Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Monolayer cells transcriptome of human embryonic stem cell differentiation

ABSTRACT: Monolayer cells transcriptome of human embryonic stem cell differentiation

PROVIDER: PRJNA880362 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Monolayer cells transcriptome of human embryonic stem cell differentiation

Project description:We examined the toxic effects of environmental pollutants on embryonic stem cell induced monolayer differentiation by RNA sequencing. RNA extraction was performed on monolayer cells exposed to multiple compounds during monolayer differentiation. The toxic effect of the compound on early embryonic development was obtained by analyzing the difference in RNA expression. Our study provides data closer to the toxic effects of human exposure to neonicotinoids, organophosphate esters and synthetic phenolic antioxidants.

2025-09-13 | GSE213301 | GEO

Embryonic stem sell differentiation time course

Project description:During in vitro differentiation, pluripotent stem cells undergo extensive remodeling of their gene expression profiles. While studied extensively at the transcriptome level, much less is known about protein dynamics, which might differ significantly from their mRNA counterparts. Here, we present deep proteome-wide measurements of protein levels during the differentiation of embryonic stem cells.

2017-01-10 | MSV000080461 | MassIVE

Metabolomics Workbench ST000003 - GNPS - Metabolomic analysis of mouse embryonic fibroblasts, embryonic stem cells, and induced pluripotent stem cells

Project description:mouse embryonic fibroblasts, embryonic stem cells, and induced pluripotent stem cells were compared via metabolomic analysis

2018-08-02 | MSV000082680 | GNPS

Anabolic Factors and Myokines Improve Differentiation of Human Embryonic Stem Cell Derived Skeletal Muscle Cells.

Project description:Skeletal muscle weakness is linked to many adverse health outcomes. Current research to identify new drugs has often been inconclusive due to lack of adequate cellular models. We have previously developed a scalable monolayer system to differentiate human embryonic stem cell (hESC) into mature skeletal muscle cells (SkMCs) within 26 days without cell sorting or genetic manipulation. Here, building on our previous work, we show that differentiation and fusion of myotubes can be further enhanced using the anabolic factors testosterone (T) and follistatin (F) in combination with a cocktail of myokines (C). Importantly, combined TFC treatment significantly enhanced both hESC-SkMC fusion index and expression of various skeletal muscle markers including the motor protein Myosin Heavy Chain (MyHC). Transcriptomic and proteomic analysis revealed oxidative phosphorylation as the most up-regulated pathway, suggesting energy metabolism is coupled to enhanced muscle differentiation. This cellular model will be a powerful tool for studying in vitro myogenesis and for drug discovery to further enhance muscle development or treat muscle diseases.

2022-04-04 | PXD025906 | Pride

Dynamic proteomic profiling of extra-embryonic endoderm differentiation in mouse embryonic stem cells

Project description:During mammalian pre-implantation development, the cells of the blastocyst’s inner cell mass differentiate into the epiblast and primitive endoderm lineages, which give rise to the fetus and extra-embryonic tissues, respectively. Extra-embryonic endoderm differentiation can be modeled in vitro by induced expression of GATA transcription factors in mouse embryonic stem cells. Here we use this GATA-inducible system to quantitatively monitor the dynamics of global proteomic changes during the early stages of this differentiation event and also investigate the fully differentiated phenotype, as represented by embryo-derived extra-embryonic endoderm (XEN) cells. Using mass spectrometry-based quantitative proteomic profiling with multivariate data analysis tools, we reproducibly quantified 2,336 proteins across three biological replicates and have identified clusters of proteins characterized by distinct, dynamic temporal abundance profiles. We first used this approach to highlight novel marker candidates of the pluripotent state and extra-embryonic endoderm differentiation. Through functional annotation enrichment analysis, we have shown that the downregulation of chromatin-modifying enzymes, the re-organization of membrane trafficking machinery and the breakdown of cell-cell adhesion are successive steps of the extra-embryonic differentiation process. Thus, applying a range of sophisticated clustering approaches to a time-resolved proteomic dataset has allowed the elucidation of complex biological processes which characterize stem cell differentiation and could establish a general paradigm for the investigation of these processes.

2015-06-13 | PXD001901 | Pride

Transcriptome analysis of human embryonic stem cell differentiation to endothelial cells

Project description:Transcriptome analysis of human embryonic stem cell differentiation to endothelial cells

| PRJNA484413 | ENA

Nucleosome positioning changes during human embryonic stem cell differentiation

Project description:Nucleosome positioning changes during human embryonic stem cell differentiation

| PRJNA200565 | ENA

Derivation and differentiation of haploid human embryonic stem cells

Project description:Derivation and differentiation of haploid human embryonic stem cells

| PRJNA291278 | ENA

Mouse embryonic stem cell phosphoproteome

Project description:Erk-driven differentiation of mouse embryonic stem cells

2019-10-22 | PXD008964 | Pride

Temporal multiomics gene expression data across human embryonic stem cell derived cardiomyocyte differentiation

Project description:Embryonic development has not been fully understood, despite significant advances in molecular and systems-level approaches. Human embryonic stem cells (hESCs) serve as a valuable in vitro model for studying early human developmental processes due to their ability to differentiate into all three germ layers. Here, we present a comprehensive multi-omics dataset generated by differentiating hESCs into cardiomyocytes via the mesodermal lineage, collecting samples at 10 distinct time points. We measured mRNA levels by mRNA sequencing (mRNA-seq), translation levels by ribosome profiling (Ribo-seq), and protein levels by quantitative mass spectrometry. Technical validation confirmed high quality and reproducibility across all datasets, with strong correlations between replicates. This extensive dataset provides critical insights into the complex regulatory mechanisms of cardiomyocyte differentiation and serves as a valuable resource for the research community, aiding in the exploration of mammalian development and gene regulation.

2024-08-14 | MSV000095595 | MassIVE

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