Search Results - EGA European Genome-Phenome Archive

Covid19 RNAseq BAM files

RNA Sequencing using Illumina’s TruSeq Stranded Total RNA with RiboZero Globin depletion library pre-kit and sequencing on the NovaSeq 6000.

Study EGAS00001007050

Covid19 RNAseq Fastq files

RNA Sequencing using Illumina’s TruSeq Stranded Total RNA with RiboZero Globin depletion library pre-kit and sequencing on the NovaSeq 6000.

Study EGAS00001007022

Whole exome sequencing, RNA sequencing and single-cell RNA sequencing of 4 melanoma patients

We perfomed whole exome sequencing and RNA sequencing of 4 melanoma patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

Study JGAS000285

Determining off-target effects of splice-switching antisense oligonucleotides using short read RNAseq in neuronally differentiated human induced pluripotent stem cells

Neuronal cells derived from female healthy control hiPSC lines LUMCi003-A, LUMCi003-B and LUMCi023-A were transfected with in total four different splice-switching AONs targeting three different human transcripts. Untransfected samples as well as samples transfected with a scrambled AON were included as controls. Three days after transfection, RNA was isolated for sequencing using Illumina Novaseq6000 in order to perform differential gene expression analysis and differential splicing analysis to determine off-target effects. Sequencing was performed in two batches: one containing the samples from cell line LUMCi003-A and the other containing cell lines LUMCi003-B and LUMCi023-A.

Dataset EGAD50000001742

ICARUS-LUNG01 dataset

A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

Dataset EGAD50000001014

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

Evolutionary Analysis of Chronic Lymphocytic Leukemia Cells During Relapse After Allogeneic Hematopoietic Stem Cell Transplant

We investigated the molecular dynamics driving relapse of chronic lymphocytic leukemia (CLL) following allogeneic hematopoietic stem cell transplant (allo-HSCT) through an integrated analysis of whole exome, bulk transcriptome, bulk methylome and single cell transcriptional data from paired leukemic samples representing 19 patients. We found that their clinical kinetics corresponded to distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are distinct from those imposed by chemotherapy.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out ribosome profiling (Ribo-seq) and RNA-sequencing on CLL samples and isolated primary B cells from healthy donors. We discovered novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

Study phs001998

Identification and characterization of tertiary lymphoid structures in brain metastases

Brain metastases (BrM) are the most common cancers in the brain. We performed transcriptome-wide gene expression profiling combined with spatial immune cell profiling to characterize the tumor immune microenvironment in BrM from different primary tumors. We found that BrM from lung carcinoma and malignant melanoma showed overall higher immune cell infiltration as compared to BrM from breast carcinoma. RNA sequencing-based immune cell deconvolution revealed gene expression signatures indicative of tertiary lymphoid structures (TLS) in subsets of BrM from lung cancer and melanoma. This finding was corroborated by multiplex immunofluorescence staining of immune cells in BrM tissue sections. Detection of TLS signatures was associated with prolonged survival after BrM diagnosis in lung cancer patients. Our findings highlight the cellular diversity of the tumor immune microenvironment in BrM of different cancer types and suggest a role of TLS formation for BrM patient outcome.

Study EGAS50000000563

Single-cell RNA sequencing of 16 NPM1 mutated AML patients

NPM1 mutated AML is the largest class in WHO classification, however several subtypes within NPM1 were already reported. Here, we sequence 16 NPM1 mutated AML samples with single-cell RNA-sequencing and multi-color flow cytometry from three major NPM1 subtypes we previously identified, totaling more than half a million cells. We show that the differences among three NPM1 subtypes are mainly driven by cell composition, and these differences are also reflected at cell surface protein level. With the re-analysis of CITE-seq data from another cohort and single cell variant calling on our data, we also report two distinct stem cell phenotypes: one with leukemic (CD34dimCD38-CD45RA+) and another with pre-leukemic (CD34+CD38-CD45RA-) origin. We believe that our data and findings provide novel insights regarding the etiology of NPM1 mutated AML.

Study EGAS50000000332

Tumor Thrombus Dataset

the dataset contains Exome and RNA fastq files of Renal Cell Carcinoma patients, which belongs to "Integrated genomic analysis of tumor thrombus"/

Dataset EGAD00001008010

Orthotopic murine Group 3 medulloblastoma in C57Bl/6 mice treated with sham or craniospinal irradiation

Mice with medulloblastoma (Group 3) were treated with sham (isofluorane and imaging xray) or CSI as described by Abbas et al (2022). Total RNA was isolated with RNeasy Plus Mini Kit (Qiagen), library preparation (SureSelect, Agilent), rRNA depletion (Ribo-Zero Plus, Illumina) and sequencing were carried out by GenomicsWA or Australian Genome Research Facility. Libraries were sequenced on NovaSeq 6000 S1 flow cells as paired-end 150bp reads (Illumina).

Dataset EGAD00001008510

Raw DNA and RNA data from breast cancer organoids, control samples and biopsies

Whole genome sequencing data for primary tumors, matching control material from blood and their corresponding organoid. Whole transcriptome data for organoids.

Dataset EGAD00001003751

Five Mantle Cell Lymphoma Patients Before and After Failure of Standard Chemotherapy

MCL cells were isolated from different tissues of five patients with MCL at diagnosis, and at the time of the first clinical relapse after failure of standard immunochemotherapy based on alternation of R(ituximab)-CHOP and R-high-dose-araC. All patients signed informed consent according to the Declaration of Helsinki. Four patients were diagnosed with classical nodal aggressive MCL, and all these patients experienced early relapse (i.e., progression of disease POD < 12 months). One patient was diagnosed with indolent non-nodal MCL and relapsed 9 years after initial MCL diagnosis. The dataset presents single cell RNA sequencing data as well as whole exome sequencing data for these five patients.

Dataset EGAD50000001213

Cell line data (RNAseq, ATACseq, ChIPseq)

Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

Dataset EGAD00001005493

UCSF-CASCADE analysis of metastatic prostate cancer

Targeted cancer therapy inevitably selects for tumor cells that harbor some form of therapy resistance. This phenomenon is a principle reason why advanced prostate cancer, which can be treated with agents targeting androgen signaling dependency and DNA repair failure, is a lethal condition. The influence of a patient's clinical history and disease evolution on how their disseminated tumors develop resistance has been difficulty to study, because few autopsy studies have been performed in heavily treated patients with DNA-repair deficient metastatic castration-resistant prostate cancer (mCRPC). Here, we assessed how resistance to targeted cancer therapies evolved in an autopsy cohort of 54 mCRPC tumors from six men. This dataset includes targeted sequencing, exome sequencing, and RNA-seq conducted on these biopsies.

Dataset EGAD00001010275

IL-17 Signaling in Human iPSC-derived Midbrain Neurons in Parkinson's Disease

To determine IL-17-induced global transcriptome changes in midbrain neurons derived from induced pluripotent stem cells (iPSC) from three sporadic Parkinson's disease (PD) patients and three age- and sex-machted controls, deep RNA sequencing (RNA-Seq) of IL-17-treated and untreated PD and control iPSC-dderived midbrain neurons was performed. Total RNA was isolated from untreated and IL-17-treated cells with the TruSeq RNA Sample Preparation Kit v2 (Illumina). RNA libraries were quantified using the KAPA SYBR FAST ABI Prism Library Quantification Kit (Kapa Biosystems) and cluster generation was performed on the cBot with the TruSeq SR Cluster Kit v3 (Illumina). The sequencing run was performed on a HiSeq 1000 instrument (Illumina) using the indexed, 50 cycles single read (SR) protocol and the TruSeq SBS v3 Kit (Illumina). Image analysis and base calling resulted in .bcl files that were then converted into .fastQ files by the CASAVA1.8.2 software. FastQ files were aligned to the human genome (hg19) using STAR.and annotated with gencode.v19. DESeq2 was used to determine differential expression. Criteria to determine significantly dysregulated genes were as follows: adjusted p-value below 0.05 and log2FC (fold change) of greater than one. Only genes with a mean expression value of greater than one RPKM (reads per kilobase per million mapped reads) throughout the dataset were considered. Control and PD samples were analyzed as two independent datasets. Upon IL-17 treatment only 17 genes were found to be dysregulated in controls but 125 genes were dysregulated in iPSC-derived midbrain neurons from PD patients. The 125 IL-17-dependent genes in PD iPSC-derived neurons separated the treated from untreated PD samples using an unsupervised, hierarchical clustering applying an Euclidean distance metric. More detailed study information can be found in Sommer A, Maxreiter F, Krach F, Fadler T, Grosch J, Maroni M, Graef D, Eberhardt E, Riemenschneider MJ, Yeo GW, Kohl Z, Xiang W, Gage FH, Winkler J, Prots I, Winner B. Th17 Lymphocytes Induce Neuronal Cell Death in a Human iPSC-Based Model of Parkinson's Disease. Cell Stem Cell. 2018 Jul 5;23(1):123-131.e6. doi: 10.1016/j.stem.2018.06.015. PMID: 29979986

Study phs001686

Single-cell spatiotranscriptomic dissection of ex vivo human heart right atrial appendage and pericardial fluid in ischemic heart disease and heart failure

We use cardiac and pericardial fluid biopsies collected during open-heart surgery in control, ischemic heart disease, heart failure, and myocardial infarction context. For each sample, single-nuclei RNA sequencing experiment is performed. We also perform spatial transcriptomics on the heart samples. We annotate the cells in major cell types, in addition to subtypes annotation of vascular and immune cells. The disease annotation enables us to reveal substantial differences in gene expression at the cell subpopulation levels. Our results demonstrate the importance of high-resolution cellular type/state mapping in the elucidation of human cardiovascular disease pathogenesis.

Study EGAS50000000653

Single-cell RNA sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

Single-cell RNA sequencing (scRNA-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

Dataset EGAD00001007015

RNA-seq

RNA-sequencing data

Dataset EGAD00010001719

Deciphering molecular mechanisms underlying hematological malignancies and development of novel therapeutic approaches

We aim to identify epigenomic features dysregulated in hematological malignancies through epigenetic analyses of hematological malignant cells. We also perform RNA sequencing to profile tumor cell-specific transcriptomes and target gene sequencing to profile somatic gene mutations in tumor cells. Regarding identified epigenomic abnormalities, we perform further analysis to determine whether they could be good candidates to translate into therapy development. To this end, we will modulate the activity of targets by using their activators and inhibitors in vitro and establish xenograft mouse models of hematological malignancies and manipulate their activity in vivo. Through these studies, we aim to develop new therapeutic agents or modalities that lead to improved patients�� prognosis.

Study JGAS000603

Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer RNA-Seq

The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the patient matched RNA-Sequencing data.

Study EGAS00001003307

RNA Splicing Dysregulation in the Pathogenesis of Chronic Lymphocytic Leukemia

RNA splicing dysregulation is a hallmark of cancers, promoting the onset and progression of disease. In chronic lymphocytic leukemia (CLL), spliceosome mutations leading to aberrant splicing occurs in approximately 20% of patients. However, the underlying mechanism for splicing defects in spliceosome unmutated CLL cases remains elusive. To discover posttranscriptional regulation of RNA splicing, we performed RNA sequencing using RNA derived from B cells from 6 healthy donors and 36 CLL patients, along with MAZTER sequencing from 9 CLL patients (8 matched with RNA sequencing cohort) and B cells from 5 healthy donors. We found that CLL cells have dysregulated m6A modification sites on transcripts from splicing factors, suggesting a critical role of m6A modification in RNA splicing dysregulation.

Study phs003191

Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia.

In this study we investigate the role of TCF7-SPI1 fusions, more specifically in cooperation with RAS mutations. We make use of patients samples. This study contains paired-end RNA sequencing of the patients, Oxford Nanopore Technologies (ONT) sequencing, single cell RNA sequencing and RNA sequencing of treatment with inhibitors of these samples.

Study EGAS00001005097

Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

Study EGAS00001001659

The Environmental Determinants of Diabetes in the Young Study (TEDDY)

Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

Study phs001442

3884 results for "RNA AND sequencing OR transcriptome"

in 13.05 milliseconds.