Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Type 2 Diabetes Specific Spatial Differential Gene Expression in Pancreas Visium Data

ABSTRACT: Understanding the spatial distribution of gene expression in the pancreas could provide new insights into its function and islet biology. Visium spatial gene expression is a powerful tool for quantifying gene expression of cells within their spatial context. We describe the generation and analysis of spatial transcriptomics data from six pancreas samples from healthy donors. Our analysis revealed high expression of INS within islets. However, we also identified a bleed of highly abundant islet genes (e.g., INS, GCG) into surrounding tissue areas. Through computational analyses, we successfully corrected for this bleed. We then identify genes which are spatially differentially expressed in the Type 2 Diabetes samples. We provide these data for researchers to study the organization of the pancreas and islets.

ORGANISM(S): Homo sapiens

PROVIDER: GSE264331 | GEO | 2024/08/31

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

RNA-Seq analysis of porcine islets and pancreas to characterize the differentially expressed genes between higher and lower islet density

Project description:Gene expression patterns that form the basis for the observed variation in islet density among porcine pancreata were examined. RNA-Seq analysis was performed to investigate differential gene expression of intact porcine pancreas samples and pure cultured islet samples according to a density of islets. Most prominently upregulated genes in the islet-rich pancreas samples included GP2 and GCG. The mRNA expression of pure islet cell samples from both groups were statistically identical. This transcriptome RNA-Seq analysis showed that pancreatic islet density is associated with GP2 expression.

2021-12-31 | GSE158226 | GEO

RNA-seq of Ins+ cells in human differentiation protocol across lines and isolated from human islets

Project description:The aim of this experiment was to observe the transcriptional profile of Ins+ cells in human cadaveric islets and at the terminal stage of our in vitro beta-cell differentiation protocol across both the Hues8 and H1 cell lines. One polyhormonal sample (Ins+/Gcg+) was also sorted for additional comparison.

2015-03-20 | E-MTAB-3429 | biostudies-arrayexpress

Single-cell transcriptional landscape of human embryonic limb development - Visium

Project description:We performed spatial transcriptomic experiments using the 10x Visium assay, generating high-quality transcriptomic profiles for samples from PCW5 to PCW8

2022-04-15 | E-MTAB-10367 | biostudies-arrayexpress

Endocrine cell type sorting and mature architecture in the islets of Langerhans require expression of Roundabout receptors in β cells

Project description:The spatial architecture of the islets of Langerhans is hypothesized to facilitate synchronized insulin secretion among β cells, yet testing this in vivo in the intact pancreas is challenging. Robo βKO mice, in which the genes Robo1 and Robo2 are deleted selectively in β cells, provide a unique model of altered islet spatial architecture without loss of β cell differentiation or islet damage from diabetes. Combining Robo βKO mice with intravital microscopy, we show here that Robo βKO islets have reduced synchronized intra-islet Ca2+ oscillations among β cells in vivo. We provide evidence that this loss is not due to a β cell-intrinsic function of Robo, mis-expression or mis-localization of Cx36 gap junctions, or changes in islet vascularization or innervation, suggesting that the islet architecture itself is required for synchronized Ca2+ oscillations. These results have implications for understanding structure-function relationships in the islets during progression to diabetes as well as engineering islets from stem cells.

2024-08-26 | GSE275474 | GEO

Spatial transcriptomics (Visium, 10x Genomics) data of Duchenne mouse models

Project description:Quadricep sections of 10µm thick were placed on Visium spatial transcriptomics slide to obtain spatial datasets for these skeletal muscle sections

2023-06-28 | GSE199659 | GEO

Visium Spatial transcriptomics analysis of human primary colorectal cancer

Project description:To reveal the spatial distribution and the difference gene expression pattern of cancer cells in colorectal cancer, Visium spatial transcriptomics of four CRC patients was applied

2023-03-14 | GSE226997 | GEO

Comparing 10x Visium spatial transcriptomic technologies

Project description:Spatial transcriptomics facilitates the understanding of gene expression within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics’ Visium which provides whole tissue section profiling, enabling whole transcriptome spatial analysis. Our dataset comprises spleen tissue from mice infected with malaria, spanning multiple experiments and sample preparation protocols for tissue preservation, either as fresh frozen at optimal cutting temperature (OCT) or formalin-fixed paraffin-embedded (FFPE). Tissue placement was also considered, comparing direct tissue placement on the slide with the use of CytAssist (CA), which expands the Visium platform’s capabilities by allowing for the pre-selection of tissue sections and genes through a set of probes. We also include a matching scRNA-seq dataset that can be integrated with the spatial data.

2024-02-26 | GSE254652 | GEO

Spatial transcriptomics of gastric cancers (Visium 10X platform)

Project description:A total of 9 primary gastric cancers (1 pair of primary-metastasis, GC6) analyzed using Visium 10X platform-based spatial transcriptomics.

2023-12-26 | GSE251950 | GEO

Genome-wide effect of islet isolation and in vitro culture on gene expression profile of pancreatic beta-cells enriched tissue.

Project description:It is known that the stresses encountered during islet isolation have deleterious effects on beta-cell physiology. The nature of these effects, however, is incompletely known, partly due to the heterogeneity of islet preparations. The objective was to assess the genome-wide effect of islet isolation and in-vitro culture on beta-cell transcriptome. Beta cells identified by their intrinsic autofluorescence, were captured from donor pancreas and isolated islets using Laser Capture Microdissection. Beta cells from donor pancreas serve as the control. Our results indicated induction of a strong inflammatory response induced by islet isolation which continues during in vitro culture manifested by upregulation of several cytokines, chemokines and their receptors. IL-8 was induced by 3.6-fold and 56-fold in fresh and 3-days cultured islets respectively. Concordantly, several pancreatic progenitor cell-specific transcription factors like were upregulated in cultured islets, suggesting progressive transformation of mature beta-cell phenotype toward an immature endocrine cell phenotype. There are three sample types in our experiment; 1) beta-cells captured from the frozen sections of donor pancreas n=8, 2) beta cells extracted from islets frozen immediately after isolation (d0 islets) n=8 and, 3) beta cells extracted from isolated islets frozen after culturing for 3 days (d3 islets) n=5. For the analysis, beta cells from pancreas were considered as the reference point.

2012-02-12 | E-GEOD-29113 | biostudies-arrayexpress

Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples

Project description:We designed a Nextflow DSL2-based pipeline, Spatial Transcriptomics Quantification (STQ), for simultaneous processing of 10x Genomics Visium spatial transcriptomics data and a matched hematoxylin and eosin (H&E)-stained whole slide image (WSI), optimized for Patient-Derived Xenograft (PDX) cancer specimens. Our pipeline enables the classification of sequenced transcripts for deconvolving the mouse and human species and mapping the transcripts to reference transcriptomes. We align the H&E WSI with the spatial layout of the Visium slide and generate imaging and quantitative morphology features for each Visium spot. The pipeline design enables multiple analysis workflows, including single or dual reference genomes input and stand-alone image analysis. We show the utility of our pipeline on a dataset from Visium profiling of four melanoma PDX samples. The clustering of Visium spots and clustering of H&E imaging features reveal similar patterns arising from the two data modalities.

2024-05-21 | GSE238004 | 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