Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Spatially resolved transcriptome of brain white matter brain lesions of a patient with progressive multiple sclerosis

ABSTRACT: Different lesion types were microdissected out from snap-frozen white matter and placed on visium slides. Optimization of RNA release and visualization with Nikon Ecclipse Ti2 were followed by barcoded recover, library preparation and sequencing.

ORGANISM(S): Homo sapiens

PROVIDER: GSE231586 | GEO | 2024/06/21

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

DNA accessibility profiling at the single nucleus level of post mortem white matter brain tissue of patients with progressive multiple sclerosis and non-neurological disease controls

Project description:Different lesion types were microdissected out from snap-frozen white matter. Brain nuclei were fluorescence-activated nuclear sorted and treated with Transposase Tn5. Gel beads-in-emulsion was generated, barcoded followed by library construction and sequencing.

2024-06-21 | GSE231584 | GEO

Gene expression profiling at single nucleus level of microdissected white matter tissue samples of patients with progressive multiple sclerosis and non-neurological disease controls

Project description:Different lesion types were microdissected out from snap-frozen white matter tissue. Brain nuclei were fluorescence-activated nuclear sorted. Gel beads-in-emulsion was generated, barcoded, reverse transcribed followed by library construction and sequencing.

2024-06-21 | GSE231585 | GEO

Spatially resolved transcriptomic profiling: an experimental comparison of GeoMx Digital Spatial Profiling and Visium CytAssist spatial transcriptomics in three cancer types (GeoMx)

Project description:We performed Visium CytAssist (10X), GeoMx DSP (Nanostring) and Chromium Flex (10X Genomics) full transcriptome profiling on Breast Cancer (BC), Lung Cancer (LC) and diffuse large B cell lymphoma (DLBCL) samples from archival FFPE blocks. We explore the data quality across blocks with different storage times and DV200 values for all the three methods. We compared the cell type signature purity between ST methods Visium and GeoMx by utilising pathology annotations and scRNAseq. For the Visium and Chromium methods with a large number of data points we explored the heterogeneity between tissues. Finally, we demonstrate the discovery of patient-specific tumor-TME interactions across all three methods.

2024-11-01 | E-MTAB-14566 | biostudies-arrayexpress

Identification of spatially-resolved markers of malignant transformation in Intraductal Papillary Mucinous Neoplasms. [Visium]

Project description:Spatial transcriptomics characterization of IPMN samples by Visium Gene Expression FFPE

2024-02-15 | GSE229877 | GEO

Spatially resolved transcriptomic analysis of acute kidney injury in a female murine model

Project description:We optimized and validated a female bilateral ischemia reperfusion injury model. Using the 10X Genomics Visium Spatial Gene Expression solution, we generated spatial maps of gene expression across the injury and repair time course, and applied two open-source computational tools, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics. An ischemia time of 34 minutes in a female murine model resulted in comparable injury to males across the time course of injury and repair. We report increased resolution of cell and gene expression with Giotto, a computational toolbox for spatial data analysis. Using a seeded non-negative matrix regression (SPOTlight) to deconvolute the dynamic landscape of cell-cell interactions, we find that injured proximal tubule cells are characterized by increasing macrophage and lymphocyte interactions even at 6 weeks after injury, consistent with a pro-inflammatory role for this cell state. In this transcriptomic atlas, we defined region-specific and injury-induced loss of differentiation markers and their re-expression during repair, as well as region-specific injury and repair transcriptional responses. Lastly, we created a data visualization web application for the scientific community to explore these results (http://humphreyslab.com/SingleCell/).

2021-11-22 | GSE182939 | GEO

Spatially resolved transcriptomic profiling: an experimental comparison of GeoMx Digital Spatial Profiling and Visium CytAssist spatial transcriptomics in three cancer types (Chromium and Visium)

2024-11-01 | E-MTAB-14560 | biostudies-arrayexpress

Dissecting the brain with spatially resolved multi-omics.

Project description:Recent studies have highlighted spatially resolved multi-omics technologies, including spatial genomics, transcriptomics, proteomics, and metabolomics, as powerful tools to decipher the spatial heterogeneity of the brain. Here, we focus on two major approaches in spatial transcriptomics (next-generation sequencing-based technologies and image-based technologies), and mass spectrometry imaging technologies used in spatial proteomics and spatial metabolomics. Furthermore, we discuss their applications in neuroscience, including building the brain atlas, uncovering gene expression patterns of neurons for special behaviors, deciphering the molecular basis of neuronal communication, and providing a more comprehensive explanation of the molecular mechanisms underlying central nervous system disorders. However, further efforts are still needed toward the integrative application of multi-omics technologies, including the real-time spatial multi-omics analysis in living cells, the detailed gene profile in a whole-brain view, and the combination of functional verification.

| S-EPMC10422112 | biostudies-literature

Spatially resolved gene expression of human protate tissue slices treated with steroid hormones for 8 hours

Project description:Spatially resolved gene expression was prepard by dissociated hman prostate tissue to single cells, and collected & prepped for RNA-seq using the Visium Spatial Gene Expression kit. 5000 cells were collected and sequenced at a depth of 50k cells/gene on a 2X150nt lane in a NovaSeq 6000. SpaceRanger alignment was performed to produce the RAW files

2021-01-19 | GSE159697 | GEO

Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

Project description:Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer’s disease (AD), but little is known about the molecular mechanisms underlying this regional vulnerability. Here we utilize the 10x Visium platform to define the spatial transcriptomic profile in both AD and control (CT) MTG. We identify unique marker genes for cortical layers and the white matter, and layer-specific differentially expressed genes (DEGs) in human AD compared to CT. Deconvolution of the Visium spots showcases the significant difference in particular cell types among cortical layers and the white matter. Gene co-expression analyses reveal eight gene modules, four of which have significantly altered co-expression patterns in the presence of AD pathology. The co-expression patterns of hub genes and enriched pathways in the presence of AD pathology indicate an important role of cell-cell-communications among microglia, oligodendrocytes, astrocytes, and neurons, which may contribute to the cellular and regional vulnerability in early AD. Using single-molecule fluorescent in situ hybridization, we validated the cell-type-specific expression of three novel DEGs (e.g., KIF5A, PAQR6, and SLC1A3) and eleven previously reported DEGs associated with AD pathology (i.e., amyloid beta plaques and intraneuronal neurofibrillary tangles or neuropil threads) at the single cell level. Our results may contribute to the understanding of the complex architecture and neuronal and glial response to AD pathology of this vulnerable brain region.

2022-12-21 | GSE220442 | GEO

Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples

Project description:Spatially resolved transcriptomics has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of unbiased SRT methods targeting the polyA tail of mRNA, relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available SRT assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), an SRT workflow designed to improve mRNA recovery from fresh frozen specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we demonstrate the RRST protocol on tissue sections collected from five challenging tissue types, including: human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyzed 52 tissue sections and our results demonstrate that RRST is a versatile, powerful, and reproducible protocol for FF specimens of different qualities and origins.

2022-12-25 | GSE221571 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data