Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Sci-Space E14 Mouse Embryo Data

ABSTRACT: Spatial patterns of gene expression span many scales, and are shaped by both local (e.g. cell-cell interactions) and global (e.g. tissue, organ) context. However, most in situ methods for profiling gene expression either average local contexts or are restricted to limited fields of view. Here we introduce sci-Space, a scale-flexible method that retains single cell resolution while resolving spatial heterogeneity in gene expression at larger scales. As a proof-of-concept, we apply sci-Space to the developing mouse embryo (E14), capturing the approximate spatial coordinates of profiled cells from whole embryo serial sections.

ORGANISM(S): Mus musculus

PROVIDER: GSE166692 | GEO | 2021/07/01

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Sci-Space E14 Mouse Embryo Data

Project description:Sci-Space E14 Mouse Embryo Data

| PRJNA701618 | ENA

Characterizing the temporal dynamics of gene expression in single cells with sci-fate

Project description:Gene expression is a dynamic process on multiple scales, e.g. the cell cycle, response to stimuli, normal differentiation and development, etc. However, nearly all techniques for profiling gene expression in single cells fail to directly capture these temporal dynamics, which limits the scope of biology that can be effectively investigated. Towards addressing this, we developed sci-fate, a new technique that combines S4U labeling of newly synthesized mRNA with single cell combinatorial indexing (sci-), in order to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. As a proof-of-concept, we applied sci-fate to a model system of cortisol response, and characterized expression dynamics in over 6,000 single cells. From these data, we quantify the dynamics of the cell cycle and of glucocorticoid receptor activation, while also exploring their intersection. We furthermore use these data to develop a framework for estimating cell state transition probabilities, and to identify factors whose dynamic expression potentially regulates these transitions. The experimental and computational methods described here may be broadly applicable to quantitatively characterize cell state dynamics in in vitro systems.

2020-04-12 | GSE131351 | GEO

sci-ATAC-seq data

Project description:sci-ATAC-seq data

| PRJNA785974 | ENA

sci-RNA-seq data

Project description:sci-RNA-seq data

| PRJNA785988 | ENA

Profiling immunological phenotypes in individuals during the first year after traumatic spinal cord injury (SCI): a longitudinal analysis

Project description:Individuals with SCI are severely affected by immune system changes, resulting in a SCI-induced immune deficiency syndrome (SCI-IDS). While recent data support that acute SCI-IDS symptoms differ from those present in the chronic phase, only limited data in humans is available. To characterize dynamic molecular and cellular immune phenotypes over the first year, we assess RNA (bulk-RNA sequencing), protein, and flow cytometry (FACS) profiles of blood samples from 12 individuals with SCI at 0-3 days and at 3, 6, and 12 months post injury (MPI) compared to 23 uninjured individuals (controls). We identified 967 differentially expressed (DE) genes in individuals with SCI (FDR<0.001) compared to controls. Within the first 6 MPI we detected a reduced expression of NK cell genes, consistent with reduced frequencies of CD56bright, CD56dim NK cells present at 12 MPI. Over 6MPI, we observed increased and prolonged expression of genes associated with inflammation (e.g. HMGB1, Toll-like receptor signaling) and expanded frequencies of monocytes acutely. Canonical T-cell related DE genes (e.g. FOXP3, TCF7, CD4) were upregulated during the first 6 MPI and increased frequencies of activated T cells at 3-12 MPI were observed. Neurological injury severity was reflected in distinct whole blood gene expression profiles at any time after SCI, indicating a persistent ‘neurogenic’ imprint. Overall, 2876 DE genes emerge when comparing profiles of motor complete to motor incomplete SCI (ANOVA, FDR<0.05), including genes related to neutrophils, inflammation, and infection. In summary, we identify dynamic SCI-IDS determinants in humans, including molecular and cellular profiles, which may provide potential targets to reduce inflammation, improve immunity, or serve as candidate biomarkers of injury severity.

2023-05-26 | GSE226238 | GEO

Differential gene expression following SCI in trkB.T1 null

Project description:We asked what genes are significantly differentially regulated in the spinal cord of SCI trkB.T1 WT and trkB.T1 KO mice. TrkB.T1 is upregulated shortly after SCI although the precise mechanisms underyling this upregulation are poorly understood. In the trkB.T1 null, we show less mechanical allodynia and better locomotor recovery following SCI. The microarray studies helped us to elucidate a signaling pathway that is differently regulated in the WT versus KO mice at 1 day after SCI. In this study, we did not examine gene changes within a genotype after SCI. Rather, we examined DGE by genotype at each time point. Spinal cord tissue from WT and KO mice in a sham condition (intact spinal cord) versus 1D, 3D and 7D following SCI was harvested for microarray analyses.

2015-12-07 | E-GEOD-42828 | biostudies-arrayexpress

Drug combination sci-Plex Data

Project description:Drug combination sci-Plex Data

| PRJNA851906 | ENA

Differential gene expression following SCI in trkB.T1 null

2015-12-07 | GSE42828 | GEO

Escherichia coli SCI-07

Project description:Escherichia coli SCI-07 Genome sequencing and assembly

| PRJNA82801 | ENA

Gene Expression profile of brain in SCI rat by MSC intravenous transplantation.

Project description:We had analysed gene expression profile of brain in SCI rat by MSC. Compared with MSC intravenous and vehicle injection at SCI day3. We used Clariom D / Gene Chip® Rat Transcriptome Array (RTA 1.0., Affymetrix, Santa Clara, CA, USA).

2018-09-01 | GSE108168 | 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