Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations

ABSTRACT: A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations

PROVIDER: PRJNA356865 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR5092420.fastq.gz	Fastqsanger.gz
	SRR5092415.fastq.gz	Fastqsanger.gz
	SRR5092416.fastq.gz	Fastqsanger.gz
	SRR5092417.fastq.gz	Fastqsanger.gz
	SRR5092418.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 6

Similar Datasets

A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations [gene expression]

Project description:Recent advances highlight the power of small molecules for promoting cellular reprogramming. Yet, the full potential of such chemicals in cell fate manipulation and the underlying mechanisms needs further characterization. Through functional screening assays, we found that mouse embryonic fibroblast can be induced to trans-differentiate into a wide range of somatic lineages simultaneously by treatment with a combination of four chemicals. Genomic analysis of the process indicates activation of multi-lineage modules and relaxation of epigenetic silencing programs. In addition, we identify Sox2 as an important regulator within the induced network. Single cell analysis uncovers a priming state that enables transition from fibroblast cells to diverse somatic lineages. Finally, we demonstrate that modification of the culture system enables directional trans-differentiation towards cardiac, neuronal or adipocytic lineages. Our study describes a cell fate control system that may be harnessed for regenerative medicine. We used microarrays to detect the global gene expression patterns underlying induced multi-lineage trans-differentiation

2017-01-17 | GSE91005 | GEO

A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations [ChIP-seq]

2017-01-17 | GSE91373 | GEO

A molecular roadmap for induced multi-lineage trans-differentiation of fibroblasts by chemical combinations.

Project description:Recent advances have demonstrated the power of small molecules in promoting cellular reprogramming. Yet, the full potential of such chemicals in cell fate manipulation and the underlying mechanisms require further characterization. Through functional screening assays, we find that mouse embryonic fibroblast cells can be induced to trans-differentiate into a wide range of somatic lineages simultaneously by treatment with a combination of four chemicals. Genomic analysis of the process indicates activation of multi-lineage modules and relaxation of epigenetic silencing programs. In addition, we identify Sox2 as an important regulator within the induced network. Single cell analysis uncovers a novel priming state that enables transition from fibroblast cells to diverse somatic lineages. Finally, we demonstrate that modification of the culture system enables directional trans-differentiation towards myocytic, glial or adipocytic lineages. Our study describes a cell fate control system that may be harnessed for regenerative medicine.

| S-EPMC5339836 | biostudies-literature

A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations

Project description:This SuperSeries is composed of the SubSeries listed below.

2017-01-17 | GSE91374 | GEO

A network-based trans-omics approach for predicting synergistic drug combinations

Project description:A network-based trans-omics approach for predicting synergistic drug combinations

| PRJNA1068432 | ENA

A network-based trans-omics approach for predicting synergistic drug combinations

Project description:We examined the mode-of-action of synergistic drug combinations by microarray analysis. We focused on the drug combination of capsaicin and mitoxantrone, which were the top predicted drug pair identified by SyndrumNET. Combination therapy can offer greater efficacy on medical treatments. However, the discovery of synergistic drug combinations is challenging. We propose a novel computational method, SyndrumNET, to predict synergistic drug combinations by network propagation with trans-omics analyses. The prediction is based on the topological relationship, network-based proximity, and transcriptional correlation between diseases and drugs. SyndrumNET was applied to analyzing six diseases including asthma, diabetes, hypertension, colorectal cancer, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML), and it outperformed the previous methods in terms of high accuracy. We performed in vitro cell survival assays to validate our prediction for CML. Of the top 17 predicted drug pairs, 14 drug pairs successfully exhibited synergistic anticancer effects. Our mode-of-action analysis also revealed that the drug synergy of the top predicted combination of capsaicin and mitoxantrone was due to the complementary regulation of 12 pathways, including the Rap1 signaling pathway. The proposed method is expected to be useful for various complex diseases.

2024-05-06 | GSE254052 | GEO

Mus musculus

Project description:A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations [gene expression]

| PRJNA356872 | ENA

Mus musculus

Project description:A Molecular Roadmap for Induced Multi-lineage Trans-differentiation of Fibroblasts by Chemical Combinations [ChIP-seq]

| PRJNA356873 | ENA

Direct reprogramming of mouse fibroblasts into cardiomyocytes with chemical cocktails

2015-08-23 | GSE69924 | GEO

Direct reprogramming of mouse fibroblasts into cardiomyocytes with chemical cocktails

Project description:The direct conversion, or trans-differentiation, of non-cardiac cells into cardiomyocytes by forced expression of transcription factors and microRNAs provide promising ways of cardiac regeneration. However, genetic manipulations are still not desirable in real clinical applications. we report the generation of automatically beating cardiomyocyte-like cells from mouse fibroblasts with only chemical cocktails. These chemical-induced cardiomyocyte-like cells (CiCMs) express cardiomyocyte-specific markers, exhibit sarcomeric organization, and possess typical cardiac calcium flux and electrophysiological features. Microarray-bassed gene expression patterns of Mouse embryonic fibroblasts (MEFs), CiCMs, and cardiomyocytes(CMs) indicated a clear transition from dividing MEFs to differentiated cardiomyocyte-like state in CiCM samples. Mouse embryonic fibroblasts were treated with a small-molecule combination CRFVPT (10 μM CHIR99021 (C); 10 μM RepSox (R); 50 μM Forskolin (F); 0.5 mM VPA (V); 5 μM Parnate, (P); 1 μM TTNPB (T)) to induce transdifferentiation to chemical-induced cardiomyocyte-like cells. CiCMs beating clusters were picked at day 24 for analysis. MEFs were isolated from mouse embryos, and CMs were isolated from mouse hearts. Total RNA of MEFs, CiCMs and CMs were extracted and hybridization on Affymetrix microarrays.

2015-08-23 | E-GEOD-69924 | biostudies-arrayexpress

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