Search Results - EGA European Genome-Phenome Archive

Transcriptomic analysis of TFEB knockdown in LT-HSC.

Long-term hematopoietic stem cells (LT-HSC) were sorted from human cord blood and cultured overnight before transduction with lentiviral vectors overexpressing an shRNA against Renilla (shCTRL) or TFEB (shTFEB). Six days later, mCherry+ transduced cells were sorted for RNA extraction and sequencing.

Study EGAS00001004967

Single-cell RNA and TCR sequencing of BALF from 11 ICI-pneumonitis patients and 6 controls

Dataset containing the FASTQ files of RNA (scr*) and TCR (vdj*) sequencing of 17 bronchoalveolar lavage fluid samples collected from ICI pneumonitis (n=11) and control (n=6) patients. To comply with GDPR regulations, please note that individual sample identifiers used for this data deposit (alphabetical ID) are different from and cannot be traced back to the patient identifiers used throughout the manuscript (numerical ID).

Dataset EGAD00001009723

Whole exome sequencing of an alveolar rhabdomyosarcoma patient with RET germline mutation

Whole exome sequencing of an alveolar rhabdomyosarcoma patient with RET germline mutation and subsequent analysis of potential therapeutic mechanisms associated with the patient's rare germline mutation. Patient sampels were sequenced from an initial biopsy and from a relapse biopsy, in addition to normal blood as the matched normal DNA. RNA sequencing was performed on the relapse sample as initial sample was unable to produce usable RNA for analysis.

Dataset EGAD00001006125

RNA sequencing in blood samples of cluster headache patients

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20).

Dataset EGAD00001002726

Sequencing data on patients with Sezary Syndrome

This dataset consists of sequencing data on 15 patients with Sezary syndrome. On 12 of these patients, we have exome sequencing data while on 10 patients, we have RNA sequencing data. In total for seven patients, we have both exome as well as RNA sequencing data. We looked for gene mutations and fusion events in these patients to identify genes that could be involved in the pathogenesis of the disease.

Dataset EGAD00001001998

Fusion gene analysis using multiplex single primer extension-based RNA-sequencing

The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains fusion gene analysis using multiplex single primer extension-based RNA-sequencing for a subset of 25 patients of the screening cohort. Data was generated on Illumina NexSeq 550 device in paired-end mode and is stored in compressed FASTQ file format.

Dataset EGAD00001011326

Clinical sequencing in multiple myeloma

DNA (n=1281) and RNA (n=767) were extracted from bone marrow aspirates where CD138+ selection had been performed to enrich plasma cells from patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or multiple myeloma (MM). DNA and/or RNA were sent to Foundation Medicine where targeted sequencing was performed using their Foundation 1 Heme panel. Resulting BAM files were returned along with annotations for somatic events including single nucleotide mutations, indels and structural rearrangements.

Dataset EGAD00001004113

RNAseq in pleural mesothelioma primary cell lines

Pleural mesothelioma (PM) requires new treatments. Drug repurposing offers a potential approach to finding effective therapies. This study aimed to explore new therapeutic options for PM using RNA sequencing. RNA sequencing was performed on 58 patient-derived PM cell lines. Drug screening of over 1300 compounds was conducted on 11 lines, with further testing of selected drugs on 48 lines. Top candidates were validated in 3D culture and mouse models.

Dataset EGAD00001015408

Single-nucleus transcriptome sequencing of the ALS-FTD motor cortex after sorting by TDP-43

Single-nucleus RNA-sequencing of NeuN+ nuclei of the post-mortem human primary motor cortex from patients with ALS-FTD confirmed for TDP-43 pathology, after sorting for TDP-43 signal, TDP-43 Low vs. TDP-43 High

Study EGAS50000001566

Identification of High-Risk PHF19 Expressing Cells in Myeloma Single-Cell Multiomics

The aim of this study is to identify novel subsets of cells that are associated with progression and response to treatment. In this project, we study the tumor fraction from 49 myeloma patients across stages of progression. Samples were collected from 10 smoldering multiple myeloma (SMM), 22 newly diagnosed multiple myeloma (NDMM), and 17 relapsed refractory multiple myeloma (RRMM) patients. These samples were then sorted using magnetic-activated cell sorting (MACS) for CD138+ cells that represent the tumor fraction of each sample. The CD138+ fraction then underwent whole genome sequencing (WGS), where possible, and single-cell multiomics. Single-cell multiomics can now measure scRNA-seq and scATAC-seq simultaneously, which we use in this project. Using single-cell multiomics, we will study subclonal changes in gene expression, chromatin accessibility, and identify novel regulatory relationships within myeloma tumors. Furthermore, we will apply state of the art single-cell and single-cell multiomic techniques to better identify the more high-risk components of myeloma.

Study phs003220

Cell-type eQTLs for single-cell Mendelian Randomisation

The following study mapped eQTLs in the post-mortem human brain from snRNA-seq generated on 391 individuals. Following eQTL discovery and identification of state-specific eQTLs (dynamic associations interacting with disease), colocalisation and MR was performed integrating GWAS from 42 traits, for the identification of putatively causal genes with cell-type specific context. This study contains raw sequencing data and genotype for two datasets used in this work; - The MRC 60 dataset, which contains snRNA-seq generated on post-mortem brain from 60 control individuals (104 samples total, split across prefrontal cortex and hippocampus). Samples were pooled into 27 distinct pools, each of which was split across 4 lanes. Following sequencing and mapping using cellranger, demultiplexing was done using Demuxlet using the pool-specific genotype data (which contain sample IDs). - The Roche PD dataset, which is 10X multiome data generated on on 70 PD and 22 control individuals.

Study EGAS50000000687

Functional Variant rs9344 at 11q13.3 Regulates CCND1 Expression in Multiple Myeloma with t(11;14)

Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). We have found the G risk allele is enriched in both healthy individuals of African ancestry and African American individuals with MM. The overall aim of this study was to identify the mechanism behind why the G allele is enriched in t(11;14) MM. To reach this goal, we performed ATAC-seq from 100,000 CD138+ tumor cells from 26 patients with MM. In addition, we performed ChIP-seq using antibodies against H3K4me1, H3K27ac and H3K4me3 from 100,000 CD138+ tumor cells from 8 patients with MM. We used these data to evaluate whether the G allele of rs9344 is associated with elevated chromatin accessibility, H3K27ac and H3K4me3 in t(11;14) MM.

Study phs003997

Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

Study EGAS00001007930

300BCG study: human population variation of trained immunity

To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live attenuated vaccine induces not only an adaptive immune response against tuberculosis, but also triggers innate immune activation and memory. We established personal chromatin accessibility maps over a time course of BCG vaccination in the 300BCG cohort using ATAC-seq.

Study EGAS50000000090

Raw scRNA-seq data from B-lineage cells in the blood of celiac disease patients

Raw scRNA-seq data from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The data was generated with the Smart-seq2 protocol and sequenced on a NextSeq500 instrument (Illumina) with 75 bp paired-end reads in high-output mode. The dataset contains R1 and R2 reads for each single cell (fastq.gz files) for cells passing quality control based on number of detected genes, reads, mitochondrial genes, reads mapping to the reference transcriptome and a productively rearranged immunoglobulin heavy chain IgA isotype reconstructed by the computational tool BraCeR. Metadata for the cells is provided in a csv file.

Dataset EGAD50000000340

Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

We generated the first single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

Study EGAS50000000735

Histone acetylome-wide association study on tuberculosis infection

Epigenetic mechanisms are thought to play an important role in the pathogenesis of infectious diseases. Here, we describe the first histone acetylome-wide association study (HAWAS) of an infectious disease, based on genome-wide H3K27 acetylation profiling of peripheral granulocytes and monocytes from subjects with active Mycobacterium tuberculosis (Mtb) infection and healthy controls (135 ChIP-seq datasets).

Study EGAS00001003118

Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell transcriptome sequencing and a novel bioinformatics pipeline

We report a deconvolution and identification strategy of scRNA-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and aquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures.

Study EGAS00001006202

Identification of Long Non-coding RNA Biomarker of Human Lupus Nephritis Disease Activity - Data Access Committee

Dac EGAC00001003281

99 HER2+ RNA Arrays

samples using Affymetrix HG_U133_+2

Dataset EGAD00010000886

Short-read scRNA-seq

10x Chromium Single Cell 3′ single-cell cDNA sequencing data for adrenal tissue sampleA and sampleB.

Dataset EGAD50000002210

input

Input dataset of human islets. To be used in conjuction with Cohesin and Mediator ChIP-Seq datasets.

Dataset EGAD00001005209

Natural genetic variation of the cardiac transcriptome in non-diseased donors and patients with dilated cardiomyopathy

Background: Genetic variation is an important determinant of RNA transcription and splicing, which in turn contributes to variation in human traits including cardiovascular diseases.Results: Here we report the first in-depth survey of heart transcriptome variation using RNA-sequencing in 149 (97)* patients with dilated cardiomyopathy and 113 (108)* non-diseased controls. We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls, affecting known as well as novel dilated cardiomyopathy genes. Moreover, we show a widespread effect of genetic variation on the regulation of transcription, isoform usage and allele specific expression. Systematic annotation of genome wide association SNPs identifies 60 functional candidate genes for heart phenotypes, representing 20% of all published heart genome wide association loci. Focusing on the dilated cardiomyopathy phenotype we found that eQTL variants are also enriched for dilated cardiomyopathy genome wide association signals in two independent cohorts.Conclusions: RNA transcription, splicing and allele specific expression are each important determinants of the DCM phenotype and are controlled by genetic factors. Our results represent a powerful resource for the field of cardiovascular genetics. (*) numbers in parentheses represent samples that the publication is based on.

Study EGAS00001002454