, b=115.6, c=119.9 Å. Finally 23 mercury-bound datasets were merged at 2.9 Å resolution in the published result (<a href="https://doi.org/10.1038/s41467-020-14687-1">Yamaguchi et al. Nature Communications, 2020</a>). Merging improved resolution and electron density of PAZ domain that was difficult to interpret with a single dataset.</p>
Data from: Genetic and environmental canalization are not correlated among altitudinally varying populations of Drosophila melanogaster
<p>Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves is limited, despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of <em>Drosophila </em>adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.</p>
Dataset of examples of Drosophila epithelia at different developmental stages
<p><strong>File list</strong></p> <p>A) notum1_GFP.TIF and notum1_mCherry.TIF</p> <p>B) notum2_GFP.tif and notum2_mCherry.tif</p> <p>C) wing_disc1.tif</p> <p>D) wing_disc2.tif</p> <p><strong>Samples</strong></p> <p>A-B) Posterior region of live drosophila pupal notum. All the cells express E-Cadherin::GFP, and a clonal subpopulation of them express active Yorkie and nuclear mCherry protein.</p> <p>C-D) Drosophila wing imaginal discs from L3 larval stage stained for (C) E-cadherin (green) and GFP (clone, magenta), (D) E-cadherin (green) and phospho-histone H3 (magenta)</p> <p><strong>Imaging conditions</strong></p> <p>(A) was done on a confocal spinning disk microscope with a 40X oil objective. (B,C,D) images were acquired using a Zeiss LSM 880 confocal microscope, equipped with an oil immersion objective (Plan-Apochromat 40x/1.3 Oil DIC UV-IR M27). (A-B) Stacks were generated with a Z interval of 1.5 um, 0.5 for (C) and 1 um for (D). (A) pixel size is 0.28um. (B-D) pixel size is 0.35um.</p>
Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift
<p>The Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>) is native to Southeast Asia. Since its first detection in 2008 in Europe and North America, it has been a pest to the fruit production industry as it feeds and oviposits on ripening fruit. Here we aim to model the potential geographical distribution of <em>D. suzukii</em>. We performed an extensive literature review to map the current records. In total, 517 documented occurrences (96 native and 421 invasive) were identified spanning 52 countries. Next, we constructed three species distribution models (SDMs) based on occurrence records in: 1) the native range (SDMnative), 2) the invasive range in Europe (SDMEurope) and 3) a global model of all records (SDMglobal). The models aimed to investigate, whether this species will be able to occupy additional ecological niches beyond its native range and expand its current geographic distribution both globally and in Europe. The SDMs were generated using Maximum Entropy algorithms (Maxent) based on present occurrence records and bioclimatic variables (WorldClim). Predictions of habitat suitability vary greatly depending on the origins of occurrence records. According to all models, precipitation and low temperatures were key limiting factors for the distribution of <em>D. suzukii</em>, which suggests that this species requires a humid environment with mild winters in order to establish a permanent population in its invasive range. Several regions in the invasive range, not presently occupied by this species, were predicted highly suitable, especially in northern Europe, suggesting that <em>D. suzukii</em> is not occupying its full fundamental niche yet. Synthesis and applications. Based on these models of potential geographic distribution of the Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>), we show a shift in the ecological niche in <em>D. suzukii</em> populations, emphasizing the importance of using presence and local environmental data. Further investigation regarding new occurrences is recommended to secure optimal pest management. Despite a continuing expansion, many countries still lack proper surveillance schemes, and we urge policymakers to initiate appropriate management programs.</p>
Drosophila simulans template brains
<p>Male and female symmetric averaged templates (11 and 10 brains, respectively) and intersex template brain for <em>Drosophila simulans</em>. Voxel size: (0.461, 0.461, 1) micron.</p>
Drosophila melanogaster template brains
<p>Male and female symmetric averaged templates (18 and 14 brains, respectively) and intersex template brain for <em>Drosophila melanogaster</em>. Voxel size: (0.461, 0.461, 1) micron.</p>
A dataset of 3D fly (Drosophila melanogaster) flight trajectories to study the role of neuropeptide degradation in visuo-motor behaviors.
<p>As part of a wide study on the role of neuropeptides in the visuo-motor behavior of Drosophila melanogaster, we exposed three fly strains with impaired neuropeptide degradation function, and corresponding controls, to different visual stimuli.</p> <p>Find further details in the provided README.</p>
Drosophila simulans LD results from PLINK for Chromosome X
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and dataset</strong>s: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3R, 3L, and 4.</p>
Drosophila simulans LD results from PLINK for Chromosome 3R
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3L, 4, and X.</p>
Drosophila simulans LD results from PLINK for Chromosome 4
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Wor</strong>k: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3R, 3L, and X.</p>
Drosophila simulans LD results from PLINK for Chromosome 2R
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Wor</strong>k: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 3L, 3R, 4, and X.</p>
Drosophila simulans LD results from PLINK for Chromosome 3L
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2L, 2R, 3R, 4, and X</p>
Drosophila simulans LD results from PLINK for Chromosome 2L
<p><strong>Abstract</strong>: Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p> <p><strong>Material type</strong>: Text files of pairwise linkage disequilibrium (LD) calculations from Plink (v). </p> <p><strong>Larger Body of Work</strong>: Pervasive incomplete selective sweeps in D. simulans account for excess variation.</p> <p><strong>Related publications and datasets</strong>: Drosophila simulans VCF, LD results from chromosomes 2R, 3L, 3R, 4, and X.</p>
ScienceDex guides
Understand access before you commit
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.