Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
Project description:The human dataset includes the gene expression profile of CD4+ T cells isolated from blood of healthy controls and plated on TCP in RPMI-1640 containing 10% FCS, Penicillin-Streptomycin (50,000 units-50 mg) and L-glutamine (2 mM). Cells were stimulated for 4 days with 20 ng/ml of IL-1beta, 100 IU/ml of IL-2, 20 ng/ml of IL-6, 20 ng/ml IL-23 plus anti-CD2/3/28 beads at a ratio of 1 bead per 10 cells. RNA samples were isolated using the RNeasy Mini Kit (Qiagen) with on-column DNA digestion. The transcriptional profile was evaluated in three different donors using the HT12v4.1 BeadChip arrays from Illumina. Total RNA obtained from CD4+ T cells exposed to Th17-promoting cytokines.
Project description:H. seropedicae wild-type or ntrC mutant were grown on three different nitrogen conditions: nitrogen limiting, ammonium shock and nitrate shock.
Project description:TGFB2-AS1 is a long non-coding RNA which is induced by ΤGFβ signaling. In order to assess the importance of TGFB2-AS1 on the regulation of gene expression, we performed an AmpliSeq transcriptomic array in human keratinocytes (HaCaT), which stably over-express TGFB2-AS1 or control pcDNA3 empty vector. In addition, cells were stimulated with TGFβ1 for 24 hours, in order to observe the effects of TGFB2-AS1 on gene expression, downstream of TGFβ signaling. RNA from the following four conditions was used in this experiment: 1) pcDNA3, 2) pcDNA3+TGFβ1, 3) pcDNA3-TGFB2-AS1, 4) pcDNA3-TGFB2-AS1+TGFβ1. Biological triplicates were used per condition.
Project description:Naïve and activated T-cells has a different response to antigenic challenge. We examine whether a cytokine like IL-6 induces different responses through the Jak-STAT pathway to affect the functional characteristics of a given CD4 T‑cell subset. We isolated naïve and effector memory (Tem) CD4 T-cells to investigated STAT1 and STAT3 binding after 1-hour treatment with 20ng/ml IL-6 in the presence of anti-CD3/CD28.
Project description:To define the role of MAGE-A1 in melanoma growth and metastasis, we performed RNA-seq analysis on MAGE-A1 overexpression (OE) and knockdown (KD) models in A375 human melanoma cell line. Our results revealed that overexpression of MAGE-A1 dramatically promoted proliferation, migration, and invasion of human melanoma cells in vitro and down-regulated of MAGE-A1 inhibited tumor cell proliferation and invasion. Furthermore, MAGE-A1 exerts its tumor promoting activity via activating including ERK-MAPK signaling pathway by RNA-seq analysis. mRNA profiles of MAGE-A1 over expression (OE), knockdown (KD), pcDNA-vector control, and pRNAT-scramble control in A375 cell line were generated using Ion torrent