Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identification and functional characterization of long non-coding RNAs associated with epithelial-to-mesenchymal transition

ABSTRACT: Identification and functional characterization of long non-coding RNAs associated with epithelial-to-mesenchymal transition

PROVIDER: PRJNA417083 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Identification and functional characterization of long non-coding RNAs associated with epithelial-to-mesenchymal transition

Project description:In the last decade, new high-throughput sequencing techniques have revealed the complexity of the human transcriptome, allowing the characterization of long non-coding (lnc)RNAs. Since their expression has been reported as very specific to tissue, developmental stage and pathological variations, some lncRNAs have been proposed as biomarkers for diagnosis as well as prognosis of tumors. In this project, we aime in identification of lncRNAs associated with the epithelial-to-mesenchymal transition (EMT), a biological process that promotes metastasis. This was performed on an in vitro model (Castro Vega et al, 2015) in which primary HEK cells naturally undergo EMT. Cells were immortalized prior and after EMT, therefore giving rise to the Epi (HA5-Early) and Mes (HA5-Late) cell-lines, which respectively display epithelial and mesenchymal phenotypes. HOTAIR is one the lcnRNAs functionning as a scaffold to tether PRC2 and Lsd1/REST/coREST complexes to gene promoter to epigenetically repress transcription. Its high expression is associated with poor-prognosis cancer and promotes EMT. To decipher a role of PRC2 and Lsd1 interacting domains in HOTAIR function we generated Epi cell lines expressing full length and truncated versions of HOTAIR missing first 5'-300 bp and last 3'-500 bp interacting with HOTAIR partners. Total RNA form these cell lines was extracted and sequenced to reveal HOTAIR targets dependent of its intercation with PRC2 and/or Lsd1.

2021-04-22 | GSE106516 | GEO

Long non-coding RNA MIR503HG controls endothelial-to-mesenchymal transition

Project description:Long non-coding RNA MIR503HG controls endothelial-to-mesenchymal transition

| PRJNA486849 | ENA

Functional Role of Non-Coding RNAs during Epithelial-To-Mesenchymal Transition.

Project description: Not available

| S-EPMC6027143 | biostudies-literature

Characterization of long non-coding RNAs expressed during oocyte-to-embryo transition in mice

Project description:Characterization of long non-coding RNAs expressed during oocyte-to-embryo transition in mice

| PRJEB14222 | ENA

Long non-coding RNA MIR503HG controls endothelial-to-mesenchymal transition

Project description:Endothelial-to-mesenchymal transition (EndMT) is a dynamic transformation process that has a functional impact upon pathological vascular remodelling. The molecular mechanisms that govern EndMT remain largely unknown. By induction of EndMT in human primary endothelial cells (EC), using a combination of transforming growth factor-β2 (TGF-b2) and interleukin-1b (IL-1β), we identified the dramatic loss of the lncRNA MIR503HG, as a common signature across multiple primary EC types. Targeted depletion of MIR503HG spontaneously induced EndMT. Overexpression of MIR503HG repressed EndMT despite TGF-β2 and IL-1β co-stimulation. RNA-seq was carried out to identify the changes in gene expression induced by MIR503HG overexpression. We showed that over 25% of the EndMT-transcriptome signature was inhibited upon MIR503HG overexpression. Crucially, phenotypic changes induced by MIR503HG were independent of the functional regulation of miR-503 and miR-424, both harbored within the MIR503HG locus. Collectively, we identify the lncRNA MIR503HG as an essential regulator of EndMT.

2020-12-31 | GSE118815 | GEO

LncReader: identification of dual functional long non-coding RNAs using multi-head self-attention mechanism

Project description:The dual functional lncRNAs have been intensively studied and identified to be involved in various fundamental cellular processes recently. It is essential to understand in which context when a dual functional lncRNA serves as a non-coding RNA or a template for coding peptide, particularly in some pathological conditions. However, apart from time consuming and cell type specific experiments, there is virtually no in-silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep-learning model with multi-head self-attention mechanism, LncReader, to identify dual functional lncRNAs based on their sequence, physicochemical and secondary structural features. Our data demonstrated that LncReader showed multiple advantage compared to various classical machine learning methods. Moreover, to obtain independent in-house datasets for robust testing, mass spectrometry proteomics combined with RNA-seq were applied in four leukemia cell lines. Remarkably, LncReader achieved the best performance among all these datasets. Therefore, LncReader provides a sophisticated and practical tool that enables fast dual functional lncRNAs identification.

2023-04-26 | PXD030066 | Pride

Long non-coding RNAs induced by TGF-beta in three breast (cancer) cell lines

Project description:Long non-coding RNAs (lncRNAs) are emerging as pivotal modulators of signaling trnasduction, and thereby regulate multiple pathological processes including cancer. TGF-beta signaling contributes to cancer metastasis by inducing epithelial-to-mesenchymal transition (EMT). To screen lncRNAs that are induced by TGF-beta, MCF10A-M1, MCF10A-M2 and MDA-MB-231 cells were stimulated with TGF-beta (5 ng/mL) fo 0 h, 2 h, 8 h and 24 h. RNA was extracted from those cells and analyzed by RNA-seq.

2023-04-27 | GSE203119 | GEO

Comprehensive Identification of Soybean Long Non-coding RNAs Reveals a Subset of Small Peptide-Coding Transcripts

Project description:Long non-coding RNAs (lncRNAs) are defined as non-protein-coding transcripts that are at least 200 nucleotides long. They are known to play pivotal roles in regulating gene expression, especially during stress responses in plants. We used a large collection of in-house transcriptome data from various soybean (Glycine max and Glycine soja) tissues treated under different conditions to perform a comprehensive identification of soybean lncRNAs. We also retrieved publicly available soybean transcriptome data that were of sufficient quality and sequencing depth to enrich our analysis. In total, RNA-seq data of 332 samples were used for this analysis. An integrated reference-based, de novo transcript assembly was developed that identified ~69,000 lncRNA gene loci. We showed that lncRNAs are distinct from both protein-coding transcripts and genomic background noise in terms of length, number of exons, transposable element composition, and sequence conservation level across legume species. The tissue-specific and time-specific transcriptional responses of the lncRNA genes under some stress conditions may suggest their biological relevance. The transcription start sites of lncRNA gene loci tend to be close to their nearest protein-coding genes, and they may be transcriptionally related to the protein-coding genes, particularly for antisense and intronic lncRNAs. A previously unreported subset of small peptide-coding transcripts was identified from these lncRNA loci via tandem mass spectrometry, which paved the way for investigating their functional roles. Our results also highlight the current inadequacy of the bioinformatic definition of lncRNA, which excludes those lncRNA gene loci with small open reading frames (ORFs) from being regarded as protein-coding.

2020-01-09 | PXD014553 | Pride

Progesterone inhibits epithelial-to-mesenchymal transition in endometrial cancer

Project description:This SuperSeries is composed of the following subset Series: GSE29435: Progesterone inhibits epithelial-to-mesenchymal transition in endometrial cancer: cell line data GSE29436: Progesterone inhibits epithelial-to-mesenchymal transition in endometrial cancer: patient data Refer to individual Series

2012-01-26 | E-GEOD-29437 | biostudies-arrayexpress

Identification and functional characterization of long non-coding RNAs in human gastric cancer.

Project description: Not available

| S-EPMC5950527 | biostudies-literature