Ontology highlight
ABSTRACT:
PROVIDER: PRJNA271409 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1737390_1.fastq.gz | Fastqsanger.gz | |||
| SRR1737390_2.fastq.gz | Fastqsanger.gz | |||
| SRR1737400_1.fastq.gz | Fastqsanger.gz | |||
| SRR1737400_2.fastq.gz | Fastqsanger.gz | |||
| SRR1737410_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 96 |
Similar Datasets
Project description:We constructed a genome wide target profile of hsa-miR-503, hsa-miR-103, and hsa-miR-494 by sequencing RNA isolated from Ago2 immunoprecipitations and total RNA samples following transfection of the respective miRNA in mature duplex form Examination of mRNA levels in HeLa cells and Ago2 immunoprecipitations from HeLa cells following miR-503, miR-103, or miR-494 mature duplex or control siRNA transfection
2015-02-04 | E-GEOD-64615 | biostudies-arrayexpress
Project description:We constructed a genome wide target profile of hsa-miR-503, hsa-miR-103, and hsa-miR-494 by sequencing RNA isolated from Ago2 immunoprecipitations and total RNA samples following transfection of the respective miRNA in mature duplex form
2015-02-04 | GSE64615 | GEO
Project description:Genome-wide hsa-miR-503, hsa-miR-103, and hsa-miR-494 target profiles [array]
| PRJNA270828 | ENA
Project description:hsa-miR-503, hsa-miR-103, and hsa-miR-494 genome wide target profiles [RNA-Seq and RIP-Seq]
| PRJNA271411 | ENA
Project description:Gene expression profile following transfection with miR-503, miR-103, or miR-494 mature duplex Examination of mRNA levels in HeLa cells following transfection of miR-503, miR-103, or miR-494 mature duplex, control siRNA against GFP, or mock transfection (lipofectamine 2000 alone)
2015-02-04 | E-GEOD-64364 | biostudies-arrayexpress
Project description:Gene expression profile following transfection with miR-503, miR-103, or miR-494 mature duplex
2015-02-04 | GSE64364 | GEO
Project description:Applying Next Generation Sequencing technique we compared the miRNA expression pattern of tumor tissue sample of 6 GPs and peritumoral region of 6 lower grade (I-II) Glioma patients, serving as control group. To determine the difference on miRNA expresion level between GBM and control cases, we performed cluster analysis on the NGS dataset of 6 replicates for each of the two goups of samples with iDEP 96 software. In order to characterize the extent of up- or downregulation, log2FC values were calculated using the iDEP.96 web tool applying the DESeq2 algorithm. On the base of that 117 known miRNAs were identified to be differentially expressed using a threshold of false discovery rate (FDR) <0.05 and fold-change> 2 during the analysis. Among them, 35 miRNAs were upregulated (log2FC > 2) and 82 miRNAs were downregulated (log2FC < -2) with biological revelance in tissue samples comparing with the control samples. To validate our results obtained by NGS, five upregulated miRNAs: hsa-miR-196a-5p, hsa-miR-21-3p, hsa-miR-92b-5p, hsa-miR-10b-3p, hsa-miR-503-5p and three downregulated miRNAs: hsa-mir-383-5p, hsa-mir-490-3p, hsa-mir-1224-3p were chosen for RT-qPCR analysis. As the result of that hsa-miR-196a-5p, hsa-miR-21-3p, and hsa-miR-10b-3p was significantly upregulated while hsa-mir-383-5p and hsa-mir-490-3p was significantly downregulated, compared with those in the control samples. The other three miRNAs: hsa-miR-1224-3p, hsa-miR-92b-5p, hsa-miR-503-5p did not show significant difference between the control group and GPs.
2024-10-31 | GSE244332 | GEO
Project description:Brain tumor neurospheres (BTCSs) are cancer cells with neural stem cell-like properties found in the fatal brain tumor glioblastoma multiforme (GBM). These cells account for less than 1% of total tumor cells, are poorly differentiated and are believed to be involved in tumor induction, progression, treatment resistance and relapse. Specific miRNAs play important roles in modulating the proliferation and differentiation of neural stem cells, therefore, we aimed to identify miRNAs controlling differentiation in GBM-BTSCs through high throughput screening miRNA array profiling. We compared the miRNA expression profiles at the neurosphere state and upon 4 and 14 days of differentiation by using LIMMA, finding 21 differentially expressed miRNAs : hsa-miR-103, hsa-miR-106a, hsa-miR-106b, hsa-miR-15b, hsa-miR-17, hsa-miR-19a, hsa-miR-20a, hsa-miR-25, hsa-miR-301a and hsa-miR-93 were found up-regulated upon differentiation, while hsa-miR-100, hsa-miR-1259, hsa-miR-21, hsa-miR-22, hsa-miR-221, hsa-miR-222, hsa-miR-23b, hsa-miR-27a, hsa-miR-27b, hsa-miR-29a and hsa-miR-29b were down-regulated. Expression of 11 of the 21 miRNAs was examined by qPCR and 7 of them were validated: hsa-miR-21, hsa-miR-29a, hsa-miR-29b, hsa-miR-221 and hsa-miR-222 increased their expression upon differentiation, while hsa-miR-93 and hsa-miR-106a were inhibited. Functional studies demonstrated that miR-21 over-expression induced the expression of glial and/or neuronal cell markers in the neurospheres, possibly due to SPRY1 targeting by miR-21 in these cells, while miR-221 and miR-222 inhibition at the differentiated state reduced the expression of those differentiation markers. On the other hand, miR-29a and miR-29b targeted MCL1 in the GBM neurospheres and increased apoptotic cell death.
2013-03-05 | GSE44842 | GEO
Project description:Objective: The purpose of this study was to investigate the miRNAs basis of tumorigenesis in LSCC, and analyze the physiological processes of target genes predicted by the screened miRNAs that may be useful for the effective therapeutic strategies. Methods: A total number of 6 patients who underwent surgery for primary laryngeal squamous cell carcinoma were recruited for miRNA array analysis. LSCC tissues compared with corresponding adjacent non-neoplastic tissues were analysed by the Affymetrix GeneChip miRNA Array 3.0 to screen effective miRNAs, then TargetScan,PITA and microRNAorg were used for target gene prediction in GeneSpring 12.5 software.Moreover, pathway-based methods were adopted to analyse physiological processes of the target genes. The screened miRNAs and the significant target genes were also validated by qRT-PCR in another 36 patients diagnosed for LSCC. Results: Analysed by the miRNAs arrays, there were seven miRNAs (hsa-miR-224, hsa-miR-183, hsa-miR-23a, hsa-miR-675, hsa-miR-27a, hsa-miR-503 and hsa-miR-4800-3p) significantly related to tumorigenesis ,and all the screened miRNAs in laryngeal squamous cell carcinoma tissues were significantly up-regulated(P<0.05). The expressions of these miRNAs were also validated by qRT-PCR. Then analysed by GeneSpring 12.5 software, there were 72 putative target genes corresponding to the seven significant miRNAs. Moreover,analysed by String database,the result indicated that most target genes could be composed of gene networks; Analysed by GO database, we observed that these target genes were involved in processes such as metabolic process, biological regulation,membrane,protein binding,ion binding and so on (P <0.05); Analysed by KEGG pathways database, MAPK signaling pathway, adherens junction and pathways in cancer played especially important role in tumorigenesis of LSCC (P<0.05). As the two important genes in MAPK signaling pathway which plays pivotal roles in tumorigenesis, FGF2 and MAP2K4 were validated by qRT-PCR, and they were significantly down-regulated(P<0.05). Conclusions: The research revealed seven miRNAs expression signature(hsa-miR-224, hsa-miR-183, hsa-miR-23a, hsa-miR-675, hsa-miR-27a, hsa-miR-503 and hsa-miR-4800-3p) of tumorigenesis in laryngeal squamous cell carcinoma,and analysed the physiological processes of the predicted target genes regulated by screened miRNAs in LSCC. The result will contribute to the understanding of the molecular basis of LSCC and help to improve the treatment. A total number of 6 patients who underwent surgery for primary laryngeal squamous cell carcinoma were recruited for miRNA array analysis. LSCC tissues compared with corresponding adjacent non-neoplastic tissues were analysed by the Affymetrix GeneChip miRNA Array 3.0 to screen effective miRNAs, then TargetScan,PITA and microRNAorg were used for target gene prediction in GeneSpring 12.5 software.Moreover, pathway-based methods were adopted to analyse physiological processes of the target genes. The screened miRNAs and the significant target genes were also validated by qRT-PCR in another 36 patients diagnosed for LSCC.
2014-10-30 | E-GEOD-62819 | biostudies-arrayexpress