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8,068 results for “Transcriptome analysis”
Reproducible data, example subsets, and analysis pipeline for the extended TAaCGH study of breast cancer genomic and transcriptomic profiles
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Genome and transcriptome analysis of the beet armyworm Spodoptera exigua reveals targets for pest control
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Transcriptomic analysis of light-induced genes in Nasonia vitripennis: possible implications for circadian light entrainment pathways
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Transcriptome analysis of invasive Gypsophila paniculata (baby's breath) populations from Michigan and Washington, USA.
<p>Invasive species provide an opportune system to investigate how populations respond to new or changing environments. While the impacts of invasive species increase annually, many gaps in our understanding of how these species invade, adapt, and thrive in the areas they are introduced to remain. Using the perennial forb <i>Gypsophila paniculata</i> as a study system, we aimed to investigate how invasive species respond to different environments. Baby's breath (<i>Gypsophila paniculata</i>) was introduced to North America in the late 1800's and has since spread throughout the northwestern United States and western Canada. We used an RNA-seq approach to explore how molecular processes may be contributing to the success of invasive <i>G. paniculata</i> populations that are thought to share similar genetic backgrounds across distinct habitats. Transcription profiles were constructed for root, stem, and leaf tissue from seedlings collected from a sand dune ecosystem in Petoskey, MI (PSMI) and a sagebrush ecosystem in Chelan, WA (CHWA). Using these data we assessed differential gene expression between the two populations and identified SNPs within differentially expressed genes. We identified 1,146 transcripts that were differentially expressed across all tissues between the two populations. GO processes enriched by genes displaying higher expression in PSMI were associated with increased nutrient starvation, while enriched processes in CHWA were associated with abiotic stress. Only 7.4% of the differentially expressed genes across all three tissues contained SNPs differing in allele frequencies of at least 0.5 between the populations. In addition, common garden studies found the two populations differed in germination rate and seedling emergence success, but not in above- and below-ground tissue allocation. Our results suggest that the success of invasive <i>G. paniculata</i> across these two environments is likely the result of plasticity in molecular processes responding to different environmental conditions, although some genetic divergence may also be contributing to these differences.</p>
Sequence data for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol" - single cells dataset
<p>Sequence data (Illumina MiSeq runs) for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol". dataset of 2300 single cells. File names indicate unique sequencing runs. In the manuscripts, the informations about cell lines are found in the Supplemental Table 1. </p>
Sequence data for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol" - Protocol optimization
<p>Sequence data (Illumina MiSeq runs) for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol". Optimization of the protocol. Files names indicate unique run identifiers. In the manuscript, the link between unique run identifiers, cells and purpose of the experiment is found in the Supplemental Table 1. </p>
Supplementary information associated with a "Whole-Organism Integrated DNA Methylation and Transcriptomics Analysis of Butterfly Metamorphosis".
<p>Supplementary information, annotation and code related to the manuscript studying <em>Bicyclus anynana</em> development entitled "Whole-Organism Integrated DNA Methylation and Transcriptomics Analysis of Butterfly Metamorphosis".</p>
Data from "FICTURE: Scalable segmentation-free analysis of sub-micron resolution spatial transcriptomics"
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Transcriptome analysis of Drosophila suzukii reveals molecular mechanisms conferring pyrethroid and spinosad resistance
<p class="MsoNormal"><em>Drosophila suzukii</em> possess a serrated ovipositor that enables them to lay eggs in soft-skinned, ripening fruits, making this insect<em> </em>a serious threat to berry production. Since its 2008 introduction into North America, growers have used insecticides as the primary approach for <em>D. suzukii</em> management, resulting in detections of insecticide resistance in this pest. This study sought to identify the molecular mechanisms conferring insecticide resistance in these resistant populations. We sequenced the transcriptomes of two pyrethroid- and two spinosad-resistant isogenic lines. In both pyrethroid-resistant lines and one spinosad-resistant line, we identified overexpression of metabolic genes that are implicated in resistance in other insect pests. In the other spinosad-resistant line, we observed an overexpression of cuticular genes that have been linked to resistance. Our findings enabled the development of molecular diagnostics that we used to confirm persistence of insecticide resistance in California. To validate these findings, we leveraged <em>D. melanogaster </em>mutants deficient in either metabolic or cuticular genes that were upregulated in resistant <em>D. suzukii </em>to demonstrate that these genes are involved in promoting resistance. This study is the first to characterize the molecular mechanisms of insecticide resistance in <em>D. suzukii</em> and provides insights into how current management practices can be optimized.</p> <p class="MsoNormal"> </p>
Transcriptome Analysis from a co-culture of Skeletonema marinoi and Prymnesium parvum
<p>This Zenodo entry refers to a study using metabolomics and transcriptomic data analysis to analyse chemical interactions between two microalgae: <em>Skeletonema marinoi</em> and <em>Prymnesium parvum</em></p> <p>p_parvum_Eukaryota_augustus_gene_prediction.faa file contains the predicted protein sequences from the transcriptome of <em>Prymnesium parvum</em> using Augustus. This list is generated from a non-restrictive Busco Analysis.</p> <p>s_costatum_Stramenopiles_augustus_gene_prediction.faa file contains the predicted protein sequences from the transcriptome of <em>Skeletonema marinoi </em>using Augustus. This list is generated from a restrictive Busco Analysis.</p> <p>The files p_parvum_deseq2_results_all.csv and s_marinoi_deseq2_results_all.csv contain differential gene expression analysis, while p_parvum_deseq2_result_sorted_regulated_with_proteins.csv and s_marinoi_deseq2_result_sorted_regulated_with_proteins.csv contain only upregulated protein sequences in co-culture conditions.</p> <p>The genes_read.R script is used to generate the p_parvum_deseq2_result_sorted_regulated_with_proteins.csv and s_marinoi_deseq2_result_sorted_regulated_with_proteins.csv. The code for analysis from RAW reads to differential gene expression analysis is available on: <a href="https://github.com/Bioinformatics-Core-Facility-Jena/SE20220705_97">https://github.com/Bioinformatics-Core-Facility-Jena/SE20220705_97</a>. The RAW files are available on BioProject: PRJNA1006530</p> <p> </p> <p> </p>
Transcriptomic Analysis of CIC and CTC from Tumor Bearing Mice
<p>CIC and CTC isolated from tumor bearing mice were subjected to transcriptomic analysis using Smart-seq3 library preparation method. n = 3 for each group. </p>
Transcriptomic Analysis Data for MSTN Mutations and Mechanisms of Muscle Hypertrophy in a New Guinea Pig Breed
<p>This dataset contains raw RNA-seq data from six guinea pig muscle samples, split into two groups:</p> <ul> <li><strong>Native guinea pigs (B1 to B3):</strong> Control group with no selective breeding.</li> <li><strong>Kuri breed guinea pigs (B4 to B6):</strong> Synthetic hybrid group selectively bred for increased muscle mass.<br>Each sample has paired-end FASTQ files (e.g., B1_1.fq.gz and B1_2.fq.gz).</li> </ul>
Mitigating autocorrelation during spatially resolved transcriptomics data analysis
<p>Here we include the marmoset brain and mouse gut STARmap data introduced in the corresponding manuscript, "Mitigating autocorrelation during spatially resolved transcriptomics data analysis". We also include the mouse brain STARmap PLUS data that was used to demonstrate cross-species spatial integration and was previously published in Shi, He, Zhou et al. 2022.</p>
Supplementary Table S5 - Article: Transcriptome Analysis Provides Novel Insights into Salinity Stress Response in two Egyptian Rice Varieties with Different Tolerance Levels
<p><strong>Table S5.</strong> Repository data showing genes identified by MapMan in Giza 178 in different pathways. </p> <p>A, Cell wall modifications.</p> <p>B, Hemicellulose synthesis.</p> <p>C, Cellulose synthesis.</p> <p>D, Mannan-xylose-arabinose-fucose. </p> <p>E, cell wall peroxidase.</p> <p>F, TF MYB. </p> <p>G, bZIP. </p> <p>H, Histone.</p>
Supplementary Table S4 - Article: Transcriptome Analysis Provides Novel Insights into Salinity Stress Response in two Egyptian Rice Varieties with Different Tolerance Levels
<p><strong>Table S4.</strong> Repository data showing genes identified by MapMan in Giza 177 in different pathways. </p> <p>A, Cell wall modifications.</p> <p>B, Hemicellulose synthesis.</p> <p>C, Cellulose synthesis.</p> <p>D, Mannan-xylose-arabinose-fucose.</p> <p>E, cell wall peroxidase.</p> <p>F, TF MYB. </p> <p>G, bZIP. </p> <p>H, Histone.</p>
Supplementary Table S2 - Article:Transcriptome Analysis Provides Novel Insights into Salinity Stress Response in two Egyptian Rice Varieties with Different Tolerance Levels
<p><strong>Table S2.</strong> Repository data for the global analysis produced for cv Giza 177. </p> <p>A, Up regulated genes observed when comparing salt stressed plants vs unstressed controls. </p> <p>B, Down regulated genes in Giza 177 observed when comparing salt stressed plants vs unstressed controls.</p> <p>C, Gene Ontology enrichment analysis (GOEA) results for Giza 177 up regulated genes. </p> <p>D, GOEA results for Giza 177 down regulated genes. </p>
Supplementary Table S3 - Article: Transcriptome Analysis Provides Novel Insights into Salinity Stress Response in two Egyptian Rice Varieties with Different Tolerance Levels
<p><strong>Table S3.</strong> Repository data for the global analysis produced for cv Giza 178. </p> <p>A, Up regulated genes observed when comparing salt stressed plants vs unstressed controls. </p> <p>B, Down regulated genes in Giza 178 observed when comparing salt stressed plants vs unstressed controls.</p> <p>C, Gene Ontology enrichment analysis (GOEA) results for Giza 178 up regulated genes. </p> <p>D, GOEA results for Giza 178 down regulated genes. </p>
Effects of acute exposure to polystyrene nanoplastics on the channel catfish larvae: Insights from energy metabolism and transcriptomic analysis
<p><span>Microplastics (nanoplastics) pollution has been a major ecological issue threatening global aquatic ecosystems. However, knowledge of the adverse effects of nanoplastics and the effects on freshwater ecosystems is still limited. To understand the impacts of nanoplastics on freshwater ecosystems, it is essential to reveal the physiological changes caused by nanoplastics in freshwater organisms, especially at their early life-history stages. In the present study, the larval channel catfish <em>Ietalurus punetaus</em> were exposed to gradient concentrations (0, 5, 10, 25 and 50 mg/L) of 75-nm polystyrene nanoplastics (PS-NPs) for 24 h or 48 h, and changes in contents of energy metabolites, metabolic enzyme activities and transcriptome were assessed. The results showed glucose and triglyceride contents increased after 24 h of exposure to 10 or 25 mg/L of PS-NPs but decreased with increased concentrations or prolonged exposure duration. Activities of most metabolic enzymes analyzed decreased in the larvae after 48 h of exposure, especially in 25 or 50 mg/L of PS-NPs. These suggested that PS-NPs caused huge energy consumption and disturbed the energy metabolism in larval fish. Transcriptomic analysis showed that 48 h of exposure to 50 mg/L PS-NPs affected the expression of genes involved in protein digestion and induced response of proteasomes or heat shock proteins in the larval <em>I. punetaus</em>. The genes involved in peroxisome proliferator-activated receptors (PPAR) pathway and biosynthesis of amino acids were activated after the exposure. PS-NPs also depressed the expression of the genes involved in gonad development or muscle contraction in the larval <em>I. punetaus</em>. Overall, acute exposure to 75-nm PS-NPs disrupted the energy metabolism by consuming the energy reserves, and affected a series of molecular pathways which may further affect the development and survival of fish. This study provided the information about adverse effects of nanoplastics on the fish larvae and revealed the molecular pathways for the potential adverse outcomes.</span></p>
Transcriptome Analysis of Retinoic Acid-Inducible Gene I Overexpression Reveals the Potential Genes for Autopha-gy-related Negative Regulation
<p>Supplementary table 1: Primer pairs used for quantitative RT-PCR analysis. Supplementary file 2: All DEGs are listed in the excel file.</p>
Supplementary Files - Transcriptomic analysis of CPM-positive hiPSCs-derived liver progenitor cells in a microfluidic device shows zonation-like patterns.
<p>Supplementary Files for the paper intitled Transcriptomic analysis of CPM-positive hiPSCs-derived liver progenitor cells in a microfluidic device shows zonation-like patterns. </p>
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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.