E-MTAB-5762
Ontology highlight
ABSTRACT:
PROVIDER: E-MTAB-5762 | ExpressionAtlas | 2019-05-14
REPOSITORIES: ExpressionAtlas
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Project description:Identification of driver genes in uterine leiomyosarcoma: RNA seq
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Project description:Endometriosis is a debilitating gynecological disorder affecting approximately 10% of the female population. Despite its prevalence, robust methods to classify and treat endometriosis remain elusive. Changes throughout the menstrual cycle in tissue size, architecture, cellular composition, and individual cell phenotypes make it extraordinarily challenging to identify markers or cell types associated with uterine pathologies since disease-state alterations in gene and protein expression are convoluted with cycle phase variations. Here, we developed an integrated workflow to generate both proteomic and single-cell RNA-sequencing (scRNA-seq) data sets using tissues and cells isolated from the uteri of control and endometriotic donors. Using a linear mixed effect model (LMM), we identified proteins associated with cycle stage and disease, revealing a set of genes that drive separation across these two biological variables. Further, we analyzed our scRNA-seq data to identify cell types expressing cycle and disease- associated genes identified in our proteomic data. A module scoring approach was used to identify cell types driving the enrichment of certain biological pathways, revealing several pathways of interest across different cell subpopulations. Finally, we identified ligand-receptor pairs including Axl/Tyro3 – Gas6, that may modulate interactions between endometrial macrophages and/or endometrial stromal/epithelial cells. Analysis of these signaling pathways in an independent cohort of endometrial biopsies revealed a significant decrease in Tyro3 expression in patients with endometriosis compared to controls, both transcriptionally and through histological staining. This measured decrease in Tryo3 in patients with disease could serve as a novel diagnostic biomarker or treatment avenue for patients with endometriosis. Taken together, this integrated approach provides a framework for integrating LMMs, proteomic and RNA-seq data to deconvolve the complexities of complex uterine diseases and identify novel genes and pathways underlying endometriosis.
2023-09-05 | PXD045115 | Pride
Project description:Uterine serous carcinoma (USC) represents only a small proportion of all uterine cancer cases, but patients with this aggressive subtype typically have high rates of chemotherapy resistance, disease recurrence, and constitute a disproportionately high percentage of the deaths. Improving the clinical management of USC is predicated by better characterization of the tumor microenvironment (TME) and the molecular features driving disease pathology. To improve our understanding of intratumoral heterogeneity (ITH) within the USC TME, we investigated proteome and transcriptome alterations in spatially resolved laser microdissection (LMD) enriched cellular subpopulations from nine USC patient tumor tissue specimens. LMD enriched samples were analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS), reverse phase protein microarray (RPPA), and targeted RNA-sequencing (RNA-seq).
2024-01-24 | PXD044197 | Pride
Project description:Raw data from E-MTAB-1585 was normalized by using reads per million. https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1585/ Strand specific RNA-Seq data E-MTAB-1585 was normalized and subtracted control from knockdown to generate tracks that more clearly displayed the unusual pattern of RNA expression caused by knockdown of 7SK. The following wig files were generated from multiple samples (i.e.raw data files), as indicated in the 'readme.txt' file. 7sk_3p_KD_norm.wig: 7SK 3P Knockdown normalized 7sk_3p_KDF_norm.wig: 7SK 3P Knockdown normalized (Forward) 7sk_3p_KDR_norm.wig: 7SK 3P Knockdown normalized (Reverse) 7sk_5p_KD_norm.wig: 7SK 5P Knockdown normalized 7sk_5p_KDF_norm.wig: 7SK 5P Knockdown normalized (Forward) 7sk_5p_KDR_norm.wig: 7SK 5P Knockdown normalized (Reverse) 7sk_Control_norm.wig: 7SK Control normalized 7sk_ControlF_norm.wig: 7SK Control normalized (Forward) 7sk_ControlR_norm.wig: 7SK Control normalized (Reverse) 7sk_3p_KDF-ControlF.wig: 7SK 3P Knockdown-Control (Forward) 7sk_3p_KDR-ControlR.wig: 7SK 3P Knockdown-Control (Reverse) 7sk_5p_KDF-ControlF.wig: 7SK 5P Knockdown-Control (Forward) 7sk_5p_KDR-ControlR.wig: 7SK 5P Knockdown-Control (Reverse)
2013-09-19 | E-GEOD-50860 | biostudies-arrayexpress
Project description:Identification of driver genes in uterine leiomyosarcoma: low-coverage WGS
| PRJEB21002 | ENA
Project description:Identification by RNA-seq of Prdm12 regulated genes
| PRJNA758268 | ENA
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
2020-02-14 | MTBLS1320 | MetaboLights
Project description: Not available
| S-BSST1361 | biostudies-other
Project description:To advance understanding of mechanisms leading to biological and transcriptional endpoints related to estrogen action in the mouse uterus, we have mapped ERM-NM-1 and RNA polymerase II binding sites using chromatin immunoprecipitation (ChIP) followed by sequencing of enriched chromatin fragments (ChIP-seq). In the absence of hormone, 5184 ERM-NM-1 binding sites were apparent in the vehicle treated ovariectomized uterine chromatin, while 17240 were seen one hour after estrogen (E2) treatment, indicating that some sites are occupied by unliganded ERM-NM-1, and that ERM-NM-1 binding is increased by E2. Approximately 15% of the uterine ERM-NM-1 binding sites were adjacent to (<10 KB) annotated transcription start sites and many sites are found within genes or are found more than 100 KB distal from mapped genes; however, the density (sites per bp) of ERM-NM-1 binding sites is significantly greater adjacent to promoters. An increase in quantity of sites but no significant positional differences were seen between vehicle and E2 treated samples in the overall locations of ERM-NM-1 binding sites either distal from, adjacent to or within genes. Analysis of the PolII data revealed the presence of poised promoter proximal PolII on some highly upregulated genes. Additionally, co-recruitment of PolII and ERM-NM-1 to some distal enhancer regions was observed. A de novo motif analysis of sequences in the ERM-NM-1 bound chromatin confirmed that estrogen response elements (EREs) were significantly enriched. Interestingly, in areas of ERM-NM-1 binding without predicted ERE motifs, homeodomain transcription factor (Hox) binding motifs were significantly enriched. The integration of the ERM-NM-1 and PolII binding sites from our uterine ChIP-seq data with transcriptional responses revealed in our uterine microarrays has the potential to greatly enhance our understanding of mechanisms governing estrogen response in uterine and other estrogen target tissues. one sample each, vehicle ER-alpha ChIP seq,1 hour estradiol ER-alpha ChIP seq, vehicle RNA polymerase II ChIP seq,1 hour estradiol RNA polymerase II ChIP seq, input DNA
2012-04-08 | E-GEOD-36455 | biostudies-arrayexpress