Differentially expressed mRNAs after silencing lncRNA DDGC
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE158555 | GEO | 2021/02/20
REPOSITORIES: GEO
Similar Datasets
Project description:Differentially expressed mRNAs after silencing lncRNA DDGC
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Project description:We have completed the lncRNA expression profiling of human granulosa cells to reveals the differentially expressed lncRNAs involved in POI.
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Project description:Using the highly sensitive lncRNA array (Arraystar human lncRNA microarray), we screened the lncRNAs and mRNA abundant in bladder cancer stem cells sorted from three bladder cancer cell lines, compared to the bladder cancer cells. And the functions of lncRNAs in bladder cancer stem cells were analyzed along the following research.
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Project description:Our study is designed to demonstrate altered profiles of lncRNAs in the granulosa cells from patients with bPOI. Functional studies will be further confirmed. This study will provide new viewpoint for understanding the roles of non-coding RNA for GCs function, as well as potential etiologic mechanism for POI.
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Project description:LncRNA expression profiling for liver tissues of mice fed for NFD, LSF and HSF groups 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.
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Project description:This study aimed to identify the crucial molecules and explore the function of noncoding RNAs and related pathways in IDD. We randomly selected 3 samples each from an IDD and a spinal cord injury group (control) for RNA-sequencing. We identified 463 differentially-expressed long noncoding RNAs (lncRNAs), 47 differentially-expressed microRNAs (miRNAs), and 1,334 differentially-expressed mRNAs in IDD. Three hundred fifty-eight lncRNAs as cis-regulators could potentially target 865 genes. Protein–protein interaction (PPI) network analysis confirmed that IL-6, VEGFA, IGF1, MMP9, CXCL8, FGF2, IL1B, CCND1, ITGAM, PTPRC, FOS and PTGS2 were hub genes. We built a competing endogenous RNA (ceRNA) network and identified lncRNA XIST–hsa-miR-4775–PLA2G7 and lncRNA XIST–hsa-miR-424-5p–AMOT/TGFBR3 ceRNA axes.
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