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• About

  About What's the EGA? The European Genome-phenome Archive (EGA) is a global network for permanent archiving and sharing of personally identifiable genetic, phenotypic, and clinical data generated for the purposes of biomedical research projects or in the context of research-focused healthcare systems. Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, we aim to advance biomedical research and promote personalised medicine worldwide by enabling discovery of and access to human genomic and health research data. The EGA contains data collected from individuals whose consent agreements authorise data release for specific research use to bona fide researchers. We ensure strict security measures to control access to the data and maintain patient confidentiality. With expertise in data management and technical infrastructure, we promote FAIR data reuse and enable researchers to share their data securely. By leveraging public funding and our strategic partnerships, the EGA provides a free service for permanent data storage, data discovery, and secure data access. In addition, we foster a federated network to provide transnational access to human research data in compliance with legal frameworks. For additional information about the EGA, please contact: Helen Parkinson and Mallory Freeberg EMBL European Bioinformatics Institute Arcadi Navarro, Roderic Guigó, and Jordi Rambla Center for Genomic Regulation History The European Genome-phenome Archive was launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. With the signing of a memorandum of understanding in 2013 and a formal agreement in 2016, the EGA became a joint project of EMBL-EBI and the Centre for Genomic Regulation (CRG). The two institutes work together to support the EGA services, including supporting submissions, website, strategic leadership, and data infrastructure developments. In 2022, the Federated EGA was officially launched with the signature of the first five countries: Finland, Germany, Norway, Spain, and Sweden. With more than 20 additional nodes worldwide preparing to join, the Federated EGA aims to become the largest human omics data sharing initiative towards understanding human health and disease. EGA overview If you're a researcher you may need to deposit, manage, or access genomic data in a secure and regulated way. The European Genome-phenome Archive (EGA) is a platform that facilitates these processes, ensuring that sensitive data is stored and shared in accordance with legal and ethical regulations. Submission process To start a submission, you need to become an EGA submitter. For that, you’ll need to sign a Data Processing Agreement (DPA) with us, that defines the terms and conditions under which your data will be processed and shared within the EGA system. The access to each study is controlled by its Data Access Committee (DAC). The DAC is responsible for managing data access requests and ensuring that the release of data is in accordance with the General Data Protection Regulation (GDPR). Please, note that once your data is released, all public metadata related to your study and dataset(s) will be searchable on the EGA website. However, the files are only accessible under controlled access, which means that a DAC has to agree to a previous data access request. Request process It is possible to submit an access request to data stored at the EGA. The DAC assigned to the study will assess the request and, if approved, grant access to the data. Requesters must provide sufficient justification for your request and comply with the intended data usage in order to get access to it. Each dataset is covered by a Data Access Agreement (DAA) that defines the terms and conditions of use for the specified dataset/s. The DAA is created and provided by the DAC, and must be signed by the individual requesting access to the given dataset/s. Download process Once the request for access is approved, the data and metadata can be downloaded. The EGA offers various download options to fit the needs: it is possible to preview files without downloading them, download specific files of interest, or even download terabytes of data. Overall, the EGA provides a secure and regulated environment for depositing, managing, and accessing human data. Regardless of the role - submitter, DAC member, or requester - the EGA provides assistance for each while ensuring that sensitive data is managed in an ethical and responsible manner. More information on how EGA handles data is available in the EGA dataflow.

  Documentation about/ega

• Compound heterozygous variants in LAMC3 in association with posterior periventricular nodular heterotopia

  Periventricular nodular heterotopia is a malformation of cortical development characterized by nodules of abnormally migrated neurons.

  Study EGAS00001004793

• Tanzania dietary intervention study 2019-2020

  We performed a dietary intervention study comparing western diet, traditional diet and the supplementation of fermented banana beverage in a cohort of 66 individuals (22 in each study arm).

  Dataset EGAD50000000457

• Long-read sequence data from two carriers of a predisposing structural variant

  This dataset contains PacBio long-read sequence data from two individuals with a chr9p.21 structural variant and two controls. Sequences were aligned againt the human reference genome HG38.

  Dataset EGAD50000002155

• Whole-genome sequencing (WGS) to characterise five metastatic tumours from a BRAF mutant melanoma patient who presented intrinsic resistance.

  We used WGS (Complete Genomics) to characterise five metastatic tumours from a BRAF mutant melanoma patient who presented intrinsic resistance.

  Dataset EGAD00001003120

• A molecular signature for IL-10-producing Th1 cells in protozoan parasitic diseases

  A molecular signature for IL-10-producing Th1 cells in protozoan parasitic diseases

  Dataset EGAD00001007532

• Kidney_tumour_DNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002486

• Comprehensive Omics Analysis of Pediatric Solid Tumors and Establishment of a Repository for Related Biologic Studies (10C0086)

  This study (10-C-0086) collected and analyzed tumor and circulating tumor omics of pediatric and young adult patients with relapsed rhabdomyosarcoma who were co-enrolled in and receiving treatment on the interventional study 17-C-0049. We sought to describe the summary genomic findings of tumors, and report on the detection of circulating tumor DNA (ctDNA) in serial samples. Tumor tissue and blood were collected and analyzed. Tumor samples were subjected to whole exome and/or whole genome sequencing paired with RNA-Seq. Cell free DNA (cfDNA) was extracted from serially collected blood samples and sequenced. Fusion status, mutations, and IGF1R and YES1 expression from tumor samples revealed the presence of a PAX3 fusion in most samples, a number of common mutations, and universal but heterogeneous expression of IGF-1R and YES1. ctDNA was detected above the 3% threshold in a majority of patients and analysis of cfDNA demonstrated an ability to monitor tumor clonal evolution.

  Study phs003243

• Blepharospasm in a Multiplex African-American Pedigree

  Blepharospasm (BSP) is a late-onset focal dystonia characterized by involuntary contractions of the orbicularis oculi muscles. Genetics plays an important role on the pathogenesis of BSP, especially in hereditary BSP families. In this project, a large African-American pedigree with BSP was phenotypically characterized and its relationship with known common dystonia genes was investigated with Sanger sequencing on dystonia genes such as THAP1, TOR1A and GNAL. And whole-exome sequencing (EXOME) of the proband was performed to identify all other dystonia-associated genes for potentially pathogenic SVs. A novel THAP1 SV (c.314T>C, p.L105S) was identified in the family, however, this SV did not co-segregate with blepharospasm in the pedigree. No pathogenic or likely pathogenic SVs in other dystonia-associated genes were identified with whole-exome sequencing. The current study makes available phenotype data and summary genotype data of n=12 family members (mutation absent/heterozygous for THAP1); whole exome sequencing data of one (het) subject are available through public SRA.

  Study phs001206

• A Whole Genome Association Scan for Myopia and Glaucoma Endophenotypes using Twin Studies

  Myopia and glaucoma are highly prevalent ophthalmic disorders worldwide and contribute significantly to ocular morbidity. There is substantial evidence that genetic factors play a significant role in the development of non-syndromic myopia and glaucoma. We propose to perform mapping studies for well-characterized twin populations in the United Kingdom and Australia in order to ultimately identify implicated genes for these disorders and related ocular parameters. This will provide a fundamental molecular understanding of how these disorders develop, and may lead to directed physiologic (i.e. pharmacologic, gene therapy) interventions. Our aim is to dissect the genetic basis of the eye disorders myopia and glaucoma. Instead of limited analyses of the trait/disease in a dichotomous manner, we are using continuous phenotypes of measures of refraction and intermediate phenotypes of glaucoma to analyze quantitative traits in unselected population samples of volunteer twins. Achievement of this goal requires cooperative efforts and large sample sizes. Thus, we have created an international collaboration of large complementary studies.

  Study phs000142

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model

  DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth DNAm analysis due to the broad coverage and preservation of rare cell-type signals, compared to array-based data such as 450K/EPIC array. Here, we propose MethylBERT, a novel Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and genomic sequence and the method estimates tumour cell fractions within bulk samples. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both tumour and non-cancerous bulk methylomes.

  Study EGAS50000000806

• A small cell lung cancer genome reports complex tobacco exposure signatures

  Cancer is driven by mutation. Worldwide, tobacco smoking is the major lifestyle exposure that causes cancer, exerting carcinogenicity through 60 chemicals that bind and mutate DNA. Using massively parallel sequencing technology, we sequenced a small cell lung cancer cell line, NCI-H209, to explore the mutational burden associated with tobacco smoking. 22,910 somatic substitutions were identified, including 132 in coding exons. Multiple mutation signatures testify to the cocktail of carcinogens in tobacco smoke and their proclivities for particular bases and surrounding sequence context. Effects of transcription-coupled repair and a second, more general expression-linked repair pathway were evident. We identified a tandem duplication that duplicates exons 3-8 of CHD7 in-frame, and another two lines carrying PVT1-CHD7 fusion genes, suggesting that CHD7 may be recurrently rearranged in this disease. These findings illustrate the potential for next-generation sequencing to provide unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with cancer.

  Study EGAS00000000051

• Full genome sequencing of a monozygotic twin discordant for schizophrenia

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000152

• ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium.

  The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGFβ on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.

  Study EGAS00000000082

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

  A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames. To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a step-wise approach to employ multiple CRISPR-Cas9 screens to elucidate functional non-canonical ORFs implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream open reading frames (uORFs) exhibited selective functionality independent of the main coding sequence. One of these, ASNSD1-uORF or ASDURF, was upregulated, associated with the MYC family oncogenes, and was required for medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future cancer genomics studies seeking to define new cancer targets.

  Study EGAS00001007426

• Transcriptome changes in circulating immune cells of critical COVID-19 patients predict a specific metabolic and epigenetic imprint

  The progression to severe COVID-19 arises predominantly from a dysregulated host immune response, although the underlying regulatory mechanisms still remain partially elusive. This limits a prompt prediction of disease progression and restrains our understanding of “long COVID”. Here, we analyzed the transcriptomes of peripheral blood mononuclear cells collected from COVID-19 patients experiencing different degrees of the disease and control patients. In critical COVID-19 patients, we found an altered regulatory network involving microRNAs, long non-coding RNAs, and coding genes that control mRNA translation-related genes, epigenetics, and metabolism. We also observed an upregulation of tRNA aminoacylation genes and increased expression of coding genes enriched for the cognate amino acids. Collectively, our findings indicate a broad perturbation of the gene expression landscape that characterizes the aberrant host immune response in critical COVID-19 patients and is potentially coordinated by alterations in microRNA expression and tRNA metabolism.

  Study EGAS50000000965

• A Genomic History of Aboriginal Australia

  The population history of Aboriginal Australians remains largely uncharacterised. We generated high-coverage genomes for 83 Aboriginal Australians (speakers of Pama-Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal Australian ancestors diversified 25-40 thousand years ago (kya), suggesting early population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all studied Aboriginal Australians descend from a single founding population that differentiated ~10-32 kya. We infer a population expansion in northeast Australia during the Holocene (past c.10 kya) associated with limited gene flow from this region to the rest of Australia consistent with the spread of the Pama-Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51-72 kya, following a single out of Africa dispersal, and subsequently admixed with different archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.

  Study EGAS00001001766

• We describe a method to culture organoids from adult human kidney tissue and describe applications for the culture system.

  Adult Stem Cell (ASC)-derived organoids are 3D epithelial structures that recapitulate essential aspects of their organ of origin. We have developed conditions for the long-term growth of primary kidney epithelial organoids. Cultures can be established from mouse and human kidney tissue, as well as from urine and can be expanded for at least 20 passages (> 6 months). Chromosome numbers remain normal. Human organoids represent proximal as well as distal nephron segments, as evidenced by gene expression, immunofluorescence and tubular functional analyses. BK virus infection of organoids recapitulates in vivo phenomena. Organoids can be established from Wilms nephroblastoma. Kidney organoids from Cystic Fibrosis (CF) patient’s urine allowed ex vivo assessment of treatment efficacy. Finally, organoids cultured on microfluidic organ-on-a-chip plates adopt a tubular conformation and display active transport function. Adult kidney-derived organoids allow studies of hereditary, infectious and malignant kidney disease in a personalized fashion.

  Study EGAS00001002729

• Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer

  Genomic alterations in metastatic prostate cancer remain incompletely characterized. Here we analyze 493 prostate cancer cases from the TCGA database and perform whole-genome plasma sequencing on 95 plasma samples derived from 43 patients with metastatic prostate cancer. From these samples, we identify established driver aberrations in a cancer-related gene in nearly all cases (97.7%), including driver gene fusions (TMPRSS2:ERG), driver focal deletions (PTEN, RYBP, SHQ1), and driver amplifications (AR, MYC). In serial plasma analyses, we observe changes in focal amplifications in 40% of cases. The mean time interval between new amplifications was 26.4 weeks (range: 5-52 weeks), suggesting that they represent rapid adaptations to selection pressure. An increase in neuron-specific enolase is accompanied by clonal pattern changes in the tumor genome, most consistent with subclonal diversification of the tumor. Our findings suggest a high plasticity of prostate cancer genomes with newly occurring focal amplifications as a driving force in progression

  Study EGAS00001001018

• A comprehensive assessment of somatic mutation detection in cancer using whole genome sequencing

  As whole genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Using tumor-normal sample pairs from two different types of cancer, chronic lymphocytic leukemia and medulloblastoma, we conducted a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines, and even validation methods. Here we show that using PCR-free methods and increasing sequencing depth to ~100x showed benefits, as long as the tumor:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artifact-prone nature of the raw data and lack of standards for dealing with the artifacts. However, armed with the benchmark mutation set we have created, we show that many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

  Study EGAS00001001539

• A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection

  Cell-free RNA (cfRNA) is a promising analyte for cancer detection. However, a comprehensive assessment of cfRNA in individuals with and without cancer has not been conducted. We performed the first transcriptome-wide characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Of 57,820 annotated genes, 39,564 (68%) were not detected in cfRNA from non-cancer individuals. Within these low-noise regions, we identified tissue- and cancer-specific genes, defined as "dark channel biomarker" (DCB) genes, that were recurrently detected in individuals with cancer. DCB levels in plasma were correlated with tumor shedding rate and RNA expression in matched tissue, suggesting that DCBs with high expression in tumor tissue could enhance cancer detection in patients with low levels of circulating tumor DNA. Overall, cfRNA provides a unique opportunity to detect cancer, predict the tumor tissue of origin, and determine the cancer subtype.

  Study EGAS00001004704

• A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories.

  Background: Atypical teratoid rhabdoid tumors (ATRTs), characterized by the loss of SMARCB1, are among the most lethal pediatric central nervous system (CNS) tumors. Three molecular subtypes have been identified, each defined by distinct molecular and clinical features. No subtype-specific treatments are available, highlighting the necessity to better understand inter- and intra-subtype heterogeneity. Methods: We generated a single-nucleus transcriptome atlas of ATRTs, validated by single-cell ATAC-seq and spatial transcriptomics, to study subtype-specific differentiation trajectories. Results: We identified brain progenitor-like expression profiles within unique subtype-specific differentiation lineages. A shared cycling, progenitor-like cell population, interspersed throughout tumors, was observed across all ATRT samples. Moreover, we demonstrate that subtype-specific differentiation trajectories can be induced pharmacologically in ATRT tumoroids directing tumor cells towards a non-proliferative, mature phenotype. Conclusions: Our study reveals that ATRT subtypes exhibit signaling trajectories mirroring normal fetal brain development, enabling the development of maturation therapies tailored towards ATRTs.

  Study EGAS00001008108

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015620

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457