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25,372 results for “Transcriptomics”
sex reversal transcriptomic analysis in Chinese tongue sole
<p>sex reseveral transcriptome data</p>
Spatial Transcriptomics data (GeoMx) of midbrain dopamine cells in control and PD subjects
<p>The repository includes Spatial Transcriptomic datasets generated by Nanostring GeoMx (Hu WTA) analysis of midbrain TH+ cells from Controls (n=10), Incidental Lewy Body Disease (n=10), early Parkinsons Disease (ePD,n=5) and late Parkinsons Disease (lPD,n=5). A total 348 Regions of Interest were analysed. The raw and processed counts and metadata are provided as an R Seurat object (geomx_edwards_thmask.rds). The scripts used for low level data processing are described in https://github.com/zchatt/ASAP-SpatialTranscriptomics/blob/main/geomx/lowlevel/README.md</p> <p>Tissue samples from pathologically confirmed asymptomatic stage I-II Lewy body disease, stage IV Lewy body PD (early-PD), stage VI Lewy body PD (late-PD)(Braak, Del Tredici et al. 2003) and controls without the neurological or neuropathological disease were obtained from the Sydney Brain Bank. The study was approved by the University of Sydney Human Research Ethics Committee (2021/845). All cases with PD were levodopa-responsive and fulfilled the UK Brain Bank Clinical Criteria for a diagnosis of clinical PD (Hughes, Ben-Shlomo et al. 1992) with no other neurodegenerative conditions. </p> <p>Cells were not extracted. Tissue sections were cut from FFPE blocks of post-mortem human midbrains at 6µm on a rotary microtome (HistoCore MULTICUT, Leica Biosystems) and mounted on Series 2 adhesive microscope slides (Trajan Scientific Medical, AU) for processing for spatial trranscriptomics. To remove the paraffin, slides were incubated in the oven at 60°C for 1hr and then submerged in HistoChoice Clearing Agent (Sigma-Aldrich, H2779) for 2x7mins, followed by rehydration in decreasing ethanol concentrations (100% ethanol for 2x3mins, 95% ethanol for 3mins, 70% ethanol for 3mins) and distilled H2O for 3mins. </p> <p>Tissue sections were immunohistochemically stained for tyrosine hydroxylase and Regions of Interest (ROIs) processed following Nanostring GeoMx® Digital Spatial Profiler using the manufacturer’s instructions. Libraries were sequenced on Illumina Novaseq 6000 platform using NovaSeq SP 100 cycle kit (XP workflow, 27-8-8-27).</p> <p>This research was funded in whole or in part by Aligning Science Across Parkinson’s (ASAP-020529) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF). For the purpose of open access, the author has applied a CC BY 4.0 public copyright license to all Author Accepted Manuscripts arising from this submission.</p>
Spatial Transcriptomics data (GeoMx) of locus coeruleus dopamine cells in control and PD subjects
<p>The repository includes Spatial Transcriptomic datasets generated by Nanostring GeoMx (Hu WTA) analysis of locus coeruleus TH+ cells from Controls (n=9), early Parkinsons Disease (ePD, n=8) and late Parkinsons Disease (lPD, n=2). A total 39 Regions of Interest were analysed. The raw and processed counts and metadata are provided as an R Seurat object (geomx_vila_thmask.rds). The scripts used for low level data processing are described in https://github.com/zchatt/ASAP-SpatialTranscriptomics/blob/main/geomx/lowlevel/README.md.</p> <p>Tissue samples from pathologically confirmed stage IV Lewy body PD (early-PD), stage VI Lewy body PD (late-PD)(Braak, Del Tredici et al. 2003) and controls without the neurological or neuropathological disease were obtained from the Sydney Brain Bank. The study was approved by the University of Sydney Human Research Ethics Committee (2021/845). All cases with PD were levodopa-responsive and fulfilled the UK Brain Bank Clinical Criteria for a diagnosis of clinical PD (Hughes, Ben-Shlomo et al. 1992) with no other neurodegenerative conditions. </p> <p>Cells were not extracted. Tissue sections were cut from FFPE blocks of post-mortem human midbrains at 6µm on a rotary microtome (HistoCore MULTICUT, Leica Biosystems) and mounted on Series 2 adhesive microscope slides (Trajan Scientific Medical, AU) for processing for spatial trranscriptomics. To remove the paraffin, slides were incubated in the oven at 60°C for 1hr and then submerged in HistoChoice Clearing Agent (Sigma-Aldrich, H2779) for 2x7mins, followed by rehydration in decreasing ethanol concentrations (100% ethanol for 2x3mins, 95% ethanol for 3mins, 70% ethanol for 3mins) and distilled H2O for 3mins. </p> <p>Tissue sections were immunohistochemically stained for tyrosine hydroxylase and Regions of Interest (ROIs) processed following Nanostring GeoMx® Digital Spatial Profiler using the manufacturer’s instructions. Libraries were sequenced on Illumina Novaseq 6000 platform using NovaSeq SP 100 cycle kit (XP workflow, 27-8-8-27).</p> <p>This research was funded in whole or in part by Aligning Science Across Parkinson’s (ASAP-020505) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF). For the purpose of open access, the author has applied a CC BY 4.0 public copyright license to all Author Accepted Manuscripts arising from this submission.</p>
Spatial Transcriptomics data (GeoMx) of midbrain tissue in control and PD subjects
<p>he repository includes Spatial Transcriptomic datasets generated by Nanostring GeoMx (Hu WTA) analysis of midbrain unmasked (whole tissue) Regions of Interest from Controls (n=10), Incidental Lewy Body Disease (n=11), early Parkinsons Disease (ePD, n=5) and late Parkinsons Disease (lPD, n=6). A total 515 Regions of Interest were analysed. The raw and processed counts and metadata are provided as an R Seurat object (geomx_vila_unmask.rds). The scripts used for low level data processing are described in https://github.com/zchatt/ASAP-SpatialTranscriptomics/blob/main/geomx/lowlevel/README.md </p> <p>Tissue samples from pathologically confirmed asymptomatic stage I-II Lewy body disease, stage IV Lewy body PD (early-PD), stage VI Lewy body PD (late-PD)(Braak, Del Tredici et al. 2003) and controls without the neurological or neuropathological disease were obtained from the Sydney Brain Bank. The study was approved by the University of Sydney Human Research Ethics Committee (2021/845). All cases with PD were levodopa-responsive and fulfilled the UK Brain Bank Clinical Criteria for a diagnosis of clinical PD (Hughes, Ben-Shlomo et al. 1992) with no other neurodegenerative conditions. </p> <p>Cells were not extracted. Tissue sections were cut from FFPE blocks of post-mortem human midbrains at 6µm on a rotary microtome (HistoCore MULTICUT, Leica Biosystems) and mounted on Series 2 adhesive microscope slides (Trajan Scientific Medical, AU) for processing for spatial trranscriptomics. To remove the paraffin, slides were incubated in the oven at 60°C for 1hr and then submerged in HistoChoice Clearing Agent (Sigma-Aldrich, H2779) for 2x7mins, followed by rehydration in decreasing ethanol concentrations (100% ethanol for 2x3mins, 95% ethanol for 3mins, 70% ethanol for 3mins) and distilled H2O for 3mins. </p> <p>Tissue sections were immunohistochemically stained for tyrosine hydroxylase and Regions of Interest (ROIs) processed following Nanostring GeoMx® Digital Spatial Profiler using the manufacturer’s instructions. Libraries were sequenced on Illumina Novaseq 6000 platform using NovaSeq SP 100 cycle kit (XP workflow, 27-8-8-27).</p> <p>This research was funded in whole or in part by Aligning Science Across Parkinson’s (ASAP-020505) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF). For the purpose of open access, the author has applied a CC BY 4.0 public copyright license to all Author Accepted Manuscripts arising from this submission.</p>
Immune Imbalance Transcriptomics (IIT) Algorithm Supplementary Materials
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Transcriptomic evidence for Brachyury expression in the caudal tip region of adult Ptychodera flava (Hemichordata)
<p>Most metazoans have a single-copy of the T-box transcription factor gene,<em> Brachyury</em>. The gene is expressed in cells of the blastopore of late blastulae and the archenteron invagination and stomodeum invagination regions of gastrulae. It appears to be crucial for gastrulation and mesoderm differentiation of embryos. Although this expression pattern is shared by most deuterostomes<a href="#_msocom_1">[AA1]</a> , <em>Brachyury</em> expression was not reported in adult stage. Here we show that <em>Brachyury</em> of an indirect-developer, a hemichordate acorn-worm, <em>Ptychodera flava,</em> is expressed not only in embryonic cells but also in cells of the caudal tip (anus) region of adults. This spatially restricted expression shown by whole-mount <em>in situ</em> hybridization was confirmed by Iso-seq RNA sequencing analyses and single cell RNA-seq (scRNA-seq) analysis. Iso-seq analysis showed that the gene expression occurred only in the caudal region of the adult but not in the anterior regions including stomochord. scRNA-seq analysis showed that a cluster that contained <em>Brachyury</em>-expressing cells composed of mesoderm-related cells, but not associated with epidermis, nervous system, and muscle. Although further studies are required to examine roles of <em>Brachyury</em> at the adult stage, this study suggests a possible evolutionary link of the <em>Brachyury</em>-expressing caudal tip of hemichordates with the anus formation region of chordates.</p>
Exploring the venom gland transcriptome of Bothrops asper and Bothrops jararaca: de novo assembly and analysis of novel toxic proteins
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A study on transcriptomics.
<p>A study on transcriptomics.</p>
Multimodal transcriptomics reveal neurogenic aging trajectories and age-related regional inflammation in the dentate gyrus
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Undetermined Non-Bilaterian 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 different undetermined non-bilaterian animals. In all cases, the specimens can be assigned to a Phylum. Some specimens are determined to genus level. We include these specimens for completeness and leave the user the decision to use them or not in their analyses.</p> <p>Currently, the following species are available:</p> <p> </p> <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>
Custom microfluidic chip design enables cost-effective three-dimensional spatiotemporal transcriptomics with a wide field of view
<pre>Data analysis code and preprocessed data for MAGIC-seq.</pre>
Understanding tumor heterogeneity in melanoma brain metastasis using spatial transcriptomics and multi-regional bulk sequencing
<p>Melanoma brain metastasis (MBM) exhibits extensive inter- and intra-tumor heterogeneity, driven by a complex tumor microenvironment (TME). The aim with this study was to profile the MBMs by using a multi-omics approach, integrating spatial transcriptomics with bulk exome, proteome, and transcriptome profiling. We identified significant patient-specific variations in immune cell infiltration, particularly in B/plasma cells, myeloid cells, and cancer-associated fibroblasts (CAFs). Notably, immunotherapy-treated patients showed enrichedpathways related to EMT, IFN-γ signaling, oxidative phosphorylation, T-cell signaling, inflammation and DNA damage, which aligned with distinct cellular compositions observed in the spatial analysis. We also uncovered considerable intra-tumor heterogeneity, especially at the protein level, revealing differential expression patterns of key tumor and immune-related markers. The correlation between mRNA and protein data highlighted consistent enrichment of critical pathways across multi-omics layers. These findings provide a comprehensive view of MBM's molecular and cellular landscape, emphasizing the importance of addressing tumor heterogeneity in developing effective therapeutic strategies.</p>
Genome deletions and rewiring of the transcriptome underlie high antimonite resistance in Achromobacter sp. SMAs-55
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Raw Image Data Repository: Repurposing Large-Format Microarrays for Scalable Spatial Transcriptomics
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Gene Expression Transcriptomics Data for benchmarking Perturbation Models - Part 3
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Spatially resolved transcriptomics and graph-based deep-learning improve accuracy of routine CNS tumor diagnostics
<p><span>The diagnostic landscape of brain tumors has recently evolved to integrate comprehensive molecular markers alongside traditional histopathological evaluation. Foremost, genome-wide DNA methylation profiling and next generation sequencing (NGS) has become a cornerstone in classifying Central Nervous System (CNS) tumors, as recognized by its inclusion into the 2021 WHO classification. Despite its diagnostic precision, a limiting requirement for NGS and methylation profiling is sufficient DNA quality and quantity which restricts its feasibility, especially in cases with small biopsy samples or low tumor cell content, both frequent challenges in specimen of diffusely growing CNS lesions. Addressing these challenges, we demonstrate a application, namely <strong>NePSTA </strong>(<strong>Ne</strong>uro<strong>P</strong>athology <strong><em>S</em></strong><em>patial <strong>T</strong>ranscriptomic<strong> A</strong>nalysis</em>), which is capable of generating comprehensive morphological and molecular neuropathological diagnostics from single 5 µm tissue sections. Our framework employs 10x Visium spatial transcriptomics with graph neural networks for automated histological and molecular evaluations. Trained and evaluated across 130 patients with CNS malignancies and healthy donors across four medical centers, NePSTA<strong> </strong>integrates spatial gene expression data and inferred CNAs to predict tissue histology and methylation-based subclasses with high accuracy. Further, we demonstrate the ability to reconstruct immunohistochemistry and genotype profiling on single thin slides of minute tissue biopsies. Our approach has minimal tissue requirements, often inadequate for conventional molecular diagnostics, demonstrating the potential to transform neuropathological diagnostics and enhance tumor subtype identification with implications for fast and precise diagnostic work-up.</span></p>
Data from: Alternative splicing substantially diversifies the transcriptome during early photomorphogenesis and correlates with the energy availability in Arabidopsis
Plants use light as source of energy and information to detect diurnal rhythms and seasonal changes. Sensing changing light conditions is critical to adjust plant metabolism and to initiate developmental transitions. Here we analyzed transcriptome-wide alterations in gene expression and alternative splicing (AS) of etiolated seedlings undergoing photomorphogenesis upon exposure to blue, red, or white light. Our analysis revealed massive transcriptome reprograming as reflected by differential expression of ~20% of all genes and changes in several hundred AS events. For more than 60% of all regulated AS events, light promoted the production of a presumably protein-coding variant at the expense of an mRNA with nonsense-mediated decay-triggering features. Accordingly, AS of the putative splicing factor REDUCED RED-LIGHT RESPONSES IN CRY1CRY2 BACKGROUND 1 (RRC1), previously identified as a red light signaling component, was shifted to the functional variant under light. Downstream analyses of candidate AS events pointed at a role of photoreceptor signaling only in monochromatic but not in white light. Furthermore, we demonstrated similar AS changes upon light exposure and exogenous sugar supply, with a critical involvement of kinase signaling. We propose that AS is an integration point of signaling pathways that sense and transmit information regarding the energy availability in plants.
Data from: Challenges and strategies in transcriptome assembly and differential gene expression quantification. A comprehensive in silico assessment of RNA-seq experiments.
Transcriptome Shotgun Sequencing (RNA-seq) has been readily embraced by geneticists and molecular ecologists alike. As with all high-throughput technologies, it is critical to understand which analytic strategies are best suited and which parameters may bias the interpretation of the data. Here we use a comprehensive simulation approach to explore how various features of the transcriptome (complexity, degree of polymorphism π, alternative splicing), technological processing (sequencing error ε, library normalization) and bioinformatic workflow (de novo vs. mapping assembly, reference genome quality) impact transcriptome quality and inference of differential gene expression (DE). We find that transcriptome assembly and gene expression profiling (edgeR vs. baySeq software) works well even in the absence of a reference genome, and is robust across a broad range of parameters. We advise against library normalization, and in most situations advocate mapping assemblies to an annotated genome of a divergent sister clade, which generally outperformed de novo assembly (Trans-Abyss, Trinity, SOAPdenovo-Trans). Transcriptome complexity (size, paralogs, alternative splicing isoforms) negatively affected the assembly and DE profiling, whereas the effects of sequencing error and polymorphism were almost negligible. Finally, we highlight the challenge of gene name assignment for de novo assemblies, the importance of mapping strategies, and raise awareness of challenges associated with the quality of reference genomes. Overall, our results have significant practical and methodological implications, and can provide guidance in the design and analysis of RNA-seq experiments, particularly for organisms where genomic background information is lacking.
Data from: A whole-transcriptome approach to evaluating reference genes for quantitative gene expression studies: a case study in Mimulus
While quantitative PCR (qPCR) is widely recognized as being among the most accurate methods for quantifying gene expression, it is highly dependent on the use of reliable, stably expressed reference genes. With the increased availability of high-throughput methods for measuring gene expression, whole-transcriptome approaches may be increasingly utilized for reference gene selection and validation. In this study, RNA-seq was used to identify a set of novel qPCR reference genes and evaluate a panel of traditional "housekeeping" reference genes in two species of the evolutionary model plant genus Mimulus. More broadly, the methods proposed in this study can be used to harness the power of transcriptomes to identify appropriate reference genes for qPCR in any study organism, including emerging and nonmodel systems. We find that RNA-seq accurately estimates gene expression means in comparison to qPCR, and that expression means are robust to moderate environmental and genetic variation. However, measures of expression variability were only in agreement with qPCR for samples obtained from a shared environment. This result, along with transcriptome-wide comparisons, suggests that environmental changes have greater impacts on expression variability than on expression means. We discuss how this issue can be addressed through experimental design, and suggest that the ever-expanding pool of published transcriptomes represents a rich and low-cost resource for developing better reference genes for qPCR.
Data from: Comparative transcriptomic analysis revealed adaptation mechanism of Phrynocephalus erythrurus, the highest altitude lizard living in the Qinghai-Tibet Plateau
Background: Organisms living at high altitudes must overcome three major environmental challenges: hypoxia, cold, and intense UV radiation. The molecular mechanisms that enable these challenges to be overcome have mainly been studied in endothermic organisms; relatively little attention has been paid to poikilothermic species. Here, we present deep transcriptome sequencing in two closely related lizards, the high altitude-dwelling Phrynocephalus erythrurus and the lowland-dwelling P. putjatia, to identify candidate genes under positive selection and to explore the convergent evolutionary adaptation of poikilothermic animals to high altitude life. Results: More than 70 million sequence reads were generated for each species via Illumina sequencing. De novo assembly produced 56,845 and 63,140 transcripts for P. erythrurus and P. putjatia, respectively. P. erythrurus had higher Ka/Ks ratios than P. putjatia, implying an accelerated evolutionary rate in the high altitude lizard lineage. 206 gene ontology (GO) categories with accelerated evolutionary rates and 43 candidate positively selected genes were detected along the P. erythrurus lineage. Some of these GO categories have functions associated with responses to hypoxia, energy metabolism and responses to UV damage. We also found that the high-altitude ranid frog R. kukunoris had higher Ka/Ks ratios than the closely related low-altitude frog R. chensinensis, and that the functional categories with accelerated evolutionary rates in R. kukunoris overlapped extensively with those detected along the P. erythrurus lineage. Conclusions: The mechanisms of high altitude adaptation in P. erythrurus were tentatively inferred. By comparing two pairs of low- and high-altitude poikilothermic species, we found that similar functional categories had undergone positive selection in high altitude-dwelling Phrynocephalus and Rana lineages, indicating that similar mechanisms of adaptation to high altitude might have evolved in both genera. Our findings provide important guidance for future functional studies on high altitude adaptation in poikilothermic animals.
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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.