Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Spatiotemporal heterogeneity of inflammatory changes in Alzheimer's disease analyzed spatially resolved transcriptome

ABSTRACT: Spatiotemporal heterogeneity of inflammatory changes in Alzheimer's disease analyzed spatially resolved transcriptome

PROVIDER: PRJNA729436 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR14509187_1.fastq.gz	Fastqsanger.gz
	SRR14509187_2.fastq.gz	Fastqsanger.gz
	SRR14509188_1.fastq.gz	Fastqsanger.gz
	SRR14509188_2.fastq.gz	Fastqsanger.gz
	SRR14509189_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 8

Similar Datasets

Spatiotemporal heterogeneity of inflammatory changes in Alzheimer's disease analyzed spatially resolved transcriptome

Project description:We investigated spatiotemporal molecular patterns related to AD pathophsiology using spatially resolved transcriptome of the AD mouse model. The late change of gray matters of AD was commonly related to neuroinflammation, while the early change in the white matter of AD represented neuronal projection and ensheathment of axons before the amyloid plaques accumulation. Disease-associated microglia and astrocyte signatures were spatially differently enriched. Our results provide a key spatiotemporally heterogeneous molecular change particularly related to inflammation in AD.

2024-01-10 | GSE174321 | GEO

Spatially resolved epigenomic profiling of single cells in complex tissues

Project description:The recent development of spatial omics enables single-cell profiling of the transcriptome and the 3D organization of the genome in a spatially resolved manner. A spatial epigenomics method would expand the repertoire of spatial omics tools and accelerate our understanding of the spatial regulation of cellular processes and tissue functions. Here, we developed an imaging approach for spatially resolved profiling of epigenetic modifications in single cells

2022-12-16 | GSE191069 | GEO

High-sensitive spatially resolved T cell receptor sequencing with SPTCR-seq

Project description:Understanding the spatial distribution of T cells is pivotal to decrypting immune dysfunction in cancer. Current spatially resolved transcriptomics fall short in directly annotating T cell receptors (TCRs), limiting the comprehension of anti-cancer immunity. We introduce a novel technology, Spatially Resolved T Cell Receptor Sequencing (SPTCR-seq), integrating target enrichment and long-read sequencing for highly sensitive TCR sequencing. This approach yields an on-target rate of ~85%, and via a bespoke computational pipeline, it provides meticulous spatial mapping, error correction, and UMI refinement. SPTCR-seq outperforms PCR-based methods, offering superior reconstruction of the complete TCR architecture, inclusive of V, D, J regions and the vital complementarity-determining region 3 (CDR3). Applying SPTCR-seq, we reveal local T cell diversity, clonal expansion, and transcriptional evolution across spatially distinct niches in glioblastoma, identifying critical involvement of NK and B cells in spatial T cell adaptation. SPTCR-seq, by bridging spatially resolved omics and TCR sequencing, stands as a robust tool for exploring T cell dysfunction in cancers and beyond.

2023-07-25 | GSE238071 | GEO

Spatially resolved transcriptomics reveals innervation-responsive functional cluster in skeletal muscle.

Project description:Striated muscle is a highly organized structure composed by well-defined anatomical domains with integrated but distinct assignments. Indeed, the lack of a direct correlation between tissue architecture and gene expression has thus far limited our understanding of how each unit responds to physio-pathologic contexts. Here, we show how the combined use of spatially resolved transcriptomics and immunofluorescence can bridge this gap by enabling the unbiased identification of such domains and the characterization of their response to external perturbations. Using a spatiotemporal analysis, we followed the changes in the transcriptomics profile of specific domains in muscle in a model of denervation. Furthermore, our approach allowed us to identify the spatial distribution and nerve dependence of atrophic signalling pathway and polyamine metabolism to glycolytic fibres. Indeed, we demonstrate a pronounced alteration of polyamine homeostasis upon denervation.

2022-12-19 | GSE198596 | GEO

Spatially resolved multiomics of human cardiac niches - Visium

Project description:Spatially resolved multiomics of human cardiac niches - Visium

| PRJEB62497 | ENA

A spatially resolved multiomic single-cell atlas of soybean development

Project description:Cis-regulatory elements (CREs) precisely control the spatiotemporal gene expression in cells. Using a spatially resolved single-cell atlas of gene expression and chromatin accessibility across ten soybean tissues, we identified 103 distinct cell types and 303,199 accessible chromatin regions (ACRs). Nearly 40% of ACRs showed cell-type-specific patterns and were enriched for transcription factor (TF) binding motifs controlling cell-type specification and maintenance. We identified non-cell autonomous activity of NIN-LIKE PROTEIN 7 (NLP7), the Nodule Inception (NIN) gene regulatory network and de novo enriched TF motifs in the nodule infected cells. With comprehensive developmental trajectories for endosperm and embryo, we found that 13 sucrose transporters, sharing the DOF11 binding motif, were co-up-regulated in late peripheral endosperm and identified the key embryo cell-type specification regulators during embryogenesis, including a homeobox TF that promotes cotyledon parenchyma identity. This resource provides a valuable foundation for analyzing gene regulatory programs in soybean cell types across tissues and life stages.

2024-07-05 | GSE270392 | GEO

Mapping spatially resolved transcriptomes in human and mouse pulmonary fibrosis

Project description:Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis and limited treatment options. Efforts to identify effective treatments are thwarted by limited understanding of IPF pathogenesis and poor translatability of available preclinical models. To address these limitations, we generated spatially resolved transcriptome maps of human IPF and bleomycin-induced mouse lung fibrosis.

2024-05-21 | GSE267904 | GEO

Spatial-CUT&Tag: Spatially resolved chromatin modification profiling at the cellular level

Project description:Spatial omics emerged as a new frontier of biological and biomedical research. Here, we present spatial-CUT&Tag for spatially resolved genome-wide profiling of histone modifications by combining in situ CUT&Tag chemistry, microfluidic deterministic barcoding, and next-generation sequencing. Spatially resolved chromatin states in mouse embryos revealed tissue-type-specific epigenetic regulations in concordance with ENCODE references and provide spatial information at tissue scale. Spatial-CUT&Tag revealed epigenetic control of the cortical layer development and spatial patterning of cell types determined by histone modification in mouse brain. Single-cell epigenomes can be derived in situ by identifying 20-micrometer pixels containing only one nucleus using immunofluorescence imaging. Spatial chromatin modification profiling in tissue may offer new opportunities to study epigenetic regulation, cell function, and fate decision in normal physiology and pathogenesis.

2022-02-10 | GSE165217 | GEO

Spatially Resolved Proteomics via Tissue Expansion

Project description:Spatially resolved proteomics is an emerging approach, however, it remains technically challenging due to the complexity of the tissue microsampling techniques and mass spectrometry analysis of nanoscale specimen volumes. Here, we describe an expansion proteomics method ProteomEx, a combination of tissue expansion with mass spectrometry-based proteomics, which enables quantitative assessment of the spatial variability of the proteome in mammalian tissues at ~125 µm lateral resolution equivalent to the tissue volume of 0.7 nL using manual microsampling without the need for a custom or special equipment. We validated and demonstrated the utility of ProteomEx for high-throughput large-scale proteomics profiling of biological tissues including brain, liver, and breast cancer. We further applied ProteomEx for identifying proteins associated with Alzheimer's disease in a mouse model by comparative proteomic analysis of brain subregions.

2022-11-04 | PXD037950 |

A spatially resolved single cell atlas of human gastrulation

Project description:A spatially resolved single cell atlas of human gastrulation

| PRJEB40781 | ENA