7205 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• IKZF5 RNAseq samples for platelets, neutrophils, monocytes and CD4+ T-cells.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing (WGS) data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor (TF)-encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy (EM) revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4+ T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes (DEGs) in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Dataset EGAD00001005107

• Multivalent State Transitions Shape the Intratumoral Composition of Small Cell Lung Carcinoma

  Small cell lung carcinoma (SCLC) is an aggressive, tobacco-associated tumor characterized by rapid growth, early metastases, and initial response followed by almost invariable resistance to chemotherapy. Studies to date have not resolved the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. We combined patient-derived xenograft (PDX) (n = 64) resources with multi-omic profiling, single-cell fluorescence tracking of ex vivo tumor cells, and mathematical and statistical models to study the topology of the SCLC transcriptional state space and its plasticity.

  Study phs003102

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual bloodderived stem cells (MenSCs) have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored. We conducted a clinical study (n=42; 19 endometriosis, 23 controls) to assess whether DNA methylation profiles of freshly isolated MenSCs can identify disease-specific biomarkers. Whole-genome methylation sequencing revealed differentially methylated regions (DMRs) enriched in genes linked to hallmarks of endometriosis (e.g., inflammation, tissue remodelling, development). These DMRs robustly distinguished cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these DMRs achieved high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset showed that the DMRs may modulate gene expression, further supporting their biological relevance. These findings position MenSC DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care.

  Dataset EGAD50000002353

• Single cell RNA-sequencing (scRNA-seq) of the human hematopoietic stem cell compartment (CD34+CD38-CD45RA-)

  To identify a trajectory of human hematopoietic stem cell (HSC) activation single cell gene expression profiling of RNA from human HSC was performed by flow cytometry-based single cell deposition of CD34+CD38—CD45RA—cells from G-CSF-mobilized peripheral blood from 3 individual donors and 1 bone marrow donor in concert with single cell index-sorting (signals indexed: CD34, CD38, CD45RA, CD90, CD49f) and followed by SMARTseq2 based protocol. We show that INKA1 and CDK6/PAK4 expressing single cells segregate across alternative states of quiescence.

  Study EGAS00001004769

• Haplotype-specific assembly of shattered chromosomes in oesophageal adenocarciomas

  Genomic and epigenomic sequencing of 5 oesphageal adenocarciomas with evidence of chromothripsis. Genomic sequencing includes: Pacbio circular consensus sequencing, Pacbio continuous long read sequencing, 10X linked read and Illumia HiSeq X Ten sequencing. Epigenomic sequencing includes: Hi-C chromosome capture, ATAC-seq, ChIP seq (for H3K27ac, H3K4me3, H3K27me3 and CTCF) and long read RNA sequencing. All data types have the bam files which have not undergone haplotype resolution (demarcated as unresolved) and some data types also have haplotype resolved reads (demarcated as resolved).

  Dataset EGAD00001010871

• A non-canonical lymphoblast in refractory childhood T-cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms or represent distinct disease states. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we perform single cell mRNA sequencing of T-ALL from 58 children (84 samples) who did, or did not respond to initial treatment. We identify a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralds refractory disease across independent datasets and is associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease with the potential for immediate clinical utility. This dataset contains 56 single-cell RNA sequencing data files with corresponding single-cell T cell receptor sequencing data files. The data here form the validation cohort in our paper.

  Dataset EGAD00001015673

• Poly(A) RNA sequencing of hepatocellular carcinoma tumors and their matched noncancerous liver tissues

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics profiling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual specificity protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identification of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002337

• Development of Computational Approaches for Cell Hashing in scRNA-Seq

  As a test of cell overloading after cell hashing, a sample of peripheral blood mononuclear cells (PBMC) from a single subject was separated into naive T cells, memory T cells, and non-T cell PBMC populations using fluorescence activated cell sorting (FACS). Each population was separated into two technical replicates, then stained with BioLegend TotalSeq-A antibodies. All 6 samples were pooled, then loaded into 6 wells of a 10X Genomics Chromium 3' RNA-seq v3 chip at increasing cell counts: 16,000 (k), 24k, 32k, 48k, 64, and 80k cells per well. We also included a single sample that was not hashed or pooled, as well as a single sample that was stained with hashing antibodies, but not pooled in two separate wells.

  Study phs002695

• HuBMAP: A 3-D Tissue Map of the Human Lymphatic System

  The major goal of the 3-D Tissue Map of the Human Lymphatic System is to use microscopic and biomolecular procedures to facilitate co-registration pipelines and common 3D reconstruction algorithms. Tissue collected from human spleen, thymus and lymph node will be spatially resolved at the single cell level both within and across individuals. The approach employed involves sequencing of transcriptomes of dissociated cells and mapping to histological sections using CO-Detection by indEXing (CODEX) and /or Imaging mass spectroscopy, two highly multiplexed methods employing antibody-tagged target epitopes. Additionally, light sheet fluorescent microscopy is used to provide a higher level context for structural localization on a larger volume. The molecular data provided by this project is obtained through single-cell RNA-seq.

  Study phs002268

• Genomics of Glomerular Disorders

  The purpose of the "Genomics of Glomerular Disorders" study is to identify genetic contributions to primary glomerulopathies. This repository includes a total of N = 4,238 patients with a kidney biopsy diagnosis of a primary glomerular disorder across the following categories: focal segmental glomerulosclerosis (FSGS, N = 583), Henoch-Schönlein purpura nephritis (HSPN, N = 403), IgA nephropathy (IgAN, N = 1,555), membranous nephropathy (MN, N = 1,003), and minimal change disease (MCD, N = 694). The dataset includes a total of 2,290 patients recruited into the Cure Glomerulonephropathy (CureGN) study and another 1,948 patients from the Columbia University CKD Biobank (i.e., non-CureGN patients). The sample sizes by phenotype are counted based on enrollment diagnoses. The repository includes 3,958 WGS samples and 2,129 RNA-seq samples.

  Study phs002480