11936 results for "cancer rna-seq"

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• Elucidation of male-specific genetic regulation through multi-layered omics analysis

  We performed single-cell RNA-sequencing of peripheral blood mononuclear cells from asthma patients and single-cell multiome (RNA+ATAC) profiling from COVID-19 patients.

  Study JGAS000862

• A Multi-Omic Single-Cell Atlas of Human Gynecological Malignancies

  Matched single-cell transcriptomic sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq) were performed for 11 fresh human tumors collected from the endometrium or ovary. More detailed information for each patient tumor will be provided in selected phenotype/attributes data. Both scRNA-seq and scATAC-seq assays revealed the underlying cellular heterogeneity in transcriptional output and in chromatin accessibility for each patient tumor specimen. In this work, we identified potential non-coding regulatory elements that mediate cell type-specific gene expression patterns. These data will serve as an important reference for the single-cell genomics and gynecologic oncology research communities.

  Study phs002340

• Combined DNA Methylation and Genotyping via scTAMARA-seq (DNA)

  This dataset features single-cell DNA methylation and nuclear genotyping data obtained using the scTAMARA-seq protocol, a combination of SDR-seq and scTAM-seq. The targeted panel, 200 DNA methylation (a subset of the orginal 448 CpG targets) and 167 genotyping targets, were applied to a CD34+ enriched bone marrow sample from patient X.1. The data was generated on the Mission Bio Tapestri platform.

  Dataset EGAD00001015496

• RNA Fusion Panel

  RNA extracted from FFPE tumour samples 368, 455, 503, and 521, sequenced using the TruSight RNA Fusion Panel

  Dataset EGAD50000000272

• H3K27Ac ChIP-seq of 9 cHL cell lines

  The dataset contains 36 ChIP-seq data for H3K27Ac and their corresponging inputs for 9 cHL cell lines. Data are raw paired-end fasq files for each histone and input, and for each cell line.

  Dataset EGAD50000001272

• ChIP-seq peaks of H3K27ac

  ChIP-seq peaks of H3K27ac. The dataset includes FASTQ files, BAM files, and analyses of the ChIP-seq peaks of H3K27ac determined using MACS2

  Dataset EGAD00001008964

• Genetic control of the transcriptomic response of monocytes to bacterial and viral stimuli assessed by RNA-seq in Africans and Europeans

  Humans differ in the outcome that follows exposure to life-threatening pathogens, yet the extent of population differences in immune responses, and their genetic and evolutionary determinants, remain undefined. Here, we characterized, using RNA-sequencing, the transcriptional response of primary monocytes from Africans and Europeans to bacterial and viral stimuli - ligands activating Toll-like receptors pathways (TLR1/2, TLR4 and TLR7/8) and influenza virus - and mapped expression quantitative trait loci (eQTL). We identify multiple cis- and trans-eQTL that contribute to the marked differences in immune responses detected within and between populations, including a TLR1 master regulator that decreases expression of pro-inflammatory genes in Europeans only. We show that regulatory variants have been privileged targets of natural selection, uncovering evolutionarily advantageous mechanisms, such as attenuated inflammation. Finally, we demonstrate that admixture with Neandertals introduced regulatory variants into European genomes, affecting preferentially responses to viral challenges, and identify archaic haplotypes that contributed to population genetic adaptation.

  Study EGAS00001001895

• Single-cell RNA-seq of celiac disease-specific plasma cells

  Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGP) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls, and performed RNA-sequencing with clonal inference and transcriptomic analysis of 3251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy-chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific vs non-disease-specific PCs and between short-lived vs long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

  Study EGAS00001004623

• Genomic Advances in Sepsis (GAinS): RNA-seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Dataset EGAD00001008730

• RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC

  For RNA sequencing (RNAseq), CD34+ hematopoietic stem cells (HSC) were isolated from healthy controls before transduction with WT-SRC and E527K-SRC lentiviral vectors in triplicate and differentiation to MK. RNA was extracted from the complete cell population as the aim was to detect differences in genes regulating MK maturation and differentiation. A total of six WT-SRC and six E527K-SRC RNA samples were used for RNAseq to identify differentially expressed genes.

  Study EGAS00001005808

• Whole-Exome-Seq-Dataset

  Whole-Exome-Seq-Dataset

  Dataset EGAD00001000042

• scATAC-seq and combined scRNA-seq of the human first trimester neurodevelopment

  Study EGAS00001007472

• whole genome seq

  20 whole genome seq

  Dataset EGAD00001004462

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Total RNA was extracted from the PaxFPE biopsy specimens (n = 116)

  Study EGAS50000000337

• An MTOR mutation hitchhikes through renal embryogenesis, driving multifocal, multiphenotypic tumours - RNA

  Embryogenesis is a vulnerable time. Mutations in developmental cells can result in the seeding of cells predisposed to disease within mature organs, creating a field effect. We characterise an embryonic cancer mutation that drives multifocal, multiphenotypic renal tumours in a 14-year-old girl. Their shared MTOR mutation, absent from normal tissues, increases protein flexibility which enables a FAT domain hinge to dramatically increase mTORC1 activity. Developmental mutations, not usually detected in traditional genetic screening, have vital clinical importance in guiding prognosis, targeted treatment, and family screening decisions for paediatric tumours.

  Dataset EGAD00001011646