Differentially expressed lncRNAs in hDPSCs between the OCT4A-overexpressing and vector groups.
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PROVIDER: PRJNA935313 | ENA |
REPOSITORIES: ENA
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Project description:To determine whether lncRNAs were involved in the OCT4A-related network that regulates the self-renewal of hDPSCs, human lncRNA microarrays were used to identify the lncRNA expression profiles in OCT4A-overexpressing and vector hDPSCs. 978 lncRNAs (250 of which were upregulated and 728 downregulated) and 404 mRNAs (222 of which were upregulated and 182 downregulated) were potential differentially expressed genes (fold change≥2, P<0.05).
2023-03-23 | GSE225345 | GEO
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.
2022-11-24 | E-MTAB-9167 | biostudies-arrayexpress
Project description:Neural stem/progenitor cells were isolated from the lateral ventricle wall of 4-6 week-old CD1 mice and grown as neurospheres under low density culture conditions. Test cells were transduced with bicistronic retroviral constructs for the over-expression of Bmi1 together with eGFP, and control cells were transduced with an empty vector construct expressing eGFP only. To identify genes, which are regulated by BMI1 in neural stem/progenitor cells, the gene expression profiles of neurosphere cells over-expressing Bmi1 were compared empty vector control cells using Affymetrix Gene mouse ST1.0 arrays 3 independent Bmi1-overexpressing neurosphere cultures (test samples) were compared to 3 independent empty vector neurosphere cultures (control samples).
2016-06-01 | E-GEOD-70451 | biostudies-arrayexpress
Project description:Neural stem/progenitor cells were isolated from the lateral ventricle wall of 4-6 week-old CD1 mice and grown as neurospheres under low density culture conditions. Test cells were transduced with bicistronic retroviral constructs for the over-expression of Bmi1 together with eGFP, and control cells were transduced with an empty vector construct expressing eGFP only. To identify genes, which are regulated by BMI1 in neural stem/progenitor cells, the gene expression profiles of neurosphere cells over-expressing Bmi1 were compared empty vector control cells using Affymetrix Gene mouse ST1.0 arrays
2016-06-01 | GSE70451 | GEO
Project description:To address the role of SE-lncRNAs in CRC tumorigenesis, we performed Arraystar human SE-lncRNA microarray to profile the differentially expressed SE-lncRNAs and mRNA in four CRC and paired peritumoral tissues. According to the filter criteria of Fold Change ≥ 1.5 and P-value < 0.05, a total of 55 significantly upregulated and 29 significantly downregulated SE-LncRNs were identified. These data confirmed that the expression of SE-lncRNA undergoes a change that cannot be ignored during CRC tumorigenesis. We also identified 165 (91 up- and 74 downregulated) differentially expressed mRNA between the two groups（Fold Change > 1.5 and P-value < 0.05）(Fig.1C), which provides help for us to findpotential target genes and further explore the biological function of SE-lncRNA in CRC
2020-05-22 | GSE151021 | GEO
Project description:Analysis transcriptome differences of 3D-cultured HUVECs upon overexpressing KANK4 or Vector.
2021-12-31 | GSE182578 | GEO
Project description:A total of 3,359 lncRNAs revealed by microarray analysis have been differentially expressed between the two groups, 1,995 lncRNAs identified to be up-regulated in COPD, whereas 1,364 lncRNAs have been down-regulated. Meanwhile，a total of 3,283 mRNAs have been differentially expressed, 2,589 mRNAs identified to be up-regulated in COPD, whereas 694 mRNAs were down-regulated.
2017-11-29 | GSE107426 | GEO
Project description:Lung cancer is a heterogeneous disease with high mortality rate globally. Lung adenocarcinoma (ADC) is the most common histological subtype of lung cancer. Multiple studies indicate that lncRNAs emerge as a novel class of critical regulators of cancer. However, the expression of lncRNAs has not been comprehensively surveyed in ADC at a genome-wide scale. Herein we examined landscapes of the lncRNAs and their potential target genes in an integrative fashion in ADC. The differences expression level of lncRNAs and mRNA were determined by microarray. qRT-PCR was performed to validate the lncRNAs expression level in a cohort of 42 tumor tissues and adjacent normal lung tissues. R and Bioconductor were used for data analysis. TF-lncRNAs-gene networks were generated by Cytoscape software. A total of 3045 lncRNAs were differentially expressed between tumor and normal tissues (1048 up and 1997 down). The qRT-PCR of 9 lncRNAs results showed that the expression patterns of these lncRNAs were consistent with the microarray data. Meanwhile, we find NONHSAT077036 expression was associated with N classification and clinical stage. Further, we analyzed the potential co-regulatory relationship between the lncRNAs and target genes using the ‘cis’ and ‘trans’ model. In the 25 related transcription factors (TFs), our analysis in TCGA database found that patients with lower expression of POU2F2 and higher expression of TRIM28 had a shorter overall survival time, suggesting that POU2F2 and TRIM28 could be biomarkers for poor prognosis of ADC. Hence, “POU2F2-lncRNAs” “TRIM28-lncRNAs” two element networks and “POU2F2-lncRNAs-mRNAs” “TRIM28-lncRNAs-mRNAs” there element relationship tables were generated.
2017-02-01 | GSE85716 | GEO
Project description:Differentially expressed SE-lncRNAs in lung adenocarcinoma
| PRJNA805532 | ENA
Project description:Hepatocellular carcinoma (HCC) is a cancer with global impact and largely refractory to current treatments. Novel treatment options are therefore urgently needed. LncRNAs play important regulatory roles in HCCs and are emerging as promising therapeutic options against HCC. We identified TP53TG1 as a promising tumor suppressor LncRNA. To understand TP53TG1 target genes and the mechanisms, we performed mRNA expression profiling in TP53TG1-overexpressing Huh7 cells and negative control.
2021-06-14 | GSE166284 | GEO