Transcriptomic deconvolution of human endometrial cell types
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA668163 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12797318_1.fastq.gz | Fastqsanger.gz | |||
| SRR12797318_2.fastq.gz | Fastqsanger.gz | |||
| SRR12797319_1.fastq.gz | Fastqsanger.gz | |||
| SRR12797319_2.fastq.gz | Fastqsanger.gz | |||
| SRR12797320_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 84 |
Similar Datasets
Project description:The human endometrium is a highly heterogeneous tissue comprising multiple cell-types and cellular states that change in cycle-dependent manner. This tissue heterogeneity is a major drawback when interpreting bulk (whole biopsy) transcriptomic data. To address this hurdle, RNA-seq analysis was performed on four isolated stromal cell populations [SUSD2+ perivascular stromal cells (PVCs), endometrial stromal cells (EnSCs), SUSD2+ clonal cells (MSCs), and clonal transit amplifying cells (TAs)], glandular epithelial cells, uNK cells, and matched whole tissue. Transcriptomic data were obtained for 3 whole endometrial biopsies and 6 matched, purified cell populations.
2020-10-09 | GSE159266 | GEO
Project description:Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types
| PRJNA758376 | ENA
Project description:In this study, whole transcriptome changes induced by P4 were analysed by RNAseq following laser capture microdissection (LCM) of endometrial biopsies to isolate LE, GE and ST cells. The study was performed in cows without any sign of uterine disease (as assessed by uterine cytology). At 45 days postpartum, the presence of a Corpus Luteum (CL) assessed by ultrasonography and plasma P4 concentrations were used to categorise healthy cows at 45 days postpartum determine if cows were in luteal phase (CL, P4 concentrations ≥1 ng/ml; n=4) or not (no CL, P4 concentrations < 1ng/ml; n=9). Overall, endometrial LE, GE, and ST cells shown specific transcriptomic profiles with different proportions and type of genes expressed over 10 tpm. Most of the genes differentially expressed (DEGs) in response to P4 were cell type-specific (93.9%). Genes involved in cell cycle and nuclear division were under-expressed in presence of P4 in GE and LE, highlighting the anti-proliferative action of P4 in epithelial cells. Elevated P4 concentrations were also associated with the under-expression of estrogen receptor 1 (ESR1) in GE and of oxytocin receptor (OXTR) in GE and ST. In ST, transcription factors such as SOX17 and FOXA2 , as well as interferon related genes which are known to regulate uterine epithelial–stromal crosstalk conveying to endometrial receptivity for embryo implantation, were over-expressed under P4. The results from this study show that progesterone regulates endometrial function in a cell type specific way, which looks independent of the expression of its main receptor PGR. These novel insights into uterine physiology, stand the cell compartment, rather than the whole tissue, as a physiological unit.
2021-12-03 | GSE182932 | GEO
Project description:microRNAs are essential regulators of gene expression. This work explores the transcriptomic effects of has-miR-30d in endometrial epithelial cells which was reported to be up-regulated during human endometrial receptivity. primary endometrial epithelial cells derived from four different endometrial biopsies taken on LH+0 were transiently transfected with miRNAs for 72 hours under two conditions (four scramble, four miR-30d mimic) and were evaluated for mRNA expression with Agilent’s gene expression microarray. A set of differentially expressed mRNAs were validated by qPCR.
2014-02-03 | E-GEOD-46721 | biostudies-arrayexpress
Project description:Transcriptomic exploration of decidualizing human endometrial stromal cell dynamics
| PRJNA1033677 | ENA
Project description:microRNAs are essential regulators of gene expression. This work explores the transcriptomic effects of has-miR-30d in endometrial epithelial cells which was reported to be up-regulated during human endometrial receptivity.
2014-02-03 | GSE46721 | GEO
Project description:Spatial barcoding-based transcriptomic (ST) data require cell type deconvolution for cellular-level downstream analysis. Here we present SDePER, a hybrid machine learning and regression method, to deconvolve ST data using reference single-cell RNA sequencing (scRNA-seq) data. SDePER removes the systematic difference between the ST and scRNA-seq data (platform effects) explicitly and efficiently to ensure the linear relationship between ST data and cell type-specific expression profile. It also considers sparsity of cell types per capture spot and across-spots spatial correlation in cell type compositions. Based on the estimations, SDePER imputes for cell type compositions and gene expression at enhanced resolution. We assessed the performance of SDePER and six existing methods using simulations and four real datasets. All results showed that SDePER achieved significantly more accurate and robust results than the existing methods suggesting the importance of considering platform effects, sparsity and spatial correlation in cell type deconvolution.
2024-08-01 | GSE231385 | GEO
Project description:Cancer progression is dependent on both cell-intrinsic processes and interactions between different cell types that constitute tumor tissue. To access this information, we develop Epigenomic Deconvolution (EDec), an in silico method that provides estimates of cell type composition of complex tissues, such as solid tumors, as well as CpG methylation and gene transcription within constituent cell types. By applying EDec to breast tumors from TCGA we detect changes in immune cell infiltration, and a striking change in stromal fibroblast to adipocyte ratio across breast cancer subtypes. We further show that a decrease in stromal adipocyte content and increase in fibroblast content is associated with a reduction of mitochondrial activity in stromal cells and a concomitant increase in oxidative metabolism in cancerous epithelial cells. These findings highlight the role of stromal cell type composition in the establishment of patterns of metabolic coupling such as the previously proposed reverse Warburg effect. Raw data files were not provided for this Series. Submitters did not have permission to share the raw data.
2016-11-17 | GSE87297 | GEO
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:Competent endometrial receptivity is a prerequisite for successful embryo implantation. Identification of novel key molecules involved in endometrial receptivity is essential to better interpret human implantation and improve pregnancy rates in assisted reproduction treatment. The isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics was performed to profile the proteomes of the prereceptive( LH+2, n=4) and receptive (LH+7, n=4) endometrial tissues. One hundred seventy-three differentially expressed proteins (DEPs) between LH+2 and LH+7 endometrial samples were identified. Integrated analysis of the proteomic data and published transcriptomic data was performed to identify the concordant DEPs with differential expression at both mRNA and protein levels. The protein-protein-interaction (PPI) network analysis were performed on concordant DEPs.We first identified 63 novel concordant DEPs and 5 hub proteins (ACSL4, ACSL5, COL1A1, PTGS1 and PLA2G4F) between LH+2 and LH+7 endometrial samples. ACSL4 was predominantly expressed in endometrial epithelial cells and its expression was significantly upregulated in the LH+7 endometrium and significantly downregulated in repeated implantation failure (RIF) patients. Knockdown of ACSL4 in endometrial epithelial cells induced the down-regulation of endometrial receptivity markers (HOXA10, COX2 and LIF) and the significant decrease of implantation rate during in vitro implantation analysis. This study provides the first gel-independent quantitative proteomes of the LH+2 and LH+7 human endometrium using iTRAQ technology. The identified concordant DEPs and hub proteins open a new avenue for future studies aimed at elucidating the underlying mechanisms governing endometrial receptivity. ACSL4 was identified as a novel regulatory molecule in the establishment of endometrial receptivity and might play important roles during implantation.
2023-01-02 | PXD039161 |