7188 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 18.63 milliseconds.

• Integrated single cell analysis in transformed follicular lymphoma

  Histological transformation of follicular lymphoma to aggressive form occurs 2-3% per year with poor outcome. Divergent evolution and an altered tumour-microenvironment (TME) have been implicated during transformation. However, phenotypic consequences of this evolution and its implication in TME remain unknown. To address this, we performed single cell whole genome and whole transcriptome sequencing of paired pre/post transformation patient samples. We further performed scWTS of additional samples from patients without transformation. Our analysis revealed evolutionary dynamics of transformation at unprecedented resolution. Integration of scWGS and scWTS identified pathways upregulated during evolution. scWTS analysis revealed a shifting TME landscape, with an exhausted signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a TME-based transformation biomarker, subsequently validated in independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and shifting cross-talk between malignant cells and TME.

  Study EGAS00001007023

• DERMATLAS__Leiomyoma_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyomas.

  Study EGAS00001007629

• DERMATLAS__Leiomyoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyomas.

  Study EGAS00001007630

• DERMATLAS__Leiomyosarcoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyosarcomas.

  Study EGAS00001007631

• Pan Prostate Cancer Group data

  The Pan Prostate Cancer Group intends to provide breakthrough advances from the analysis of a very large series of Whole Genome DNA data, contributed by many of the leading scientists and clinicians working in prostate cancer genomics generating Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The accumulated data, collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals, are presented in this series. This project will provide a global framework for the future analysis of even larger series of genomes as costs of DNA sequencing, storage, and sequence analysis decrease. In addition to these WGS data from different clinical categories, ethnicities, levels of aggressiveness, and disease managed by different treatments with information linked to long-term clinical follow up, we intend to add additional layers of data, including transcriptome and methylation data. The current data series focuses primarily on the analysis of WGS data. For further information, please refer to https://panprostate.org/, and The Pan Prostate Cancer Group Data Sharing Policy, EGAP00001003712.

  Study EGAS00001002876

• Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma

  Diffuse large B cell lymphoma (DLBCL) is the most common hematologic malignancy and is characterized by a striking degree of heterogeneity. We enrolled a total of 1001 DLBCL patients and comprehensively defined the landscape of genetic mutations, copy number alterations and expression through whole-exome and transcriptome sequencing. We identified 150 genetic drivers of DLBCL including many novel, clinically relevant genes (e.g. SPEN, SETD1B and KLHL14). Genetic drivers were highly enriched among essential genes identified by CRISPR screening in DLBCL cell lines including those of immediate potential therapeutic relevance such as MTOR, SYK, SF3B1 and XPO1. RHOA emerged as a critical driver gene from our genetic analysis and CRISPR screen; we further delineated its functional role in vitro and in vivo models to define its role as an essential oncogene in DLBCL. Our work thus identifies the functional landscape of genetic drivers and their clinical and therapeutic relevance in DLBCL patients.

  Study EGAS00001002606

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• Multi-omic characterisation of PBMCs in IBD

  We generated 10X, droplet-based Multiome (paired RNA+ATAC) data of PBMCs in 38 IBD patients. Patients are either UC or CD patients. To test the responsiveness of the cells to bacterial stimuli, we stimulated samples with either RPMI, LPS or S. Salmonella (total: 80 samples). Single-nuclei libraries are multiplexed across donors. Genotypes are provided in this dataset to perform genetic demultiplexing, phenotypes providing mapping information to retrace donors / pools / stimulations.

  Study EGAS50000000140

• Single cell and spatial transcriptomics of adult human adrenal glands

  Adrenal glands are endocrine organs secreting a variety of hormones, known to undergo tissue remodelling through constant cellular turnover. Here we employed single cell and spatial transcriptomics to investigate thoroughly adult human adrenals from 14 individuals with a focus on adrenocortical cell types and cell states. By including both male and female tissue donors of various ages, we extended the study to sexual dimorphic features of the adult gland.

  Study EGAS50000000269

• scRNAseq of ARID1B+/+ (control) and ARID1B+/- human telencephalic organoids at D120

  This dataset contains scRNAseq data of human telencephalic organoids, at day 120, from 4 different sequencing runs (libraries), as follows (please see cell line clone nomenclature in original publication): 1. Library 177136: Pat.2 ARID1B+/+ clone 2c (2 organoids, E11rep_1, E11rep_2), Pat.2 ARID1B+/- clone 2a (2 organoids: B002orig_1, B002orig_2) 2. Library 178119: Pat.2 ARID1B+/+ clone 2c (3 organoids: E11rep_1, E11rep_2, E11rep_3), Pat.2 ARID1B+/- clone 2a (3 organoids: B002orig_1, B002orig_2, B002orig_3) 3. Library 178120: Pat.2 ARID1B+/+ clone 2d (3 organoids: A3rep_1, A3rep_2, A3rep_3), Pat.2 ARID1B+/- clone 2b (3 organoids: B002_F7_1, B002_F7_2, B002_F7_3) 4. Library 184337: Pat.1 ARID1B+/- clone 1a (3 organoids: B001orig_1, B001orig_2, B001orig_3), HD.1 ARID1B+/+ clone 3a (3 organoids: 176_1, 176_2, 176_3), HD.1 ARID1B+/- clone 3b (3 organoids: F10_1, F10_2, F10_3)

  Dataset EGAD50000000498

• MRC 60 snRNA-seq

  This dataset includes snRNA-seq generated from post-mortem brain and genotype from 60 individuals. The snRNA-seq data was generated using the 10X Single Cell Next GEM Chip targeting a minimum 5,000 nuclei per sample and libraries prepared using the Chromium Single Cell 3′ Library and Gel Bead v3 kit according to manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 system at a minimum sequencing depth of 30,000 paired-end reads per nucleus. Samples were pooled (max 4 per pool) and sequenced over 4 lanes. Pool-specific genotype files (containing genotype information at individual level) were used to demultiplex mapped pools into individual-level single-cell data. Donor DNA from samples processed at Imperial College were genotyped using the Illumina Infinium Global Screening Array v2.0.

  Dataset EGAD50000000965

• MOSAIC - Multi-Omics Spatial Atlas In Cancer

  MOSAIC is a collaborative initiative founded by Owkin, Lausanne University Hospital (CHUV), Charité Universitätsmedizin Berlin, University Hospital Erlangen (UKER), Gustave Roussy Institute in Paris, and University of Pittsburgh. The goal of MOSAIC is to build the largest collection of spatial omics data in cancer. By integrating comprehensive high quality clinical annotations with advanced deep profiling techniques, MOSAIC aims to uncover novel cancer subtypes and identify key drug targets and biomarkers within them.

  Study EGAS50000000689

• Comparison Across Multiple Types of Sleep Deprivation

  This study is designed to assess neurobehavioral performance, as well as molecular and physiological changes associated with variations in timing and quantity of sleep. Gene expression changes associated with neurobehavioral (cognitive) performance were assessed in a time-series among individuals randomly assigned to four separate sleep conditions during a 10-day inpatient study: a well-rested control, sleep restriction with nighttime sleep, sleep restriction with daytime sleep to roughly simulate shiftwork schedules, and total (acute) sleep deprivation.

  Study phs003924

• Low T cell diversity is associated with poor outcome in bladder cancer - Single cell RNAseq and TCRseq data

  T cells are crucial effector cells in the endogenous defense against cancer, yet the clinical impact of their quantity, diversity, and dynamics remains underexplored. In this study we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients (n samples = 8). The goal was to investigate T cell subtypes of expanded and non-expanded T cell clones in blood and in tumors.

  Study EGAS50000000938

• Circulating cell-free and extracellular vesicles-derived microRNA as prognostic biomarkers in patients with early-stage NSCLC: results from RESTING study

  Lung cancer, especially non-small cell lung cancer (NSCLC), has high mortality rates. Early-stage NSCLC shows a 50% relapse rate post-surgery, with most recurrences occurring within two years and a 5-year survival of only 30%. This study focuses on the prognostic value of circulating miRNAs in surgically treated ES-NSCLC patients, aiming to assess their predictive accuracy and compare them to standard prognostic factors.

  Study EGAS50000001032

• Genomic Rearrangements in Pediatric Cancer

  Dataset EGAD00001007701

• scRNAseq of acute myeloid leukemia

  This study analyzes T-cell transcriptional state in acute myeloid leukemia (AML) and healthy donors. The goal of the study is to correlate T-cell transcriptional states abundances with response to chemotherapy. 12 samples (5 baseline and post-treatment, 2 baseline-only) from AML patients and 3 samples from healthy donors were collected and sequenced on Illumina platforms. The files were created using the GRCh38 reference through CellRanger count (10xGenomics).

  Study EGAS50000000357

• Single-cell RNA sequence analysis of iPS cell-derived cardiomyocytes treated with S-RBD-sfGFP or GFP

  To determine the transcriptional response in human cardiomyocytes treated with SARS-CoV-2 spike receptor-binding domain (S-RBD-sfGFP), human cardiomyocytes differentiated from induced pluripotent stem cells (iPSC-CMs) were replated on day 21 after differentiation and treated with S-RBD-sfGFP or control-GFP for 48 hours on day 26-28. iPSC-CMs were dissociated and the single cell suspension was analyzed by single cell RNA-sequence.

  Study JGAS000620

• Molecular analyses of stage IIIa NSCLC patients treated with neoadjuvant chemmoimmuntherapy

  This dataset comprises molecular and immunogenomic profiles from 60 individual NSCLC patients (30 male, 30 female), with samples collected at multiple timepoints including initial biopsies (IB), resections (RES), and peripheral blood mononuclear cells (PBMC) at different timepoints during treatment. It includes 32 FFPE tumor samples sequenced on Illumina with the FoundationOne panel, 20 FFPE samples sequenced on IonTorrent with the Oncomine Comphrehensive Assay Plus, and 41 samples assessed with IonTorrent via Oncomine Immune Response Research Assay panel for targeted gene expression. T-cell receptor (TCR) repertoire profiling was performed on 62 tumor samples (initial biopsies and resections, Oncomine TCR Beta-SR Assay), and 155 blood-derived samples were sequenced with Oncomine TCR Beta-LR Assay. Data files include processed sequencing results in bam format.

  Dataset EGAD50000001630

• Dataset for study Genome-wide gene expression analysis following CRISPRi of transposable elements

  Transposable elements (TEs), once regarded as parasitic genomic remnants, are now recognized as key regulators of gene expression and genome evolution, yet the functional specificity of individual TE subfamilies remains largely unexplored. This dataset investigates the transcriptional consequences of targeted repression of MER57E3 and LTR10B2 elements using CRISPR interference (CRISPRi) in human induced pluripotent stem cells (hiPSCs). hiPSCs expressing CRISPRi machinery (n = 2 biological replicates) were transduced with guide RNAs targeting individual or grouped copies of MER57E3 and LTR10B2, as well as the ZNF678 promoter or a lacZ non-targeting control. Transduced cells were subsequently differentiated into neural progenitor cells (NPCs), and total RNA was extracted for mRNA library preparation and sequencing. The dataset comprises 24 single-end mRNA-seq FASTQ files generated from these NPCs and wild-type controls.

  Dataset EGAD00001015689

• Spatial profiling of hepatocellular carcinoma identifies distinct tumor and immune micro-ecosystems related to patient outcomes

  Hepatocellular carcinoma (HCC) shows substantial intra-tumor heterogeneity that remains poorly understood. Using spatial transcriptomics, we identified 13 recurrent tumor and stromal micro-ecosystems (MES) and mapped their spatial organization and biological functions. One immune-enriched MES containing Kupffer cell–like macrophages was strongly associated with improved disease-free survival and response to atezolizumab–bevacizumab. Our findings demonstrate the value of spatial profiling for revealing rare but clinically meaningful cellular communities.

  Study EGAS50000001474

• Bone morphogenetic protein-9 controls pulmonary vascular growth and remodeling

  Human PMECs from 10 donor lungs were isolated, cultured (passages 3 to 4), synchronized by serum starvation (0.3% FCS), and stimulated with 10 ng/mL BMP-9 for 4 h. Single-cell profiling was performed using the 10X Genomics Chromium RNA 3' V3.1 kit. Five experimental groups were analyzed using cell hashing and sequenced on an Illumina NextSeq500. Data were processed with Cell Ranger and Seurat for differential gene expression and functional enrichment analysis.

  Study EGAS50000001026

• miRNA_expression_in_response_to_LPS_stimulus_in_macrophages

  Our lab is currently using macrophages as a model system for understanding how geneticvariation modulates the response to external environmental stimulus. We want to extend thisbeyond regular polyadenylated RNA to small RNAs such as miRNAs. This project wouldcover the costs of a pilot to study miRNA response to LPS stimulus, and will be performed aspart of a rotation project in the lab. We will require a small number of miRNA libraries and asingle lane of MiSeq

  Study EGAS00001000691

• scRNA_seq_of_circulatory_immune_cells_from_Crohn_s_disease_patient_blood

  Whole blood from Crohn's disease patients with active inflammation in the terminal ileum was depleted of red blood cells and partially depleted of granulocytes before single cell sequencing using 10X genomics 3'v3 kit followed by Illumina sequencing (HS4000 and NovaSeq) 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 EGAS00001004150

• Cell of Origin and Early Evolution of Leukemia in Down Syndrome

  To investigate the mechanism by which GATA1s and STAG2 deficiency contribute to Down Syndrome leukemogenesis, specifically within the propagating CD34/CD117 cell fractions from primary xenografts, we carried out transcriptional and epigenetic profiling by RNAseq and ATACseq. The chromatin accessibility landscape was compared to bulk ATACseq of individually sorted N-FL HSPC subpopulations. To investigate the mechanism underlying the synergy between T21 and GATA1s in driving preleukemia development, we analyzed the binding occupancy of GATA1. We performed Cut&Run assays to profile genome-wide GATA1 binding sites and also to quantify binding changes upon GATA1s editing in N-FL and T21-FL CD34+ enriched HSPCs. Lastly, we profiled miRNAs from N-FL and T21-FL CD34+ enriched HSPCs by miRNA-Seq.

  Dataset EGAD00001006555