Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
25,372
datasets available to search
ShareScore release 0.7.1
Dataset results
25,372 results for “Transcriptomics”
Data from: Transcriptomic responses to the consumption of nuptial food gifts by female decorated crickets
<p>Nuptial food gifts offered by males to females at mating are shaped by sexual conflict, allowing males direct access to female physiology. However, a molecular dissection of their effect on females is rare. In decorated crickets, the male's nuptial gift comprises part of<span> the male's spermatophore, the spermatophylax,</span> which functions to deter the female from prematurely removing the sperm-containing portion, the ampulla, from her genital opening. However, ingested spermatophylax compounds and proteins contained in the ampulla could also influence female physiology and behavior to the male's benefit. We investigated how mating per se and these two distinct routes of potential male-mediated manipulation influence the transcriptional response of females. We conducted an RNA-sequencing experiment on the gut and head tissue from females for whom consumption of nuptial food gifts and receipt of an ejaculate had been independently manipulated. In the gut tissue, we found that females not permitted to feed during mating exhibit a decreased expression of many genes, which seems to be caused by reduced gut function, but this was countered by female feeding on the spermatophylax or a sham gift. In the head tissue, we found only low numbers of differentially expressed genes, but a gene co-expression network analysis revealed that both the attachment of the ampulla and the consumption of the spermatophylax independently induce their own distinct patterns of gene expression. This study provides evidence that spermatophylax feeding alters the female post-mating transcriptomic response in decorated crickets, highlighting its potential to mediate sexual conflict in this system.</p>
Transcriptomes of Rotaria rotatoria under thermal stress
<div> <p>Global warming has raised concerns regarding the potential impact on aquatic biosafety and health. To illuminate the adaptive mechanisms of bdelloid rotifers in response to global warming, the ecological and transcriptomic characteristics of two strains (HX and ZJ) of <em>Rotaria rotatoria</em> were investigated at 25°C and 35°C. Our results showed an obvious genetic divergence between the two geographic populations. Thermal stress significantly reduced the average lifespan of <em>R. rotatoria</em> in both strains, but increased the offspring production in the ZJ strain. Furthermore, the expression levels of genes <em>Hsp70 </em>were significantly upregulated in the HX strain, while <em>GSTo1 </em>and <em>Cu/Zn‐SOD</em> were on the contrary. In the ZJ strain, the expression levels of genes <em>Hsp70</em>, <em>CAT2</em>, and <em>GSTo1 </em>were upregulated under thermal stress. Conversely, a significant decrease in the expression level of the <em>Mn‐SOD</em> gene was observed in the ZJ strain under thermal stress. Transcriptomic profiling analysis revealed a total of 105 and 5288 differentially expressed genes (DEGs) in the HX and ZJ strains under thermal stress, respectively. The PCA results showed clear differences in gene expression pattern between HX and ZJ strains under thermal stress. Interestingly, compared to the HX strain, numerous downregulated DEGs in the ZJ strain were enriched into pathways related to metabolism under thermal stress, suggesting that rotifers from the ZJ strain prioritize resource allocation to reproduction by suppressing costly metabolic processes. This finding is consistent with the life table results. This study provides new insights into the adaptive evolution of aquatic animals in the context of global climate change.</p> </div>
Tumor-induced alterations in single-nucleus transcriptome of atrophying muscles
<h3><strong>Experimental Design</strong></h3> <p>Syngeneic C57BL/6 mice injected with Lewis Lung Carcinoma (LLC) cells were sacrificed 16 days after tumor inoculation while they experienced moderate cachexia and loss of muscle mass and function. We investigated single-nucleus transcriptomes of the tibialis anterior (TA) muscle from tumor-bearing mice and their non-tumor-bearing controls.</p> <h3><strong>Protocols</strong></h3> <p>Mice were housed at 22°C and under 50% humidity with 12 hours of light and 12 hours of dark cycles (07:00 – 19:00) and given ad libitum access to a standard rodent chow diet and water in Koc University Animal Research Facility in accordance with institutional policies and animal care ethics guidelines.</p> <p>8-12 weeks old male mice with C57BL/6 background and Lewis lung carcinoma (LLC) cells were used for tumor inoculation. LLC cells were cultured in DMEM (Sigma, no. 5796) with 10% fetal bovine serum (FBS) and penicillin/streptomycin (Invitrogen). 5 million LLC cells were injected subcutaneously over the flank while control mice received PBS only. Muscle tissues were harvested at 16 days after LLC inoculation.</p> <p>TA muscle samples dissected from 6 mice in each group were combined and processed together. Samples were chopped with dissection scissors and placed into a lysis buffer containing 10 mM Tris-HCl, 10 mM NaCl, 3 mM MgCl2, and 0.1% NP40 in nuclease-free water. Samples were homogenized using a douncer and filtered with 70 µm and 40 µm cell strainer. After centrifugation for 5 min at 500 g at 4 °C, supernatant was discarded and nuclei were resuspended and stained with DAPI and subjected to fluorescence activated cell sorting.</p> <p>10X Genomics applications were used following the manufacturer’s guidelines (Chromium Next GEM Single Cell 3ʹ Reagent Kits) to prepare the libraries, which were sequenced using the Illumina HiSeq X system.</p> <h3><strong>Data</strong></h3> <p>Sequencing data was first analyzed and filtered using Cell Ranger (v7.0) Single-Cell Software Suite provided by 10X Genomics. Data was counted and mapped with cellranger count function with --include-introns option for pre-mRNAs (mm10).</p> <p>Further analysis was performed using Seurat (v4.3.0) R (v4.2.2) package on R Studio (v2022.12.0), which filters nuclei, normalizes expression data, and carries out principal component analysis for clustering and Uniform Manifold Approximation and Projection (UMAP) visualization.</p> <h3><strong>Code</strong></h3> <p>You can see the code in R script file.</p>
Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 hours
<p><strong>Aims/hypothesis</strong>: Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycemia, beta cell glucotoxicity, and subsequently type 2 diabetes. In this study, we explored the effects of <em>in vitro</em> hyperglycemic conditions on human pancreatic islet gene expression across 24 hours in six pancreatic cell types: alpha, beta, gamma, delta, ductal, and acinar cells. We hypothesized that genes associated with hyperglycemic conditions may be relevant to the onset and progression of diabetes.</p> <p><strong>Methods</strong>: We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 hours <em>in vitro</em>. To assess the transcriptome, we performed single-cell RNA sequencing (scRNA-seq) at seven time points. We modeled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterized the effect on insulin production and secretion using CRISPR interference to knockdown gene expression in EndoC-βH1 cells, followed by a glucose-stimulated insulin secretion assay.</p> <p><strong>Results</strong>: Across all cell types, we identified 1,447 genes associated with time, 680 genes associated with glucose exposure, and 418 genes associated with interaction effects between time and glucose. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2,449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose, and fasting blood glucose. Of these candidate effector genes, we showed that three—<em>ERO1B</em>, <em>HNRNPA2B1</em>, and <em>RHOBTB3</em>—exhibited an effect on glucose-stimulated insulin secretion and production in EndoC-βH1 cells.</p> <p><strong>Conclusions/interpretation</strong>: The findings of our study provide an in-depth characterization of the 24-hour transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production.</p>
Transcriptomic characterization of 2D and 3D human induced pluripotent stem cell-based in vitro models as New Approach Methodologies for developmental neurotoxicity testing
<p><strong>Abstract:</strong> The safety and developmental neurotoxicity (DNT) potential of chemicals remain critically understudied due to limitations of current in vivo testing guidelines, which are low throughput, resource-intensive, and hindered by species differences that limit their relevance to human health. To address these issues, robust new approach methodologies (NAMs) using deeply characterized cell models are essential. This study presents the comprehensive transcriptomic characterization of two advanced human-induced pluripotent stem cell (hiPSC)-derived models: a 2D adherent and a 3D neurosphere model of human neural progenitor cells (hiNPCs) differentiated up to 21 days. Using high-throughput RNA sequencing, we compared gene expression profiles of 2D and 3D models at three developmental stages (3, 14, and 21 days of differentiation). Both models exhibit maturation towards post-mitotic neurons, with the 3D model maturing faster and showing a higher prevalence of GABAergic neurons, while the 2D model is enriched with glutamatergic neurons. Both models demonstrate broad applicability domains, including excitatory and inhibitory neurons, astrocytes, and key endocrine and especially the understudied cholinergic receptors. Comparison with human fetal brain samples confirms their physiological relevance. This study provides novel in-depth applicability insights into the temporal and dimensional aspects of hiPSC-derived neural models for DNT testing. The complementary use of these two models is highlighted: the 2D model excels in synaptogenesis assessment, while the 3D model is particularly suited for neural network formation as observed as well in previous functional studies with these models. This research marks a significant advancement in developing human-relevant, high-throughput DNT assays for regulatory purposes.</p> <p><strong>This data sets contains:</strong></p> <p><strong>Tab. S1</strong> - Significant genes results</p> <p><strong>Tab. S2</strong> - Enriched pathways_GO_Biological Processes</p> <p><strong>Tab. S3</strong> - Enriched pathways_GO_Cellular Components</p> <p><strong>Tab. S4</strong> - Enriched pathways_GO_Molecular Function</p> <p><strong>Tab. S5</strong> - Enriched pathways_KEGG</p> <p><strong>Tab. S6</strong> - EnrichEnriched pathways_Panther</p> <p><strong>Tab. S7</strong> - Enriched pathways_Reactome</p> <p><strong>Tab. S8</strong> - Gene counts</p> <p><strong>Tab. S9</strong> - Gene selection for targeted analysis</p>
Representation learning for multi-modal spatially resolved transcriptomics data
<p>This folder contains the already unified input used for the models. The raw data is referenced here:</p> <ul> <li>LIBD Human DLPFC dataset is available at <a href="https://github.com/LieberInstitute/HumanPilot">https://github.com/LieberInstitute/HumanPilot</a> and <a href="http://research.libd.org/spatialLIBD" rel="nofollow">http://research.libd.org/spatialLIBD</a>;</li> <li>Human Breast Cancer - Zenodo <a href="https://doi.org/10.5281/zenodo.4739739" rel="nofollow">https://doi.org/10.5281/zenodo.4739739</a>,</li> <li>Human Liver Normal and Cancer - <a href="https://nanostring.com/products/cosmx-spatial-molecular-imager/human-liver-rna-ffpe-dataset/" rel="nofollow">https://nanostring.com/products/cosmx-spatial-molecular-imager/human-liver-rna-ffpe-dataset/</a>.</li> </ul>
Figure 4 in Transcriptomic analysis of Bursaphelenchus xylophilus treated by a potential phytonematicide, punicalagin
Figure 4: (CONtiNUed)
Figure 2 in Transcriptomic analysis of Bursaphelenchus xylophilus treated by a potential phytonematicide, punicalagin
Figure 2: Functional annotation statistics of unigenes.
Figure 1 in Transcriptomic analysis of Bursaphelenchus xylophilus treated by a potential phytonematicide, punicalagin
Figure 1: Sequence length distribution of assembled unigenes.
Figure 2 in Omics in Weed Science: A Perspective from Genomics, Transcriptomics, and Metabolomics Approaches
Figure 2. Workflow of transcript analyses by RNA-Seq and qRT-PCR.
Figure A2 in Transcriptomic analysis of Bursaphelenchus xylophilus treated by a potential phytonematicide, punicalagin
Figure A2: (CONtiNUed)
Resolving single-cell expression profiles by pseudo-temporal integration of transcriptomic and proteomic datasets.
<p>Raw and processed single cell proteomics (scp-MS) and scRNA-Seq data of HEK293-PIP-FUCCI cells which were challanged with hypoxia. The repository contains data for recreating the pseudo-temporal alignment analysis of transcription-translation profiles.</p>
Single-cell transcriptomic analysis of B cells reveals new insights into atypical memory B cells in COVID-19
<p><span>Here, we performed single-cell RNA sequencing of S1 and RBD protein-specific B cells from convalescent COVID-19 patients with different clinical manifestations. This study aimed to evaluate the role and developmental pathway of atypical memory B cells in response to SARS-CoV-2 infection. The results revealed a proinflammatory signature across B cell subsets associated with disease severity, as evidenced by the upregulation of genes such as <em>GADD45B</em>, <em>MAP3K8</em>, and <em>NFKBIA</em> in critical and severe individuals. Furthermore, the analysis of atypical memory B cells suggested a developmental pathway similar to that of conventional memory B cells through germinal centers, as indicated by the expression of several genes involved in germinal center processes, including <em>CXCR4</em>, <em>CXCR5</em>, <em>BCL2</em>, and <em>MYC</em>. Additionally, the upregulation of genes characteristic of the immune response in COVID-19, such as <em>ZFP36</em> and <em>DUSP1</em>, suggested that the differentiation and activation of atypical memory B cells may be influenced by exposure to SARS-CoV-2 and that these genes may contribute to the immune response for COVID-19 recovery. Our study contributes to a better understanding of atypical memory B cells in COVID-19 and the role of other B cell subsets across different clinical manifestations.</span></p>
Spatial transcriptomics defines injury specific microenvironments and cellular interactions in kidney regeneration and disease
<p>This dataset contains raw and processed seqFISH data quantifying 1300 genes within single cells from three Acute Kidney Injury (AKI) and three control mice kidneys. The dataset also contains the codebook and probe sequences used to create probe libraries for the seqFISH experiments.</p> <p><strong>Supplementary_data_tables</strong> folder contains the supplementary data tables for the manuscript: Data_1 contains DE gene expression, Data_2 and Data_3 contain the codebook and probe sequence information needed to generate the probe libraries used for the seqFISH experiments. Data_4 contains the probe sequence information needed to generate the serial probes against <em>Vcam1</em> and <em>Havcr1</em></p> <p><strong>AKI_Ctrl_object.rds</strong> - Seurat object generated from seqFISH data for the AKI and healthy control mice as detailed in the manuscript.</p> <p><strong>Counts_raw.csv </strong>contains raw gene counts for all cells in the dataset.</p> <p><strong>coordinates.csv</strong> contains the xy coordinates (in um) for every cell in the dataset.</p> <p><strong>metadata.csv</strong> contains the metadata for each cell in the dataset including sample and cell type allocation as well as Microenvironment (ME) assignment. This file also contains expression data of <em>Vcam1</em> and <em>Havcr1, </em>which were detected using serial probes as detailed in the manuscript.</p>
Spatial transcriptomics defines injury specific microenvironments and cellular interactions in kidney regeneration and disease
<p>Kidney injury disrupts the intricate renal architecture and triggers limited regeneration, and injury-invoked inflammation and fibrosis. Deciphering molecular pathways and cellular interactions driving these processes is challenging due to the complex renal architecture. Here, we apply single cell spatial transcriptomics to examine ischemia-reperfusion injury in the mouse kidney. Spatial transcriptomics reveals injury-specific and spatially-dependent gene expression patterns in distinct cellular microenvironments within the kidney and predicts <em>Clcf1-Crfl1</em> in a molecular interplay between persistently injured proximal tubule cells and neighboring fibroblasts. Immune cell types play a critical role in organ repair. Spatial analysis reveals cellular microenvironments resembling early tertiary lymphoid structures and identifies associated molecular pathways. Collectively, this study supports a focus on molecular interactions in cellular microenvironments to enhance understanding of injury, repair and disease.</p>
Single-molecule dynamics and genome-wide transcriptomics reveal that NF-kB (p65)-DNA binding times can be decoupled from transcriptional activation
<p>Data and analysis code repository for: </p> <p>Single-molecule dynamics and genome-wide transcriptomics reveal that NF-kB (p65)-DNA binding times can be decoupled from transcriptional activation</p> <p>https://doi.org/10.1101/255380</p>
Data and script for Laass et. al "Characterization of the transcriptome of Haloferax volcanii with mixed RNA-Seq"
<p>Data and script to accompany the manuscript "Characterization of the transcriptome of Haloferax volcanii with mixed RNA-Seq".</p>
Dendrobates auratus skin transcriptome
<p>A skin transcriptome from the Neotropical poison frog Dendrobates auratus. Data accompanies a forthcoming manuscript.</p>
Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries
<p>Processed data files for manuscript: "Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries" <a href="https://doi.org/10.1093/nar/gky1204">https://doi.org/10.1093/nar/gky1204</a> . Scripts for generating figures are found here: https://github.com/rnabioco/scrna-subsets</p>
The Cortical Synaptic Transcriptome is Organized by Clocks, but its Proteome is Driven by Sleep
<p>Images, ROIs and databases with the results of Particle analysis from RNA in situ hybridization performed with the RNA scope technology onto CA1 and cortex from mice collected at 6 different times of day .</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.