7190 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 117.15 milliseconds.

• RNAseq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing. Files were processed and quantified with kallisto v0.42.5 using the human reference transcriptome (Gencode Release 28). Countdata was rlog-transformed.

  Dataset EGAD00001009649

• On-target mutations confer resistance to WRN helicase inhibitors in Microsatellite Unstable Cancer Cells

  This study investigates genetic dependencies and resistance mechanisms to Werner helicase inhibitors (WRNi) in microsatellite-unstable (MSI) cancer models. To define determinants of WRN dependency and acquired resistance, we performed genome-wide CRISPR-Cas9 knockout screens, CRISPR base-editing mutagenesis screens targeting WRN, targeted sequencing of resistance-associated variants, bulk RNA sequencing, and whole-genome sequencing. The datasets deposited in EGA comprise raw sequencing files from CRISPR-Cas9 knockout screens, CRISPR base-editing screens, targeted DNA sequencing, RNA-seq experiments, and whole-genome sequencing of parental and drug-treated cell populations, including models with spontaneously acquired resistance. These data enable investigation of WRN synthetic lethality, genetic modifiers of WRNi response, and genomic alterations emerging under selective pressure.

  Dataset EGAD00001015822

• scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

  Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

  Study EGAS00001002882

• Human iPSC-derived brain cell RNA sequencing data DAC at UEF (DAC-hiPSC)

  RNA sequencing data from human iPSC-derived cell model systems

  Dac EGAC50000000949

• RNA-seq of PDAC patient-derived xenograft tumors

  Study EGAS00001007070

• RNA sequencing of Non-Small Cell Lung Cancer and adjacent normal tissue

  RNA sequencing was performed on 108 NSCLC tumor samples and their paired adjacent normal tissues (n=21) to identify associations with clinical and immune characteristics.

  Study EGAS50000000246

• Impact of Glycolysis Inhibition on the Epigenome of Synovial Fluid T Cells in Juvenile Idiopathic Arthritis

  Juvenile Idiopathic Arthritis (JIA) encompasses a group of childhood-onset autoimmune conditions characterized by joint inflammation and mononuclear cell infiltration, especially of activated CD4+ memory/effector T (Tmem/Teff) cells in synovial fluid (SF). JIA CD4+ T cells exhibit a distinct inflammation-associated epigenomic profile, though the underlying molecular mechanisms remain unclear. This study investigates the role of glycolysis in shaping the epigenomic landscape of JIA SF CD4+ T cells, with a focus on H3K27ac histone modifications. Using an ex vivo model of antigen stimulation, CD4+ T cells were isolated from peripheral blood (PB) of healthy controls (HC) and synovial fluid from JIA patients. Cells were activated in vitro with anti-CD3/CD28 for 24 hours, and changes in H3K27ac were assessed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). To explore the specific role of glycolysis, cells were also treated with 2-deoxyglucose (2DG), an inhibitor of glucose-6-phosphate production. This inhibition impacted both H3K27ac acetylation patterns and gene expression associated with the activated epigenomic regions. Additionally, HC CD4+ T cells were activated in vitro in the presence of 30% SF or 30% plasma from JIA patients. RNA sequencing (RNA-seq) was performed to examine SF-induced transcriptional changes, providing insight into the metabolic dysregulation and epigenomic alterations observed in JIA SF CD4+ T cells. This dataset includes ChIP-seq and RNA-seq data that collectively advance our understanding of how glycolysis and the SF environment contribute to the epigenetic and transcriptional regulation in JIA CD4+ T cells.

  Study EGAS50000000808

• RNA-seq FASTQ files studied in A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  This data set contains 18 paired fastq files (RNA-seq).

  Dataset EGAD50000000948

• H3K27ac ChIP-seq and RNA-seq of lung neuroendocrine tumors

  H3K27ac ChIP-seq and RNA-seq of lung neuroendocrine tumors

  Dataset EGAD50000000083

• subset of RNA-Seq data from umbrella study EGAS00001004338, used in EGAS00001004786

  linking 55 samples/74 RNA-Seq runs - out of EGAS00001004338 Umbrella study to EGAS0001004786

  Dataset EGAD00001006615