GEO accession GSE273803 is currently private and is scheduled to be released on Jul 29, 2025.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1143372 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We used PURE-seq with single-cell RNA-sequencing (scRNA-seq) to study murine long-term hematopoietic stem cells (LT-HSCs) and their transcriptomes in the context of hematopoietic aging.
2025-10-31 | GSE273803 | GEO
Project description:We used PIP-seq with a CROP-seq library to evaluate the feability of PIP-seq for large pooled CRISPR screens
2023-01-12 | GSE202915 | GEO
Project description:The study of the compond PIP-RBPJ-1‘ function on neural stem cell. Synthetic DNA-binding inhibitors capable of gaining precise control over neurogenesis factors could obviate the current clinical barriers associated with small molecule use in regenerative medicine. Here, we show the design and bio-efficacy of a synthetic ligand PIP-RBPJ-1 to cause promoter-specific suppression of neurogenesis-associated HES1, and its downstream genes. Furthermore, PIP-RBPJ-1 alone could alter the neural system-associated notch signaling factors and remarkably induce neurogenesis with an efficiency that is comparable to a conventional approach. Here is one day treatment of the PIP-RBPJ-1 on neural stem cells.
2018-07-19 | GSE109916 | GEO
Project description:Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted a combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Results Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP-] cells were identified. Functional and regulatory network analyses based on knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The networks identified appear associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines. Finally, the STAT5 motif was identified in promoters of an important part of genes belonging to the PIP networks. Conclusion Our global exploratory approach was found to be an effective strategy to identify the biological pathways modulated along with the PIP expression, thus supporting good prognostic value of disease-free survival time in breast cancer based on previous reports focusing on PIP’s favorable signature. Moreover, our data allowed us to provide the first insight in its regulatory subnetwork in which STAT5 appears as a potential key regulator.
2009-03-06 | GSE11627 | GEO
Project description:PIP variable region deep sequencing from Enterococcal wastewater isolates
| PRJEB13161 | ENA
Project description:Proteins were pulled down using PIP beads to determine what proteins may be interacting with different PIPs
2024-12-16 | PXD046124 | Pride
Project description:Methylophilus sp. 'Pure River' Genome sequencing
| PRJNA1180274 | ENA
Project description:Metaproteomics is an essential approach to analyse the in situ metabolic activity of microbes across various environments. In such highly diverse environmental samples, the functionality of specific microorganisms of importance often remains underexplored due to the protein inference problem arising from sequence homologies between organisms. One approach to overcome this challenge is the enrichment of non-culturable target organisms. However, this often result in samples with low protein content. In this study, we have developed a workflow that combines fluorescence in situ hybridisation (FISH) and fluorescence-activated cell sorting (FACS) with mass spectrometry-based proteomics to analyse proteins from non-culturable bacteria directly from environmental samples. We show that 1x105 cells are sufficient for reliable qualitative protein identifications, while 5x105 to 1x106 cells allow for reproducible protein quantification after FISH and FACS. Furthermore, the use of a taxon-specific database improves data analysis by significantly reducing the size of protein groups compared to metaproteomics data.
2025-09-29 | PXD057908 | Pride
Project description:We developed a novel FACS-based method to isolate enriched populations of neurons, astrocytes, and microglia. Whole mouse brains were digested, and populations of neurons, astrocytes, and microglia were subsequently enriched by FACS using a combination of positive gating on cell-type specific markers and stringent negative selection against markers of oligodendrocytes and endothelial cells. We confirmed a strong enrichment of corresponding cell-type specific genes in isolated populations and a reduction in gene markers of endothelial cells and oligodendrocytes, demonstrating that highly pure populations of neurons, astrocytes, and microglia were obtained.
2020-09-16 | GSE139000 | GEO