Browse
Submit Data
Databases
API
Help

Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell RNA-Sequencing of neurons labeled by retrograde FastBlue tracing (BarcodeSeq)

ABSTRACT: Most cancers including pancreatic ductal adenocarcinoma (PDAC) are infiltrated by PNS neurons participating in their complex tumor microenvironment. However, their cell bodies and nuclei are located in the para- and pre-vertebral PNS ganglia located far from the tumor mass itself. Thus, molecular information on healthy organ- vs. cancer-infiltrating neurons is currently lacking in any sequencing dataset of healthy or tumor tissue. To specifically identify and molecularly characterize the identity and transcriptomes of PDAC-infiltrating neurons at single cell resolution, we developed “Trace-n-seq”. This method is based on retrograd tracing of axons from target tissues to their respective ganglia, followed by individual FACS-isolation and transcriptomic analysis. We characterized >2000 sympathetic and sensory neurons that infiltrate PDAC, healthy pancreas, or other abdominal organs.

INSTRUMENT(S): NextSeq 550

ORGANISM(S): Mus musculus

SUBMITTER:

PROVIDER: E-MTAB-12941 | biostudies-arrayexpress |

SECONDARY ACCESSION(S): ERP169722

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Single-cell RNA-Sequencing of pancreatic and PDAC stromal cells

Project description:Most cancers including pancreatic ductal adenocarcinoma (PDAC) are infiltrated by PNS neurons participating in their complex tumor microenvironment. However, their cell bodies and nuclei are located in the para- and pre-vertebral PNS ganglia located far from the tumor mass itself. Thus, molecular information on healthy organ- vs. cancer-infiltrating neurons is currently lacking in any sequencing dataset of healthy or tumor tissue. Here, we specifically isolate fibroblasts, immune, endothelial and PDAC cells and subject them to single-cell RNA-Sequencing using the 10x genomics platform.

2025-02-28 | E-MTAB-12906 | biostudies-arrayexpress

Co-culture of fibroblasts and pancreatic ductal adenocarcinoma cells with mouse peripheral ganglia

Project description:The peripheral nervous system (PNS) orchestrates organ function during homeostasis and stress. Most cancers including pancreatic ductal adenocarcinoma (PDAC) are infiltrated by PNS neurons participating in their complex tumor microenvironment. Here, we analyze the effect of neuronal interactions with fibroblasts and cancer cells with dorsal root and celiac ganglia. To this end, both cell types were co-cultured with both peripheral ganglia and subjected to bulk RNA-Sequencing.

2025-02-28 | E-MTAB-12899 | biostudies-arrayexpress

Mapping the cellular and molecular landscape of cardiac non-myocytes in murine type-2 diabetes

Project description:Here we define key single-cell transcriptional alterations within cardiac non-myocytes, from ventricles of spontaneously type-2 diabetic (db/db) and control (db/h) mouse hearts ([B6.BKS(D)-Lepr<db>/J], stock #000697). The cell preparation sequenced consisted of metabolically active, live and nucleated non-myocyte cells, which were depleted of endothelial cells. The objective of this experiment was to develop a framework for understanding the dynamics of cardiac cell networks in murine type-2 diabetes, as a resource for future mechanistic studies.

2022-11-29 | E-MTAB-11940 | biostudies-arrayexpress

Target mRNAs induce tailing and trimming of Ago2-loaded miRNAs in neurons

Project description:We show that target mRNAs trigger the non-templated addition of nucleotides (mainly adenosines and uridines) and shortening of their cognate miRNAs in primary hippocampal neurons. The induced effect is observable both in total RNA and in Ago2-associated RNA, demonstrating that the process is initiated in Ago2 bound miRNAs. Illumina Small RNA sequencing was performed on rat hippocampal neurons infected with different target mRNAs in different conditions. The data includes 3 independent experiments: 1. Hippocampal neurons (DIV15) 6 days after transducing them with target mRNAs (driven by the Synapsin promoter) against different miRNAs. Samples are titled "Syn-Target". Samples transduced with targets containing extensive complementarity are labeled "Ext" and those with Seed complementarity are labeled "Seed". 2. Hippocampal neurons (DIV16) 7 days after transducing them with an inducible target mRNA against miR-132, and inducing for different times with Doxycycline. Samples are titled "Time-course" 3. Hippocampal neurons (DIV16) 7 days after co-transducing them with FLAG/HA-Ago2 plus an inducible target mRNA against miR-132, and inducing them for different times with Doxycycline. Samples are titled "Time-course_Ago2"

2015-03-02 | E-GEOD-57663 | biostudies-arrayexpress

Expression data from of HD-iPSC and CON-iPSC neuron derivatives

Project description:Compared the global gene expression profiles of HD- and CON-iPSC-derived neurons We used microarrays to detail the global programme of gene expression for comparing the global gene expression profiles of HD- and CON-iPSC-derived neurons and facilitating studies of medium spiny neurons (MSN)-degenerative processes of Huntington's Disease (HD). By using a step-wise in vitro differentiation protocol combining EB formation, neural induction by small molecules, treatment with inhibitors of the TGFß pathway (SB431542) and the BMP pathway (LDN193189), and mechanical isolation/purification of neural progenitors and neurons, we induced 60-70% of control iPSCs or HD-iPSCs to differentiate into GABA- and DARPP-32- double positive neurons.

2015-09-02 | E-GEOD-59051 | biostudies-arrayexpress

DNA binding factors shape the mouse methylome at distal regulatory regions [RNA_seq]

Project description:To gain insights into the interplay between DNA methylation and gene regulation we generated a basepair resolution reference map of the mouse methylome in stem cells and neurons. High genome coverage allowed for a novel quantitative analysis of local methylation states, which identified Low Methylated Regions (LMR) with an average methylation of 30%. These regions are evolutionary conserved, reside outside of CpG islands and distal to promoters. They represent regulatory regions evidenced by their DNaseI hypersensitivity and chromatin marks of enhancer elements. LMRs are occupied by transcription factors (TF) and their reduced methylation requires TF binding while introduction of TF binding sites creates LMRs de novo. This dependency on TF activity is further evident when comparing the methylomes of embryonic stem cells and derived neuronal cells. LMRs present in both cell types are occupied by broadly expressed factors, while LMRs present at only one state are occupied by cell-type specific TFs. Methylome data can thus enhance the prediction of occupied TF binding sites and identification of active regulatory regions genome-wide. Our study provides reference methylomes for the mouse at two cell states, identifies a novel and highly dynamic feature of the epigenome that defines distal regulatory elements and shows that transcription factor binding dynamically shapes mammalian methylomes. RNA_sequencing of mouse embryonic stem (ES) cells and derived neuronal progenitors (NP).

2011-12-22 | E-GEOD-30280 | biostudies-arrayexpress

Genomic prevalence of heterochromatic H3K9me2 and transcription do not discriminate pluripotent from terminally differentiated cells (RNA-seq)

Project description:Cellular differentiation entails reprogramming of the transcriptome from a pluripotent to a unipotent fate. This process was suggested to coincide with a global increase of repressive heterochromatin, which results in a reduction of transcriptional plasticity and potential. Here we report the dynamics of the transcriptome and an abundant heterochromatic histone modification, dimethylation of histone H3 at lysine 9 (H3K9me2), during neuronal differentiation of embryonic stem cells. In contrast to the prevailing model, we find H3K9me2 to occupy over 50% of chromosomal regions already in stem cells. Marked are most genomic regions that are devoid of transcription and a subgroup of histone modifications. Importantly, no global increase occurs during differentiation, but discrete local changes of H3K9me2 particularly at genic regions can be detected. Mirroring the cell fate change many genes show altered expression upon differentiation. Quantitative sequencing of transcripts reveals however that the total number of active genes is equal between stem cells and several tested differentiated cell types. Together, these findings reveal high prevalence of a heterochromatic mark in stem cells and challenge the model of low abundance of epigenetic repression and resulting global transcription in stem cells. Instead cellular differentiation entails local rather than global changes in epigenetic repression and transcriptional activity. Our dataset comprises of 2 ChIP-seq samples using chromatin from embryonic stem (ES) cells and derived terminal neurons (TN) which was immunoprecipitated, using antibodies against H3K27me3 and H3K4me2. For the same cells we generated H3K9me2 ChIP-chip samples in biological replicates. For ES cells, neurons and mouse embryonic fibroblasts (MEFs) we generated biological replicates of RNA-seq data.

2011-06-21 | E-GEOD-27843 | biostudies-arrayexpress

Expression data from human ESCs-derived neural precursors (NPs) and neurons

Project description:We performed microarray analyses on human ESCs-derived NPs and neurons carrying loss-of-function mutation in the MeCP2 gene. Neural precursors and differentiating neurons at 2 and 4-week were used for RNA extraction and affymetrix microarrays. We added ERCC RNA spike-in controls to normalize to cell number input.

2013-10-01 | E-GEOD-50584 | biostudies-arrayexpress

Expression and SNP data from fibroblasts, iPSCs and neurons with four copies of SNCA, and equivalent cell lines from an unaffected first degree relative

Project description:This SuperSeries is composed of the following subset Series: GSE28365: Expression data from fibroblasts, iPSCs and neurons with four copies of SNCA, and equivalent cell lines from an unaffected first degree relative GSE28366: SNP data from genomic DNA from a subject, fibroblasts, iPSCs and neurons with four copies of SNCA, and genomic DNA from an unaffected first degree relative and equivalent cell lines Refer to individual Series from fibroblasts, iPSCs and neurons with four copies of SNCA, and equivalent cell lines from an unaffected first degree relative

2011-09-14 | E-GEOD-28367 | biostudies-arrayexpress

Neocortical projection neurons instruct inhibitory interneuron circuit development in a lineage dependent manner

Project description:Neocortical circuits consist of stereotypical motifs that must self-assemble during development. Recent evidence suggests the subtype identity of both excitatory projection neurons (PNs) and inhibitory interneurons (INs) is important for this process. We knocked out the transcription factor Satb2 in PNs to induce those of the intratelencephalic (IT)-type to adopt a pyramidal tract (PT)-type identity. Loss of IT-type PNs selectively disrupted the lamination and circuit integration of INs derived from the caudal ganglionic eminence (CGE). Strikingly, reprogrammed PNs demonstrated reduced synaptic targeting of CGE-derived INs relative to controls. In control mice, IT-type PNs targeted neighboring CGE INs while PT-type PNs did not in deep layers, confirming this lineage-dependent motif. Finally, single cell RNA-sequencing revealed that major CGE IN subtypes were conserved after loss of IT PNs, but with differential transcription of synaptic proteins and signaling molecules. Thus, IT-type PNs influence CGE-derived INs in a non-cell autonomous manner during cortical development.

2019-03-06 | GSE127724 | 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