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Differential messenger RNA expression in Granulosa Cells from polycystic ovary syndrome with Normoandrogen and Hyperandrogen: Identification of gene sets through bioinformatic Filtering analysis

ABSTRACT: Differential messenger RNA expression in Granulosa Cells from polycystic ovary syndrome with Normoandrogen and Hyperandrogen: Identification of gene sets through bioinformatic Filtering analysis

PROVIDER: PRJNA566203 | ENA |

REPOSITORIES: ENA

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Differential messenger RNA expression in Granulosa Cells from polycystic ovary syndrome with Normoandrogen and Hyperandrogen: Identification of gene sets through bioinformatic Filtering analysis

Project description:PCOS is a widespread disease that primarily caused in-pregnancy in pregnant-age women. Normoandrogen (NA) and Hyperandrogen (HA) PCOS are distinguished under distinct level of testosterone, while markers and expression patterns for both subtypes were not adequately studied. Text-mining analysis stated the correlation for PCOS with granusola cells and thus we performed microarray analysis on granusola cells from HA PCOS, NA PCOS and normal tissue from individuals, and afterwards downloaded RNA-seq and microarray data from NCBI GEO database on granusola cells from PCOS and normal ovary. Applying our newly developed method using Monte Carlo algorithm and text mining method on combined data, we identified several potential markers for HA and NA PCOS. RT-PCR and Western blotting results validated the expression pattern of these markers for HA and NA PCOS as bioinformatical prediction. Further gene ontology (GO) and text-mining analysis discovered that (1) NA PCOS was highly correlated with estrogen-driven tumors including ovarian, breast and endometrial cancer as compared with normal granusola cells. NA PCOS specific genes IL6R and CD274 were bioinformatically predicted and experimentally validated and thus might be the key factor behind the mechanism responsible for the tumor-like pattern for NA PCOS; (2) HA PCOS showed high correlation with keratinization, epidermis development, GTPase activity, glomerular basement membrane development and apoptosis corresponding to the fact HA PCOS patients express characteristic of hirsutism, diabetes and obesity. Meanwhile HA PCOS was sustantially lowerly related with estrogen-driven tumors as compared with normal granusola cells.

2019-09-19 | GSE137684 | GEO

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Project description:Recent technological developments in single-cell RNA-seq CRISPR screens enable high-throughput investigation of the genome. Through transduction of a gRNA library to a cell population followed by transcriptomic profiling by scRNA-seq, it is possible to characterize the effects of thousands of genomic perturbations on global gene expression. A major source of noise in scRNA-seq CRISPR screens are ambient gRNAs, which are contaminating gRNAs that likely originate from other cells. If not properly filtered, ambient gRNAs can result in an excess of false positive gRNA assignments. Here, we utilize CRISPR barnyard assays to characterize ambient gRNA noise in single-cell CRISPR screens. We use these datasets to develop and train CLEANSER, a mixture model that identifies and filters ambient gRNA noise. This model takes advantage of the bimodal distribution between native and ambient gRNAs and includes both gRNA and cell-specific normalization parameters, correcting for confounding technical factors that affect individual gRNAs and cells. The output of CLEANSER is the probability that a gRNA-cell assignment is in the native distribution over the ambient distribution. We find that ambient gRNA filtering methods impact differential gene expression analysis outcomes and that CLEANSER outperforms alternate approaches by increasing gRNA-cell assignment accuracy.

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Polycystic Kidney Disease Progression Expression Analysis

Project description:Polycystic Kidney Disease (PKD) is a genetic disease of the kidney characterized by the gradual replacement of normal kidney parenchyma by fluid-filled cysts and fibrotic tissue. Autosomal Dominant Polycystic Kidney Disease (ADPKD) is caused by mutations in the PKD1 or PKD2 gene. Here we present an RNASeq experiment designed to investigate the effect of a kidney specific and Tamoxifen inducible knockout of the Pkd1 gene in mice. The Pkd1cko mice were harvested at different time points 2-weeks, 3-weeks, 5-weeks, 10.5-weeks, 11-weeks and 15-weeks after gene inactivation.

2019-12-24 | E-MTAB-8086 | biostudies-arrayexpress

Differential Gene Expression in Granulosa Cells from Polycystic Ovary Syndrome Patients with and without Insulin Resistance: Identification of Susceptibility Gene Sets through Network Analysis

2012-11-06 | GSE34526 | GEO

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Differential Gene Expression in Granulosa Cells from Polycystic Ovary Syndrome Patients with and without Insulin Resistance: Identification of Susceptibility Gene Sets through Network Analysis

Project description:Polycystic ovary Syndrome (PCOS) is a heterogeneous endocrine disorder that shows evidence of genetic predidposition among affected individuals. We have utilized the Microarray data from granulosa cells of normal and PCOS women for network construction. Human granulosa cells were isolated from ovarian aspirates from normal and PCOS women undergoing IVF and for each sample, RNA was extracted and hybridized to an Affymetrix GeneChip.

2012-11-06 | E-GEOD-34526 | biostudies-arrayexpress

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