Effect of Glucocorticoids on microRNA, lncRNA and mRNA Expression Profile of the Human Bone Microcirculatory Endothelial Cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Qingsheng Yu
PROVIDER: E-GEOD-60333 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Appropriate gene expression patterns form the basis for bone microcirculatory endothelial cellsM-bM-^@M-^Y function and bone morphology. Although previous studies have elucidated the impact of hydrocortisone on bone microcirculatory endothelial cellsM-bM-^@M-^Y specific gene expression, the exact differential transcriptomes and comprehensive gene expression profiles remain unknown. We have investigated the mRNA and lncRNA expression patterns before and after hydrocortisone administration of bone microcirculatory endothelial cells. At mRNAs level totally 518 differentially expressed genes were identified. Furthermore, we identified 73 upregulated and 166 downregulated long non-coding RNAs after administration of hydrocortisone. These RNAs appeared to be highly important to gene co-expression network. Transcriptomic analysis of bone microcirculatory endothelial cells from human samples is highly informative due to their relevance to the large number of expressed genes. Our study provides a very valuable basis for investigation of genes, regulation and their co-expression network contributing to hydrocortisone induced disorders. Two-condition experiment, hydrocortisone treated vs. untreated bone microcirculatory endothelial cells. Biological replicates: 8 control replicates, 8 treated replicates.
2015-01-01 | E-GEOD-60332 | biostudies-arrayexpress
Project description:Long noncoding RNAs (lncRNAs) play a key role in regulating immunological functions. Their impact on the chronic inflammatory disease multiple sclerosis (MS), however, remains unknown. We investigated the expression of lncRNAs in peripheral blood mononuclear cells (PBMCs) of patients with MS and try to explain their possible role in the process of MS. we recruited 26 MS patients according to the revised McDonald Criteria. Then we chosen 6 patients for microarray analysis randomly. Microarray assays identified outstanding differences in lncRNA expression, which were verified through real-time PCR. LncRNA functions were annotated for target genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and regulatory relationships between lncRNAs and target genes were analyzed using the “cis” and “trans” model.
2017-12-08 | E-MTAB-6193 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC), the main form of liver cancer, is the sixth most common cancer and the third most frequent cause of cancer death worldwide1. The exact mechanism of HCC initiation and development is still unclear, though inflammation has been shown to play a key role in this progression. Herein, we performed a gene expression assay to screen for alterative expression of genes among normal liver tissues, HCC tissues and its paracancer tissues with hepatitis. A gene assay to screen the expression of total RNA in liver tissues, including 3 normal liver tissues, 3 HCC paracancer specimens and 3 HCC samples with HBV-induced hepatitis. The normal liver samples were obtained from normal hepatic tissue in three hepatic hemangioma surgical operative patients, and three matched pairs of HCC and its paracancer tissues were respectively obtained from three HCC surgical operative patients without any chemotherapy and radiotherapy.
2015-04-11 | E-GEOD-67764 | biostudies-arrayexpress
Project description:LncRNA expression profiling for liver tissues of mice fed for a normal diet (NFD, 3mice) and a high-fat diet (HFD, 3mice) Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.
2022-11-23 | E-MTAB-8730 | biostudies-arrayexpress
Project description:Many studies have demonstrated miRNAs as key regulators of inflammatory responses in endothelial cells (Ecs). However, because of the complexity of inflammatory genes and miRNAs, there would be many undiscovered miRNAs involved in inflammatory responses of ECs. Let-7e is an important member of let-7e family and plays key roles in the regulation of inflammation and endothelial cell proliferation. Furthermore, let-7e expression is significantly increased in many cardiovascular diseases including coronary heart disease. Therefore,we speculated that let-7e might play important roles in the regulation of inflammatory responses in endothelial cells by directly or indirectly targeting certain inflammatory genes. In order to reveal the action of let-7e in vascular endothelial cells, the expression profiles of mRNAs and lncRNAs induced by let-7e in human umbilical vein endothelial cells (HUVECs) were investigated using microarray technology.
2018-12-29 | E-MTAB-4971 | biostudies-arrayexpress
Project description:The miRNA microarray analysis was performed to explore the expression profiles of miRNAs using the same liver tissues of NFD-fed mice and HFD-fed mice Summary: An abstract of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: miRCURY™ LNA expression array information. Data Analysis for miRNAs: 1. Low intensity filtering and data normalization: After low intensity miRNAs filtering, raw signal intensities are normalized in Median method. (miRNAs that intensities>=30 in all samples are chosen for calculating normalization factor) 2. Quality assessment of miRNA data after filtering: Contains box plot, Correlation Matrix and scatter plot for miRNAs after normalization. 3. Differentially expressed miRNAs screening: Contains significant differentially expressed miRNAs that pass Volcano Plot filtering. (Fold Change>=1.5, P-value<=0.05) 4. Heat map and hierarchical clustering: Hierarchical clustering on the significant differentially expressed miRNAs that passed Volcano Plots filtering. Sample RNA Quality Control: Sample quality control data file from Nanodrop 1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction for microarray, experiment, and data analysis. FAQ: Frequently asked question Additional miRNA Array Analysis (charge an extra fee): Prediction Analysis for Microarrays (PAM analysis) miRNA Target Gene Prediction and Functional Analysis Additional files provided: Graphs (*.jpg) Raw Intensity File(*.xls, raw miRNAs signal intensity) Layout File (*.gal, the files contain information on the positioning of the capture probes on the array and microRNA annotations for your species of interest) Raw data files produced by GenePix Pro 6.0
2022-11-23 | E-MTAB-8731 | biostudies-arrayexpress
Project description:Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and the second most common form of leukemia in children. Multiple lncRNAs participate in normal and may be implicated in malignant hematopoiesis associated with blood cell cancers, such as leukemia. Currently, the expression profile of lncRNAs in pediatric AML is unclear. In this study, we evaluated the lncRNA expression profile in the tissue of three pediatric AML patients with lncRNA microarray techniques. In order to gain insight into the function of targets of lncRNAs, GO term and KEGG pathway annotation were applied to the target gene pool. qPCR was performed to evaluate the expression patterns of dys-regulated lncRNAs. Bone marrow specimens were obtained at the time of diagnosis during routine clinical assessment of 3 pediatric patients with AML, who presented at the Department of Hematology and Oncology, Children's Hospital of Soochow University between 2000 and 2011. Additionally, bone marrow samples from 3 healthy donors were analyzed as controls. Human LncRNA Array analysis was performed by KangChen Bio-tech, Shanghai P.R. China. Total RNA from each sample was quantified by the NanoDrop ND-1000 and RNA integrity was assessed by standard denaturing agarose gel electrophoresis. For microarray analysis, Agilent Array platform was employed. The sample preparation and microarray hybridization were performed based on the manufacturerâs standard protocols with minor modifications. Briefly, mRNA was purified from total RNA after removal of rRNA (mRNA-ONLY⢠Eukaryotic mRNA Isolation Kit, Epicentre). Then, each sample was amplified and transcribed into fluorescent cRNA along the entire length of the transcripts without 3â bias utilizing a random priming method. The labeled cRNAs were hybridized onto the Human LncRNA Array v2.0 (8 x 60K, Arraystar). After having washed the slides, the arrays were scanned by the Agilent Scanner G2505C. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed using the GeneSpring GX v12.0 software package (Agilent Technologies). After quantile normalization of the raw data, LncRNAs and mRNAs that at least 4 out of 6 samples have flags in Present or Marginal (âAll Targets Valueâ) were chosen for further data analysis. Differentially expressed LncRNAs and mRNAs with statistical significance between the two groups were identified through Volcano Plot filtering. Pathway analysis and GO analysis were applied to determine the roles of these differentially expressed mRNAs played in these biological pathways or GO terms. Finally, Hierarchical Clustering was performed to show the distinguishable LncRNAs and mRNAs expression pattern among samples.
2015-12-31 | E-GEOD-65263 | biostudies-arrayexpress
Project description:RAW cells or ABHD5-KD RAW cells were subjected to microarray assays. Each group contain 3 samples. To explore the regulatory role of ABHD5 in metabolic pathways, RAW cells or ABHD5-KD RAW cells were subjected to microarray assays.
2016-05-12 | E-GEOD-80066 | biostudies-arrayexpress
Project description:To study the difference of gene expression pattern of whole blood between klinefelterM-bM-^@M-^Ys syndrome and normal individuals and discovered the disease-related genes and biological pathway. 717 differentially expressed genes (480 up regulated, 237 down regulated) were identified between whole blood samples of the klinefelterM-bM-^@M-^Ys patients and normal volunteers. Function enrichment analysis identified a number of genes involved in immune response, metabolism etc. Three genes with significant down-regulation in KlinefelterM-bM-^@M-^Ys patients were also confirmed by qRT-PCR.Using the whole blood as material in patients with klinefelterM-bM-^@M-^Ys syndrome, the differentially expressed genes was identified. It is noticed that genes involved in metabolism pathways were significantly decreased. These observations may suggest aberrant of metabolism may be important for developing the klinefelterM-bM-^@M-^Ys syndrome. In addition, our results also show that no X-linked genes are overexpression in the peripheral blood cells of KS patients. In the present study, we examined gene expression in whole blood of 5 klinefelterM-bM-^@M-^Ys patients and 5 healthy control volunteers. The RNA of 10 samples was isolated and Gene expression was detected by gene microarray. The different expressed genes were analyzed by SAM software.
2013-09-01 | E-GEOD-47584 | biostudies-arrayexpress
Project description:We have employed whole genome microarray expression profiling as a discovery platform to identify different gene expression in normal or tumor-primed peritoneal macrophages Mouse peritoneal macrophages were extracted and treated with regular medium or CT-26 cell medium for 24 hours, and then subjected to microarray assays. Each group contain 3 samples.
2016-05-12 | E-GEOD-80065 | biostudies-arrayexpress