Similar Datasets
Project description:miRNA expression profiling of prostate cancer cell lines, PC-3, DU145, LAPC-4, VCaP, LNCaP, 22rv1, and normal prostate epithelial cells, PrECs, was done after treating the cells with DNA demethylating agent 5-aza-2'-deoxycytidine (5azadC; Sigma-Aldrich, St. Louis, MO) and histone deacetylase inhibitor trichostatin A (TSA; Sigma-Aldrich). These treatments relieve epigenetic modifications, and thus reveal potentially epigenetically silenced miRNAs amongst the miRNAs with increased expression after the treatments.
2010-01-29 | E-MEXP-2313 | biostudies-arrayexpress
Project description:NMNAT1 is a nuclear enzyme in the mammalian NAD+ salvage pathway. Expression microarray analysis was used to study the effect of NMNAT1 knockdown on gene expression in MCF-7 breast cancer cells. Experiment Overall Design: NMNAT1 stable knockdown was achieved using a retroviral shRNA construct. An shRNA directed against Luciferase was used to generate the Luc control cells. Three independent cell populations with matching Luc controls were prepared for the expression analysis. Each cell population was treated with either vehicle control (ethanol) or estradiol (E2) for 3 hours before harvest of RNA samples. Four samples in one replicate (LUC2 CON, LUC2 E2, NMNAT2 CON and NMNAT2 E2) were hybridized to Affymetrix U133 Plus 2.0 arrays, while the other two replicates of eight samples were hybridized to Affymetrix U133A 2.0 arrays. Experiment Overall Design: All 12 samples were included for the following data normalization steps: common probe sets on both U133A 2.0 and U133 Plus 2.0 platforms were selected; within each sample group hybridized to the same microarray platform, the signal values were log2 transformed, median centered for each array, and median centered for each gene; the data sets were further adjusted using the parametric empirical Bayes method (Combat R) to eliminate batch effect caused by the different array platforms.
2009-06-05 | E-GEOD-13458 | biostudies-arrayexpress
Project description:Untargeted data independent acquisition proteomics analysis using Orbitrap mass spectrometers and DIA-Umpire
2016-06-16 | PXD003179 | Pride
Project description:Gene expression profiling in circulating endothelial cells before and after Iloprost infusion in patients with progressive Systemic sclerosis.
2010-06-28 | E-MEXP-2769 | biostudies-arrayexpress
Project description:The objective of this study is to identify genes involved in arsenic stress and more particularly to see whether the presence of arsenic can highlight a link between mobility and oxidation
2011-01-01 | E-MEXP-3021 | biostudies-arrayexpress
Project description:The eukaryotic translation initiation factor (eIF) 3a is described in various tumor entities as potential tumor marker involved in development and progression of cancer. eIF3a is the largest subunit of the eIF3 complex, a key functional entity in 80S establishment and translation initiation. We hypothesize that eIF3a is more a specific than global translation initiator and involved in signalling pathways that are frequently targeted in UBC therapy. Methods: In FFPE samples of UBC patients eIF3a expression was analysed together with overall survival. In cell culture we investigated proliferation, migration, clonogenicity and tumorgenicity of UBC cell lines with and without knockdown of eIF3a and compared the cytotoxicity of eIF3a knockdown with other translational inhibitors, including the chemotherapeutic Rapamycine. Detailed information on changed gene expression and global translation initiation were gathered by mRNA expresssion and polysomal profiling. Results: and Conclusion eIF3a is upregulated in UBC and high expression of eIF3a corresponds with longer overall survival in low grade tumors. Knockdown of eIF3a in UBC cell lines reduces their malignant phenotype, including reduced tumor growth in xenotransplanted mice. eIF3a regulates DNA damage response (ATM, ATR, CDC25A) on a translational level and we show that reduction in eIF3a expression does not hamper global translation initiation. The knockdown of eIF3a strongly influences proliferation of UBC cell lines without dramatically disturbing general translation as depicted in polysomal profiles. We therefore analysed potential changes on the mRNA level in eIF3a knockdown compared to control HT1197 cells. Differential expression of genes between eIF3a knock-down and control samples was assessed with the moderated t-test (Bioconductor's limma package). Raw p-values were adjusted for multiple hypothesis testing using the method from Benjamini and Hochberg for a strong control of the false discovery rate.
2014-08-12 | E-GEOD-45636 | biostudies-arrayexpress
Project description:To determine the physiological targets of the NELF complex, and provide insight into the mechanism of NELF activity in vivo. Experiment Overall Design: Drosophila melanogaster S2 cells, obtained from the Drosophila Genomics Resource Center, were untreated, or treated with dsRNA for 72 hours, as described in Armknecht, S. et al. (2005) Methods in Enzymology, 392: pp. 55-73. Total RNA was then extracted using the RNeasy RNA extraction kit, with on column DNAse digestion (Qiagen), according to manufacturerâs protocol. Gene expression analysis was conducted using Drosophila Genome 2.0 Genechip® arrays (Affymetrix, Santa Clara, CA). Starting with 1ug of total RNA, biotin-labeled cRNA was produced using the Affymetrix 3â Amplification One-Cycle Target labeling kit according to manufacturerâs protocol. For each array, 10ug of amplified cRNAs were fragmented and hybridized to the array for 16 hours in a rotating hybridization oven using the Affymetrix Eukaryotic Target Hybridization Controls and protocol. Slides were stained and washed as indicated in the Antibody Amplification Stain for Eukaryotic Targets protocol using the Affymetrix Fluidics Station FS450. Arrays were then scanned with an Affymetrix Scanner 3000 and data was obtained using the Genechip® Operating Software (Version 1.2.0.037) and imported into the Rosetta Resolver system (Version 6.0).
2008-10-18 | E-GEOD-6141 | biostudies-arrayexpress
Project description:High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomics studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Several different quantification approaches have been proposed, ranging from simple counting of reads overlapping given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of both performance and interpretability. We also illustrate that while the presence of differential isoform usage can lead to inflated false discovery rates in differential expression analyses on simple count matrices, and incorporation of transcript-level abundance estimates improves the performance in simulated data, the difference is relatively minor in several real data sets. Finally, we provide an R package (tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.
2015-12-10 | E-MTAB-4119 | biostudies-arrayexpress
Project description:Fusarium Head Blight (FHB) is a disease of wheat and other cereal crops, where, among other species, Fusarium graminearum infects the wheat inflorescence. Microarrays were used to observe differential gene expression in FHB-challenged spikes of the two European winter wheat genotypes Dream (moderately resistant) and Lynx (susceptible). Plants were either inoculated with the Fusarium graminearum strain IFA 65 (IFA Tulln) (500 macroconidia/floret) or were as control plants mock treated with desalted water. The inocula were injected into four spikelets at early anthesis and spikelets were later on collected at 32 and 72 h after inoculation. Four plants were sampled per genotype/treatment/sampling date. Total RNA was extracted from collected spikelets, and microarray analysis was performed using the Affymetrix Wheat GeneChip.
2013-01-09 | E-MEXP-3509 | biostudies-arrayexpress
Project description:'Background: Large-scale sequencing of cDNA (RNA-seq) has been a boon to the quantitative analysis of transcriptomes. A notable application of significant biomedical relevance is the detection of changes in transcript usage between experimental conditions. For example, discovery of pathological alternative splicing may allow the development of new treatments or better management of patients. From an analysis perspective, there are several ways to represent RNA-seq data to unravel differential transcript usage, such as annotation-based exon-level counting, differential analysis of the `percent spliced in'' measure or quantitative analysis of assembled transcripts. The goal of this research is to compare and contrast current state-of-the-art methods, as well as to suggest improvements to commonly used workflows. Results: We assess the performance of representative workflows using synthetic data, and explore the effect of using non-standard counting bin definitions as input to a state-of-the-art inference engine (DEXSeq). Although the canonical counting provided the best results overall, several non-canonical approaches were as good or better in specific aspects, and most counting approaches outperformed the evaluated event- and assembly-based methods. We show that an incomplete annotation catalog can have a detrimental effect on the ability to detect differential transcript usage in transcriptomes with few isoforms per gene, and that isoform-level pre-filtering can considerably improve the false discovery rate (FDR) control. Conclusion: Count-based methods generally perform well in detection of differential transcript usage. Controlling the FDR at the imposed threshold is difficult, mainly in complex organisms, but can be improved by pre-filtering of the annotation catalog.'
2015-07-23 | E-MTAB-3766 | biostudies-arrayexpress