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15,738 results for “stem cell”
Characterization of a loss-offunction NSF attachment protein beta mutation in monozygotic triplets affected with epilepsy and autism using cortical neurons from proband-derived and CRISPR-corrected induced pluripotent stem cell lines
<p>RNA-seq data of matured cortical neurons (8-weeks old) derived from the induced pluripoent stem cells (iPSC) of control parents (CtrlF and CtrlM) and corrected proband. There are three replicates (Rep1, Rep2, Rep3) for each sample with Forwad read (R1_001.fastq.gz)</p> <p>CtrlF: Control Father sample</p> <p>CtrlM: Control mother sample</p> <p>NDD_01_Corr_Het: Heterozygous correction of NAPB mutation (c.354+2T>G) in NDD_01 proband</p> <p>NDD_05_Corr_Hom: Homozygous correction of NAPB mutation (c.354+2T>G) in NDD_05 proband</p>
Dataset for a publication: "PLLA honeycombs activated by plasma and high energy excimer laser for stem cell support"
<p>The dataset accompanies the article <em>"PLLA Honeycombs Activated by Plasma and High-Energy Excimer Laser for Stem Cell Support."</em> It is organized into several subfolders, each corresponding to a different analytical method used in the study, with data presented in the manuscript. The main folder is structured as follows:</p> <ol> <li><strong>AFM</strong></li> <li><strong>Contact Angle</strong></li> <li><strong>Zeta Potential</strong></li> <li><strong>SEM</strong></li> <li><strong>EDS</strong></li> <li><strong>XPS</strong></li> <li><strong>Cytocompatibility</strong></li> </ol> <p>Each subfolder contains the relevant data associated with the specific analysis.</p> <p> </p> <p>For more details, please read the <strong>README - Description of data and analysis informations_PS.txt</strong> file.</p> <p> </p> <p><strong> </strong></p> <p><strong>Dataset versions:</strong></p> <p>There are no newer versions so far.</p>
Efficient embryoid-based method to improve generation of optic vesicles from human induced pluripotent stem cells data
<p>Animal models have provided many insights into ocular development and disease, but they remain suboptimal for understanding human oculogenesis. Eye development requires spatiotemporal gene expression patterns and disease phenotypes can differ significantly between humans and animal models, with patient-associated mutations causing embryonic lethality reported in some animal models. The emergence of human induced pluripotent stem cell (hiPSC) technology has provided a new resource for dissecting the complex nature of early eye morphogenesis through the generation of three-dimensional (3D) cellular models. By using patient-specific hiPSCs to generate <em>in vitro </em>optic vesicle-like models, we can enhance the understanding of early developmental eye disorders and provide a pre-clinical platform for disease modelling and therapeutics testing. A major challenge of <em>in vitro </em>optic vesicle generation is the low efficiency of differentiation in 3D cultures. To address this, we adapted a previously published protocol of retinal organoid differentiation to improve embryoid body formation using a microwell plate. Established morphology, upregulated transcript levels of known early eye-field transcription factors and protein expression of standard retinal progenitor markers confirmed the optic vesicle/presumptive optic cup identity of <em>in vitro </em>models between day 20 and 50 of culture. This adapted protocol is relevant to researchers seeking a physiologically relevant model of early human ocular development and disease with a view to replacing animal models.</p>
Human-mouse syntenic Long Range Interactions in Neural Stem Cells
<p>This repository contains the list of human DNA regions corresponding to long-range interactions in RNA polII-mediated long-range interactions in mouse. They are named human-mouse syntenic Long Range Interactions (hmsLRI) and were obtained via synteny from mouse neonatal forebrain stem cells. They were also annotated for their overlap with DNA sequence variants (SNPs; CNVs) associated with human neurodevelopmental disease (NDD). The lists of genes identified via inferred that are potentially involved in NDD, eye-development, and traits (schizophrenia, bipolar disorder, intelligence).</p> <p>This is a resource for exploring the potential of the non-coding regions of DNA, the largest part of the genome (~98%), in NDD. Indeed, despite the numerous NDD-causative genes identified, only 42% of patients with severe developmental disorders carry pathogenic <em>de novo</em> mutations within coding sequences. More than a half of patient could be diagnosed and treated with further research and technologies, one option is studying the non-coding genome and how alterations affect genes. </p> <p>Tracks for visualization onto UCSC Genome Browser and WashU, are also provided.<br> See README for more details. </p> <p>The peer-reviewed publication for this dataset has now been published in International Journal of Molecular Science, available OA at: <a href="https://www.mdpi.com/1422-0067/23/14/7964">https://www.mdpi.com/1422-0067/23/14/7964</a>. Please cite this when using the dataset.</p>
Generation of beta-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids
<p>This repository contains single-cell RNA-sequencing data files (raw FASTQ files generated from Illumina HiSeq sequencing) related to the article entitled "Generation of beta-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids" by Lisa Morisseau et al. (2023) published in the Molecular Omics journal (DOI: 10.1039/d3mo00050h).</p> <p> </p>
Dataset related to article "TNF-Stimulated Gene-6 Is a Key Regulator in Switching Stemness and Biological Properties of Mesenchymal Stem Cells."
<p>Mesenchymal stem cells (MSCs) are well established to have promising therapeutic properties. TNF-stimulated gene-6 (TSG-6), a potent tissue-protective and anti-inflammatory factor, has been demonstrated to be responsible for a significant part of the tissue-protecting properties mediated by MSCs. Nevertheless, current knowledge about the biological function of TSG-6 in MSCs is limited. Here, we demonstrated that TSG-6 is a crucial factor that influences many functional properties of MSCs. The transcriptomic sequencing analysis of wild-type (WT) and TSG-6<sup>-/-</sup> -MSCs shows that the loss of TSG-6 expression leads to the perturbation of several transcription factors, cytokines, and other key biological pathways. TSG-6<sup>-/-</sup> -MSCs appeared morphologically different with dissimilar cytoskeleton organization, significantly reduced size of extracellular vesicles, decreased cell proliferative rate, and loss of differentiation abilities compared with the WT cells. These cellular effects may be due to TSG-6-mediated changes in the extracellular matrix (ECM) environment. The supplementation of ECM with exogenous TSG-6, in fact, rescued cell proliferation and changes in morphology. Importantly, TSG-6-deficient MSCs displayed an increased capacity to release interleukin-6 conferring pro-inflammatory and pro-tumorigenic properties to the MSCs. Overall, our data provide strong evidence that TSG-6 is crucial for the maintenance of stemness and other biological properties of murine MSCs.</p> <p> </p> <p>Some dataset of this research are in prism format, to ensure open access we attach a pdf instruction about this format and a link where downoladed it</p>
Lactate Increases Stemness of CD8+ T Cells to Augment Anti-Tumor Immunity
<p>The immunological role of lactate in antitumor immunity is not well understood. In this study, we report lactate treatment significantly augments antitumor efficacy of immune checkpoint blockade or T cell vaccine therapy in multiple tumor models. Single cell transcriptomics and flow cytometry analysis revealed an increased subpopulation of stem-like TCF-1-expressing CD8<sup>+</sup> T cells upon lactate treatment.</p>
GFP-GOWT1 mouse stem cells TIFF file
<p>This is accompanying file to the CellMAPtracer software (<a href="https://doi.org/10.5281/zenodo.3878087">https://doi.org/10.5281/zenodo.3878087</a>).</p>
Cryo-4D-STEM datasets on cells and cellular organelles for demonstrating a dose-Efficient cryo-EM technique: tilt-Corrected Scanning Transmission Electron Microscopy
<p>This upload contains three 4D-STEM datasets in .raw format for demonstrating a dose-efficient cryo-EM technique for thick samples: tilt-corrected Scanning Transmission Electron Microscopy (tcBF-STEM). The dataset dimension is 128130256*256. Data were acquired on vitrified intact E.coli cells and isolated human cell organelles. This upload also contains the EFTEM images in .mrc acqired in the same ROI as the 4D-STEM dataset. </p> <p>It also contains analysis of the manuscript's Fig 3 and Ext. data fig 8. </p>
Underlying and Extended Data for Refined and benchmarked homemade media for cost-effective, weekend-free human pluripotent stem cell culture
<p>Extended Data and raw data for the manuscript "Refined home-brew media for cost-effective, weekend-free hiPSC culture and genetic engineering"</p> <p> </p> <p dir="ltr">Extended Data 1.zip - protocol for preparation of the supplement for hE8 and B8+ media</p> <p dir="ltr">Extended Data 2.zip - Gene counts, supporting files, and output results of bulk analyses</p> <p dir="ltr">Extended Data 3.zip - Images of iPS cells adapted to cE8, hE8 and B8+ taken 24, 48 and 72 hours after passage. Contains raw .tiff files for each image and a .pdf with a compiled figure</p> <p dir="ltr">Extended Data 4.zip - Results of miloR analysis on the differences in the distribution of cells adapted to cE8, hE8 and B8+ to assigned monocle clusters </p> <p dir="ltr">Manuscript Data.zip – Raw data underlying the Figures 1, 2, 4, 5, 6 and 7.</p> <p>Bulk_RNA_seq_archive – archived source code used for generating results in Figure 3</p>
Single-cell sequencing data of human umbilical cord and placental mesenchymal stem cells
<p>Expression matrix of umbilical cord and placenta single-cell sequencing data from the same donor.Table1 is the umbilical cord and Table2 is the placenta.</p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 4 relative to Figure 7 – ArhGEF11 CRISPR interference
<p><span>Raw image files (TIFF format), corresponding 2D-cartographies (_2Dmap.tiff files) and metadata files for 2D-cartographies (.xml files, readable with the opensource software Icy), relative to <strong>Figure 7B </strong>and<strong> Figure 7 - Figure Supplement 6</strong> (see <strong>Materials and Methods — Morphological and morphometric analysis of aortic and hemogenic cells</strong>).</span></p> <p><span>The source data comprises for each 48 - 55 hpf <em>Tg(kdrl:eGFP-JAM3b; kdrl:nls-mKate2)</em> zebrafish embryo 3 z-stack and 2D cartographies (segments 1 to 3) encompassing the whole length of the aorta, for control condition (n = 2 individuals) and morpholino splicing interference condition (n = 2 individuals). For z-stacks of both control and morphant conditions, two fluorescence channels were acquired, corresponding to the nuclear mKate2 expressed in endothelial cells and the eGFP-JAMs signal localized at the intercellular junctions of endothelial cells. Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.3 µm. 2D-cartographies were obtained using the Icy plugin “TubeSkinner”, and the semi-manual segmentation of all aortic cells can be uploaded from the corresponding metadata file on the 2D-cartographies using the load ROI function of Icy.</span></p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 3 relative to Figure 7 – ArhGEF11 morpholino splicing interference
<p><span>Raw image files (TIFF format), corresponding 2D-cartographies (_2Dmap.tiff files) and metadata files for 2D-cartographies (.xml files, readable with the opensource software Icy), relative to <strong>Figure 7A </strong>and<strong> Figure 7 - Figure Supplement 5</strong> (see <strong>Materials and Methods — Morphological and morphometric analysis of aortic and hemogenic cells</strong>).</span></p> <p><span>The source data comprises for each 48 - 55 hpf <em>Tg(kdrl:eGFP-JAM2a; kdrl:nls-mKate2)</em> zebrafish embryo 3 z-stack and 2D cartographies (segments 1 to 3) encompassing the whole length of the aorta, for control condition (n = 2 individuals) and morpholino splicing interference condition (n = 3 individuals). For z-stacks of both control and morphant conditions, two fluorescence channels were acquired, corresponding to the nuclear mKate2 expressed in endothelial cells and the eGFP-JAMs signal localized at the intercellular junctions of endothelial cells. Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.3 µm. 2D-cartographies were obtained using the Icy plugin “TubeSkinner”, and the semi-manual segmentation of all aortic cells can be uploaded from the corresponding metadata file on the 2D-cartographies using the load ROI function of Icy.</span></p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 1 relative to Figure 3
<p><span>Raw image files (TIFF format) relative <strong>to Figure 3</strong> (see <strong>Materials and Methods — Dt-runx1 phenotype analysis – cell count</strong>).</span></p> <p><span>The source data comprises for each 52 - 55 hpf zebrafish embryo 3 z-stack (segments 1 to 3) encompassing the whole length of the aorta, for control condition (<em>Tg(Kdrl:Gal4;UAS:RFP), </em>n = 3 individuals) and mutant condition (<em>Tg(kdrl:Gal4;UAS:RFP;4xNR:dt-runx1-eGFP), </em>n = 7 individuals). For control condition, one fluorescence channel was acquired, corresponding to the cytoplasmic RFP expressed in endothelial cells. For mutant condition, two fluorescence channels were acquired, corresponding first to the cytoplasmic RFP expressed in endothelial cells using the same reporter as for the control condition, and second the cleaved cytoplasmic GFP reporting the expression of our dt-runx1 mutant construct in endothelial cells. Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.3 µm.</span></p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 2 relative to Figure 4
<p><span>Raw image files (TIFF format) and segmented 3D images (.ims, Imaris proprietary files) relative to <strong>Figure 4</strong> and <strong>Figure 4 Figure Supplement 3</strong> (see <strong>Materials and Methods — RNAscope image analysis – Pard3</strong>).</span></p> <p><span>The source data comprises for each 52 - 55 hpf zebrafish embryos 2 z-stack (segments 1 to 2) encompassing the whole length of the aorta, for control condition (<em>Tg(Kdrl:eGFP), </em>n = 7 individuals) and mutant condition (<em>Tg(kdrl:Gal4; 4xNR:dt-runx1-eGFP), </em>n = 12 individuals). For both control and mutant conditions, two fluorescence channels are displayed, corresponding to the cytoplasmic GFP expressed in endothelial cells (in green) and the RNAscope signal (OPAL-570, in magenta). Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.4 µm. The .ims files contain the 3D rendering of the z-stacks as well as the segmentations of Pard3ba mRNA RNAscope spots (in magenta), in the aorta (Spots 1 Selection) or outside (Spots 1), as well as the segmentation of endothelial cells (green) (Cells 1) and hemogenic endothelial cells (Cells 1 Cell export).</span></p>
GC-MS raw data_Figure 6E_Lysophosphatidic Acid Shifts Metabolic and Transcriptional Landscapes to Induce a Distinct Cellular State in Human Pluripotent Stem Cells
<p><strong>Sample name</strong></p> <p>hESCs (H1 cells) were given treatments for two days and then collected for GC-MS analysis.</p> <p>E8: E8 medium</p> <p>AX: E8 + 1.6% AlbuMAX;</p> <p>BSA: E8 + 1% albumin;</p> <p>BSA+hCDL: E8 + 1% albumin + 0.1% hCDL;</p> <p>LPA+BSA: E8 + 1 μM LPA + 1% albumin;</p> <p>LPA+BSA+hCDL: E8 + 1 μM LPA + 1% albumin + 0.1% hCDL</p> <p>STD: standard lipids mixture used as reference</p> <p><strong>Extraction and Methylation</strong></p> <p>Sample preparation was conducted according to the previously reported method (Araujo et al., 2008) with the modification. Briefly, spent medium was removed, and cells were rinsed with 1 mL/well 0.9% (w/v) saline twice. Then 0.5 mL/well -80°C 80% methanol was added to quench the metabolism. Five wells of cells (from 6-well plate) were scrapped off into a glass screw-cap tube. Then 4 mL heptadecanoate containing chloroform (4 μg/mL, internal standard for fatty acids) was added into the tube. Vortex, and then centrifuge at 2000 rpm for 5 min. Cellular debris was carefully removed, and nitrogen blow the solution till dry. Add 1.5 mL hexane and 1.5 mL 14% boron trifluoride (BF<sub>3</sub>)/methanol solution. Seal the tube with nitrogen gas, heat it at 100°C for 1 h using MK200-2 dry bath incubator (Aosheng), and then cool down to room temperature. Add 1 mL water into the tube, vortex and then centrifuge at 3000 rpm for 10 min. The upper layer was transferred into a new 1.5-mL eppendorf tube and evaporated by nitrogen gas. The residue was re-dissolved in 100 μL hexane for GC-MS analysis.</p> <p><strong>GC-MS method</strong></p> <p>Samples were analyzed using an Agilent GC-MS system (Agilent) consisting of a 6890 gas chromatography and a 5973 mass spectrometer. Fatty acid methyl esters were separated by an Omegawax™ 250 fused silica capillary column (30 m × 0.25 mm i.d., 0.25 μm film thickness, Supelco, Bellefonte, PA). The optimized oven temperature program was: initial temperature set at 180°C and held for 3 min; ramped to 206°C at 2°C/min and held at 206°C for 25 min, then, ramped to 240°C at 10°C/min and held for 5 min. Overall, the total run time was 50 min. Carrier gas was high-purity helium at a flow rate of 1.5 mL/min. Injector temperature was set at 250°C. Injection volume was 2 μL with a split ratio of 1:15. The mass spectrometer was operated in electron-impact (EI) mode at 70 eV ionization energy. The temperatures of quadrupole and ionization source were set at 150°C and 280°C, respectively. The spectra from 3 to 50 min were acquired with the <em>m/z</em> range of 35–550 at a scan rate of 0.34 s per scan.</p>
LC-MS raw data_Lysophosphatidic Acid Shifts Metabolic and Transcriptional Landscapes to Induce a Distinct Cellular State in Human Pluripotent Stem Cells
<p><strong>LC-MS/MS analysis</strong></p> <p><strong>Metabolite extraction</strong></p> <p>For LC-MS/MS quantification, cell sample preparation was conducted as described in the previous literatures (Ying, Kimmelman et al. 2012, Zhang, Badur et al. 2016). Briefly, the spent medium was removed, and cells were rinsed with 1 mL/well 0.9% (w/v) saline twice. Then 0.5 mL/well -80°C 0.2 μg/mL norvaline containing 80% methanol was added to quench the metabolism. Cells were scraped off into 1.5-mL eppendorf tube and stored in -80℃ overnight. The mixtures were vortexed and then centrifuged 12500 × <em>g </em>for 15 min at 4℃. The supernatant was used for LC-MS analysis.</p> <p><strong>LC-MS/MS method</strong></p> <p>Waters Xevo TQD coupled with Waters Acquity UPLC system was used for quantification. Acquity UPLC BEH HILIC column (2.1 × 100 mm, 1.7 μm), Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm), and Acquity UPLC BEH amide column (2.1 × 100 mm, 1.7 μm) were used for the separation of metabolites. Column temperature was set at 40 °C.</p> <p>For the quantification of norvaline, amino acids, GSH, GSSG, SAH, SAM, ascorbic acid and myo-inositol, amide column was used for the separation. Acetonitrile with 0.1% formic acid (A) and water with 0.1% formic acid (B) were used as mobile phases. The gradient setting is: 0-4 min, 99% A to 90% A; 4-10 min, 90% A to 67% A; 10-13 min, 67% A to 1% A; 13-15 min, 1% A; 15-16.5 min, 1% A to 99% A; 16.5-20 min, 99% A. Flowrate was set as 0.4 mL/min.</p> <p>For the quantification of metabolites involved in TCA cycle, energy related and ribonucleotides, an amide column was used for the separation. Acetonitrile with 0.1% formic acid (A) and water with 0.1% formic acid (B) were used as mobile phases. The gradient setting is: 0-2 min, 80% A; 2-3 min, 80% A to 20% A; 3-5 min, 20% A; 5-6 min, 20% A to 80% A; 6-10 min, 80% A. Flowrate was set as 0.4 mL/min.</p> <p>For the quantification of acetate, acetyl-CoA and metabolites involved in glycolysis and pentose phosphate pathway, HILIC column was used for the separation. Acetonitrile (A) and 10 mM ammonium bicarbonate were used as mobile phases. The gradient setting is: 0-2 min, 10% A; 2-5 min, 10% A to 5% A; 5-6 min, 5% A to 10% A; 6-10 min, 10% A. Flowrate was set as 0.2 mL/min.</p> <p>For the quantification of LPA, LPC and PC, HILIC column was used for the separation. Acetonitrile (A) and 10 mM ammonium bicarbonate aqueous solution (B) were used as mobile phases. The gradient setting is: 0-2 min, 95% A; 2-4 min, 95% A to 10% A; 4-7 min, 10% A; 7-9 min, 10% A to 95% A; 9-15 min, 95% A. Flowrate was set as 0.2 mL/min.</p> <p>For the quantification of CDL lipids, C18 column was used for the separation. 98% Acetonitrile aqueous solution (A) and 10 mM ammonium acetate 90% acetonitrile aqueous solution (B) were used as mobile phases. The gradient setting is: 0-5 min, 0.1% A; 5-6 min, 0.1% A to 99.9% A; 6-11 min, 99.9% A; 11-12 min, 99.9% A to 0.1% A; 12-15 min, 0.1% A. Flowrate was set as 0.4 mL/min.</p> <p>Argon was used as source gas, capillary voltage was 3500 V, and desolvation temperature was 500 °C. Multiple reaction monitoring (MRM) was conducted, and the ion transitions are listed in the supplemental Table S2. Selected ion recording (SIR) was conducted for the detection of CDL-related lipids, and the setting is listed in the supplemental Table S3.</p> <p>Standard solutions of TCA metabolites (100 μg/mL) and intermediates of glycolysis and pentose phosphate pathway (10 μg/mL) were prepared to confirm the retention time. Peak intensity of product ion was used for the quantification. Data analysis was performed by TargetLynx software (Waters) with statistical analysis in Graphpad Prism (version 8.4.0) and R.</p>
Stem cell hierarchies and developmental origins of rhabdomyosarcoma
<p>Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma of childhood and is comprised of two major molecular subtypes. Despite sharing features with skeletal muscle, the conservation of underlying cellular hierarchy with human muscle development and the identification of molecularly-defined tumor-propagating cells have not been reported. Using single-cell RNA sequencing of patient-derived RMS, DNA-barcode cell fate mapping, and antibody enrichment and functional stem cell assays using <em>in vitro</em> culture and mouse xenografts, we have uncovered tumor cell hierarchies in Fusion-negative (FN-) RMS that are shared with normal human muscle development. We also identified common developmental stages at which tumor cells become arrested. FN-RMS resemble early muscle found in embryonic and larval development, while fusion-positive (FP-)RMS express a highly specific developmental gene program found in muscle cells transiting from embryonic to fetal development at 7-7.75 weeks of age. FP-RMS also have neural-pathway enriched cell states, suggesting less-rigid adherence to muscle development hierarchies in this disease. Finally, we identify a molecularly-defined tumor-propagating cell in FN-RMS that shares remarkable similarity to the newly described bi-potent, muscle mesenchyme stem/progenitor cell that makes both muscle and osteogenic cells.</p>
Gene expression counts from induced Pluripotent Stem Cells
<p><strong>File description:</strong></p> <ol> <li> <p>Gene-level counts using the gtf file from the release 34 of GENCODE <a href="https://www.gencodegenes.org/human/release_34">https://www.gencodegenes.org/human/release_34</a></p> </li> <li> <p>Split counts spanning from one exon to another using an annotation-free algorithm, therefore capturing new splice sites</p> </li> <li> <p>Non-split counts covering exon-intron boundaries</p> </li> <li> <p>Sample annotation describing each sample from the dataset</p> </li> <li> <p>Description file with global information from the dataset</p> </li> </ol> <p><strong>Use: </strong>The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, the workflow DROP can be used to compute expression and splicing outliers (<a href="https://github.com/gagneurlab/drop">https://github.com/gagneurlab/drop</a>).</p> <p><strong>Maintainer: </strong>Vicente A. Yépez, <a href="mailto:yepez@in.tum.de">yepez@in.tum.de</a></p> <p><strong>URL:</strong> <a href="https://github.com/gagneurlab/drop/">https://github.com/gagneurlab/drop/</a></p> <p> </p> <p><strong>Title: </strong>induced Pluripotent Stem Cells<br> <strong>Number of samples:</strong> 330<br> <strong>Tissue:</strong> iPSCs<br> <strong>Organism:</strong> Homo sapiens<br> <strong>Genome assembly:</strong> hg19<br> <strong>Gene annotation:</strong> gencode34<br> <strong>Disease:</strong> None<br> <strong>Strand specific:</strong> True<br> <strong>Paired end:</strong> True<br> <strong>Dataset contact:</strong> Marc Bonder, marcj89 at gmail.com</p> <p><strong>Citation:</strong> Cite both the resource using Zenodo's citation and the publication under References</p>
Establishment of a Spermatogonial Stem Cell Line with Potential of Meiosis in a Hermaphroditic Fish, Epinephelus coioides
<p>Figure S1. Cell localization of ly75, thy1, and dmc1 in adult testis of orange-spotted grouper. (A-C) Antisense probe signals of ly75, thy1, and dmc1. (D-F) Sense probe signals of ly75, thy1, and dmc1. Sg, Spermatogonium; Sc, Spermatocyte; St, spermatid. Scale Bars: 20 μm.</p> <p>Figure S2. Fluorescent immunostaining of antibodies in adult testis of orange-spotted grouper. (A-D and M-O) Fluorescence signals of Piwi, Dazl, Ssea1, Nanog, PCNA, Sycp3, and Dmc1. (E-H and P-R) Nuclei are counterstained with PI. (I-L and S-U) Merge images. Sg, Spermatogonium; Sc, Spermatocyte; St, spermatid; Sz, spermatozoa. Scale Bars: 20 μm.</p> <p>Figure S3. Derivation of a single colony from a single cell of GPT line. (A) A small colony after five days of culture. (B) A distinct colony after 10 days of culture. (C) A large colony containing hundreds of cells after 20 days of culture. Scale Bars: 20 μm in A; 50 μm in B; 200 μm in C.</p> <p>Figure S4. Prolonged cultivation of GPT cells under the lack of bFGF. (A-D) All GPT cells would differentiate into large epithelial-like cells and gradually die out during 25 days of culture under the lack of bFGF, LIF, and SCF (-/-). (E-H, J-M, and O-R) GPT cells consisted of some polygonal-like cells and many epithelial-like cells during 25 days of culture in the ESM media containing SCF and/or LIF. (I, N and S) All GPT cells transformed into very large epithelial-like cells and gradually died after 35 days of culture in the ESM media containing SCF and/or LIF. Scale Bars: 50 μm.</p> <p>Figure S5. Morphology of GPT cells under a condition of high cell confluence. (A) GPT cells were cultured for 14 days without subculture and (B) generated a few spherical cells (Arrows). Scale Bars: 50 μm in A; 20 μm in B.</p> <p>Figure S6. Establishment of a GPT cell line stably expressing green fluorescence protein. (A-C) Bright-field image, fluorescent image, and merged image of GPT cells after 48 hours of culture following electrotransfection with pEGFP-N3 plasmid. (D-F) Bright-field image, fluorescent image, and merged image of GPT cells after G418 resistance screening. Scale Bars: 200 μm in A-C; 100 μm in D-F.</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.