Search Results - EGA European Genome-Phenome Archive

ChIP-Seq data for 5 sample(s) for thymocyte from thymus, on Genome GRCh38. 17 run(s), 17 experiment(s), 17 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001002947

H3K27ac ChIP-seq in primary prostate tumours

H3K27ac ChIP-seq and input genome sequencing was performed in 19 primary prostate tumours classified as intermediate risk. Sequencing of ChIP DNA was performed on an Illumina HiSeq 2000 as either single end 50 bp reads (for 7 samples) or paired end 100 bp reads (for 12 samples). Input DNA from all samples was sequenced using single-end 50 bp reads. The files provided are in fastq format.

Dataset EGAD00001003461

Human Embryonic Multi-tissue ChIP-seq (Manchester)

Histone ChIP-seq of 13 human embryonic tissues from weeks 6-8 of gestation. H3K4me3, H3K27me3 and H3K27ac. Biological replicates (n=2) for 11 tissues. Tissues (n): Brain (2); Retinal Pigmented Epithelium (eye)(2); Palate(2); Tongue (1); Left ventricle (heart)(2); Lung(2); Liver(2); Pancreas (2*); Stomach(1); Upper limb (2); Lower limb (2); Adrenal gland (2); Kidney (2)

Dataset EGAD00001004335

COVID-19 Postmortem Lung snRNA-seq

A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

Study EGAS00001004689

Single Cell ATAC-Seq of MELAS

This dataset includes combined single Assay for Transposase-Accessible Chromatin, using sequencing (ATAC-seq), and mitochondrial DNA sequencing of peripheral blood mononuclear cells from three individuals with m.3243A>G associated MELAS (Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like episodes).

Study phs002217

Gene Expression and Biomarker Utility in Post-Mortem Samples

The FAA Functional Genomics Team examined the feasibility of analyzing gene expression profiles using post-mortem brain, lung, muscle, and blood samples collected from aviation accident fatalities, with the goal of validating post-mortem extracted RNA for use in RNA sequencing. We compared the RNA sequencing results obtained from THC-positive and THC-negative samples to determine whether RNA sequencing on samples collected from aviation accident fatalities was possible and if any differences in gene expression associated with THC consumption were detectable post-mortem. The study population included 57 males of indeterminant age who perished in general aviation accidents and for whom post-mortem toxicological testing identified delta-9-THC or its primary or secondary metabolites, as well as negative controls. We determined that RNA sequencing on post-mortem aviation accident fatality samples is possible, and further identified genes showing differential expression in lung and muscle between THC-positive and THC-negative samples. We conclude that post-mortem tissue samples collected from aviation accident fatalities are suitable for gene expression profiling, but caution researchers that such samples have low RNA integrity numbers and some degree of microbial contamination is both probable and to be expected. Raw sequencing files (.fastq) from this study are available in dbGaP.

Study phs003546

COVID-19 severity correlates with airway epithelium–immune cell interactions identified by single-cell analysis

To investigate the immune response and mechanisms associated with severe COVID-19, we performed single-cell RNA-seq on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from 5 healthy controls. We identified airway epithelial cell types and states vulnerable to SARS-CoV-2 infection. In COVID-19 patients, epithelial cells showed an average threefold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared with moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells , including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF . The transcriptional differences in critical cases compared with moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways may suppress immune hyperactivation in critical COVID-19.

Dataset EGAD00001006339

RNA-seq data of bone marrow CD34-positive cells from 57 patients with myelodysplastic syndromes (MDS) and 5 healthy individuals (62 participants in total)

Genetic mutations in hematopoietic neoplasms, seen in disease-specific and non-specific ways, are key drivers in pathogenesis. Typically, these mutations alone don't cause neoplasms; rather, multiple mutations or breakdowns in regulatory mechanisms occur, progressing the disease through stages. Genetic mutation patterns vary even within subtypes, suggesting shared gene expression abnormalities from different mutations may drive neoplasm development. Identifying these "common factors" is vital for effective molecular-targeted therapy development. Our study aims to elucidate neoplasm pathogenesis by analyzing patient genetic abnormalities, pinpointing "common factors" in each subtype for novel targeted therapy development.

Study JGAS000724

small RNA-sequencing and RNA-sequencing of human brain tissue with temporal lobe epilepsy

This data set contains the raw .fastq files from two RNA-sequencing experiments and two small RNA-sequencing experiments. Both control brain tissue and tissue from sufferers of mesial temporal lobe epilepsy were sequenced. Two different brain regions were sequenced; the cortex and the hippocampus. For more details please see: Mills, James D., et al. "Coding and non-coding transcriptome of mesial temporal lobe epilepsy: Critical role of small non-coding RNAs." Neurobiology of disease 134 (2020): 104612.

Dataset EGAD00001005735

Primary_DIPG_expression_profiles

In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

Study EGAS00001007181

RNA sequencing data from visceral and abdominal subcutaneous adipose tissue from morbidly obese women with normal glucose tolerance or type 2 diabetes

The study group consisted of 17 obese women with normal glucose tolerance and 15 obese women with T2DM. Adipose tissue specimens were taken from the epigastric region of the abdominal wall (SAT) and from the major omentum (VAT). RNA was isolated and RNA sequencing was used to analyse the transcriptome. Dharuri H et al, Diabetologia. 2014;57(11):2384-92.

Study EGAS00001001872

MuTHER adipose tissue small RNA expression

Dataset EGAD00001000105

Pilocytic Astrocytoma ICGC PedBrain RNA sequencing

Dataset EGAD00001000617

TST170 Pilot RNA VCF

Dataset EGAD00001005710

TST170 Pilot RNA FASTQ

Dataset EGAD00001005711

Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance

Background Monocytes are key mediators of innate immunity to infection, undergoing profound and dynamic changes in epigenetic state and immune function which are broadly protective but may be dysregulated in disease. Here, we aimed to advance understanding of epigenetic regulation following innate immune activation, acutely and in endotoxin tolerant states. Methods We exposed human primary monocytes from healthy donors (n=6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2hr) and two models of endotoxin tolerance: repeated stimulations (6+6hr) and prolonged exposure to endotoxin (24hr). Another subset of monocytes was left untreated (naïve). We identified context-specific regulatory elements based on epigenetic signatures for chromatin accessibility (ATAC-seq) and regulatory non-coding RNAs from total RNA sequencing. Results We present an atlas of differential gene expression for endotoxin and interferon response, identifying widespread context specific changes. Across assayed states, only 24-29% of genes showing differential exon usage are also differential at the gene level. Overall, 19.9% (6884 of 34616) of repeatedly observed ATAC peaks were differential in at least one condition, the majority upregulated on stimulation and located in distal regions (64.1% vs 45.9% of non-differential peaks) within which sequences were less conserved than non-differential peaks. We identified enhancer-derived RNA signatures specific to different monocyte states that correlated with chromatin accessibility changes. The endotoxin tolerance models showed distinct chromatin accessibility and transcriptomic signatures, with integrated analysis identifying genes and pathways involved in the inflammatory response, detoxification, metabolism and wound healing. We leveraged eQTL mapping for the same monocyte activation states to link potential enhancers with specific genes, identifying 1,946 unique differential ATAC peaks with 1,340 expression associated genes. We further use this to inform understanding of reported GWAS, for example involving FCHO1 and coronary artery disease. Conclusion This study reports context-specific regulatory elements based on transcriptomic profiling and epigenetic signatures for enhancer-derived RNAs and chromatin accessibility in immune tolerant monocyte states, and demonstrates the informativeness of linking such elements and eQTL to inform future mechanistic studies aimed at defining therapeutic targets of immunosuppression and diseases.

Study EGAS00001007362

Non-coding RNAs Activated by the Wnt/Beta-catenin Signaling Pathway in Hepatoblastoma

Hepatoblastoma (HB) is the most common pediatric liver tumor, affecting mostly children under 3 years of age. This rare tumor represents 1% of all pediatric cancers. Genetic studies have shown that HB is characterized by high frequency mutations of the CTNNB1 gene encoding beta-catenin (around 75%) and relative genomic stability. Here we have analyzed the transcriptional profile of 21 HBs compared to matched non-tumor livers by Cap Analysis of Gene Expression (CAGE), which provides accurate and quantitative profiling of all transcripts. CAGE analysis revealed strong upregulation of known Wnt target coding genes in most tumors analyzed, consistent with previous transcriptomic studies. To better define the Wnt-dependent transcriptional landscape of HB, we integrated CAGE data with TCF4 ChIP-seq data from a CTNNB1-mutated cancer cell line and with the FANTOM5 genomic coordinates of TCF/LEF binding motifs. Both TCF/LEF binding motifs and ChIP-seq peaks were strongly enriched in the immediate upstream region, not only for protein-coding genes, but also for non-coding transcripts. Among the selected 112 top Wnt target genes at FDR<1.0E-6 and fold change>8, we found clear over-representation (66%) of distant transcription start sites (TSSs) representing lncRNAs and enhancer RNAs, which raises the question of their role in HB pathogenesis. Analysis of the 112 promoters using CAGEd-oPOSSUM confirmed the predominant involvement of Tcf/Lef transcription factors, together with HNF4G, GATA2, Sox3 and Ets-related genes. Finally, the 112 Wnt target signature defined 3 tumor subclasses, T1, T2 and T3, characterized by progressive alteration of the non-coding part of the transcriptome and significant differences in clinical behavior.

Study phs001433

1M-scBloodNL

Here we present the 1M-scBloodNL study, in which we performed single-cell RNA-seq on 120 individuals of the Northern Netherlands population cohort Lifelines. For each individual peripheral blood mononuclear cells (PBMCs) were sequenced in an unstimulated condition, and after 3 and 24 hour in vitro stimulation with C. albicans (CA), M. tuberculosis (MTB) and P. aeruginosa (PA), totalling approximately 1.3 million cells. scRNA-seq was conducted with the 10X Genomics 3'-end v2 (72 libraries) and v3 (33 libraries) technology. In general, each library contains PBMCs from 8 donors and 2 different stimulation-timepoint combinations. Donors were demultiplexed using a combination of SoupOrCell (https://www.nature.com/articles/s41592-020-0820-1) and genotype information to assign the correct donor to a donor-specific cell cluster.

Dataset EGAD00001007764

scRNA-seq data of BALF and blood cells from COPD and control

Chronic obstructive pulmonary disease (COPD) is ranked the third leading cause of death worldwide and hence constitutes a significant burden, both medically and financially. To date, the cellular mechanism underlying COPD is poorly understood and thus no effective therapy is currently available. To broaden the current knowledge of the immune landscape in the alveolar space, we performed scRNA-Seq of CD45-enriched bronchoalveolar lavage fluid (BALF) cells and isolated blood leukocytes obtained from COPD patients and healthy controls using both the Seq-Well and the Chromium (10x Genomics) technology.

Study EGAS00001004369

Dataset for upper_gastrointestinal_tumor-RNA

Rare cancer sequencing data of 44 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008853

Dataset for melanoma-RNA

Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008858

Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

Dataset EGAD00001004938

ChIP-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

Dataset EGAD00001003432

Primary Neuroblastoma Circle-seq Data

Circle-seq data for 21 primary neuroblastoma samples supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

Dataset EGAD00001006580

ATAC-seq

This dataset contains the raw sequencing data (Runs) for all 10x Genomics single-cell ATAC-seq Experiment.

Dataset EGAD00001009822

Dataset to study clonal evolution in iAMP21 patient SJBALL030072using scWGS-seq

scWGS-seq of flow sorted blast and normal cells from SJBALL030072with 66 high quality cells sequenced (61 blast and 5 normal)

Dataset EGAD00001010288

ATAC-seq of cohesin-mutated and -wildtype adult AMLs

ATAC-seq (Illumina TDE1 Transposase) to profile accessible chromatin regions of cohesin-mutated (STAG2 or RAD21 mutations) and -wildtype adult AMLs.

Dataset EGAD00001011267

HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

Dataset EGAD00001003534

RNA sequencing of myxofibrosarcoma

RNA sequencing (fastq files) of 29 samples of myxofibrosarcoma

Dataset EGAD00001004102

HipSci - Embryonic Stem Cells - RNA Sequencing - April 2016

Dataset EGAD00001002000

HipSci - Alport Syndrome - RNA Sequencing - July 2017

Dataset EGAD00001003532

HipSci - Battens Disease - RNA Sequencing - July 2017

Dataset EGAD00001003533

HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

Dataset EGAD00001003535

HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

Dataset EGAD00001003540

HipSci - Macular Dystrophy - RNA Sequencing - July 2017

Dataset EGAD00001003541

HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

Dataset EGAD00001003542

HipSci - Usher Syndrome - RNA Sequencing - July 2017

Dataset EGAD00001003543

release_2: ICGC PedBrain: whole exome sequencing and Target-Seq

Dataset EGAD00001001624

IVF MeDIP-seq bam files

Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins conceived through in vitro fertilisation

Dataset EGAD00001003158

UCSF brain tumor data

Single Nuclei ATAC seq data from GBM tumor samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005314

Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A063 using scWGS-seq

scWGS-seq of flow sorted blast and normal cells from SJE2A063 with 80 high quality cells sequenced (75 blast and 5 normal)

Dataset EGAD00001011328

Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A066 using scWGS-seq

scWGS-seq of flow sorted blast and normal cells from SJE2A066 with 69 high quality cells sequenced (62 blast and 7 normal)

Dataset EGAD00001011329

Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A067 using scWGS-seq

scWGS-seq of flow sorted blast and normal cells from SJE2A067 with 78 high quality cells sequenced (73 blast and 5 normal)

Dataset EGAD00001011330

9296 results for "cancer rna-seq"

in 40.94 milliseconds.

BLUEPRINT: WGBS-seq of B cells

WGS seq data (56 tumor/control pairs) for study EGAS00001001394

4C-seq data

single-cell ATAC-seq

ALI culture bronchial cells and alveolar lung surgical resection scRNA-Seq

Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

Single-cell ATAC-Seq (Chromium Next GEM Single Cell ATAC kit v1.1 from 10X Genomics )

BLUEPRINT September 2016, ChIP-Seq for thymocyte from thymus, on Genome GRCh38