3744 results for "RNA AND sequencing OR transcriptome"

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• HG Transcriptome sequencing in the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Study EGAS00001003346

• Pooled Single-Cell RNA-Seq of iPSC-Derived Neural Stem Cells from ADHD and Control Individuals

  This dataset contains FASTQ files from pooled single-cell RNA sequencing (scRNA-seq) of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs). The iPSCs were reprogrammed using the non-integrative Sendai virus system (CytoTune-iPS 2.0), introducing OCT3/4, SOX2, KLF4, and cMYC. Donor somatic cells included keratinocytes, PBMCs, and lymphoblastoid cell lines from individuals with ADHD and age-matched healthy controls (6–18 years). iPSCs underwent standard quality control, including immunocytochemistry, qRT-PCR, mycoplasma testing, and SNP genotyping. NSCs were produced via neural induction and validated by qRT-PCR and immunostaining for PAX6, SOX2, NESTIN, TUJ1, and FOXG1. Sequencing was performed on the Illumina NovaSeq 6000.

  Dataset EGAD00001015644

• LCM-RNAseq on human lung macrophages

  In the reported study, we employed Laser Capture Microdissection (LCM) for the transcriptome profiling of lung macrophages cells populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (100 cells each) were collected by LCM from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation) and processed for RNA-seq.

  Dataset EGAD00001008694

• Bulk RNA sequencing of human T and B cells before and after interleukin-2 immunotherapy

  Bulk RNA sequencing of flow cytometry sorted human CD4+ regulatory T (Treg), CD4+ conventional T (Tcon), CD8+ T, and CD19+ B cells from systemic lupus erythematosus patients collected at baseline (day 0, before interleukin-2 immunotherpay), day 5 (after 1 treatment cycle of interleukin-2 immunotherapy), and day 68 (after 4 treatment cycles of interleukin-2 immunotherapy). The dataset comprises files from the above-mentioned 4 immune cell subsets, collected at 3 time points (day 0, day 5, and day 68) of 12 systemic lupus erythematosus patients. Due to technical reasons, day 5 samples of patient SLE_012 could not be processed and are thus missing. The complete dataset totals in 140 raw sequencing files (fastq format).

  Dataset EGAD50000000661

• RNAseq data

  RNAseq FASTq files from 797 tumors from AVANT. Sequencing libraries were generated with the TruSeq Stranded Total RNA kit (Illumina) following ribosomal RNA (rRNA) depletion with the Ribo-Zero Gold kit (Illumina). The libraries were sequenced on the HiSeq4000 (Illumina) with a sequencing protocol of 75 bp paired-end sequencing. Note: 10 samples used in the original publication were excluded from this upload due to regulations from the Human Genetics Resources Administration of China (HGRAC).

  Dataset EGAD00001009728

• Single-cell RNA sequencing of control and Notch inhibitor treated HCC PDX model

  We generated single-cell RNA-seq data for anti-Notch2 (n=3), anti-JAG1 (n=1) and anti-gD (n=4) treated LIV78 tumors. NCR nude mice bearing similarly sized LIV78 tumors (volumes between 300-900mm3) were injected intravenously with 30mg/kg body weight of either anti-Notch2, anti-Jag1 or anti-gD control antibody 72hrs prior to tumor harvest and tumor cell isolation. Following the depletion of CD45+ and Ter119+ cells, the samples were processed for single-cell RNA-seq (scRNAseq) as described previously (Long et al., 2019) using the Chromium Single Cell 3’ Library and Gel bead kit v2, following the manufacturer’s manual. cDNAs and libraries were prepared following the manufacturer’s manual (10X Genomics). Libraries were profiled by Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified using Kapa Library Quantification Kit (Kapa Biosystems, Wilmington, MA). Each library was sequenced in one lane of HiSeq 2500 (Illumina) following the manufacturer’s sequencing specification (10X Genomics) to produce the resulting FASTQ files.

  Dataset EGAD50000000738

• Tumor-resident T-cell regulate responses to checkpoint blockade immunotherapies

  In cancer models, CD103+CD8 TRM cells are implicated in the response to anti-PD-1 immunotherapy, and a subset of CD4 TRM cells expressing the integrin CD49a is required for response to anti-CTLA-4 immunotherapy. We performed single-cell RNA sequencing on tumour-infiltrating T lymphocytes (TILs) isolated from colon carcinoma et unsupervised analyses reveal several TRM populations.

  Study EGAS50000000826

• Differentiation-associated ISG expression of NK cells in chronic viral hepatitis

  Little is known about the effects of ISGs on NK cell responses in chronic viral hepatitis. Here, we determined the expression, regulation and function of ISGs in NK cells with respect to phenotype and function, we performed high-throughput single cell RNA sequencing of circulating CD3-CD56+ NK cells from healthy donors (HD) and patients with chronic HBV or HCV infections.

  Study EGAS00001007771

• scCRISPRi/a-seq Control and IFN treated iPS derived human GPC/OPCs

  Datasets consists of 2 batches of human glial progenitors (iPS), cells were sequenced as controls and IFN treated. Using the 10Genomics platform from the samples 2 libraries were built forgene expression libraries (scRNA-seq) and captured guides sequencing library (gRNA) on a set of Multiple Sclerosis associated SNPs. Batch one includes KRAB and P300 perturbed cells in 2 rounds sequenced RNA libraries for Ctrl and IFN and 1 round of capture guides for Ctrl and IFN. Batch 2 includes 1 round of both RNA expresison library and captures guides for KRAB and P300 perturbations in Ctrl and IFN treated cells.

  Dataset EGAD50000002053

• single cell RNA-seq data of circulating tumor cells from three small cell lung cancer patients

  This dataset contains raw 10x Genomics single-cell RNA sequencing data from a total of eight runs of circulating tumor cells from three small cell lung cancer patients. Each run represented by four FASTQ files (R1, R2, I1, I2) generated using the Illumina NextSeq 2000 platform. These files include read pairs as well as sample and cellular barcode indices. Circulating tumor cells were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Dataset EGAD50000002035

• Mapping_genetic_variants_underlying_gene_regulation_in_inflammed_intestinal_cell_types_to_identify_novel_IBD_drug_targets

  Biopsies from the terminal ileum and rectum of individuals with Crohn's disease are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003770

• Extensive patient-to-patient single nuclei transcriptome heterogeneity in pheochromocytomas and paragangliomas

  Pheochromocytomas (PC) and paragangliomas (PG) are rare neuroendocrine tumors of varied genetic makeup, associated with high cardiovascular morbidity and a variable risk of malignancy. We focused on PCPG tumors with germline SDHB and RET mutations, representing distinct prognostic groups with worse or better prognoses, respectively. We applied single-nuclei RNA sequencing (snRNA-seq) on tissue samples from 11 patients.

  Study EGAS00001006230

• Whole Exome and Transcriptome Sequencing in Sporadic ALS

  Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease, is a fatal and devastating neurodegenerative disorder that causes the progressive death of upper and lower motor neurons. Although many efforts have been done to elucidate molecular factors involved in the onset and progression of the disorder, the causes of ALS are yet unknown and undefined. Transcriptome studies, based mostly on microarrays, have revealed multiple perturbations of the motor neuron function, supporting the current idea that several cellular events contribute to the pathobiology of the disease, including mitochondrial dysfunction, enhanced apoptosis, glutamate-mediated excitotoxicity, free radical injury, protein misfolding, abnormal calcium metabolism and altered axonal transport. In the present study, we have deeply sequenced the whole transcriptome of ventral horns of the human lumbar spinal cord from matched control and ALS post-mortem donors. Whole exome sequencing from the same donors has also been performed to exclude known genetic variants associated to the familiar form of ALS. In addition, to characterize the ALS transcriptome we have sequenced the RNA fraction at low molecular weight in the same tissues and individuals. Genomic and transcriptomic reads have been generated using the Illumina HiSeq2000 sequencer.

  Study phs000747

• Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas

  Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents and ranges on the spectrum of malignancy from low-grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF. However, in approximately 50% of cases, no genetic driver has been established. Clinical whole genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine−threonine kinase that activates MEK. The patient who had exhausted all other therapeutic options was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1-8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements - uncovered by comprehensive clinical sequencing of a single case - are the most common genetic event in spitzoid melanoma, are present in adult melanomas, and could be amenable to MEK inhibition.

  Study EGAS00001003430

• Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

  In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

  Study EGAS50000000701

• Genetic and Epigenetic Determinants of Pediatric Obesity-Associated Asthma

  Fifty-nine obese and sixty-one normal-weight asthmatic children of African American or Hispanic background, age 7-11 years, with well controlled asthma, were recruited from clinics affiliated with Children's Hospital at Montefiore, Bronx, New York, USA. We isolated CD4+ T cells (Th cells) from a fasting sample of peripheral blood and conducted genome-wide assays of gene expression by Directional Transcriptome Sequencing (RNA-seq), DNA methylation by HELP-tagging, and examined genetic polymorphisms and single nucleotide polymorphisms (SNPs), informative about ancestry, by array-based genotyping using Multi-Ethnic Genotyping Array.

  Study phs001812

• Manchester Eye Tissue Repository Genome-Transcriptome Project

  The Manchester Eye Tissue Repository Genome-Transcriptome (METR-GT) Project comprises whole genome sequencing data and paired short read, high-depth bulk-RNA sequencing data from the neurosensory retina (NSR) and the retinal pigment epithelium (RPE) from 201 unrelated individuals that donated eye-tissue post-mortem. None of the individuals included in the cohort had phenotypic presentation, assessed post-mortem, consistent with late-stage AMD or monogenic ophthalmic disorders. In this dataset we include WGS fastq files, WGS VCF files (at an individual level and an aggregate VCF that has undergone variant-level quality control), RNASeq BAM files of the NSR and RPE, gene expression quantification files of the NSR and RPE (including raw gene counts generated by RNASeQC and estimated TPM and FPKM values generated by RSEM). Additionally, we have included the output files from eQTL mapping in both tissues, generated by tensorQTL and instances of aberrant gene expression events generated by the OUTRIDER module of the DROP pipeline.

  Dataset EGAD50000002082

• Single-cell RNA-seq of immune cells from human tumor fragments after 48 hour culture ex vivo (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of immune cells from human ovarian carcinoma, renal carcinoma and melanoma samples after 48h of ex vivo culture using the patient-derived tumor fragment platform (5 samples total). Samples were cultured in various conditions, including: untreated, CD8-IL2v-treated, CD8-IL2v + LCKi -treated, aPD1-treated, CD8-IL2v + aPD1 -treated, Untargeted IL2-treated, aCD3-treated and aCD3 + CD8-IL2-treated . FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on immune cells from all conditions combined per patient.

  Dataset EGAD50000000377

• RNA-seq datatset of primary human thymocyte subsets

  FASTQ-files of RNA-seq experiments of 8 primary human thymocyte subsets, isolated by flow-cytometry (FACS) from neonatal thymus biopsies. All samples were sorted to be negative for the expression of the lineage surface markers CD11c, CD19, CD56, CD141 and CD303 and additionally had the following surface phenotypes: DN1 (CD4-CD8-CD7+CD1a-CD161-CD38-); DN2 (CD4-CD8-CD7+CD1a-CD161-CD38+CD3-TCRab-); DN3 (CD4-CD8-CD7+CD1a+); ISP (CD4+CD8-CD3-TCRab-CD1a+); DPE (CD4+CD8+TCRab-CD69-); DPL (CD4+CD8+TCRab+CD69+); SP4 (CD4+CD8-); SP8 (CD4-CD8+). Samples were sorted from 2-4 pediatric patients undergoing heart surgery.

  Dataset EGAD50000001599

• BLUEPRINT release August 2016, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 6 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 24 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002339

• BLUEPRINT release August 2014, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 4 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000903

• BLUEPRINT release January 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001165

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  RNA-Seq data for 212 CD4-positive, alpha-beta T cell sample(s). 212 run(s), 212 experiment(s), 212 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002671

• BLUEPRINT release August 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001534