567ca34f-a914-4e51-b3a9-b647e4b941a6 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001011099 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:To decipher the cell type composition within single spheres we performed RNA-Seq of 25 selected spheres of 4 different categories (including 8 signature-/balanced, 9 signature+/balanced, 1 signature-/aberrant, 7 signature+/aberrant). To track the individual cell types within single spheres we performed deconvolution analysis.
| EGAS00001007369 | EGA
Project description:High-grade serous ovarian carcinoma (HGSOC) is the deadliest gynecologic cancer. Key to the progression and ultimate lethality of this subtype is the intra-tumoral heterogeneity (ITH), which is defined as the coexistence of different cell types and populations within a single tumor. Among those, ovarian cancer stem cells (OCSCs) are a distinct subpopulation of tumor cells endowed with stem-like properties, which can survive current standard therapies, resulting in tumor recurrence. Here, we generated ex vivo primary OCSC-enriched three-dimensional (3D) spheres from ten distinct treatment naive patient-derived adherent (2D) cultures. We used state-of-the-art quantitative mass spectrometry to characterize the molecular events associated with OCSCs by analyzing their phosphoproteome and proteome. Our data revealed a stemness-related protein signature, shared within a heterogeneous patient cohort, which correlates with chemo-refractoriness in a clinical proteomics dataset. Moreover, we identified targetable deregulated kinases and aberrant PDGF receptor activation in OCSCs. Pharmacological inhibition of PDGFR in adherent OC cells reduced the stemness potential, measured by sphere formation assay. Overall, we provide a valuable resource to identify new OCSC markers and putative targets for OCSC-directed therapies.
2025-04-24 | PXD061015 | Pride
Project description:Multiprotein complexes execute and coordinate diverse cellular processes such as organelle biogenesis, vesicle trafficking, cell signaling, and metabolism. Knowledge about their composition and localization provides useful clues about the mechanisms of cellular homeostasis and systems-level control. This is of great biological importance and practical significance in heterotrophic rice (Oryza sativa) endosperm and aleurone-subaleurone tissues, which are a primary source of seed vitamins and stored energy. Dozens of protein complexes have been implicated in the synthesis, transport, and storage of seed proteins, lipids, vitamins, and minerals. Mutations in protein complexes that control RNA transport result in aberrant endosperm with shrunken and floury phenotypes, significantly reducing seed yield and quality. The purpose of this study was to broadly predict protein complex composition in the aleurone-subaleurone layers of developing rice seeds using co-fractionation mass spectrometry. Following orthogonal chromatographic separations of biological replicates, thousands of protein elution profiles were subjected to distance-based clustering to enable large-scale multimerization state measurements and protein complex predictions. The predicted complexes had predicted functions across diverse functional categories, including novel heteromeric RNA binding protein complexes that may influence seed quality. This effective and open-ended proteomics pipeline provides useful clues about systems-level post-translational control during the early stages of rice seed development.
2022-02-17 | PXD022357 | Pride
Project description:Schmitz2014 - RNA triplex formation
The model is parameterized using the
parameters for gene CCDC3 from Supplementary Table S1. The two
miRNAs which form the triplex together with CCDC3 are miR-551b and
miR-138.
This model is described in the article:
Cooperative gene regulation
by microRNA pairs and their identification using a
computational workflow.
Schmitz U, Lai X, Winter F,
Wolkenhauer O, Vera J, Gupta SK.
Nucleic Acids Res. 2014 Jul; 42(12):
7539-7552
Abstract:
MicroRNAs (miRNAs) are an integral part of gene regulation
at the post-transcriptional level. Recently, it has been shown
that pairs of miRNAs can repress the translation of a target
mRNA in a cooperative manner, which leads to an enhanced
effectiveness and specificity in target repression. However, it
remains unclear which miRNA pairs can synergize and which genes
are target of cooperative miRNA regulation. In this paper, we
present a computational workflow for the prediction and
analysis of cooperating miRNAs and their mutual target genes,
which we refer to as RNA triplexes. The workflow integrates
methods of miRNA target prediction; triplex structure analysis;
molecular dynamics simulations and mathematical modeling for a
reliable prediction of functional RNA triplexes and target
repression efficiency. In a case study we analyzed the human
genome and identified several thousand targets of cooperative
gene regulation. Our results suggest that miRNA cooperativity
is a frequent mechanism for an enhanced target repression by
pairs of miRNAs facilitating distinctive and fine-tuned target
gene expression patterns. Human RNA triplexes predicted and
characterized in this study are organized in a web resource at
www.sbi.uni-rostock.de/triplexrna/.
This model is hosted on
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and identified by:
BIOMD0000000530.
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2024-09-02 | BIOMD0000000530 | BioModels
Project description:In this study monoclonal cell lines carrying mutations in snoRNA genes (SNORD74, SNORD75, SNORD77, SNORD80) were obtained. Next, whole transcriptome analysis of obtained cell lines was performed on an Illumina NextSeq 500 platform. RNA-seq libraries was constructed on PolyA mRNA-enriched fraction. The comparison of the expression levels of genes and transcripts in RNA-Seq experiments was carried out using CuffDiff tool. Mutations in SNORD75 in the obtained monoclonal cell line were shown to result in aberrant splicing of Gas5.
2019-10-14 | E-MTAB-8269 | biostudies-arrayexpress
Project description:The goal of RNA-seq is to identify the differential expressed genes in the wild-type worm and nmad-1 mutant worm at 20°C and 25°C respectively. 100 pairs of germlines were extracted and collected from worm tips. Two biological replicates were assigned for each group and the RNA profiles were generated by deep sequencing, using NEXTseq 500 Illumina. We mapped about 20 - 30 million reads per sample to C. elegans genome (build ce10) with bowtie2 workflow. Differential expression genes were identified through EBSeq in RSEM pipeline with 0.05 p value and 1.2 fold change. Our results showed elevated number of misregulated genes in the nmad-1 mutant groups at 25°C.
2019-06-21 | GSE112484 | GEO
Project description:Purpose: To better characterise the population structure of primary bovine retinal microvascular endothelial cells (RMECs) based upon their individual transcriptomes. Methods: Individual RMECs were captured on the Fluidigm C1 system (Fluidigm), cDNA libraries were prepared using a Nextera XT kit and sequencing performed on a NextSeq (Illumina). Results: Application of a single cell RNA-seq analysis workflow showed that RMECs form a relatively homogeneous population in culture, with the main subgroup being proliferating cells. Expression of markers from along the arteriovenous tree suggests that most cells originate from capillaries. An in silico model of the blood retinal barrier was created, including junctional proteins not previously reported within the retinal vasculature. Numerous alternative splicing events involving exons within microvascular barrier genes were observed and in many cases individual cells expressed exclusively one isoform. Conclusions: We have optimised a workflow for single-cell transcriptomics in primary RMECs. Our results have provided fundamental insights into the genes involved in retinal microvascular barrier formation.
2020-09-01 | GSE136800 | GEO
Project description:Ex-vivo drug sensitivity screening (DSS) only provides a readout on mixtures of cells, potentially occulting important information on clinically relevant cell subtypes. Here we developed a machine-learning framework to deconvolute bulk RNA expression matched with bulk drug sensitivity into cell subtype composition and cell subtype drug sensitivity. We first determined that our method could decipher the cellular composition of bulk samples more accurately than current state-of-the-art methods. We then optimized an algorithm capable of estimating cell subtype- and single-cell-specific drug sensitivity, which we evaluated by performing in-vitro drug studies
2022-11-16 | GSE217919 | GEO