Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

An abundance of binary promoter switches in lineage-determining transcription factors indicates a digital component of cell fate determination

ABSTRACT: An abundance of binary promoter switches in lineage-determining transcription factors indicates a digital component of cell fate determination

PROVIDER: PRJNA1011326 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR25863313_1.fastq.gz	Fastqsanger.gz
	SRR25863313_2.fastq.gz	Fastqsanger.gz
	SRR25863314_1.fastq.gz	Fastqsanger.gz
	SRR25863314_2.fastq.gz	Fastqsanger.gz
	SRR25863315_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 32

Similar Datasets

An abundance of binary promoter switches in lineage-determining transcription factors indicates a digital component of cell fate determination

Project description:An examination of transcription factor genes revealed an abundance of convergent and divergent sense/antisense promoter pairs, suggesting that competing promoters may control cell fate determination. We used 5' single cell RNAseq (5' scRNAseq) to examine divergent and convergent transcription in CD34+ hematopoietic progenitors, freshly purified innate lymphocytes from tonisl, and peripheral blood NK cells

2023-10-27 | GSE242100 | GEO

Determining cell type abundance and expression from bulk tissues with digital cytometry.

Project description:Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.

| S-EPMC6610714 | biostudies-literature

Cell Fate Determining Molecular Switches and Signaling Pathway in Pax7-expressing Somitic Mesoderm

Project description:During development, different cell types are originated from a common progenitor at a specific time frame. Previous lineage tracing of Pax7+ progenitors in somitic mesoderm has built the foundation of its development trajectory towards dermis, brown adipocytes, and skeletal muscle at dorsal trunk. Yet the molecular switches and mechanisms of such differentiation remain unknown. By combining inducible lineage tracing and single-cell RNA sequencing, here we show the transcriptomic profile of the Pax7 lineage, precise differentiation time point, and transcription factors that could drive lineage-specific differentiation. Utilizing surface markers identified in each cell types, we successfully enriched brown adipocytes, dermal fibroblasts, and cell-type specific progenitors for in vitro culture. Further characterization has shown the importance of Wnt5a and Rgcc for lineage development during embryogenesis. We also propose eFAP (embryonic fibro/adipogenic progenitor) that resembles adult FAPs lineage potentials. The work provides further understanding of the Pax7 lineage during embryonic development.

2022-04-12 | GSE158887 | GEO

Efficient detection and purification of cell populations using synthetic microRNA switches

Project description:Isolation of specific cell types, including pluripotent stem cell (PSC)-derived populations, is frequently accomplished using cell surface antigens expressed by the cells of interest. However, specific antigens for many cell types have not been identified, making their isolation difficult. Here, we describe an efficient method for purifying cells based on endogenous miRNA activity. We designed synthetic mRNAs encoding a fluorescent protein tagged with sequences targeted by miRNAs expressed by the cells of interest. These miRNA switches control their own translation levels by sensing miRNA activities. Several miRNA switches (miR-1-, miR-208a-, and miR-499a-5p-switches) efficiently purified cardiomyocytes differentiated from human PSCs, and switches encoding the apoptosis inducer Bim enriched for cardiomyocytes without cell sorting. This approach is generally applicable, as miR-126-, miR-122-5p- and miR-375-switches purified endothelial cells, hepatocytes and INSULIN-producing cells differentiated from hPSCs, respectively. Thus, miRNA switches can purify cell populations for which other isolation strategies are unavailable.

2015-05-20 | GSE60633 | GEO

Cell Fate Determining Molecular Switches and Signaling Pathway in Pax7-expressing Somitic Mesoderm

Project description:Cell Fate Determining Molecular Switches and Signaling Pathway in Pax7-expressing Somitic Mesoderm

| PRJNA666903 | ENA

Massively parallel reporter assay for identification of RNA switches

Project description:RNA structural switches are key regulators of gene expression in bacteria, yet their characterization in Metazoa remains limited. Here we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3’UTR of the RORC transcript. In vivo DMS-MaPseq, coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated mRNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally-driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

2024-07-05 | GSE266058 | GEO

YAP and TAZ Dictate Binary Pan-Cancer Superclasses

Project description:YAP and TAZ Dictate Binary Pan-Cancer Superclasses

| PRJNA605473 | ENA

YAP and TAZ Dictate Binary Pan-Cancer Superclasses

Project description:This SuperSeries is composed of the SubSeries listed below. We defined pan-cancer binary classes based on distinct expression of YAP (and its paralog TAZ/ WWTR1) and YAP-responsive adhesion regulators. Combining informatics with in vivo and in vitro gain- and loss-of-function studies across multiple murine and human tumor types, we showed that opposite pro- or anti-cancer YAP activity functionally defines binary YAPon or YAPoff cancer classes that express or silence YAP, respectively. Essentially all leukemia and lymphoma fall into the YAPoff class, as do multiple neural and neuroendocrine YAPoff solid cancers. YAPoff solid cancers are frequently RB1-/-, such as retinoblastoma, small cell lung cancer and neuroendocrine prostate cancer. YAP-silencing was intrinsic to the cell-of-origin, or acquired with lineage-switching and drug-resistance. The binary cancer groups exhibit distinct YAP-dependent adhesive behavior, and pharmaceutical vulnerabilities, underscoring clinical relevance. Mechanistically, whereas YAP induces cell cycle genes in YAPon cancers, extensive RNAseq data showed that forced YAP expression in YAPoff cancers instead activated adhesion genes that are normally co-silenced with YAP. YAP regulates both of these anti-cancer adhesive or pro-cancer cell cycle programs through the TEAD DNA binding family (TEAD1-4). YAP/TEAD targets AP1-bound enhancers in YAPon cancers, but Chipseq studies revealed that in YAPoff cancers, YAP/TEAD instead targeted elements co-bound with neural and neuroendocrine lineage-defining basic helix-loop-helix (bHLH) and Homeobox transcription factors (e.g. NEUROD, ASCL1, NKX2, OTX2). A CRISPR screen revealed that, among the adhesion regulators, ITGAV/ITGB5 pair are required for YAP induced cytostasis in YAPoff cancers. YAP is thus pivotal across all cancer, but in opposite pro- or anti-cancer ways, which define contrasting genetic and drug sensitivities.

2021-06-21 | GSE144975 | GEO

Notch1 switches progenitor competence in inducing medulloblastoma

Project description:Notch1 switches progenitor competence in inducing medulloblastoma

| PRJNA727475 | ENA

Widespread N6-methyladenosine-dependent RNA Structural Switches Regulate RNA-Protein Interactions

Project description:We show that N6-methyladenosine (m6A), the most abundant internal modification in mRNA/lncRNA with still poorly characterized function, alters RNA structure to facilitate the access of RBM for heterogeneous nuclear ribonucleoprotein C (hnRNP C). We term this mechanism m6A-switch. Through combining PAR-CLIP with Me-RIP, we identify 39,060 m6A-switches among hnRNP C binding sites transcriptome-wide. We show that m6A-methyltransferases METTL3 or METTL14 knockdown decreases hnRNP C binding at 16,582 m6A-switches. Taken together, 2,798 m6A-switches of high confidence are identified to mediate RNA-hnRNP C interactions and affect diverse biological processes including cell cycle regulation. These findings reveal the biological importance of m6A and provide insights into the sophisticated regulation of RNA-RBP interactions through m6A-induced RNA structural remodeling.

2015-02-27 | GSE56010 | 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