Rattus norvegicus
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PROVIDER: PRJNA122859 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. This SuperSeries is composed of the following subset Series: GSE16369: Limitations and possibilities of small RNA digital gene expression profiling: library preparation comparison (454) GSE16370: Limitations and possibilities of small RNA digital gene expression profiling: library preparation comparison (SOLiD) GSE16371: Limitations and possibilities of small RNA digital gene expression profiling: spleen and liver comparison (SOLiD) GSE16372: Limitations and possibilities of small RNA digital gene expression profiling: synthetic miRNAs replicates (SOLiD) GSE16373: Limitations and possibilities of small RNA digital gene expression profiling: synthetic miRNA replicates (Illumina) Refer to individual Series
2009-07-28 | E-GEOD-16374 | biostudies-arrayexpress
Project description:Limitations and possibilities of small RNA digital gene expression profiling: library preparation comparison (454)
| PRJNA122857 | ENA
Project description:Limitations and possibilities of small RNA digital gene expression profiling: spleen and liver comparison (SOLiD)
| PRJNA122861 | ENA
Project description:Limitations and possibilities of small RNA digital gene expression profiling: synthetic miRNAs replicates (SOLiD)
| PRJNA122863 | ENA
Project description:Comparison of RNA- or LNA-Hybrid Oligonucleotides in Template-Switching Reactions for high-speed Sequencing Library Preparation
| PRJDB1832 | ENA
Project description:Limitations and possibilities of small RNA digital gene expression profiling: synthetic miRNA replicates (Illumina)
| PRJNA122865 | ENA
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination of three different library preparation methods for small RNAs, two replicates per library method
2009-07-28 | E-GEOD-16370 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination of three different library preparation methods for small RNAs, two replicates per library method
2009-07-28 | E-GEOD-16369 | biostudies-arrayexpress
Project description:Living organisms are intricate systems with dynamic internal processes. Their RNA, protein, and metabolite levels fluctuate in response to variations in health and environmental conditions. Among these, RNA expression is particularly accessible for comprehensive analysis, thanks to the evolution of high throughput sequencing technologies in recent years. This progress has enabled researchers to identify unique RNA patterns associated with various diseases, as well as to develop predictive and prognostic biomarkers for therapy response. Such cross-sectional studies allow for the identification of differentially expressed genes (DEGs) between groups, but they have limitations. Specifically, they often fail to capture the temporal changes in gene expression following individual perturbations and may lead to significant false discoveries due to inherent noise in RNA sequencing sample preparation and data collection. To address these challenges, our study hypothesized that frequent, longitudinal RNA sequencing (RNAseq) analysis of blood samples could offer a more profound understanding of the temporal dynamics of gene expression in response to drug interventions, while also enhancing the accuracy of identifying genes influenced by these drugs. In this research, we conducted RNAseq on 829 blood samples collected from 84 Sprague-Dawley lab rats. Excluding the control group, each rat was administered one of four different compounds known for liver toxicity: tetracycline, isoniazid, valproate, and carbon tetrachloride. We developed specialized bioinformatics tools to pinpoint genes that exhibit temporal variation in response to these treatments.
2023-12-13 | GSE250058 | GEO