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25,372 results for “Transcriptomics”
Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in African American and European American patients with TNBC (Spatial Transcriptomic 10X Visium portion)
<p>Racial disparities in triple-negative breast cancer (TNBC) outcomes have been reported. However, the biological mechanisms underlying these disparities remain unclear. We integrated imaging mass cytometry and spatial transcriptomics, to characterize the tumor microenvironment (TME) of African American (AA) and European American (EA) patients with TNBC. The TME in AA patients was characterized by interactions between endothelial cells, macrophages, and mesenchymal-like cells, which were associated with poor patient survival. In contrast, the EA TNBC-associated niche is enriched in T-cells and neutrophils suggestive of an exhaustion and suppression of otherwise active T cell responses. Ligand-receptor and pathway analyses of race-associated niches found AA TNBC to be “immune cold” and hence immunotherapy resistant tumors, and EA TNBC as ‘inflamed’ tumors that evolved a distinctive immunosuppressive mechanism. Our study revealed the presence of racially distinct tumor-promoting and immunosuppressive microenvironments in AA and EA patients with TNBC, which may explain the poor clinical outcomes.</p> <p> </p> <p>This dataset contains the 10X Visium Spatial Transcriptomic data of TNBC patients. There are two cohorts.</p> <p> </p> <p><strong>Baylor Scott and White (BSW) cohort</strong>: <strong>10x.visium.tar.gz</strong>, containing 10 patients with TNBC from Baylor Scott and White affiliated Hospital. </p> <p>Each sample is made of Space Ranger processed spot-separated gene expression data (processed to HDF5 AnnData file). There are also H&E images, and spot coordinate files available. </p> <p> </p> <p>For <strong>Georgia validation cohort</strong>, 400 genes used for validation of ESG signatures (associated with BA-Community 1 and WA-Community-1) were obtained and provided by Ritu Aneja's lab. These 400 genes' spot-based expression data across Black and White TNBC patients are provided. See file <strong>georgia.validation.visium.tar.gz</strong>. Expression was normalized by total counts per spot, followed by log-normalization by Giotto.</p> <p> </p> <p>As well in our paper, we integrated a published racial TNBC cohort for deriving some of initial results in the paper. This refers to the Bassiouni et al (Cancer Research) paper in Carpten's group. <strong>GSM_giotto_processed.tar.gz</strong> refers to this dataset, which we deposit here. The data were normalized by Giotto using standard procedure.</p>
Supplementary tables for publication "A reference-free algorithm discovers regulation in the plant transcriptome"
<p>Supplementary tables for publication "A reference-free algorithm discovers regulation in the plant transcriptome" (doi: https://doi.org/10.1101/2024.05.23.595613)</p> <p>Table A: complete list of significant anchors and associated genes from analysis of sorghum dataset</p> <p>Table B: complete list of significant anchors and associated genes from analysis of maize dataset</p> <p>Table C: complete list of significant anchors and associated genes from analysis of Arabidopsis P/Fe dataset</p> <p>Table D: complete list of significant anchors and associated genes from analysis of Arabidopsis FLOE1 dataset</p> <p>arabidopsis_floe1_ALL_anchors_satc_truncated.txt: data from the Arabidopsis FLOE1 dataset used to generate figures in the paper. Columns are sample ID, anchor, target, and counts of that anchor/target combination in that particular sample. </p> <p>arabidopsis_pfe_ALL_anchors_satc_truncated.txt: data from the Arabidopsis P/Fe dataset used to generate figures in the paper. Columns are sample ID, anchor, target, and counts of that anchor/target combination in that particular sample. </p> <p>maize_pollen_ALL_anchors_satc_truncated.txt: data from the maize dataset used to generate figures in the paper. Columns are sample ID, anchor, target, and counts of that anchor/target combination in that particular sample. </p> <p>sorghum_drought_ALL_anchors_satc_truncated.txt: data from the sorghum dataset used to generate figures in the paper. Columns are sample ID, anchor, target, and counts of that anchor/target combination in that particular sample.</p> <p>cryptic_splicing_anchors.tsv: list of anchors described in Supplementary Information section of the article that are examples of cryptic splicing. Columns are dataset name, gene name/ID, anchor sequence, target 1 sequence, and target 2 sequence. </p>
Human pan-body age- and sex-specific molecular phenomena inferred from public transcriptome data using machine learning - Data
<p>Expression data used in manuscript <i>Human pan-body age- and sex-specific molecular phenomena inferred from public transcriptome data using machine learning</i></p>
Kellet's whelk genome and transcriptome assembly
<p>Understanding genomic characteristics of non-model organisms can help bridge gaps in ecology and evolutionary sciences, but lack of a reference genome and transcriptome for these species challenges their study. We advance this goal by conducting the first full genome and transcriptome sequence assembly and analysis of the non-model organism Kellet's whelk, <em>Kelletia kelletii</em>, a marine gastropod and fisheries species exhibiting a northern range expansion along the US west coast that is potentially driven by climate change. We used a combination of Oxford Nanopore Technologies, PacBio, and Illumina platforms for sequencing, and integrated a set of bioinformatic pipelines to create a comprehensive and contiguous de novo genome assembly. Our results represent the most complete and continuous documented genome among the <em>Buccinoidea</em> superfamily to date. Genome validation revealed its relatively high completeness with low missing metazoan BUSCOs, and an average coverage of ~70x for all contigs, indicating a robust assembly. Characteristics of the <em>K. kelletii</em> genome showed that short-read data contributed significantly to genome coverage and accuracy; however, long-read data was imperative to the completeness and continuity of the genome assembly. Genome annotation identified a large number of protein-coding genes compared to other closely related species, suggesting the presence of a complex genome structure. We conducted the transcriptome assembly and analysis of individuals during their period of peak embryonic development, and revealed highly expressed genes associated with specific GO terms and metabolic pathways, most notably lipid, carbohydrate, glycan, and phospholipid metabolism. We also identified numerous heat shock proteins (HSPs) in the transcriptome and genome with a potential association between the transcriptional expansion of HSP families and the marine environment experienced by the sessile life history stage of the developing embryo. This study offers a valuable reference genome and transcriptome for conducting comprehensive bioinformatic analyses of the non-model organism <em>K. kelletii</em>. Such resources will enhance our understanding of its ecology and evolution, as well as that of other coastal marine species facing environmental changes.</p>
Supplementary File 7 from: Rapier-Sharman N et. al., Secondary Transcriptomic Analysis of Triple-Negative Breast Cancer Reveals Reliable Universal and Subtype-Specific Mechanistic Markers, 2024
<p>Supplementary Materials File 7. Please note that though the order of the supplementary materials has changed since initial upload (File S7 was previously File S9 or S10), the contents of this zipped folder remain the same.</p>
Molecular features of luminal breast cancer defined through spatial and single-cell transcriptomics (codes and data files)
<p>This dataset includes all the relevant codes and data files associated with the paper ("Molecular features of luminal breast cancer defined through spatial and single-cell transcriptomics") in Clinical and Translational Medicine journal.</p>
Transcriptomic signatures induced by the herbicide bentazone and pharmaceutical atorvastatin in Myriophyllum spicatum
<p>Within this study, the non-model organism Myriophyllum spicatum was used to evaluate ecotoxic modes of action at the gene expression level. M. spicatum was exposed to low-effect concentrations of bentazone and atorvastatin in a shortened and modified version of the OECD guideline test No. 239, followed by RNA extraction of the shoot tip tissue and a subsequent RNA-seq analysis utilizing a de novo assembly of the transcriptome. While the herbicide bentazone is an inhibitor of photosynthesis, the widely spread pharmaceutical atorvastatin acts as an inhibitor of the hydroxymethylglutaryl-CoA reductase and thus the isoprenoid biosynthesis. The aim of this study was to determine molecular fingerprints and biomarkers distinguishing these distinct modes of action at a molecular level.</p>
Analysis of 3,760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes
<p>Abnormal gene expression and splicing play a key role in hematologic malignancy. Here, we provide a catalog of transcriptomic and genomic aberrations of 3,760 hematologic malignancy samples spanning 24 disease entities. This version contains 19,732 protein-coding genes from GRCh37 annotated by Gencode (v33b).</p> <p>doi: <a href="https://doi.org/10.1101/2023.08.08.23293420">https://doi.org/10.1101/2023.08.08.23293420</a></p>
Clonally resolved spatial transcriptomics data of mouse spleen
<p>The BGI Stereo-seq strategy was applied to a mouse spleen sample containing SPLINTR barcoded AML cells.</p> <p>Data generated with <a href="https://github.com/DaneVass/bartools_manuscript_code/blob/main/spatial-analysis/data_preprocessing_m4_paper.py" target="_blank" rel="noopener">https://github.com/DaneVass/bartools_manuscript_code/blob/main/spatial-analysis/data_preprocessing_m4_paper.py</a>.</p> <p>mouse4_bin*_bc_counts.tsv:<br>Binned barcode counts across whole slide.<br>Can be merged with AnnData file by `cell_id`.<br>Contains all barcodes detected in a bin (`barcode`) and UMI counts summed by bin (`count_binned`).<br>`isin_adata` marks whether the bin is on the manually segmented tissue section.</p> <p>mouse4_bin*_bc_counts_top1.tsv:<br>Binned barcode counts on tissue section, barcode with most UMI per bin is selected. </p> <p>mouse4_bin*_bc.h5ad:<br>Binned stereo-seq data with barcode information.</p> <p>mouse4_bin*_bc_clustered.h5ad:<br>Filtered, log1p transformed, scaled, clustered stereo-seq data.<br>Data is not zero centered for bin10 for memory efficiency.</p>
De novo transcriptome assembly and discovery of drought-responsive genes in eastern white spruce (Picea glauca)
<p>Forests face an escalating threat from the increasing frequency of extreme drought events driven by climate change. To address this challenge, it is crucial to understand how widely distributed species of economic or ecological importance may respond to drought stress. Here, we used RNA-sequencing to investigate transcriptome responses at increasing levels of water stress in white spruce (<em>Picea glauca</em> (Moench) Voss), distributed across North America. We began by generating an expanded transcriptome assembly emphasizing short-term drought stress at different developmental stages. We also analyzed differential gene expression at four time points over 22 days in a controlled drought stress experiment involving 2-year-old plants and three genetically unrelated clones. De novo transcriptome assembly and gene expression analysis revealed a total of 33,287 transcripts (18,934 annotated unique genes), with 4,425 unique drought-responsive genes. Many transcripts that had predicted functions associated with photosynthesis, cell wall organization, and water transport were down-regulated under drought conditions, while transcripts linked to abscisic acid response and defense response were up-regulated. Our study highlights a previously uncharacterized effect of drought stress on lipid metabolism genes in conifers and significant changes in the expression of several transcription factors, suggesting a regulatory response potentially linked to drought response or acclimation. Our research represents a fundamental step in unraveling the molecular mechanisms underlying short-term drought responses in white spruce seedlings. In addition, it provides a valuable source of new genetic data that could contribute to genetic selection strategies aimed at enhancing the drought resistance and resilience of white spruce to changing climates.</p>
Data from: Transcriptome analysis of apical meristem enriched bud samples for size dependent flowering commitment in Crocus sativus reveal role of sugar and auxin signalling
<p><strong>Background</strong></p> <p>Cultivation of <em>Crocus sativus</em> (saffron) faces challenges due to inconsistent flowering patterns and variations in yield. Flowering takes place in a graded way with smaller corms unable to produce flowers. Enhancing the productivity requires a comprehensive understanding of the underlying genetic mechanisms that govern this size based flowering initiation and commitment. Therefore, samples enriched with non-flowering and flowering apical buds from small (<6g) and large (>14g) corms were sequenced. </p> <p><strong>Methods and Results</strong></p> <p>Apical bud enriched samples from small and large corms were collected immediately after break of dormancy in July. RNA sequencing was performed using Illumina Novaseq 6000. <em>De-novo</em> transcriptome assembly and analysis using flowering committed buds from large corms at post-dormancy and their comparison with vegetative shoot primordia from small corms pointed out the major role of Auxin and ABA hormonal regulation. Many genes with known dual responses in flowering development and circadian rhythm like Flowering locus T and Cryptochrome 1 along with a transcript showing homology with small auxin upregulated RNA (SAUR) exhibited induced expression in flowering buds. Thorough prediction of <em>Crocus sativus</em> non-coding RNA repertoire has been carried out for the first time. Enolase was found to be acting as a major hub with protein-protein interaction analysis using Arabidopsis counterparts.</p> <p><strong>Conclusion</strong></p> <p>Transcripts belong to key pathways including phenylpropanoid biosynthesis, hormone signaling and carbon metabolism were found significantly modulated. KEGG assessment and protein-protein interaction analysis confirm the expression data. Findings unravel the genetic determinants driving the size-dependent flowering in <em>Crocus sativus</em>.</p>
Comparison of spatial transcriptomics technologies used for tumor cryosections
<p>This repository contains data from a spatial transcriptomics (ST) analysis of brain tumor cryosections (medulloblastoma with extensive nodularity, MBEN). It is associated with the preprint by Rademacher, Huseynov, Bortolomeazzi et al. 2024, <em>bioRxiv</em>, <a href="https://doi.org/10.1101/2024.04.03.586404">https://doi.org/10.1101/2024.04.03.586404</a>, that has a full description of the work. In the study four imaging-based ST methods – RNAscope HiPlex, Molecular Cartography, MERFISH/Merscope, and Xenium – as well as sequencing-based ST (Visium) and single cell RNA sequencing of dissociated nuclei (snRNA-seq) were compared. The files provided here are described in readme.txt and include the transcript count matrices acquired on the Visium platform as well as Seurat objects of the data and analysis results for the comparison of the different technologies. The data for snRNA-seq, RNAscope HiPlex and Molecular Cartography included in the Seurat objects are based on the primary data acquired in a previous study (Ghasemi et al. 2024, Nat Commun, <a href="https://doi.org/10.1038/s41467-023-44117-x">https://doi.org/10.1038/s41467-023-44117-x</a>). </p>
Phylum Cnidaria (Hydrozoa) CANTATA Transcriptomes
<p>CANTATA is a Community bAsed Non-bilaTeriAn Transcriptome Archive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p><p> </p><p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Cnidaria (Class Hydrozoa).</p><p> </p><p>Currently, the following species are available:</p><ul><li><i>Aegina citrea</i></li><li><i>Apolemia lanosa</i></li><li><i>Bargmannia amoena</i></li><li><i>Bargmannia elongata</i></li><li><i>Bargmannia lata</i></li><li><i>Chelophyes appendiculata</i></li><li><i>Chuniphyes multidentata</i></li><li><i>Craseoa lathetica</i></li><li><i>Erenna richardi</i></li><li><i>Forskalia asymmetrica</i></li><li><i>Hippopodius hippopus</i></li><li><i>Hydractinia symbiolongicarpus</i></li><li><i>Hydra oligactis</i></li><li><i>Hydra viridissima K10</i></li><li><i>Hydra vulgaris AEP</i></li><li><i>Lilyopsis fluoracantha</i></li><li><i>Liriope tetraphylla</i></li><li><i>Lychnagalma utricularia</i></li><li><i>Marrus claudanielis</i></li><li><i>Millepora alcicornis</i></li><li><i>Nanomia bijuga</i></li><li><i>Physalia physalis</i></li><li><i>Resomia ornicephala</i></li><li><i>Rhizophysa filiformis</i></li><li><i>Stephalia dilata</i></li></ul><p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (https://gitlab.lrz.de/palmuc/cantata)</p>
Phylum Cnidaria (Scyphozoa) CANTATA Transcriptomes
<p>CANTATA is a Community bAsed Non-bilaTeriAn Transcriptome Archive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p><p> </p><p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Cnidaria (Class Scyphozoa).</p><p> </p><p>Currently, the following species are available:</p><ul><li><i>Atolla vanhoeffeni</i></li><li><i>Aurelia aurita</i></li><li><i>Chrysaora fuscescens</i></li><li><i>Cyanea capillata</i></li><li><i>Cyanea nozakii</i></li><li><i>Nemopilema nomurai</i></li><li><i>Pelagia noctiluca</i></li><li><i>Stomolophus meleagris</i></li></ul><p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (https://gitlab.lrz.de/palmuc/cantata)</p>
Phylum Cnidaria (Cubozoa) CANTATA Transcriptomes
<p>CANTATA is a Community bAsed Non-bilaTeriAn Transcriptome Archive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p><p> </p><p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Cnidaria (Class Cubozoa).</p><p> </p><p>Currently, the following species are available:</p><ul><li><i>Chironex fleckeri</i></li><li><i>Copula sivickisi</i></li><li><i>Tripedalia cystophora</i></li></ul><p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (https://gitlab.lrz.de/palmuc/cantata)</p>
Phylum Cnidaria (Staurozoa) CANTATA Transcriptomes
<p>CANTATA is a Community bAsed Non-bilaTeriAn Transcriptome Archive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p><p> </p><p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Cnidaria (Class Staurozoa).</p><p> </p><p>Currently, the following species are available:</p><ul><li><i>Calvadosia campanulata</i></li><li><i>Calvadosia cruxmelitensis</i></li><li><i>Craterolophus convolvulus</i></li><li><i>Haliclystus auricula</i></li></ul><p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (https://gitlab.lrz.de/palmuc/cantata)</p>
Phylum Placozoa CANTATA Transcriptomes
<p>CANTATA is a Community bAsed Non-bilaTeriAn Transcriptome Archive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p> <p> </p> <p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Placozoa.</p> <p> </p> <p>Currently the following species are available:</p> <ul> <li><em>Trichoplax adherens</em></li> <li><em>Hoilungia hongkongensis</em></li> </ul> <p> </p> <p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (https://gitlab.lrz.de/palmuc/cantata)</p> <p> </p> <p> </p>
Phylum Ctenophora CANTATA Transcriptomes
<p>CANTATA is a Community bAsed Non-bilaTeriAn Transcriptome Archive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p><p> </p><p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Ctenophora.</p><p> </p><p>Currently the following species are available:</p><ul><li><i>Aulacoctena acuminata</i></li><li><i>Bathocyroe fosteri</i></li><li><i>Bathyctena chuni</i></li><li><i>Beroe abyssicola</i></li><li><i>Beroe forskalii</i></li><li><i>Beroe ovata</i></li><li><i>Bolinopsis microptera</i></li><li><i>Cestum veneris</i></li><li><i>Charistephane fugiens</i></li><li><i>Deiopea kaloktenota</i></li><li><i>Dryodora glandiformis</i></li><li><i>Euplokamis dunlapae</i></li><li><i>Haeckelia beehleri</i></li><li><i>Haeckelia rubra</i></li><li><i>Hormiphora californensis</i></li><li><i>Lampea lactea</i></li><li><i>Lampocteis cruentiventer</i></li><li><i>Leucothea pulchra</i></li><li><i>Ocyropsis maculata</i></li><li><i>Thalassocalyce inconstans</i></li><li><i>Velamen paralellum</i></li></ul><p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (https://gitlab.lrz.de/palmuc/cantata)</p><p> </p>
Phylum Porifera CANTATA Transcriptomes
<p><strong>CANTATA</strong> is a <strong>C</strong>ommunity b<strong>A</strong>sed <strong>N</strong>on-bila<strong>T</strong>eri<strong>A</strong>n <strong>T</strong>ranscriptome <strong>A</strong>rchive aiming to provide an archive of non-bilaterian transcriptomic resources assembled and annotated in a standardized manner.</p> <p>In this repository, we provide the transcriptomes assemblies corresponding to the Phylum Porifera.</p> <p>Currently the following species are available:</p> <p><strong>Demospongiae:</strong></p> <ul> <li><em>Amphimedon queenslandica</em></li> <li><em>Aplysina aerophoba</em></li> <li><em>Axinella polypoides</em></li> <li><em>Baikalospongia bacillifera</em></li> <li><em>Chondrosia reniformis</em> (ASG)</li> <li><em>Cinachyrella alloclada</em></li> <li><em>Cliona varians</em></li> <li><em>Crella elegans</em></li> <li><em>Cymbastella concentrica</em></li> <li><em>Dendrilla antarctica</em></li> <li><em>Dysidea avara</em></li> <li><em>Ephydatia fluviatilis</em></li> <li><em>Ephydatia muelleri</em></li> <li><em>Geodia atlantica</em></li> <li><em>Geodia hentscheli</em></li> <li><em>Geodia macandrewii</em></li> <li><em>Geodia phlegraei</em></li> <li><em>Halichondria panicea</em></li> <li><em>Haliclona amboinensis</em></li> <li><em>Haliclona tubifera</em></li> <li><em>Halisarca dujardinii</em></li> <li><em>Lantrunculia apicalis</em></li> <li><em>Lendenfeldia chondrodes</em></li> <li><em>Lubomirskia abietina</em></li> <li><em>Lubomirskia baikalensis</em></li> <li><em>Mycale cecilia</em></li> <li><em>Mycale phylophylla</em></li> <li><em>Neopetrosia compacta</em></li> <li><em>Petrosia ficiformis</em> (ASG)</li> <li><em>Pleraplysilla spinifera</em></li> <li><em>Pseudospongosorites suberitoides</em></li> <li><em>Sarcotragus fasciculatus</em></li> <li><em>Spongia officinalis</em></li> <li><em>Spongilla lacustris</em></li> <li><em>Tedania anhelans</em></li> <li><em>Tethya wilhelma</em></li> <li><em>Vaceletia crypta</em></li> <li><em>Xestospongia testudinaria</em></li> </ul> <p><strong>Hexactinellida:</strong></p> <ul> <li><em>Amphidiscella abyssalis</em></li> <li><em>Aulocalyx serialis</em></li> <li><em>Bolosoma cyanae</em></li> <li><em>Caulophacus discohexaster</em></li> <li><em>Farrea occa</em></li> <li><em>Farrea similaris</em></li> <li><em>Regadrella okinoseana</em></li> <li><em>Saccocalyx tetractinus</em></li> <li><em>Walteria leuckarti</em></li> </ul> <p><strong>Calcarea:</strong></p> <ul> <li><em>Clathrina coriacea</em></li> <li><em>Grantia compressa</em></li> <li><em>Leucetta chagosensis</em></li> <li><em>Leuconia nivea</em></li> <li><em>Sycon cyliatum</em></li> <li><em>Sycon coactum</em></li> </ul> <p><strong>Homoscleromorpha:</strong></p> <ul> <li><em>Corticium candelabrum</em></li> <li><em>Oscarella lobularis</em></li> <li><em>Oscarella pearsei</em></li> <li><em>Plakina jani</em></li> </ul> <p> </p> <p>The details about the read files used to assemble each transcriptome can be found at the CANTATA repository (<a href="https://gitlab.lrz.de/palmuc/cantata">https://gitlab.lrz.de/palmuc/cantata</a>)</p> <p> </p>
Transcriptomic atlas reveals organ-specific disease tolerance in sickle cell mice. Dataset for bone marrow, HbSS Townes mice injected or not with heme
<p>The objective of this experiment was to explore the transcriptome of the HbSS Townes mouse model of sickle cell disease. Townes model mice carry several human hemoglobin knock-in genes replacing the endogenous mouse genes and may be useful in studying sickle cell disease. All mice were genotyped, age- and sex-matched littermates. All HbAA (control, normal human hemoglobin) vs HbSS (sickle cell disease, mutated human hemoglobin) mice were used for experimentations at 6-8 weeks of age, to limit intra-group heterogeneity. Hemin (Ferriprotoporphyrin IX) was purchased from Frontiers Scientific and injected intravenously (iv.) in a retroorbital sinus at a concentration of 24 µmol/kg. Control mice received PBS instead. Mice were anesthetized with isoflurane 2-3% for injections, blood collection and sacrifice. All mice were sacrificed by cervical dislocation, 4 hours after injection.</p> <p>Here the dataset for HbSS mice injected or not with heme is uploaded.</p> <p>The corresponding dataset for the HbAA mice injected or not with heme can be found at <strong>10.5281/zenodo.10961162</strong></p> <p>Bone marrow RNA was extracted by Macherey Nagel kit, according to the manufacturer’s instructions. The quality and quantity of mRNA were evaluated using a 2100<br>bioanalyzer with TNA 6000 NanoKits (all Agilent Technologies, Palo Alto, CA, USA). RNA Integrity Numbers superior to 7 were eligible for subsequent reverse transcription into cDNA. RNAseq was performed at the GenomIC plateform Cochin Institute INSERM U1016. After RNA extraction, RNA quality (RNA integrity number) was estimated. 1μg of high-quality total RNA sample (RIN &gt;7) was processed to build up the libraries, using TruSeq Stranded mRNA kit (Illumina) according to manufacturer instructions. Briefly, purified poly-A containing mRNA molecules were fragmented and reverse-transcribed using random primers. Replacement of dTTP by dUTP during second strand synthesis allowed us to achieve strand specificity. Addition of a single A base to the cDNA was followed by ligation of Illumina adapters.<br>Libraries were quantified by qPCR using KAPA Library Quantification Kits for Illumina Libraries (KapaBiosystems, Wilmington, MA). Library profiles were assessed using DNA High Sensitivity LabChip kits on an Agilent Bioanalyzer. Libraries were sequenced on an Illumina Nextseq 500 instrument using 75 base-lengths read V2 chemistry in a paired-end mode. After sequencing, primary analysis based on AOZAN software (ENS, Paris), was applied to demultiplex and control the quality of the raw data (based of FastQC modules / version 0.11.5).</p> <p>The dataset here represents 4 groups of mice, 4 mice per group as follows: HbAA PBS, HbAA heme, HbSS PBS, HbSS heme. </p> <p> </p>
ScienceDex guides
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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.