3796 results for "RNA AND sequencing OR transcriptome"

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• Elucidation of the association between viruses and autoimmune diseases and COVID-19

  We determined the presence or absence of endogenous herpesvirus 6 (eHHV-6) and calculated annelovirus levels from whole genome sequencing of 2,238 patients with autoimmune diseases and 2,919 controls. We performed genome-wide association analysis using WGS of 22 eHHV-6B-positive cases and -negative cases. Single-cell RNA sequencing was performed using human peripheral blood mononuclear cells from 3 eHHV-6B-positive SLE patients and 5 -negative SLE patients.

  Study JGAS000741

• The genomic landscape of follicular and diffuse large B-cell lymphoma

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing and RNA sequencing of follicular and diffuse large B-cell lymphoma. Follicular and diffuse large B-cell lymphomas are the most common B-cell lymphomas in adulthood. Analyses were performed in concordance with the guidelines of the ICGC. The results define the genomic landscape of structural variants, somatic single nucleotide variants and mutational signatures in these lymphomas

  Study EGAS00001002199

• Comprehensive molecular profiling of high-grade serous ovarian cancer

  The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. Here, we performed comprehensive molecular analysis, including high-pass whole genome sequencing, targeted deep sequencing, RNA sequencing, reverse phase protein arrays and immune assessment, on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

  Study EGAS00001003804

• Single cell RNAseq of lung adenocarcinoma

  Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing as well as single-cell BCR sequencing of cells from 16 LUADs and 47 multi-region normal lung tissues of defined spatial proximities from the tumors. Our multi-region single-cell sequencing analyses unravel cell populations, states, and phenotypes in the spatial and ecological evolution LUAD from the lung that comprise high-potential targets for early interception.

  Study EGAS00001005021

• Bulk-tissue RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Parkinson’s disease (PD), Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB) are three clinically, genetically and neuropathologically overlapping neurodegenerative diseases collectively known as the Lewy body diseases (LBDs). A variety of molecular mechanisms have been implicated in PD pathogenesis, but the mechanisms underlying PDD and DLB remain largely unknown, a knowledge gap that presents an impediment to the discovery of disease-modifying therapies. Transcriptomic profiling can contribute to addressing this gap, but remains limited in the LBDs. Here, we applied paired bulk-tissue and single-nucleus RNA-sequencing to anterior cingulate cortex samples derived from 28 individuals, including healthy controls, PD, PDD and DLB cases (n = 7 per group), to transcriptomically profile the LBDs. Using this approach, we (i) found transcriptional alterations in multiple cell types across the LBDs; (ii) discovered evidence for widespread dysregulation of RNA splicing, particularly in PDD and DLB; (iii) identified potential splicing factors, with links to other dementia-related neurodegenerative diseases, coordinating this dysregulation; and (iv) identified transcriptomic commonalities and distinctions between the LBDs that inform understanding of the relationships between these three clinical disorders. Together, these findings have important implications for the design of RNA-targeted therapies for these diseases and highlight a potential molecular “window” of therapeutic opportunity between the initial onset of PD and subsequent development of Lewy body dementia.

  Study EGAS00001005305

• Bulk-tissue RNA-sequencing paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from post-mortem neuropathologically-confirmed control individuals.

  Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.

  Study EGAS00001006380

• resistance mechanims to targeted therapies from RNA sequencing

  WTS of tumor tissue biopsies collected at resistance to molecular targeted agents

  Study EGAS50000000487

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• WES profiles from the CheckMate-274 clinical trial

  The dataset contains WES profiles of 487 patients from the CA209-274 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. Normalized WES libraries were pooled and sequenced on Illumina NovaSeq 6000 at a plex level appropriate to the coverage of tumor: 2 × 100 bp PE 100 M reads, germline: 2 × 100 bp PE 25 M reads.

  Dataset EGAD50000000792

• Clonal Evolution and Transcriptomic Analysis of Chronic Lymphocytic Leukemia Treated with Ibrutinib

  Disease progression has been increasingly appreciated with the use of ibrutinib to treat chronic lymphocytic leukemia (CLL). Understanding the pattern of clonal evolution and transcriptomic changes during the early treatment period with ibrutinib may provide insight into the mechanisms of resistance. We performed whole exome sequencing on sequential samples with matched germline controls from 61 patients with CLL during the first 12 months of ibrutinib monotherapy or ibrutinib in combination with rituximab. Additionally, RNA sequencing was done on a subset of 14 patients treated with ibrutinib monotherapy. The presence of clonal shifts was associated with an increased risk of disease progression, suggesting that resistant clones are more likely to emerge in CLL with greater evolutionary capacity.This cohort was later augmented with additional data (including data from 15 additional patients). In total, this second set of data contained whole exome sequencing (31 samples), RNA sequencing (6 samples) and reduced representation bisulfite sequencing (67 samples) for CLL samples and used them to identify expression subtypes of CLL. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs001473