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236 results for “Cell nucleus”
Nucleus and cell segmentations for data in the mudRapp-seq paper
<p>Segmentation masks for images published with the paper describing </p> <p>"<em>Multiple direct RNA padlock probing in combination with in-situ sequencing (mudRapp-seq)</em>":</p> <blockquote> <p>Ahmad S, Gribling-Burrer AS, Schaust J, Fischer SC, Ambil UB, Ankenbrand MJ, Smyth RP. <em>Visualizing the transcription and replication of influenza A viral RNAs in cells by multiple direct RNA padlock probing and in-situ sequencing (mudRapp-seq)</em> (in review)</p> </blockquote> <p>Raw images are published in the <a href="https://www.ebi.ac.uk/bioimage-archive/">Bioimage Archive</a> (identifier pending). To use these masks, run the data formatting code in the accompanying code repository to get the raw data in the correct structure and extract this zip archive into the repository root (the folder structure in the archive matches the folder structure of the repository).</p> <p>Filenames in `analysis/segmentation` contain a hint about how they were created:</p> <ul> <li>cp: direct segmentation with a cellpose model (<a href="https://github.com/BioMeDS/mudRapp-seq/blob/main/models/cellpose/nuclei">nuclei</a>, <a href="https://github.com/BioMeDS/mudRapp-seq/blob/main/models/cellpose/cells">cells</a>)</li> <li>cpws: cell segmentation through watershed with nucleus masks as seeds</li> <li>cpmc: manually corrected cellpose segmentations</li> </ul> <p>Besides the final segmentation masks, the training data are included in `data/training` and the models in `models/cellpose`.</p> <p>Changes:</p> <ul> <li>v1.1 training data and models added</li> </ul>
Multiple Nuclei HeLa cell ground truth images with four labels (nuclear envelope, nucleus, rest of the cell, and background) for deep learning architecture training.
<p>This is a data set that contains <strong>labelled HeLa cell images</strong>, indicating the four different classes - nuclear envelope, nucleus, rest of the cell, and background. Similar ground truth have been published for this data set, but in this case, multiple nuclei have been labelled, whilst previous ones only focused on the central cell (https://doi.org/10.5281/zenodo.3874949)</p> <p>Details of the imaging, preparation and segmentation have been published in:</p> <ul> <li>Cefa Karabağ, Martin L. Jones, Christopher J. Peddie, Anne E. Weston, Lucy M. Collinson, Constantino Carlos Reyes-Aldasoro. Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy. <em>J. Imaging</em> <strong>2019</strong>, <em>5</em>(9), 75; <a href="https://doi.org/10.3390/jimaging5090075">https://doi.org/10.3390/jimaging5090075</a></li> <li>Cefa Karabağ, Martin L. Jones, Christopher J. Peddie, Anne E. Weston, Lucy M. Collinson, Constantino Carlos Reyes-Aldasoro. Semantic segmentation of HeLa cells: An objective comparison between one traditional algorithm and four deep-learning architectures, PLOS ONE, <strong>2020</strong>; <a href="https://doi.org/10.1371/journal.pone.0230605">https://doi.org/10.1371/journal.pone.0230605</a></li> <li> <p>Cefa Karabağ, Martin L. Jones, Constantino Carlos Reyes-Aldasoro, Segmentation of the Plasma Membrane of HeLa Cells,<em> J. Imaging</em> <strong>2021</strong>, <em>7</em>(6), 93; <a href="https://doi.org/10.3390/jimaging7060093">https://doi.org/10.3390/jimaging7060093</a></p> </li> </ul> <ul> <li>The data sets are freely available through EMPIAR: http://dx.doi.org/10.6019/EMPIAR-10094 EMPIAR.</li> </ul>
Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provides both common and discordant biological insights
<p>The datasets generated by <em>Cellranger </em>for all 24 samples (.h5 format).<br><br></p>
◂Fig. 5 Gametogenesis in male and female Veneriserva pygoclava. A–D Semi-thin histological sections of female Veneriserva pygoclava, stained with toluidine blue. A Cross-section of a female Veneriserva. B Close-up of large mature oocytes without discernible nurse cells. C Developing oocytes attached to mesenteries (mes), and oogonia proliferating from the ventral side of the dorsal blood vessel (bv). D Details of vitellogenic oocytes and nurse cells. Arrowheads indicate brownstained yolk platelets and yolk bodies. E Live sperm cells captured in a light micrograph. F–G Cross-sections of male Veneriserva. Note the absence of a gut in the cross-sections. Abbreviations—ac acicula, acr acrosome, bv blood vessel, coe coelomic cavity, mes mesentery, nc nurse cell, nn nurse cell nucleus, nu sperm cell nucleus, Oo oocyte, on oocyte nucleus, sp spermatogonia, vnc ventral nerve cord in Hardly Venus's servant-morphological adaptations of Veneriserva to an endoparasitic lifestyle and its phylogenetic position within Dorvilleidae (Annelida)
◂Fig. 5 Gametogenesis in male and female Veneriserva pygoclava. A–D Semi-thin histological sections of female Veneriserva pygoclava, stained with toluidine blue. A Cross-section of a female Veneriserva. B Close-up of large mature oocytes without discernible nurse cells. C Developing oocytes attached to mesenteries (mes), and oogonia proliferating from the ventral side of the dorsal blood vessel (bv). D Details of vitellogenic oocytes and nurse cells. Arrowheads indicate brownstained yolk platelets and yolk bodies. E Live sperm cells captured in a light micrograph. F–G Cross-sections of male Veneriserva. Note the absence of a gut in the cross-sections. Abbreviations—ac acicula, acr acrosome, bv blood vessel, coe coelomic cavity, mes mesentery, nc nurse cell, nn nurse cell nucleus, nu sperm cell nucleus, Oo oocyte, on oocyte nucleus, sp spermatogonia, vnc ventral nerve cord
Data for: Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq of Drosophila testes
<p><span>Proper differentiation of sperm from germline stem cells, essential for production of the next generation, requires dramatic changes in gene expression that drive remodeling of almost all cellular components, from chromatin to organelles to cell shape itself. Here we provide a single nucleus and single cell RNA-seq resource covering all of spermatogenesis in <em>Drosophila</em> starting from in-depth analysis of adult testis single nucleus RNA-seq (snRNA-seq) data from the Fly Cell Atlas (FCA) study (Li et al., 2022). With over 44,000 nuclei and 6,000 cells analyzed, the data provide identification of rare cell types, mapping of intermediate steps in differentiation, and the potential to identify new factors impacting fertility or controlling differentiation of germline and supporting somatic cells. We justify assignment of key germline and somatic cell types using combinations of known markers, <em>in situ</em> hybridization, and analysis of extant protein traps. Comparison of single cell and single nucleus datasets proved particularly revealing of dynamic developmental transitions in germline differentiation. To complement the web-based portals for data analysis hosted by the FCA, we provide datasets compatible with commonly used software such as Seurat and Monocle. The foundation provided here will enable communities studying spermatogenesis to interrogate the datasets to identify candidate genes to test for function <em>in vivo</em>.</span></p>
Data for: Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq of Drosophila testes
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Identification of an inhibitory neuron subtype, the L-stellate cells of the cochlear nucleus
<p>Auditory processing depends upon inhibitory signaling by interneurons, even at its earliest stages in the ventral cochlear nucleus (VCN). Remarkably, to date only a single subtype of inhibitory neuron has been documented in the VCN, a projection neuron termed the D-stellate cell. With the use of a transgenic mouse line, optical clearing and imaging techniques, combined with electrophysiological tools, we revealed a population of glycinergic cells in the VCN distinct from the D-stellate cell. These novel multipolar glycinergic cells were smaller in soma size and dendritic area, but over 10-fold more numerous than D-stellate cells. They were activated by auditory nerve fibers and T-stellate cells, and made local inhibitory synaptic contacts on principal cells of the VCN. Given their abundance, combined with their narrow dendritic fields and axonal projections, it is likely that these neurons, here termed L-stellate cells, play a significant role in frequency-specific processing of acoustic signals.</p>
Exploring cell diversity and fidelity in crustacean limb regeneration using single-nucleus RNA sequencing
<p>R objects containing datasets generated by snRNA-seq on Parhyale hawaiensis limbs. These datasets have been generated during my Phd thesis.</p>
INTERVERTEBRAL DISC NUCLEUS PULPOSUS CELLS CORPUS
<p>Intervertebral disc degeneration (IDD) arises from an intricate imbalance between the anabolic and catabolic processes governing the extracellular matrix (ECM) within the disc. Biochemical processes are complex, redundant and feedback-looped, thus improved integration of knowledge is needed. To address this, a literature-based regulatory network model (RNM) for nucleus pulposus cells (NPC) is proposed, representing the normal state of the intervertebral disc (IVD) cells, in which proteins are represented by nodes that interact among each other through activation and/or inhibition edges. This model includes 33 different proteins and 153 edges by incorporating critical biochemical interactions in IVD regulation, tested in vivo or vitro in human and animal NPC, alongside non-tissue-specific protein-protein interactions. We used the network to calculate the dynamic regulation of each node through a semi-quantitative method. The basal steady state successfully represented the activity of a normal NPC, and the model was assessed through the published literature, by replicating two independent experimental studies in human normal NPC. Pro-catabolic or pro-anabolic shifts of the network activated by nodal perturbations could be predicted. Sensitivity analysis underscored the significant influence of transforming growth factor beta (TGF-β) and interleukin-1 receptor antagonist (IL-1Ra) on the regulation of structural proteins and degrading enzymes within the system. Given the ongoing challenge of elucidating the mechanisms that drive ECM degradation in IDD, this unique IVD RNM holds promise as a tool for exploring and predicting IDD progression, shedding light on IVD phenotypes and guiding experimental research efforts.</p>
Simulations of cochlear nucleus bushy cells reconstructed from serial blockface electron microscopy (V1.3)
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Identification of an inhibitory neuron subtype, the L-stellate cells of the cochlear nucleus
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Single-nucleus Transcriptomics of IDH1- and TP53-mutant Glioma Stem Cells Displays Diversified Commitment on Highly Invasive Cancer Progenitors
<p><strong>Fig. S1</strong>. <strong>Marker genes for Seurat clusters.</strong> (<strong>A</strong>) distribution of marker genes for cluster 0 on the 2D-UMAP space. (<strong>B</strong>) distribution of marker genes for cluster 1 on the 2D-UMAP space. (<strong>C</strong>) distribution of marker genes for cluster 2 on the 2D-UMAP space. (<strong>D</strong>) distribution of marker genes for cluster 3 on the 2D-UMAP space. (<strong>E</strong>) distribution of marker genes for cluster 4 on the 2D-UMAP space. (<strong>F</strong>) distribution of marker genes for cluster 5 on the 2D-UMAP space. (<strong>G</strong>) Stuck violin plot of marker gene expression for Seurat clusters (bottom panel) and their annotation (right side panel). The violin shape displays the number of the cells expressing a gene, the continuous color panel defines median expression value of a gene from the absence of expression (white) to high expression (dark blue).</p> <p><strong>Fig. S2</strong>. <strong>Expression of genes marking cell malignization.</strong> (<strong>A</strong>) expression of collagens in Surat clusters (bottom panel) (<strong>B</strong>) expression of genes linked to Migration and ECM in Surat clusters (bottom panel) (<strong>C</strong>) expression of genes classified as Proto-oncogenes in Surat clusters (bottom panel). The violin shape displays the number of the cells expressing a gene, the violin color defines the Seurat cluster. Gene expression displayed in log-transformed normalized expression values.</p> <p><strong>Fig. S3</strong>. <strong>Expression of genes involved in proliferation and survival of cancer cells.</strong> (<strong>A</strong>) Genes involved in Wnt-pathway in Surat clusters (bottom panel). (<strong>B</strong>) Genes involved in Akt-pathway in Surat clusters (bottom panel). (<strong>C</strong>) Genes inducing resistance to cancer therapeutics in Surat clusters (bottom panel). The violin shape displays the number of the cells expressing a gene, the violin color defines the Seurat cluster. Gene expression displayed in log-transformed normalized expression values.\</p> <p><strong>Fig. S4</strong>. <strong>Expression of genes marking CSC profile.</strong> (<strong>A</strong>) Ion channel genes in Surat clusters (bottom panel). (<strong>B</strong>) Antioncogenes in Surat clusters (bottom panel). <strong>C</strong>. Stem-cell genes in Surat clusters (bottom panel). (<strong>D</strong>) Antiapoptotic genes in Surat clusters (bottom panel). The violin shape displays the number of the cells expressing a gene, the violin color defines the Seurat cluster. Gene expression displayed in log-transformed normalized expression values.</p> <p><strong>Fig. S5</strong>. <strong>Genes differentially expressed between UMAP clusters</strong>. (<strong>A</strong>) Heatmap for wt-GSCs. (<strong>B</strong>) Heatmap for mt-GSCs. Upper colour panel in the heatmap designates Seurat clusters. Gene expression is indicated by continuous colour panel starting from the most downregulated (blue) to the most upregulated (red).</p> <p><strong>Fig. S6</strong>. <strong>Marker genes defying cell annotations</strong>. (<strong>A</strong>) Stack violin plot displays marker gene expression in wt-GSC clusters. (<strong>B</strong>) Stack violin plot displays marker gene expression in mt-GSC clusters. Genes grouped by cell annotations (side description) and UMAP clusters (down column bar). The violin shape displays the number of the cells expressing a gene, the continuous color panel defines median expression value of a gene from the absence of expression (white) to high expression (dark blue).</p> <p><strong>Fig. S7</strong>. <strong>Differentially expressed proliferation and adhesion pathways comparing mutant samples to wild type.</strong> (<strong>A</strong>) ERBB signalling pathway. (<strong>B</strong>) Wnt signalling pathway. (<strong>C</strong>) Genes linked to Focal adhesion. (<strong>D</strong>) Genes classified as Cell adhesion molecules. Red rectangles display upregulated genes (proteins), green rectangles define downregulated genes (proteins). Pictures obtained by KEGG pathview.</p> <p><strong>Table S1. Glioma genotyping primers</strong></p> <p><strong>Table S2. Smart-seq2 Primers</strong></p>
Mouse Kidney Atlas (MKA) & MKA-Extended: Single-cell and single-nucleus reference atlases of the mouse kidney
<p>This deposit contains two linked datasets of the mouse kidney:<br><br></p> <h4><strong>1. MKA (Mouse Kidney Atlas)</strong></h4> <p>A comprehensive reference atlas of the healthy adult mouse kidney, generated by integrating approximately <strong>140,000 cells and nuclei</strong> from <strong>59 publicly available single-cell and single-nucleus RNA-sequencing datasets</strong> across <strong>eight independent studies</strong>.<br>The MKA harmonizes annotations through a <strong>hierarchical cell-type model</strong>, enabling robust cross-study comparisons and accurate labeling of novel or rare cell populations.</p> <ul> <li> <p><strong>Original publication:</strong> Novella-Rausell <em>et al.</em>, <em>iScience</em> (2023). <em>“A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery.” </em>DOI: <a target="_new" rel="noopener">10.1016/j.isci.2023.106877</a></p> </li> <li> <p><strong>Format:</strong> <code>AnnData</code> object (~141,401 observations × 3,000 genes)</p> </li> </ul> <h4><strong>2. MKA-Extended</strong></h4> <p>An expanded version of the MKA. This extended atlas incorporates <strong>immune, injury-induced, and polycystic kidney disease–specific</strong> cellular populations, providing a unified reference for <strong>Tangram-based deconvolution</strong> of spatial transcriptomics datasets.</p> <ul> <li><strong>Original publication: </strong>Yasinoglu <em>et al.</em>, <em>JASN</em>, (2025). <em>“Spatial Transcriptomics Reveals Injured Cells, Signature Genes, and Communication Patterns in the Cyst Microenvironment of Polycystic Kidney Disease.” </em>DOI: 10.1681/ASN.0000000894</li> <li> <p><strong>Format:</strong> <code>AnnData</code> object (~303,791 observations × 12,156 genes)</p> </li> </ul>
Single-nucleus RNA-sequencing reveals oligodendrocytes and their progenitors as vulnerable cell types in prefrontal cortex and anterior cingulate of brains with Parkinson's disease
<p>Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson's disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from post-mortem control and PD brain tissue. We found a dramatic association of oligodendrocytes and oligodendrocyte precursor cells with PD-linked risk loci and reported several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria.</p>
Data from: Cell migration through three-dimensional confining pores: speed accelerations by deformation and recoil of the nucleus
Directional cell migration in dense three-dimensional (3D) environments critically depends upon shape adaptation and is impeded depending on the size and rigidity of the nucleus. Accordingly, the nucleus is primarily understood as a physical obstacle, however, its pro-migratory functions by step-wise deformation and reshaping remain unclear. Using atomic force spectroscopy, time-lapse fluorescence microscopy and shape change analysis tools, we determined nuclear size, deformability, morphology and shape change of HT1080 fibrosarcoma cells expressing the Fucci cell cycle indicator or being pre-treated with chromatin-decondensating agent TSA. We show oscillating peak accelerations during migration through 3D collagen matrices and microdevices that occur during shape reversion of deformed nuclei (recoil), and increase with confinement. During G1 cell cycle phase, nucleus stiffness was increased and yielded further increased speed fluctuations together with sustained cell migration rates in confinement as compared to interphase populations, or to periods of intrinsic nuclear softening in the S/G2 cell cycle phase. Likewise, nuclear softening by pharmacological chromatin decondensation or after lamin A/C depletion reduced peak oscillations in confinement. In conclusion, deformation and recoil of the stiff nucleus contributes to saltatory locomotion in dense tissues.
An integrated single-cell RNA-seq atlas of the mouse hypothalamic paraventricular nucleus links transcriptional and function types
<p>The hypothalamic paraventricular nucleus (PVN) is a highly complex brain region that is crucial for homeostatic<br> regulation through neuroendocrine signalling, outflow of the autonomic nervous system (ANS), and projections<br> to other brain areas. The past years, single-cell datasets of the hypothalamus have contributed immensely<br> to the current understanding of the diverse hypothalamic cellular composition. While the PVN has been<br> adequately classified functionally, its molecular classification is currently still insufficient.</p> <p>To address this, we created a detailed atlas of PVN transcriptional cell types by integrating various PVN<br> single-cell datasets into a recently published hypothalamus single-cell transcriptome atlas. Furthermore, we<br> functionally profiled transcriptional cell types, based on relevant literature, existing retrograde tracing data<br> and existing single-cell data of a PVN-projection target region.</p>
◂Fig. 5 Cells of phylogenetically related strains (light microscopy). a Thecate cell in dorsal view. b Thecate cell in ventral view, note the sulcus extending onto the epitheca (arrow). c Putatively necrotic, thecate cell. d Thecate cell with one bulge on the epitheca (arrow), note that this was the only such cell among thousands of inspected cells. e, f Coccoid cells, apparently without thecae. g Two thecate cells enclosed in the parental theca. h Two connected, immotile cells enclosed in the parental thecae. j Lid of epitheca in dorsal-apical view (mirrored), composed of plates 2′‒4′, all intercalary plates and plates 2′′‒6′′. l‒m Same opened theca in ventral view (l) and dorsal view (m), note the sulcus extending onto the epitheca (arrow), the dorsal opening and all apical and all intercalary plates and plates 3′′‒5′′ remaining with the hypotheca. n Chloroplasts (as inferred from autofluorescence), note the space occupied by the nucleus. Plate labelling follows the Kofoidean notation, n′: apical plate; n′′: precingular plate; n′′′: postcingular plate; na: anterior intercalary plate. Scale= 10 µm in Bumps on the back: An unusual morphology in phylogenetically distinct Peridinium aff. cinctum (= Peridinium tuberosum; Peridiniales, Dinophyceae)
◂Fig. 5 Cells of phylogenetically related strains (light microscopy). a Thecate cell in dorsal view. b Thecate cell in ventral view, note the sulcus extending onto the epitheca (arrow). c Putatively necrotic, thecate cell. d Thecate cell with one bulge on the epitheca (arrow), note that this was the only such cell among thousands of inspected cells. e, f Coccoid cells, apparently without thecae. g Two thecate cells enclosed in the parental theca. h Two connected, immotile cells enclosed in the parental thecae. j Lid of epitheca in dorsal-apical view (mirrored), composed of plates 2′‒4′, all intercalary plates and plates 2′′‒6′′. l‒m Same opened theca in ventral view (l) and dorsal view (m), note the sulcus extending onto the epitheca (arrow), the dorsal opening and all apical and all intercalary plates and plates 3′′‒5′′ remaining with the hypotheca. n Chloroplasts (as inferred from autofluorescence), note the space occupied by the nucleus. Plate labelling follows the Kofoidean notation, n′: apical plate; n′′: precingular plate; n′′′: postcingular plate; na: anterior intercalary plate. Scale= 10 µm
scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data
<p><span>In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, specific evaluation for different contamination levels is lacking. Here, we show that DecontX and CellBender under-correct highly-contaminating genes, while SoupX and scAR over-correct lowly-/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly-contaminating genes while avoiding over-correction of other genes.</span></p>
EvaluatIon of Autologous Nucleus Pulposus Cells (aNPC) in Degenerative Disc Disease
ClinicalTrials.gov study NCT07168603. IPD Sharing: NO. Countries: 0. Publications: 0.
Data from: Cell migration through three-dimensional confining pores: speed accelerations by deformation and recoil of the nucleus
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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.