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• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Profiles of Extracellular RNA in Cerebrospinal Fluid and Plasma from Subarachnoid Hemorrhage Patients

  Brain injury resulting from hemorrhagic stroke is clinically challenging to manage and results in high rates of morbidity and mortality. The pathophysiology of brain damage resulting from aneurysmal subarachnoid hemorrhage (aSAH) is largely unknown, and methods to treat and monitor patients are variable with no meaningful correlations to patient outcome. Prediction of patient risk for serious neurological complications is currently a significant clinical obstacle. An extracellular RNA (exRNA) biomarker to predict onset and severity of brain damage would improve patient outcomes. We sequenced plasma and CSF samples from adult patients with SAH. Samples were collected from post bleed day 1 to day 7. Total exRNA was isolated from each sample. In addition, we prepared a subset of 140 CSF samples, isolating the RNA contained within extracellular vesicles and vesicle-depleted biofluid.

  Study phs001759

• DAC of the STIC project

  Ovarian high-grade serous carcinoma (HGSC) originates in the fallopian tube, with secretory cells carrying a TP53 mutation, known as ‘p53 signatures’, identified as potential precursors. p53 signatures evolve into serous tubal intraepithelial carcinomas (STIC) lesions, which, in turn, progress into invasive HGSC that readily spread to the ovary and disseminate around the peritoneal cavity. We recently investigated the genomic landscape of early- and late-stage HGSC and found higher ploidy in late-stage (median 3.1) than early-stage (median 2.0) samples. Here, to explore whether the high ploidy and possible whole genome duplication observed in late-stage disease are determined early in the evolution of HGSC, we analysed archival formalin-fixed paraffin-embedded samples (FFPE) from five HGSC patients. p53 signatures and STIC lesions were laser-capture microdissected and sequenced using shallow whole genome sequencing (sWGS), while invasive ovarian/fallopian tube and metastatic carcinoma samples underwent macrodissection and were profiled using both sWGS and targeted next generation sequencing. Results showed highly similar patterns of global copy number change between STIC lesions and invasive carcinoma samples within each patient. Ploidy changes were evident in STIC lesions, but not p53 signatures, and there was strong correlation between ploidy in STIC lesions and invasive ovarian/fallopian tube and metastatic samples in each patient. The reconstruction of sample phylogeny for each patient from relative copy number indicated that high ploidy, when present, occurred early in the evolution of HGSC, which was further validated by copy number signatures in ovarian and metastatic tumours. These findings suggest that aberrant ploidy, suggestive of whole genome duplication, arises early in HGSC, and is detected in STIC lesions, implying that the trajectory of HGSC may be determined at the earliest stages of tumour development.

  Dac EGAC50000000227

• CNS Embryonal tumors

  The dataset represents a total of 58 DNA samples from 16 male and 12 female pediatric patients affected with embryonal central nervous system tumors. The samples were subject to whole genome sequencing, WGS, [48 samples, (representing 12 male and 11 female individuals)] and whole exome sequencing, WES, [10 samples, (representing 4 male and 1 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 26 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from two patients. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 58 files in the CRAM format (lossless compression) with a total file size of ~8,8 TB. All CRAM files but one, are derived from one sequence run and one sample. P4551_227N_P4552_112N is a CRAM file where 2 sequence runs (P4551_227N and P4552_112N) from peripheral blood samples from the same individual, P019, were aligned into one single CRAM file. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000298

• Establishment of xenogfafts and cultured cell lines from clinical samples

  The purpose of the present study was to clarify the presence or absence of alterations in the molecular properties of patient-derived xenografts (PDXs) with up to eight passages in endometrial carcinomas. Alterations in the proportion of immunohistochemically positive/negative cells for PAX8, estrogen receptor, PAX2, and PTEN were observed in established PDXs of endometrioid carcinomas and carcinosarcomas, whereas proportions of cells with AE1/AE3, TP53, ARID1A PMS2, and MSH6 were maintained. Variants of cancer-associated genes in PDX compared to those in the parental tumors were examined in two cases, a frameshift deletion in BRCA1 was observed in the parental tumor tissue, and additional genomic alterations were found in the PDXs of this case. Genomic and phenotypic alterations in endometrial carcinoma PDXs relative to the parental tumors were observed and were partly associated with endometrial cancer-specific characteristics in cellular differentiation and gene mutations.

  Study JGAS000585

• Raw human sequencing data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  This dataset contains raw FASTQ files generated from peripheral blood and intestinal biopsy samples collected for the study “Characterization of intestinal immune responses in generalized human and murine lipodystrophy.” Peripheral blood sequencing was performed on samples from three healthy donors as controls and from a patient with acquired generalized lipodystrophy and Crohn’s disease (AGLCD) at two distinct timepoints. Intestinal biopsy–derived immune cells were sequenced from three individuals with Crohn’s disease as disease controls, as well as from the AGLCD patient (single timepoint). The data include paired-end FASTQ files derived from single-cell RNA sequencing and T-cell receptor repertoire profiling, enabling analyses of immune composition, transcriptional states, and clonal T-cell expansion. All data are controlled-access human genomic datasets and require appropriate authorization for secondary use.

  Study EGAS50000001517

• Molecular and Clonal Evolution in Recurrent Metastatic Gliosarcoma

  We present a rare case of a 37-year-old woman who was initially diagnosed with IDH wild-type gliosarcoma in the frontal lobe and later developed two local recurrences and extracranial metastases to the vertebral and pelvic bones. In order to understand the clonal relationships between the four tumor instances and the origin of metastasis, we performed whole genome sequencing of the intracranial tumors and the tumor located in the right iliac bone. Mutational and copy number profile comparisons of the metastatic to intracranial tumors highlighted a high similarity in molecular profile, but contrasting evidence regarding the origin of the metastasis. Subclonal reconstruction suggested a parallel evolution of the recurrent tumors, and that the metastatic tumor was largely derived from the first recurrence. We conclude that metastasis in glioma can be a late event in tumorigenesis.

  Study EGAS00001004076

• Quantitative microbiome profiling disentangles inflammation- and bile duct obstruction-associated microbiota alterations across IBD/PSC diagnoses

  Disease-association microbiome dataset comprising 106 primary sclerosing cholangitis and/or inflammatory bowel disease (PSC/IBD) patients. Assessing quantitative taxon abundances, we study microbiome alterations beyond symptomatic stool moisture variation. We observe a high prevalence of a low cell count Bacteroides2 enterotype across patient groups when compared to healthy controls, with microbial loads correlating inversely with intestinal and systemic inflammation markers. Quantitative analyses allow us to differentiate between taxa associated to either intestinal inflammation severity (Fusobacterium) or cholangitis/biliary obstruction (Enterococcus) among previously suggested PSC marker genera. We identify and validate a near-exclusion pattern between the inflammation-associated Fusobacterium and Veillonella genera, with Fusobacterium detection being restricted to Crohn’s disease (CD) and PSC-CD patients. Overall, through absolute quantification and confounder control, we single out clear-cut microbiome markers associated to pathophysiological manifestations and disease diagnosis.

  Study EGAS00001003600

• Heterogeneous Genomic Evolution and Immune Microenvironments in Metastatic Lung Cancer

  The mechanism underlying the occurrence of lung cancer metastasis to different tissues/organs remains elusive. We investigated the genomic evolution and immune microenvironments of paired primary-metastatic tumors by employing multi-region whole-exome sequencing in 179 samples of 106 tumors from 51 lung cancer patients and subsequent immunohistochemistry assays in 70 of them. Our data revealed differences in genomic landscapes, molecular determinants, evolutionary dynamics, and lymphocyte infiltration among different metastatic sites. We demonstrated commonly late arising of metastatic seeding of lung cancer with quantitative evidence. Most distant metastases originated from independent origins of earlier lymph node spreads. Immune-heterogeneity and -homogeneity were primarily driven by arm-level and focal copy number events in primary tumors, respectively. These findings implied the combinatorial role of multiple factors in shaping patterns of dissemination and advanced the clinical evaluation and intervention of lung cancer metastasis.

  Study EGAS00001004228

• BLUEPRINT DNase accessibility of Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

  Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes and epigenomes in four primary cell types: monocytes, in vitro differentiated naïve, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

  Study EGAS00001000954

• BLUEPRINT RNA-seq of Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

  Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes and epigenomes in four primary cell types: monocytes, in vitro differentiated naïve, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

  Study EGAS00001000953

• Integrative sequencing reveals alterations in untreated and castration resistant prostate cancer

  We report the integrative sequencing of genomic, transcriptomic and DNA methylation changes in 28 untreated (PC) and 13 castration resistant prostate cancers (CRPC). AR, TGF-β and WNT signaling pathways were altered in CRPCs. We identified two new fusion genes, TMPRSS2-SKIL and DOT1L-HES6. Fusion analysis in an independent cohort validated SKIL as a recurrent 3’ fusion partner and oncogene in prostate cancer. The HES6 fusion was found in an AR-negative CRPC, and HES6 overexpression in vitro led to androgen independent growth. A distinct DNA methylation signature was found for CRPC. Transcriptome assembly uncovered 128 previously unannotated prostate cancer associated transcripts, including the ERG regulated transcript TPCAT-10-36067 whose knockdown had a dramatic effect on the growth, invasiveness, and rate of apoptosis of prostate cancer cells.

  Study EGAS00001000526

• BLUEPRINT ChIP-seq of Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

  Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes and epigenomes in four primary cell types: monocytes, in vitro differentiated naïve, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

  Study EGAS00001000951

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We analyzed pulmonary monocyte and macrophage responses as well as and pulmonary pathology in two cohorts of patients with COVID-19 associated ARDS. Monocyte-derived macrophages accumulated in the lung during ARDS and acquired a profibrotic signature, characterized by high expression of known fibrogenic factors like TGFB1, SPP1 and LGMN. COVID-19 associated macrophages showed highly significant transcriptional similarity with profibrotic macrophage populations identified in idiopathic pulmonary fibrosis (IPF). Notably, overnight exposure to SARS-CoV-2, but not influenza A virus or viral RNA analogues, induced a similar phenotype in human monocytes from healthy volunteers in vitro. Patients with severe COVID-19 associated ARDS showed clear clinical, radiographic and histopathological features of scarring and fibrotic tissue remodeling. In conclusion, SARS-CoV-2 triggers profibrotic macrophage responses, fibroproliferative ARDS, and lung fibrosis

  Study EGAS00001004928

• ATAC-Seq of healthy and IBD blood samples

  PBMCs from blood samples of 9 age- and gender-matched healthy subjects and 25 IBD patients were isolated through a Ficoll density gradient and used to isolate live CD4 T cells through a magnetic cell isolation kit (Miltenyi Biotec). Twelve thousand live CD4 T cells were then used to prepare ATAC-Seq libraries. Briefly, crude nuclei of live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007343

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• H3K27ac ChIP-seq in primary inflammatory macrophages from 2 minor allele homozygotes and 2 major allele homozygotes at rs2836882

  This dataset consists of H3K27ac ChIP-sequencing in inflammatory (TPP) macrophages from 2 minor allele homozygotes and 2 major allele homozygotes at rs2836882. Monocytes were positively selected from PBMC using CD14 Microbeads and inflammatory macrophage differentiation performed using conditions that model chronic inflammation (TPP): 3 days GM-CSF (50ng/mL) followed by 3 days GM-CSF, TNFa (50ng/mL), PGE2 (1mg/mL), and Pam3CSK4 (1mg/mL). After harvesting, cells were cross-linked, quenched, lysed, and sheared. Immunoprecipitation of histone-DNA complexes was performed overnight at 4C with rotation using an anti-H3K27ac antibody and the SimpleChIP Plus Sonication ChIP kit (Cell Signaling Technology). Following reverse cross-linking, 50ng of immunoprecipitated DNA or input DNA were used to prepare sequencing libraries using the iDeal Library Preparation kit (Diagenode), according to manufacturer instructions. 10 PCR cycles were used for the amplification step and size selection was not performed. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 (Agilent) and the libraries were sequenced in pools of 8, with each pool being sequenced in 2 lanes of an Illumina HiSeq2500 high output flow-cell (50bp, single-end reads). Raw data are provided as raw and aligned single-end sequencing reads from H3K27ac-bound DNA and the input chromatin. Raw reads were trimmed using Trim Galore and aligned to the reference human genome (hg19) using Burrows-Wheeler Aligner (v0.7.12) with default parameters. Aligned reads were converted to BAM files, sorted, and technical duplicates merged before indexing – all using SAMtools (v1.4). PCR duplicates were identified using Picard tools (v2.18.1) and removed together with unmapped reads using SAMtools (v1.4). The resulting BAM files were re-sorted and indexed after filtering.

  Dataset EGAD00001011351

• miRNA expression data from primary tumors, metastasis and matched normals.

  MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs are differentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expression profiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples, including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245 known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue with paired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC with normal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Two hundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR) <0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC with potential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentially expressed between pCRC and the corresponding metastases (FDR <0.1), consisting of five known miRs (miR-320b, miR-320d, miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). These results indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition, miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosis or response to treatment in patients with advanced CRC.

  Dataset EGAD00001001644

• Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Most patients with late stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, thus making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft (PDX) models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the pro-apoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death and displayed synergy in vitro in most models. In vivo, the GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models – those with high BIM at baseline that was increased with MEK inhibition and those with low basal Bim and high pERK levels. Models with low BIM and low pERK were non-responsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

  Dataset EGAD00001005111

• Providing access to COVID-19 data: one year later

  response efforts On 11 March 2020 the World Health Organization declared the novel coronavirus outbreak a global pandemic. Four months later, the European Genome-phenome Archive (EGA) released its first COVID-19 dataset. This dataset – single cell RNA and VDJ sequencing of B cells from 60 COVID-19 patients – showed that neutralizing antibodies could be identified by high-throughput sequencing in response to SARS-CoV-2 infection. That was one year ago. Today, the EGA provides access to fifteen COVID-19 datasets from researchers across seven countries in Asia, Europe, and North America. These studies represent almost 17,000 individuals and have resulted in at least sixteen publications and preprints. Researchers deposit controlled access COVID-19 data at EGA The global research community has come together rapidly to investigate the SARS-CoV-2 coronavirus and better understand the related disease, COVID-19. These research efforts generate valuable genetic and phenotypic data from patients and research participants that can be shared with approved researchers. The EGA enables sharing of this research data by providing a service for archiving and controlled distribution of sensitive data. Over the past year, the EGA has worked with researchers to archive and distribute COVID-19 data from high-throughput sequencing experiments, genotyping studies, and phenotypic information. These datasets investigate the immune system, blood, and cells and tissues of the lung, which are relevant for studying a contagious respiratory illness caused by a viral infection. *Study Spotlight. In January 2021, Ancestry.com demonstrated the utility of deep phenotyping based on self-reported outcomes from a large population of mild and asymptomatic COVID-19 cases. They identified genetic associations with eight COVID-19 phenotypes and showed distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. The supporting data is available at the EGA to approved researchers and includes both genotype and phenotype data for 15,000 individuals. EGA collaborates with global COVID-19 community Since the coronavirus outbreak, the EGA has collaborated with other life science resources to support discovery and access to COVID-19 datasets. COVID-19 Host Genetics Initiative. With the NHGRI’s Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) platform, the EGA enables sharing of individual-level genetic and phenotypic data from the COVID-19 Host Genetics Initiative (HGI). This initiative aims to generate, share, and analyze data from COVID-19 host genetics research projects to better understand the genetic determinants of COVID-19 susceptibility, severity, and outcomes. In response to COVID-19, the EGA actively supports COVID-19 data submissions and integration of data access and flow into the COVID-19-HGI analysis platform. *Study Spotlight. The COVID-19 HGI has combined individual-level data for 13,868 COVID-19 positive patients (N=7,167 hospitalized) from 17 cohorts in nine countries. The data were used to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. The genotype and phenotype data for 10 of these cohorts is available at the EGA to approved researchers under accession EGAS00001005304. Fig 1: EGA COVID-19 studies are searchable in the European COVID-19 Data Portal alongside other COVID-19 and SARS-CoV-2 public datasets. European COVID-19 Data Portal. EGA-archived COVID-19 data are discoverable via the European COVID-19 Data Portal (Fig. 1), which brings together public and controlled access data to accelerate coronavirus research for the international community. By indexing all COVID-19-related data in one place, researchers can more easily discover relevant datasets of interest, thus increasing the “FAIRness” (Findability, Accessibility, Interoperability, Reusability) of this valuable data. Fig 2: SARS-CoV-2 viral sequences are imported from ENA and analysed in Galaxy to detect variants. Results are accessible to researchers through the COVID-19 Viral Beacon. COVID-19 Viral Beacon. The COVID-19 Viral Beacon tool was developed in collaboration with the European Nucleotide Archive and Galaxy to enable near real-time browsing of SARS-CoV-2 variability at genomic, amino acid, and motif levels (Fig. 2). The COVID-19 Viral Beacon allows researchers to (i) perform detailed searches about genomic variants, (ii) filter queries and find unique cases, (iii) filter data based on strain-specific variants, and (iv) explore associated metadata. It uses the Global Alliance for Genomics and Health (GA4GH) Beacon standard including new Beacon v2 features. With this tool, researchers can study intra-host mutations on genomic regions of interest, or trace any variant frequency over time using raw read data. More than 200,000 SARS-CoV-2 analysed genomic data files are now available to researchers for further exploration. Ongoing COVID-19 efforts at EGA Addressing the COVID-19 pandemic is a global effort. Federated resources are necessary to support transnational deposition, access, and analysis of sensitive COVID-19 host genetics and other related data. At the same time, many countries now have emerging personalized medicine programmes which are generating data from national or regional healthcare initiatives. These data are subject to more stringent information governance than research data and often must comply with national data protection legislation. To address this need, the Federated EGA was established to serve as the primary global resource for discovery and access of sensitive human omics and associated data consented for secondary use. The Federated EGA will comprise a network of national human data repositories and will implement community standards and common interfaces. Launching Federated EGA promises to accelerate not only global research efforts to understand, diagnose, and treat COVID-19, but also to foster data reuse, enable reproducibility, and accelerate biomedical and disease research to ultimately improve human health.

  Blog providing-access-to-covid-19

• Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

  We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

  Study phs003865

• Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

  Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

  Blog safe-access-to-sensitive-human-data-federated-ega

• Whole Exome Sequencing of One Nuclear Family with Non-syndromic Sensorineural Hearing Loss

  Our goal is to find genes responsible for non-syndromic sensorineural hearing loss. Blood samples were collected from the JS6 family affected with hearing loss. The family is of Caribbean Hispanic ethnicity. Family JS6 consisted of two deaf siblings, JS6.001 (Male) and JS6.002 (Female) and healthy parents, JS6.100 (mother) and JS6.200 (father). The siblings had no other medical findings. Audiometry tests and Rinne and Weber tuning fork tests identified sensorineural hearing loss in the two siblings. We performed whole exome sequencing of the four individuals and identified a recessive mutation, p.(Arg186Trp), in the CIB2 gene in the two affected siblings. Both parents were unaffected carriers.

  Study phs000969