3786 results for "RNA AND sequencing OR transcriptome"

in 19.53 milliseconds.

• Single-cell GoT sequencing from CH, MDS and AML patients with CH mutations

  Single-cell targeted amplicon RNA sequencing from CH (n = 3), MDS (n = 6, MDS02 in 2 replicates) and AML (n =1, in 2 replicates) samples with mutations in splicing factors (SF3B1 - n = 8 [2 -CH, 6 MDS], U2AF1 n = 1) or transcription regulators (DNMT3A - CH04). The transcripts are targeted to detect a particular CH mutation in the listed genes. U2AF1 GoT are full-length cDNA, while the rest follow the 10x 3' V3 protocol.

  Dataset EGAD00001011284

• Next Generation Sequencing Characterization of Hematopoietic Stem and Progenitors Cells in Human Systemic Lupus Eryhtematosus

  This dataset contains RNA-sequencing of Bone marrow-derived CD34+ cells from Healthy Controls (n=2) and SLE patients (n=8). SLE patients are divided into two categories based on severity: patients with moderate/mild disease (n=3) and patients with severe disease (n=5). Libraries were generated using the Illumina TruSeq Sample Preparation kit v2. Single-end 75-bp mRNA sequencing was performed on Illumina NextSeq 500. The raw fastq files are uploaded.

  Dataset EGAD00001005052

• Single Cell Sequencing of Medulloblastoma Samples

  This dataset contains the results of sequencing 9 samples (7 human/PDX, 2 cell lines) of medulloblastoma tumours (or 2 Neural Stem Cell lines). The data was collected to characterize the intratumour heterogeneity of chromothripsis in this tumour type. The 7 tumour samples underwent single cell DNA and RNA sequencing using the 10x CNVkit and 10xRNA protocols, and 1 of the tumour samples as well as the Neural Stem Cell lines underwent StrandSeq sequencing. All experiments were sequenced on Illumina sequencers. The provided files are paired-end fastq files from the sequencing experiments.

  Dataset EGAD50000000909

• Raw molecular data for "Subclonal immune evasion in non-small cell lung cancer"

  Whole exome, RNA sequencing and TCR sequencing of organoid samples derived from TRACERx patients. The dataset also includes whole exome sequencing from the tumour samples from which the organoids were generated, as well as whole exome sequencing from PDX derived from said tumours.

  Dataset EGAD00001015537

• Long-read single-cell RNA sequencing uncovers cell-type specific transcript regulation in COVID-19

  SARS-CoV-2 infection leads to extensive host transcriptomic changes, but the role of alternative splicing in shaping the immune response remains underexplored. Here, we present the first application of long-read single-cell RNA sequencing on nasopharyngeal swabs from COVID-19 patients and healthy controls to resolve transcript-level changes across cell types. Leveraging the strengths of long-read sequencing, we characterize alterations in both gene and isoform expression within cell populations of the upper respiratory tract—the primary site of SARS-CoV-2 entry. This approach provides new insights into how transcriptional regulation and splicing shape host immune responses to viral infection.

  Study EGAS50000001290

• TCR- and BCR-sequencing data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen, and RNA was extracted using the miRNeasy Mini kit. Nanodrop was used to assess quality (260/280) and quantity. Total RNA samples were also QC checked using the Caliper HT RNA HiSens assay. Samples ranging from 60-255ng RNA were re-arrayed into a 96-well plate. 5'-RACE PCR was carried out as described in "The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer" (Zhang et al.). Briefly, this involved first round and nested PCR with TRB (TCR beta chain) and IGH (immunoglobulin heavy chain) gene-specific primers. The indexed libraries were sequenced on the Illumina HiSeq platform with paired-end 250bp reads using v2 chemistry reagents.

  Dataset EGAD00001003985

• Pathogenesis and Immunity in Endemic Burkitt Lymphoma

  This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

  Study phs001282

• UNITO_Molpheno_Closed

  This dataset contains Whole Genome Sequencing, RNA-sequencing and ATAC-sequencing data obtained from PBMCs derived from blood samples of one patient with complex genomic rearrangements and the biological parents. The patient has multiple congenital anomalies and delayed development. Data access is closed.

  Dataset EGAD00001004863

• UMCU Molpheno Closed

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data obtained from PBMCs derived from blood samples of two patients with intellectual disability and/or multiple congenital anomalies and eight parents included in the University Medical Center Utrecht (The Netherlands). Data access is closed.

  Dataset EGAD00001004864

• Covid19 Transcriptomic Data analysis in Irish Population

  The Samples were collected from Saint James's Hospital, Dublin and after informed consent. RNA-Sequencing library preparation was performed using the Illumina TruSeq Stranded Total RNA Library Prep Globin kit (20020612) with an input amount of 100 – 1000 ng. Library preparation was automated and processed using a Hamilton NGS Star. Library quality was assessed using the Roche KAPA Library Quantification Kit (7960298001) and GX Caliper HS Assay (CLS760672, 760517), run on Roche Lightcycler 480 II and Perkin Elmer LabChip GX Touch analyser respectively. Libraries were pooled and sequenced (75bp PE) on an Illumina NovaSeq 6000 instrument using NovaSeq 6000 S2 Reagent Kit v1.5 (20028314) targeting 50M paired reads. Raw data (BCL format) were demultiplexed and converted to FASTQ format using BCL2FastQ (Illumina). Adapters were trimmed using Skewer (PMID: 24925680) and QC assessed using FASTQC. STAR (PMID: 23104886) was used to align reads to the reference genome (GRCh38/hg38) as well as to the transcriptome (GENCODE v. 25). Quality of the RNA alignment was assessed using Picard QC. Gene and isoform quantification was performed using RSEM (PMID: 21816040). The study shares expression data (gene.results) and chimeric.junction.out.

  Study EGAS00001007116

• Investigating immunopathological signatures associated with COVID-19 severity post Omicron

  The aim of this study was to investigate the type and duration of protective immunity alongside immunopathological signatures associated with COVID-19 severity. RNA sequencing was performed using the Illumina Stranded mRNA Prep Ligation kit to investigate the protein coding transcriptome of PBMC cells. T cell receptor (TCR) repertoire profiling was performed with the TakaraBio SMART-Seq Human TCR (with UMIs) on PBMC cells to investigate the depth and persistence of SARS-CoV-2 targeting TCRs. The cohort (n=20) consisted of 10 non-hospitalised and 10 Hospitalised individuals with samples analysed 3 months post positive SARS-CoV-2 PCR.

  Study EGAS50000000926

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• OSTEOMICS_RNA

  RNA sequencing of 79 libraries were prepared, from sample of Osteosarcoma tumors biopsied at diagnosis, with TruSeq Stranded mRNA kit following recommendations: the key steps consist of PolyA mRNA capture with oligo dT beads using 1µg total RNA, fragmentation to approximately 400pb, DNA double strand synthesis, and ligation of Illumina adaptors amplification of the library by PCR for sequencing. Libraries sequencing was performed using Illumina sequencers (NextSeq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode.

  Dataset EGAD00001008213

• RNA-sequencing of primary urothelial bladder cancer samples

  Paired-end RNA-sequencing of tumour tissue samples (n=85) from primary urothelial bladder cancer patients. Sequencing was performed using either HiSeq (n=27) or NextSeq (n=58) Illumina platforms. Of the 85 samples, 78 are Non-muscle invasive (NMIBC) and 7 are Muscle invasive (MIBC).

  Dataset EGAD00001007005

• RNAseq SCLC Cell lines MYC

  RNAseq data set (Mollaoglu et al., MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to Aurora kinase inhibition) RNA isolation from primary tumors and healthy lungs was performed using RNeasy Mini Kit (Qiagen) with the standard protocol. RNA was subjected to library construction with the Illumina TruSeq Stranded mRNA Sample Preparation Kit (cat# RS-122-2101, RS-122-2102) according to manufacturer’s protocol. Chemically denatured sequencing libraries (25 pM) are applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Following transfer of the flowcell to an Illumina HiSeq 2500 instrument (HCSv2.2.38 and RTA v1.18.61), a 50 cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002).

  Dataset EGAD00001003099

• Human omentum cell atlas

  This dataset contains single-cell RNA sequencing data derived from freshly dissociated human omental tissue. The study investigates the transcriptomic landscape of the omentum by comparing samples from patients with benign conditions against those with ovarian cancer metastasis. To capture the heterogeneity of the metastatic niche, sampling was performed across distinct anatomical sites, including non-metastasized tissue, distant omental regions, peritumoral zones, and the tumor core. This comprehensive profiling aims to define the cellular remodeling associated with malignant transformation

  Dataset EGAD50000002110

• ScRNA-seq of 6 human FL

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Dataset EGAD00001007691

• LSC RNA-Sequencing

  To infer the proteomic Mito signature in the LSC subcompartiment, myeloid blasts for 10 patients from the discovery cohort were FACS-sorted into CD34-GPR56+NKG2DLigands- (CD34-), alias 61dc5fb798e2520001702c03 CD34+GPR56+NKG2DLigands- (CD34+), alias 61dc5fb798e2520001702c03 Detailed gating strategy will be described in Donato, Correia, Andresen and Trumpp et al., (manuscript in preparation)

  Dataset EGAD00001008488

• Single circulating tumor cells in hepatocellular carcinoma

  We determined intra- and inter-vascular transcriptional heterogeneity within the circulatory system using single-cell RNA-sequencing of 113 CTCs isolated from four key vascular sites along their dissemination route in ten HCC patients. The dataset consists of 146 paired-end fastq files from 113 sigle CTCs, HuH-7 cell line, Hep3B cellline, white blood cell, tumor and normal bulk tissue.

  Dataset EGAD00001007642

• RNAseq Iron-Treated iPSC-derived Microglia

  Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms including neuroinflammation. To study the interaction between iron accumulation and inflammation, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with an increasing concentration of iron, in combination with inflammatory stimuli such as interferon gamma and amyloid β, and performed RNA sequencing.

  Dataset EGAD00001008660

• Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19

  These data correspond to samples used in the following papers: 1. GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19 2. Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19. 3. Identification of Genetic Determinants of Transcriptional Response to Metformin in Primary Human Monocytes. They are the raw RNA sequencing files as used in all downstream analysis.

  Dataset EGAD00001010176

• Transcriptomic profiling of primary tumor and paired hepatic oligometastasis of PDAC

  The dataset was generated for studying metastatic mechanism of pancreatic ductal adenocarcinoma (PDAC). It is consisted of pair-end raw RNA sequencing reads of 33 fresh froze PDAC specimens, which includes 6 tumor-adjacent normal tissues (N), 13 primary tumors (PT), and 14 hepatic metastases (HM) from 14 PDAC patients (6 N-PT-HM trios, 7 PT-HM paires, and 1 HM).

  Dataset EGAD00001006598

• miRNA data for aSAH patients with or without subsequent vasospasm

  These files contain the normalized and raw count abundances miRNA for aSAH patients. These abundances were obtained using Next-Generation Sequencing after selection of the miRNA in the RNA biobank. In total, there are 28 VSP- and 28 VSP+ patients for two-time points. Normalized data were obtained by applying size factor and VSN normalizations as described in Pulcrano-Nicolas et al. Stroke 2018. Raw count data corresponding to the raw abundances of miRNA in aSAH patients.

  Dataset EGAD00001004185

• Pheno-seq profiles of single clonal tumor spheroids derived from a patient with colorectal cancer

  Pheno-seq is a new approach that integrates high-throughput imaging and transcriptomic profiling of clonal spheroids/organoids to dissect functional tumor cell heterogeneity in 3D cell culture systems. The method is based on the iCELL8 technology (TakaraBio) that uses barcoded nanowells and a micro-solenoid valve dispenser. The CRC_spheroid dataset contains demultiplexed RNA-sequencing profiles (FASTQ file format, NextSeq 500) of 95 clonal tumor spheroids derived from a patient with colorectal cancer.

  Dataset EGAD00001004131

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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/

  Dataset EGAD00001000640

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043

• Bell_activation_timecourse

  We purified human naive and memory B cells from PBMCs. We stimulated them with IgM cross-linker providing BCR stimulation, multimeric CD40L that engages costimulatory receptor CD40 on the B cell, and cytokines IL-2 and IL-21. To comprehensively characterise activation dynamics of naive and memory B cells, we performed single-cell RNA sequencing (scRNA-seq) and B cell receptor sequencing (BCR-seq) in resting cells (day 0), before the first division (day 1), at the time of the first division (day 3) and following the full B cell differentiation (day 6)

  Dataset EGAD50000002115

• Dataset for Ewing_sarcoma_PNET-RNA

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008845

• Comprehensive single cell study of lung adenocarcinoma from early to metastatic stages

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001005054

• Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

  Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007493

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• Sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  Mapping the spatial organization of DNA-level somatic copy number changes in tumors can provide insight to understanding higher-level molecular and cellular processes that drive pathogenesis. We describe an integrated framework of spatial transcriptomics, tumor/normal DNA sequencing, and bulk RNA sequencing to identify shared and distinct characteristics of an initial cohort of eleven gliomas of varied pathology and a replication cohort of six high-grade glioblastomas.

  Dataset EGAD50000001394

• scRNAseq of ALS patients

  The data set contains information from 9 individuals (5 ALS + 4 controls) using single cell RNA sequencing in combination with TCR V(D)J sequencing to study the immune profile of the central nervous compartment (CSF). Sequencing was done using 10x Genomics platform (5’ scRNAseq & V(D)J Reagent Kits v1.1). 5P and TCR libraries were then pooled and for sequencing on the NovaSeq sequencer. Provided files are in .fastq.gz format and per individual four files are available (Read 1&2 and Lane 1&2).

  Dataset EGAD00001009623

• Newcastle COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Newcastle University hospitals. These data also include healthy control volunteers treated with IV-LPS as inflammatory controls. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors.

  Dataset EGAD00001007866

• MSC_busulfan_small_intestine_organoids

  This dataset represent the RNA-seq, which was done on untreated small intestinal organoids; small intestinal organoids treated with chemotherapeutic, busulfan; untreated small intestinal organoids co-cultured wth mesenchymak stromal/stem cells (MSCs; busulfan treated small intestinal organoids co-cultured with MSCs. The same set of samples was done for 3 different primary bone marrow MSC donors.

  Dataset EGAD00001011176

• RNA-seq data of Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Patient-matched normal kidney organoid (103H) and MRT tumoroid (103T2) models were treated for 24h with either DMSO (ctrl), 400nM MTX, or 50nM BAY to investigate the direct effects of drug treatment on the expression of key metabolic enzymes in the nucleotide biosynthesis pathways.

  Dataset EGAD00001015391

• Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [scRNAseq]

  Single-cell RNA-sequencing of brain organoids at day 120 grown in four distinct growth protocols designed to generate dorsal (D) and ventral (V) forebrain, midbrain (M) and striatum (S) tissue using eight different pluripotent stem cell lines. Per per cell line-protocol combination two organoids (biological replicates) were grown. For cell line 176 the experiment was conducted in two independent biological replicates (repititions E1 and E2).

  Study EGAS50000000662

• Immune control of functional memory CD8 T cells in normal-appearing vitiligo skin

  This study aimed to characterize immune cell states in nonlesional (NL) and perilesional (PL) skin of patients with vitiligo using single-cell RNA sequencing. Shared CD8⁺ T cell clusters were detected in both regions, with PL-derived cells enriched for immune activation pathways and NL skin showed stronger infiltration of regulatory T cells. These findings reveal functional T cell heterogeneity in vitiligo and highlight regulatory mechanisms that may limit depigmentation in NL skin.

  Study EGAS50000001317

• Bulk RNA-seq paired fastq files from i3Ns harbouring a SNCA A53T mutation, with or without RSL3 treatment

  FASTQ files from bulk RNA sequencing of a iPSC-derived rapid neuronal model (i3Ns) harbouring the SNCA A53T mutation in a WTC11 background as a model of synucleinopathy, with or without treatment of 300nM RSL3 for 6 hours. Libraries were prepared using the Watchmaker rRNA and globin depletion kit and sequenced on a NovaSeq X with an average depth of ~27 million paired-end reads with a fragment length of 100 base pairs, per sample. 19 samples are included in this dataset, each with two paired fastq files (R1 and R2). The dataset includes control neurons (WT: dcas9 parental line and C4 CRISPR control) and A53T clones (B7, H8 and L8) across two neuronal inductions (ind1 vs ind2), with or without treatment of RSL3 (UT vs. RSL3).

  Dataset EGAD50000002209

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Samples, in a form of PAXgene fixed and paraffin-embedded biopsies, were collected from the multi-site, double-blind, randomized, placebo-controlled trial, aimed at dose-finding and assessing the efficacy and tolerability of a 6-week treatment with ZED1227 capsules vs. placebo in subjects with well-controlled celiac disease undergoing gluten challenge. Total RNA was extracted from the PaxFPE biopsy specimens (n = 116) using additional cuttings from the samples on which histomorphometry was previously assessed. For the extraction, an RNeasy Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Library preparation and next-generation sequencing (NGS) were performed by the Qiagen NGS Service. A total of 10 ng of purified RNA was converted into cDNA NGS libraries. Library preparation was quality controlled using capillary electrophoresis. Based on the quality of the inserts and the concentration measurements, the libraries were pooled in equimolar ratios and then sequenced on a NextSeq (Illumina Inc., San Diego, USA) sequencing instrument according to the manufacturer’s instructions, with 100 bp read length for read 1 and 27bp for read 2. The raw data were de-multiplexed, and FASTQ files for each sample were generated using bcl2fastq2 software (Illumina Inc., San Diego, USA).

  Dataset EGAD50000000491

• A Pilot Study of Rapid Autopsy and Procurement of Tissue in Thoracic Malignancy Cancer Patients to Investigate Tumor Heterogeneity

  Integrated proteo-genomics studies to characterize tumor heterogeneity of metastatic lung adenocarcinoma and thymic carcinoma are lacking. We carried out whole exome sequencing, RNA sequencing, copy number estimation and mass spectrometry-based proteomics of 40 tumors from five rapid/warm autopsy patients. We found highly variable mutational heterogeneity that was largely driven by APOBEC-mutagenesis with the expression of APOBEC3B (Gene ID: 9582) and APOBEC3A_B (Gene ID: 100913187) due to underlying APOBEC3 region germline variants as the likely mediating mechanism. APOBEC3A_B expression was associated with increased immune tumor microenvironment and CD274 (Gene ID: 29126) expression while smoking was associated with increased APOBEC-mutagenesis in TP53 (Gene ID: 7157) mutant tumors with high APOBEC3B expression. Heterogeneity at the level of the transcriptome and proteome occurred in association with copy number heterogeneity, not APOBEC-induced mutational heterogeneity. Arm and focal copy number alterations (CNAs) occurred as an evolutionarily late event in a subset of patients, with corresponding changes in the transcriptome and proteome, implicating CNAs as a driving force of heterogeneity in the evolution of metastatic disease.

  Study phs001432

• Capture-based Methods for Transcriptomic Profiling of FFPE material

  This dataset includes all FASTQ files for 11 samples where different capture-based methods for transcriptome profiling have been tested. Specifically, we have the 'traditional' RNA-seq experiment with fresh frozen (FF) material, and 3 different capture methods for the matching formalin-fixed paraffin-embedded samples: Agilent (AGI), IDT, and Twist Biosciences (TBS). In total, there are 43 samples with paired-end FASTQ files (1 sample did not have sufficient material to test all methods). Samples are identified by the R01-R11 IDs with a suffix that indicates the capture method used (or FF for fresh frozen).

  Dataset EGAD00001007655

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Genomics of Pediatric Renal Medullary Carcinomas

  Version 1We derived faithful cancer cell lines from patients with a diagnosis of renal medullary carcinomas (RMC). These models have been sequenced with whole genome, exome and transcriptome technologies along with the patient's primary germline and tumor samples. We took these faithful models and performed loss-of-function genetic perturbation screens (e.g. RNAi and CRISPR-Cas9) along with an orthogonal small molecule screen. We identified the ubiquitin-proteasome system as an important target in RMC as well as other SMARCB1 deficient cancers.Version 2We have collaborated with the Children's Oncology Group and the study AREN03B2 to study the cohort of patients with a central diagnosis of RMC. Here, we used 10x linked read sequencing along with RNA-sequencing to profile these matched tumor-normal pairs.

  Study phs001800

• Single cell transcriptome and TCR sequencing of EBNA1, ANO2 and CRYAB-reactive T cells in multiple sclerosis.

  Molecular mimicry between Epstein-Barr virus (EBV) and self antigens in the brain has been suggested as a mechanism for how adaptive immune responses to EBV may contribute to multiple sclerosis (MS) disease pathogenesis. Anoctamin-2 (ANO2) and ɑ-crystallin B (CRYAB) have been identified as having homologous peptide sequences with the EBV antigen EBNA1. To explore T cell cross-reactivity, we stimulated PBMC from four natalizumab-treated persons with MS with full-length bead-coupled antigens and sorted proliferating CD4+ T cells by flow cytometry after 8 days. Single cell RNA sequencing was performed on T cells reacting to EBV EBNA1, ANO2, CRYAB, albumin binding domain (ABD, irrelevant protein control) and anti-CD3.

  Study EGAS50000001531

• Bulk RNA sequencing of day 2 and day 7 biopsies from the tuberculin skin test in people with latent tuberculosis, and of day 2 biopsies from saline controls

  We used the tuberculin skin test (TST) as human challenge model to study the temporal evolution of the immune response to Mycobacterium tuberculosis (Mtb) antigens in vivo. Study participants comprised healthy HIV seronegative adults, 18-60 years of age. Latent tuberculosis (TB) infection was defined as immune memory for Mtb-specific antigens identified by positive peripheral blood IFNg release assays, but no clinical or radiological evidence of active TB. Two units tuberculin each were injected intradermally into the contralateral forearms of participants. After 2 days (n=216) or 7 days (n=158), 3 mm skin punch biopsies were taken from the injection sites and processed for whole genome transcriptional profiling by bulk RNA sequencing. The time points reflect maximum clinical inflammation (day 2) and maximum T cell infiltration (day 7) of the TST. TST samples were compared to skin biopsies taken two days after control injection of saline in a separate group of individuals (n=33), comprising healthy volunteers as well as patients with active or latent TB, ranging from 18-75 years of age. This dataset includes 407 samples from 256 individuals (n=33 saline, n=223 with Day 2 and/or Day 7 TST). Skin biopsies were collected into RNAlater (Qiagen) for RNA extraction. Total RNA was obtained with the Precellys Evolution homogenizer (Bertin Instruments) and Qiagen RNeasy mini kit. RNA was subjected to DNase treatment to remove contaminating genomic DNA using a TURBO DNA-free kit (Ambion, Life Technologies). The KAPA mRNA HyperPrep Kit (Roche Diagnostics) was used to construct stranded mRNA-Seq libraries from up to 500 ng intact total RNA. Paired-end sequencing was performed on the Illumina Nextseq using the Nextseq 500/550 High Output 75 cycle kit (Illumina). Runs were demultiplexed using bcl2fastq by Illumina.

  Dataset EGAD50000001208

• Discovery of Non-ETS Gene Fusions in Human Prostate Cancer using Next Generation RNA Sequencing

  Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date little is known about the presence of non-ETS fusion events in prostate cancer. We employed next-generation transcriptome sequencing (RNA-Seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and five involving non-ETS genes such as CDKN1A (p21), CD9 and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency but interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement prone phenotype.

  Study phs000310

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• SCANDARE HNSCC 3' Tag RNA-seq

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 264 FFPE samples at baseline from 90 HNSCC patients using 3'-tag RNA-seq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001655