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• Botensilimab, an Fc-enhanced Anti-CTLA-4 Antibody, is Effective Against Tumors Poorly Responsive to Conventional Immunotherapy

  This study explores the genomic landscape associated with a novel Fc-engineered anti-CTLA-4 antibody (botensilimab) in advanced solid tumors. We seek to understand if enhancing the Fc-region affinity of anti-CTLA-4 antibodies can improve anti-tumor efficacy and expand clinical benefit to tumors poorly responsive to conventional immunotherapy. As part of an ongoing open-label, Phase 1, multicenter study, we conducted an exploratory sub-analysis of genomics data. The primary study evaluates the safety, tolerability, pharmacokinetics, and pharmacodynamics of botensilimab monotherapy and in combination with an anti-PD-1 antibody (balstilimab) in participants with advanced solid tumors. RNA from formalin-fixed paraffin-embedded (FFPE) tumor biopsies and matched normal blood samples were isolated and subjected to RNA-sequencing using the Personalis ImmunoID NeXT Platform. We demonstrated that anti-CTLA-4 engineered for enhanced FcγR affinity leverages FcγR-dependent mechanisms to potentiate T cell responsiveness, reduce intratumoral Tregs, and enhance antigen presenting cell activation. This genomic analysis contributes to our understanding of the molecular mechanisms underlying patient responses to Fc-engineered anti-CTLA-4 therapy and may inform future strategies to expand the clinical benefit of immune checkpoint blockade in cancer immunotherapy.

  Study phs003704

• A Dose Escalation Study of Efmarodocokin Alfa (UTTR1147A) in Healthy Volunteers and Patients with Ulcerative Colitis

  Background: The interleukin-22 cytokine (IL-22) has demonstrated efficacy in nonclinical colitis models with a non-immunosuppressive mechanism-of-action. Efmarodocokin alfa (UTTR1147A) is a fusion protein agonist that links IL-22 to the crystallizable fragment (Fc) of human immunoglobulin (IgG4) for improved pharmacokinetic characteristics, but with a mutation to minimize Fc effector functions. Methods: This randomized, phase 1b study evaluated the safety, tolerability, pharmacokinetics, and pharmacodynamics of repeat intravenous dosing of efmarodocokin alfa in healthy volunteers (HVs; n=32) and patients with ulcerative colitis (UC; n=24) at 30–90 µg/kg doses given biweekly (Q2W) or monthly (Q4W) (6:2 active:placebo per cohort). Results: The most common adverse events (AEs) were on-target dermatological effects (dry skin, erythema, and pruritus) that were reversible. Dose-limiting non-serious dermatological AEs (severe dry skin, erythema, exfoliation, and discomfort) were seen in two HVs and one patient at 90 ug/kg Q2W. Pharmacokinetics were generally dose-proportional across the dose levels tested, but patients demonstrated lower drug exposures relative to HVs at the same dose. IL-22 serum biomarkers and IL-22 responsive genes in colon biopsies were induced with active treatment. Patients demonstrated changes in microbiota composition following active treatment, thereby reversing baseline dysbiosis. Clinical response was observed in 7/18 active- and 1/6 placebo-treated patients; clinical remission was observed in 5/18 active- and 0/6 placebo-treated patients.

  Study EGAS00001006172

• Fgl2 Regulates FcγRIIB+ CD8+ T Cell Responses during Infection

  While the inhibitory receptor FcγRIIB has been shown to be upregulated on activated CD8+ T cells in both mice and humans, its impact on T cell fate during infection has not been fully elucidated. We identified an increase in FcγRIIB-expressing CD8+ T cells in COVID patients relative to healthy controls, and in mouse models of viral infection. Despite its well-known role as an Fc receptor, FcγRIIB also ligates the immunosuppressive cytokine Fgl2, resulting in CD8+ T cell apoptosis. Both chronic LCMV infection in mice and COVID in humans resulted in a significant increase in plasma Fgl2. Further, plasma Fgl2 was directly proportional to CD8+ T cell lymphopenia in COVID patients. To further understand the association of Fgl2 and CD8+ T cell lymphopenia following COVID infection, we assessed the transcriptomic profiles of PBMCs with high (≥ 9.153 ng/ml) vs low (defined as

  Study phs003870

• High titers and low fucosylation of early phase anti-SARS-CoV-2 IgG promote hyper-inflammation by alveolar macrophages

  We show that early phase anti-Spike IgG in serum of critically ill COVID-19 patients induces hyper-inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for severe COVID-19. First, inflammation is driven by high titers of anti-Spike IgG, a hallmark of severe disease. Second, we found that anti-Spike IgG from severely ill patients is intrinsically more pro-inflammatory because of different glycosylation of the Fc tail, particularly by low fucosylation. This dataset is linked with the following ArrayExpress Experiment: E-MTAB-10431 - 2020_COVID19_FCGR_MIL10_IgGfucosylation

  Study EGAS00001005206

• Characterization of a human iPSC-derived endocrine pancreas model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Study EGAS00001001803

• Data Access Committee KCL FC

  Dac EGAC00001000386

• Anti-TIGIT antibody tiragolumab improves PD-L1 blockade via myeloid and Treg cells

  Tiragolumab, an anti-TIGIT antibody with an active IgG1/kappa Fc, demonstrated improved outcomes in the phase 2 CITYSCAPE trial (NCT03563716) when combined with atezolizumab (anti-PD-L1) versus atezolizumab alone1. However, there remains little consensus on the mechanism(s) of response with this combination2. We found that high baseline intratumoral macrophages and Tregs were associated with better outcomes in patients treated with atezolizumab plus tiragolumab but not with atezolizumab alone. Serum sample analysis revealed that macrophage activation was associated with clinical benefit in patients receiving the combination treatment. In mouse tumor models, tiragolumab surrogate antibodies inflamed tumor-associated macrophages, monocytes, and dendritic cells through Fc gamma receptors (FcɣR), in turn driving anti-tumor CD8+ T cells from an exhausted effector-like state to a more memory-like one. These results uncover a mechanism of action by which TIGIT checkpoint inhibitors can remodel immunosuppressive tumor microenvironments, and suggest that FcɣR engagement is an important consideration in anti-TIGIT antibody development.

  Study EGAS50000000251

• Expression profiling of a human endocrine pancreas iPSC model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to the endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Dataset EGAD00001002148

• MCF10A 12h IL6 classical signaling

  Gene expression after cell culture, 12h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001970

• MCF10A 24h IL6 classical signaling

  Gene expression after cell culture, 24h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001963

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• Ribo-depleted RNA-sequencing of II.3, III.1, and III.3

  This datasets contains the Ribo-depleted RNA-sequencing of patients II.3, III.1, and III.3. Libraries were sequenced to a minimum depth of 195 million read pairs (2x75nts) on an Illumina NextSeq500 Midoutput FC.

  Dataset EGAD50000002364

• Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

  Study EGAS50000000566

• Federated EGA

  Federated EGA Federated EGA Index Overview Map of FEGA status across the world Current status of the FEGA Network Documentation Overview Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Our vision is to accelerate scientific discovery and healthcare breakthroughs by creating the go-to worldwide sensitive human data resource. Our values are: Privacy & Trust: Ensuring privacy of data subjects, security of services and acting with integrity to build community trust.FAIRness: Driving reuse of data through standardisation of metadata and clear access policies.Diversity: Expanding our network and representing global diversity in the data we host to bring benefits worldwide. Federated EGA - European by name, global by nature Federated EGA collaborates with European and global initiatives (GA4GH, ELIXIR, 1+ Million Genomes Framework, GDI), demonstrating that a network for transnational discovery of and access to human data is possible. By providing a solution to emerging challenges around secure and efficient management of human omics and associated data, the FEGA Network fosters data reuse, enables reproducibility, and accelerates biomedical research. For general enquiries or to request more information about Federated EGA, please send an email to fega-info [at] lists [dot] ega-archive [dot] org. Read more about the Federated EGA in our commentary in Nature Genetics! Learn more about setting up a Federated EGA Node in our onboarding documentation. Map of FEGA status across the world Current status of the FEGA Network Node Description Joined CEGA Central EGA is managed by the Centre for Genomic Regulation (CRG) and EMBL-EBI. The EGA has been a trusted repository for sensitive data since 2008. CEGA coordinates the FEGA network, hosts central services and the EGA catalogue. 2022 Finland FEGA Finland is hosted by CSC - IT Center for Science Ltd., which is the national ELIXIR Node in Finland. CSC is a state-owned company specialising in providing high-quality IT infrastructure and services for Finnish higher education and research. 2022 Germany The German Human Genome-Phenome archive (GHGA) is part of the German National Research Data Infrastructure (NFDI). It is coordinated by the German Cancer Research Center (DKFZ) and includes over 20 academic partners. 2022 Norway FEGA Norway is a service by ELIXIR Norway, the Norwegian node of the European organisation ELIXIR. University of Oslo as a partner institution in ELIXIR Norway is hosting the service relying on the TSD infrastructure for sensitive data. ELIXIR Norway is a consortium of 5 Norwegian universities and is coordinated by University of Bergen. 2022 Spain FEGA Spain is co-hosted by the Barcelona Supercomputer Center (BSC) and the Centre for Genomic Regulation (CRG), both part of ELIXIR Spain and the Spanish National Infrastructure for Personalised Medicine associated with Science and Technology (IMPaCT). 2022 Sweden FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. 2022 Poland FEGA Poland is hosted by Biobank Lodz, which is part of University of Lodz. Biobank Lodz is an element of the infrastructure of the Regional Digital Medicine Centers established by the Medical Research Agency. 2022 Portugal FEGA Portugal is managed by BioData.pt, the distributed infrastructure for Life and Health data for Portugal. This entity is a non-profit association of 15 life sciences R&I organisations spread across the country, and the home of ELIXIR Node in Portugal. 2023 Canada Canadian Genome-phenome Archive is part of the Pan Canadian Genome Library, with the mandate to allow the secure and responsible sharing and analysis of Canadian genomic information. 2024 Switzerland Swiss FEGA is hosted by SIB Swiss Institute of Bioinformatics, which is the national ELIXIR Node in Switzerland, on behalf of the Swiss FEGA Partnership which includes 4 other key partners (ETH Zurich, Health 2030 Genome Center, Swiss Data Science Center and Switch). 2025 Documentation Title Version Description Mission, vision, values Federated EGA Mission, vision, values 1.0 The official Mission-Vision-Values statement for FEGA, produced and formally approved by the FEGA Strategic Committee in September 2025. Structure and Organisation Federated EGA Structure and Organisation 2.0 The structure of the FEGA network and service expectations, responsibilities and commitments. FEGA is organised into three tiers: Central EGA, FEGA Nodes and FEGA Affiliates. Strategic Committee Federated EGA Strategic Committee 1.1 Terms of reference for the FEGA Strategic Committee describe the purpose and objectives of the committee, which is to provide direction and strategic planning for the FEGA network. The committee receives input from, and provides feedback for the EGA Strategic Committee. Operations Committee Federated EGA Operations Committee 1.1 Terms of reference for the FEGA Operations Committee describe the purpose and objectives of the committee, which is to review operational performance and coordinate technical roadmaps of FEGA Nodes and Central EGA. The committee receives advice from, and provides operational reporting to the FEGA Strategic Committee. Guidelines Node Operations guidelines 2.1 An overview of the operational areas which require resources in order to create a FEGA Node. The document is based on more than 15 years' experience of EMBL-EBI and CRG operating the EGA and initial expericences of the inaugural FEGA Nodes. The operational areas of responsability are in line with the FEGA Maturity Model, which guides establishment and operation of FEGA Nodes. Collaboration Federated EGA Node Collaboration Agreement 1.3 Nodes are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior signing through its official channels.

  Documentation about/projects-and-funders/federated-ega

• Genome-Wide Association Study of Schizophrenia

  The goal of the study is to find susceptibility genes for schizophrenia. Dataset versioning Version 1: European-American (EA) ancestry only Version 2: Version 1 plus African-American (AA) ancestry Consent groups and participant set General research use (GRU): 4591 cases and controls (1217 EA cases, 1442 EA controls, 953 AA cases, 979 AA controls) This consent group includes a subset of schizophrenia cases and all controls (which overlap with Bipolar study controls in Bipolar: GRU dataset). Schizophrenia and related disorders (SARC): 475 cases (187 EA cases, 288 AA cases) This consent group includes a subset of schizophrenia cases.

  Study phs000021

• Whole Genome Association Study of Bipolar Disorder

  The goal of the project is to identify genes that make individuals more susceptible to bipolar disorder (manic depressive illness) and to better understand the brain pathways involved in the disease. Dataset versioning Version 1: European-American (EA) ancestry only Version 2: Version 1 plus African-American (AA) ancestry Version 3: EA and AA samples plus updated diagnostic criteria Consent groups and participant set General research use (GRU): 1767 controls (1081 EA controls, 686 AA controls) This consent group includes all controls for the Bipolar study, which are a subset of controls for the Schizophrenia study (subset of Schizophrenia: GRU). Bipolar and related disorders (BARD): 841 cases (691 EA cases, 150 AA cases) This consent group includes a subset of the Bipolar cases. Bipolar disorder only (BDO): 653 cases (388 EA cases, 265 AA cases) This consent group includes a subset of the Bipolar cases.

  Study phs000017

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): NIH Digital Health Solutions for COVID-19: Clear2Go - A Digital Identity Wallet for Health Status

  Clear2Go is a solution/app that provides digital, non-refutable cryptographic proof of testing or vaccination that can be used to evaluate risk of allowing individuals to return to normal work, travel, and public life activities. It is a mobile service that maps a person's vetted identity and biometrics to the phone and then cryptographically binds it with their COVID-19 test and vaccination records. The person can then prove their status by utilizing the credentials with a QRCode or NFC tap.DOI: https://rapids.ll.mit.edu/10.57895/b2d6-8060

  Study phs002628

• GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

  1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child's behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school's database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

  Study phs000852

• Molecular Genetics of Histiocytic Sarcoma

  This is a comprehensive genomic analysis of a rare set of histiocytic sarcomas from the consult service of the Hematopathology section of the Laboratory of Pathology, NCI, NIH. The study identifies two distinct groupings of these tumors based on the site of disease, their mutational spectrum, and proliferation signature.

  Study phs001748

• Rare_renal_tumours_RNA_

  Rare renal tumours are by hard to classify and there is very little available information regarding prognosis and sensitivity to treatment. Here we endevour to understand their genomic properties in order to better understand their biology.

  Study EGAS00001004323

• Rare_renal_tumours_WGS_

  Rare renal tumours are by hard to classify and there is very little available information regarding prognosis and sensitivity to treatment. Here we endevour to understand their genomic properties in order to better understand their biology.

  Study EGAS00001004322

• Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study (BEAGESS)

  BEAGESS is a genome-wide association study (GWAS) which takes advantage of the extensive data collected by investigators in the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON, http://beacon.tlvnet.net), representing many of the high-quality population-based and other epidemiologic studies of BE and EA in the world. The overall goal of our research is to evaluate the influence of genetic susceptibility on risk of EA and its main precancerous condition, BE. The primary aims of the study are to identify tagSNPs most strongly associated with risk of esophageal adenocarcinoma (EA) and Barrett's esophagus (BE). In the secondary aims we will evaluate the extent to which the most significant associations vary according to key environmental and host factors for these conditions, including gender, obesity and cigarette smoking. These results will guide additional exploratory analyses examining ways in which individual SNP results might be aggregated to shed light in the importance of specific pathways relevant to the etiology of BE and EA, and to identify possible epistatic effects.

  Study phs000869

• Foregut Microbiome in Development of Esophageal Adenocarcinoma

  The distal esophagus is an important anatomical area where gastric acid reflux can cause reflux esophagitis (RE), Barrett's esophagus (BE) (intestinal metaplasia), and esophageal adenocarcinoma (EA). The incidence of EA has increased 6-fold in the U.S. since the 1970s, parallel to a significant increase in the prevalence of gastroesophageal reflux diseases (GERD). Although specific host factors might predispose one to disease risk, such a rapid increase in incidence must be predominantly environmental. The cause remains unknown. Our hypothesis is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in the GERD sequence. We will conduct a case control study to characterize the microbiome in every stage of the GERD sequence as well as analyze the trend in changes in the microbiome along disease progression toward EA. Specific Aim 1. To conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence, by a 16S rRNA gene survey. We will analyze samples of the foregut microbiome at three anatomic loci: mouth, distal esophagus, and gastric corpus. Changes of the microbiota in the distal esophagus will be correlated with the phenotypes. Spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Specific Aim 2. To define distal esophageal metagenome and demonstrate its association with GERD sequence, by shotgun metagenomic analysis. We will first classify samples of the metagenome into metagenotypes by between-sample k-mer distance and correlate the metagenotypes with the four phenotypes. Subsequent detailed analyses will include pathway-disease and gene-disease associations. DNA viruses and fungi, if identified, also will be correlated with the phenotypes. A significant association between the foregut microbiome composition and GERD sequence, if demonstrated, will be the first step for eventually testing the causal hypothesis that an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microbial ecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiome through use of antibiotics, probiotics, or prebiotics. Causative therapy for GERD could prevent its progression and reverse the current trend of increasing incidence of EA.

  Study phs000260

• Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN)

  This study is part of the Molecular Genetics of Schizophrenia (MGS) genome wide association study (GWAS) of 3,972 cases (2,686 EA and 1,286 AA) and 3,629 controls (2,656 EA and 973 AA) (analyzed sample remaining after quality control exclusions), comprised of European ancestry (EA) and African American (AA) samples. We genotyped about half of the EA sample and almost all of the AA sample under the auspices of the Genetic Association Information Network (GAIN) with the Affymetrix 6.0 platform at the Broad Institute. The remainder of the included sample was also genotyped with the Affymetrix 6.0 platform at the Broad Institute, and we refer to this component as the nonGAIN sample. Cases met criteria for schizophrenia (SCZ) or schizoaffective disorder (SA) per the Diagnostic and Statistical Manual of Mental Disorders version IV (DSM-IV) for all three collections (SGI, MGS1, and MGS2) comprising these cases. However, for the older SGI collection, codes for the secondary diagnoses refer to the older DSM-III-R version. Controls were screened briefly and excluded if they endorsed a history of these illnesses.

  Study phs000167

• Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

  The breast cancer health disparity between women of African ancestry (AA) and European ancestry (EA) remains a major public health challenge in the United States. AA women are afflicted by higher rate of triple-negative breast cancer (TNBC) and bear the highest mortality rate of all populations from the disease. Even within TNBC, some data suggest that AA women have poorer outcomes than EA women. Mounting evidence points to population differences in cancer biology, a fundamental question that remains unsettled. The disparity also manifests in representativeness in tumor sequencing projects, due to the low inclusion of AAs in genomic studies. A recent analysis of The Cancer Genome Atlas (TCGA) data revealed that the number of AA cases sequenced was sufficient only for studying frequently mutated genes (≥10%), and the power was worse for TNBC as a separate disease entity. As a result, the breast tumor mutational landscape elucidated to date is derived mostly from EA cases, and may not necessarily represent AA cancer genomes. Moreover, as discovery potential for new driver genes has come close to a plateau, cancer in AAs derived from distinct genetic and environmental contexts may provide a powerful venue for discovering mutations that are rare in EA cases. This is showcased in recent studies in colon and prostate cancer. Thus, we carried out a collaborative project, B-CAUSE, to characterize the mutational landscape of AA breast cancer genomes by pooling resources from five established studies, including the Women's Circle of Health Study (WCHS), the Black Women's Health Study (BWHS), the Southern Community Cohort Study (SCCS), the Nashville Breast Health Study (NBHS), and the Southern Tri-State Breast Health Study (STSBHS). This effort has created the largest AA-specific breast tumor mutation dataset to date in an efficient manner. The data deposited here are from the whole-exome sequencing (WES) of matched tumor-normal pairs of 462 TNBC in AA women from the B-CAUSE Study.

  Study phs003962

• Analysis of exonic somatic variants in light-chain amyloidosis (ALA) and ALA concomitant with multiple myeloma

  We aim to provide the very first insight into ALA+MM molecular profiles and compare the results with ALA and with MM. Our detailed study of ALA and ALA+MM represents an important step towards improved understanding of their genetic and transcriptomic background, which is a prerequisite for development of optimal treatment strategies in the future.

  Study EGAS00001004214

• DAC Ghent University - Department of Movement and Sports Sciences

  DAC of Ghent University for RNA-seq data of human skeletal muscle biopsies collected at the Department of Movement and Sports Sciences

  Dac EGAC50000000263

• Kids First: Genomic Analysis of Esophageal Atresia and Tracheoesophageal Fistulas and Associated Congenital Anomalies

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Esophageal atresia/tracheoesophageal fistula (EA/TEF) is a rare and complex aerodigestive congenital anomaly with an estimated incidence of 1 in 2500 to 1 in 4000 live births. We propose to elucidate the underlying genomic architecture of EA/TEF by performing whole genome sequencing to characterize new clinical syndromes associated with EA/TEF to provide more accurate clinical prognostic information.

  Study phs002161

• Phenotype information

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the using the SMARTer Stranded Total RNA-Seq Kit v3.

  Dataset EGAD50000000806

• Alcohol Dependence GWAS in European- and African Americans

  This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1889 African-American (AA) subjects and 1020 European-American (EA) subjects. Among the AAs, 1397 meet DSM-IV criteria for alcohol dependence and 491 are controls. Among the EAs, 1010 meet the criteria for alcohol dependence and 9 are controls. (One in each population meets criteria for alcohol abuse and not dependence, and is therefore counted in neither category.) Although alcohol dependence is the major focus, the sample is informative also for cocaine, nicotine, and opioid dependence.

  Study phs000425

• EuCANCan: EUropean-CANadian Cancer network

  The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

  Blog eucancan

• Privacy Notice for Helpdesk service

  Privacy Notice for EGA Helpdesk service This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from users of the service: Name Email address Job title Date and time when the support request was sent We will use your personal data for the following purposes: To provide uninterrupted user access to the service To better understand the needs of the users and guide future improvements of the service To create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organizations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-helpdesk

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• Dedifferentiated Melanoma (2021-02-02)

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006931

• Link to the Finnish FEGA Node's service provider

  We would like to direct you to the service provider for the Finnish FEGA Node, which is CSC – IT Center for Science (https://research.csc.fi/-/fega). It's important to note that this is not a genuine DAC and does not serve as the data controller. To obtain access to data stored in FI-FEGA, it is essential to utilize the local access management system SD Apply. Please be aware that applications submitted through the EGA DAC portal will not be processed. For a seamless experience, we kindly request you to refer to the policy of your selected dataset and submit your access application through SD Apply (https://sd-apply.csc.fi/). Your cooperation is highly appreciated.

  Dac EGAC50000000022

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge

  Tumors are composed of many different cell types, ranging from the normal tissue micro-environment, infiltrating immune cells and tumour cells. This group of tumour cells is itself intrinsically highly heterogeneous, driven by the rapid mutation rate of cancer cells to become a mixture of different sub-populations. These different types of cells, called subclones, have different sets of mutations in their DNA. Because some subclones evolve from others, many subclones share mutations. While it is increasingly easy to determine what mutations are present in the tumor, it remains very difficult to determine which subclones have which mutations. The task of assigning mutations to subclones is called subclonal reconstruction.The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge (SMC-Het) is an international effort to improve standard methods for subclonal reconstruction: to quantify and genotype each individual cell population present within a tumor. The goal of this challenge is to identify the best subclonal reconstruction algorithms and to identify the conditions that affect their performance.

  Study EGAS00001002092

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• Genomic Landscape of Pediatric Myelodysplastic Syndromes

  Pediatric myelodysplastic syndromes (MDS) are a rare disease and unlike their adult counterpart, very little is known about their genomic landscape. We characterized a cohort of patients from a single institution by whole exome sequencing, as well as a subset of patients by whole genome sequencing, RNA-sequencing and targeted deep sequencing. We found a spectrum of mutations, both somatic and germline, that are distinct from those observed in adult MDS. In turn, we observed mutations commonly observed in other pediatric myeloid tumors.

  Study EGAS00001002202

• Molecular Genetics of Secondary Histiocytic/Dendritic Sarcoma

  This is a comprehensive genomic analysis of a rare set of secondary histiocytic/dendritic sarcomas from the consult service of the Hematopathology section of the Laboratory of Pathology, NCI, NIH.

  Study phs001942

• Discovery of Colorectal Cancer Susceptibility Genes in High-Risk Families

  Colorectal cancer remains one of the most common cancers in the US with 146,970 new diagnoses and 49,920 deaths estimated for 2009. Colon cancer is also one of the most familial of cancers. Individuals with a first-degree relative with colon cancer have a 2- to 3-fold increased risk, and those with more than one first-degree relative with colon cancer, or a single first-degree relative affected at age 50 years, have a 3- to 6-fold greater risk than those with no family history. The most prominent high-risk colorectal cancer susceptibility genes, APC, MLH1, MSH2, MSH6, and PTEN, were all discovered more than a decade ago. Currently, mutation screening of these genes, plus a short list of additional genes that are responsible for a very small fraction of colorectal cancer, plays an important role in the clinical management of individuals with a strong family history of the disease or syndromic evidence for the presence of a gene mutation. At the other end of the risk spectrum, genome-wide association studies have identified a number of common alleles with very modest effects on colorectal cancer risk; their clinical utility has yet to be established. However, taken together, the known spectrum of genetic effects only explain about one quarter of the overall familial excess of colorectal cancer. It should be emphasized that, at present, the vast majority of individuals seen at familial cancer clinics are counseled on the basis of their family history alone because they do not have mutations in the known susceptibility genes. Accordingly, the long-term objective of this project is to identify the majority of genes responsible for the unexplained component of inherited colorectal cancer risk. Nextgen DNA sequencing is well suited for application to research questions in genetic susceptibility for which linkage analysis is confounded by extensive genetic heterogeneity. Taking advantage of unparalleled familial cancer genetics resources available through the Utah Population Database, candidate genes have been identified by sequencing all of the gene exons in the human genome from a series of colorectal cancer cases with a very strong family history of colorectal cancer not explained by one of the currently known high-risk susceptibility genes.

  Study phs001787

• Analysis of the Genetic Basis of Height in Large Jewish Nuclear Families

  This is a family based study of the genetic basis of height, which focused on very large nuclear families (10 siblings or more, average of 12), all from a founder (Jewish) population. All participants have completed their growth. This study design increases the frequency of some genetic variants that are rare in a cosmopolitan population but segregate in our cohort. Participants were genotyped with a ~630,000 SNP array (Affymetrix Axiom Biobank), and their standing height, sitting height and arm span were measured with high accuracy (±0.1 cm, with 4 technical repeats). All genomic coordinates refer to genome build hg19.

  Study phs001852

• International Age-Related Macular Degeneration Genomics Consortium - Exome Chip Experiment

  Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. To further our understanding of AMD genetics, we examined the contribution of common and rare genetic variation in the International AMD Genomics Consortium that included ~50,000 samples of 26 AMD case - control cohorts that were jointly genotyped. Analyzing 16,144 patients with late stage AMD and 17,832 controls, we identified 52 independently associated common and rare variants distributed across 34 loci. Besides these single variant signals, we also observed gene-based enrichment of very rare coding variants (frequency < 0.1%) in cases that implicated causal roles for CFH, CFI and TIMP3 in three of the known AMD risk loci. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

  Study phs001039

• Everything you need to know about Federated EGA Affiliates: Q&A

  Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

  Blog fega-affiliates-q&a

• Privacy Notice for Data Access Committee Account

  Privacy Notice for EGA Data Access Committee Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at mfreeberg@ebi.ac.uk , orpost at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: email at dpo@embl.org, orpost at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, orpost at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eupost at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: NameEmail addressTitle/PositionOrganisationOrganisational affiliationBusiness addressTelephone numberIP addressesDate and time of a visit to the service websiteOperating systemAmount of data transmittedBrowserUsernamePassword The data controller will use your personal data for the following purposes: To provide DAC user account and authenticated access to the service,To publicly publish some information to facilitate scientific research,To better understand the needs of the data subjects and guide future improvements of the service,To create anonymous usage statistics (from number of DACs, datasets per DAC). 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data),The general public via Internet will get access to your name, email address, business address, telephone number and organisation you belong to. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Data categories ‘name`, `email address`, `telephone number`, `business address`; `organisation’ of the DAC user are published on the Internet. They thus become accessible to recipients in countries outside the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI), is necessary for important reasons of public interest embedded in the aims of EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-dac

• RNAseq SCLC Cell lines MYC

  RNAseq data set (Mollaoglu et al., MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to Aurora kinase inhibition) RNA isolation from primary tumors and healthy lungs was performed using RNeasy Mini Kit (Qiagen) with the standard protocol. RNA was subjected to library construction with the Illumina TruSeq Stranded mRNA Sample Preparation Kit (cat# RS-122-2101, RS-122-2102) according to manufacturer’s protocol. Chemically denatured sequencing libraries (25 pM) are applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Following transfer of the flowcell to an Illumina HiSeq 2500 instrument (HCSv2.2.38 and RTA v1.18.61), a 50 cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002).

  Dataset EGAD00001003099

• Cell types of the human retina and its organoids at single-cell resolution. Cowan et al

  Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers, and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas.

  Study EGAS00001004561

• Transcriptome analysis of endometrial organoids derived from patients with Mayer-Rokitansky-Küster-Hauser syndrome

  The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. The cause of the disease is still enigmatic. Here, we developed organoid cultures from endometrium found in uterine rudiment horns of MRKH patients. Phenotypically they share great similarity between healthy control organoids and are fully hormone responsive. Transcriptome analysis using RNA-seq identified possible disease-causing pathways altered in MRKH patients during development of the female reproductive tract. Thus, the organoid cultures provide a powerful research model for further insight into disease-causing alterations.

  Study EGAS00001005908

• Implementation of the GDPR

  Data Protection 1 About the EGA The European Genome-phenome Archive (EGA) was formally 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. In late 2012, with the signing of a memorandum of understanding (and subsequent formal agreement in 2016) between EMBL-EBI and the Centre for Genomic Regulation (CRG), the EGA formally became a joint project of the two institutes. The two institutes work together to support the EGA services, including supporting submissions, web site, strategic leadership, and data infrastructure developments. 2 EMBL-EBI & GDPR The EGA is co-managed by EMBL-EBI and CRG. EMBL-EBI is an international organisation established by treaty and has certain privileges and immunities (e.g. exemptions from the application of national law) and also may self-regulate its activities (e.g. establish its own institutional legal framework) within the framework of its founding act of 1973. The General Data Protection Regulation (GDPR) is a European Union (EU) regulation that legislates how organisations can share and process personal data of EU citizens. EMBL places great value in maintaining collaboration with researchers who are subject to GDPR. For that reason, it is of utmost importance for EMBL to handle data received from those collaborators in a secure and responsible manner. Mindful of its public mandate and the sensitivity of the data it handles, EMBL has always ensured a high level of data protection in its activities. Since the introduction of GDPR in May 2018, EMBL has established its internal policy on General Data Protection (IP68), exercising its right to self-regulate its operations,., IP 68 establishes a robust personal data protection framework that provides for data protection principles, enforceable data subject rights and oversight and redress mechanisms offering a level of protection comparable with GDPR. 3 CRG & GDPR The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, created in July 2000 and mainly participated by the Catalan Government. It is a non-profit foundation and its mission is to discover and advance knowledge for the benefit of society, public health and economic prosperity. The CRG is a CERCA center. CERCA is the collective organisation for all research centres of excellence in Catalonia. CERCA ensures these centres develop successfully by promoting synergies and strategic cooperation improving their visibility and the impact of their research and promoting the dialogue amongst both public and private stakeholders. As a legal entity based in Spain and operating within the EU, the CRG ensures the compliance with the GDPR and the legal regulations on personal data protection applicable at the national level, as well as any other legislation that may replace, modify or supplement the above-mentioned in terms of personal data protection. 4 EGA & GDPR EGA GDPR Schema 4.1 Genetic and phenotypic data Within GDPR, there are two main actors: data controllers and data processors. Data controllers are persons or entities which determine the purposes and means that the personal data may be processed, e.g. companies, researchers, or universities. For EGA, the data controller is ultimately the data producer and the submitter(s) who submit the data to EGA. The data controller also creates a Data Access Committee (DAC) who will decide on data access permissions at EGA. Data processors are the persons or entities which process the data on behalf of a data controller. With regard to GDPR, EGA is a data processor as it processes data as instructed by the data controller. GDPR applies to any organisation which accesses personal data from an individual within the EU. Under GDPR, personal data is defined as any data that is identifiable, including names and email addresses as well as health-related and genetic data. EGA does not accept personally identifiable data except genetic and phenotypic data, so all other data submitted to EGA, such as names and addresses, must be pseudonymised. GDPR requires that data controllers implement data protection principles, such as data minimisation, to minimise the risk of data leakage, and protect the rights of the data subjects. As a data processor, EGA has a set of security policies that are followed to minimise the risk of unauthorised data access or data loss. In its role as a data processor, EGA requires all submitters to sign a Data Processing Agreement (DPA) when the submission account is first created. This agreement is only required to be signed once per submitter, and will remain valid for future submissions to EGA. 4.2 Other personal data The EGA also collects personal data as part of our interactions with submitters, data access committees, and researchers accessing data distributed by EGA. The below privacy notices explain what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Privacy Notices for EGA Title Version Last Updated EGA Data Access Committee Account Privacy Notice for EGA Data Access Committee Account 1.0 February 6, 2019 EGA User Account Privacy Notice for EGA User Account 1.0 February 6, 2019 EGA Helpdesk Service Privacy Notice for EGA Helpdesk Service 1.0 February 6, 2019 EGA Website Service Privacy Notice for EGA Website Service 1.0 February 6, 2019 Documentation Title Version Description EGA Security Overview Security Document 1.1 The EGA Security Document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. EGA Data Processing Agreement Data Processing Agreement 1.5 The Data Processing Agreement must be completed and returned as part of the submission process. Please note that this document is non-negotiable. Authorised Submitters Authorised Submitters Formulary 1.0 The Authorised Submitters Form must be completed and returned as part of the submission process. Please list all those that should have access to the submission account in order to submit to the EGA should be detailed here. Dispute Resolution Any controversy or claim arising out of, or relating to, the DPA (including the enforceability or breach thereof, any question regarding its existence, validity or termination) or relating to the EGA Service shall be resolved using the internal dispute resolution mechanisms of EGA including those related to Data Protection. The EGA’s internal dispute resolution mechanism has the following procedure: EGA OPERATIONAL PHASE: Meetings between EGA staff and the Data Controller.LEGAL MANAGEMENT PHASE: Meetings between legal teams of EMBL, CRG and the Data Controller. DIRECTION MANAGEMENT PHASE: Negotiation between the legal representatives of EMBL, the CRG and the Data Controller. If the internal dispute resolution mechanism doesn’t resolve the controversy or claim the next phase is:ARBITRATION PHASE: Resolution by arbitration under the WIPO Expedited Arbitration Rules (“Rules”).

  Documentation about/privacy-notice

• INSIGHT (Intervention Nurses Start Infants Growing on Healthy Trajectories) Cohort

  This is a study of the biological risk factors for children enrolled in the INSIGHT (Intervention Nurses Start Infants Growing on Healthy Trajectories) study. INSIGHT is a randomized, controlled trial testing a responsive parenting intervention designed for the primary prevention of childhood obesity against a safety control. These first-born children were deeply studied in this time period with data collected on a wide variety of variables including mode of delivery, gender, weight and height (collected at 7 time points), medication usage, diet information, and maternal health information (gestational weight gain, gestational diabetes, smoking during pregnancy). This study includes a survey of the oral and gut microbiota from 226 mother-child dyads. It was designed to investigate the relationship between a cross-sectional view of the child's microbiome (at two years of age) and the patterns of growth between birth and 2 years. Microbiome samples from children (buccal swab and stool sample) and their mothers (buccal swab) are collected at the children's 2-year clinical research visit. Stool metabolites have also been assayed for a subset of the 226 children using 1H-NMR. Additionally, we genotyped the same individuals for SNPs across the genome. For a subset of 48 individuals we have added second-born siblings. For these additional 48 children, we characterized the methylation pattern across the genome using cord blood and placenta samples.

  Study phs001498

• The Federated EGA network

  In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

  Blog the-federated-ega-network

• JMML targeted sequencing (2013)

  Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic myeloproliferative neoplasm of early childhood initiated by germline or somatic RAS-activating mutations (Chang, Dvorak et al. 2014). Clinical evolution is heterogeneous, with acute myeloid leukemia (AML) transformation in 1/3 of cases and frequent relapses after hematopoietic-stem-cell transplantation (HSCT), although some patients experience spontaneous remission (Locatelli, Nollke et al. 2005; Matsuda, Shimada et al. 2007; Takagi, Piao et al. 2013; Locatelli and Niemeyer 2015). The initiating lesion incompletely predicts outcome, suggesting the involvement of additional mutations. Genetic profiling of a large JMML cohort (n=118), including whole-exome sequencing (WES) in 30 cases, uncovered additional genetic abnormalities in 56 cases (47%). Somatic events were rare (0.38/case/Mb) and restricted to sporadic (47/78; 60%) or NF1-associated (8/8; 100%) JMML. Multiple concomitant genetic hits were identified targeting the RAS pathway in 13/78 (17%), RAC2D63V, which activates the PI3K/PDK1/AKT and the mTORC2 pathways, and a novel pathway for JMML, the polycomb repressive complex 2 (PRC2), in 26/78 (33%) of the sporadic JMML cases. Interestingly, PRC2 imbalance was recently shown to synergize with RAS activation (De Raedt, Beert et al. 2014). JMML outcome was associated to the mutational profile, suggesting a dose-dependent effect for RAS-pathway activation, distinguishing very aggressive JMML rapidly progressing to AML.

  Study EGAS00001001324

• Rare Disease Susceptibility Alleles in Children with Crohn Disease

  The overall goal of this proposed project is to identify rare genetic variants contributing to childhood onset-Crohn disease. Crohn disease is a chronic inflammatory disorder of the gastrointestinal tract of unclear etiology and no known cure. Affected children suffer from diarrhea, abdominal pain, growth disturbances, and an impaired quality of life. The identified Crohn disease susceptibility alleles have improved our understanding of Crohn disease pathogenesis. However, the identified susceptibility alleles do not account for the observed heritability, nor have disease-causing alleles in many genomic regions been identified. For the proposed studies, we will use 1) existing DNA samples collected from high-risk Crohn kindreds identified using the extensive genealogical records available only in Utah, 2) existing DNA samples obtained from very young children with Crohn disease and their parents, and 3) existing DNA samples obtained from healthy controls that are free of a personal or family history of autoimmune disorders.

  Study phs000926

• Kidney Two-Hit Mapping

  Germ-line genetic variants identified thus far generally account for only part of the genetic risk predicted for most cancers. A component of the remaining risk may be explained by functionally consequent genetic variants that are individually very rare (or private to that individual's family). While their identification may be highly informative for cancer etiology and biological knowledge, strategies that allow for agnostic (genome-wide) identification of such genes are not straight forward. This is particularly true for rare cancers where sufficient numbers of patients may simply not be available for appropriate statistically powered studies. In this project we have explored a study design based around the concept of "two-hit mapping" using the co-occurrence of germ-line and somatic mutations in the same gene to assist in the identification of susceptibility genes. The dataset includes 54 kidney cancer patients selected for enrichment of genetic disease, that is patients with: early age of onset and/or family history and/or bilateral disease. Germ-line and somatic (kidney cancer) tumor sequencing was carried out. These data may improve our understanding of kidney cancer.

  Study phs001971

• Targeted bisulfite sequencing

  Raw reads from targeted bisulfite sequencing. The SureSelect Methyl-Seq target enrichment system (Agilent Technologies, Inc., CA, USA) was used to prepare bisulfite sequencing libraries from blood DNA samples of lymphoma patients (Ly1, Ly2), healthy family members (Ly8, Ly9, Ly10, Ly11, Ly12, Ly13 and Ly14), baseline controls (Control1-5), DNMT3A mutation carriers (Id5, Id7, Id9, Id11) and their age-matched controls (Id6, Id8, Id10, Id12). In addition, blood DNA sample of a patient (HLRCC_N7) with germline fumarate hydratase (FH) mutation is included. Illumina paired-end sequencing for targeted libraries from Ly1, Ly2, Ly8, Ly9, Ly10 and Ly11 was done at Karolinska Institutet using 100 base-pair read length and the HiSeq2000 platform. Illumina paired-end sequencing for targeted libraries from Ly12, Ly13, Ly14, and DNMT3A mutation carriers and their age-matched controls was done as a service at BGI (BGI Tech Solutions Co., Ltd., China) using 126 base-pair read length and the HiSeq2500 platform.

  Dataset EGAD00001004785

• Episodic Ataxia Syndrome: Longitudinal Study

  Individuals with episodic ataxia experience recurrent attacks of dizziness and incoordination; between attacks patients are typically normal. The majority of cases are likely caused by an inherited genetic mutation. However, in some patients we are unable to identify the mutation. So far, 2 genes have been identified which cause different types of episodic ataxia. Ultimately, when the actual mutation is identified the protein product of the gene can be studied and specific medications can be designed. During this study, we will clinically evaluate patients with EA and follow them over time to help us better characterize the disease. We will also obtain blood samples to test for the known genetic mutations. In the future, we plan to coordinate trials of medications for the treatment of these disorders.

  Study phs000521

• A Retrospective and Cross-Sectional Analysis of Patients Treated for SCID Since January 1, 1968

  Individuals with a past diagnosis of severe combined immune deficiency (including many cases of "leaky SCID", Omenn syndrome, and reticular dysgenesis) who have undergone blood and marrow transplant, gene therapy, or enzyme replacement in the past may be eligible for 6902. The purpose of 6902 is very similar to 6901, except 6902 is looking backwards at what has already been done in the past (compared to 6901 which is looking into the future). Over 800 patients with SCID are expected to be enrolled on 6902. This makes 6902 the largest study ever to describe outcomes for patients with SCID treated at many different hospitals around North America. One of the most important components of the 6902 study is the "cross sectional" study. Patients who have received their treatments (BMT, gene therapy, enzyme replacement) many years ago are asked to come back to the hospital where they were treated. During this visit, additional research blood work is drawn and information is gathered regarding long-term transplant outcomes such as infections, graft-versus-host disease, autoimmune diseases, and quality of life. This will allow PIDTC researchers to better understand long-term outcomes from procedures that occurred many years ago (sometimes over 30 years ago) - something that is not possible at the present time with 6901. This will help researchers to best design new treatments and clinical trials in the future for children with SCID.

  Study phs001326

• Genomic Predictors of Combat Stress Vulnerability and Resilience

  The Genomic Predictors of Combat Stress Vulnerability and Resilience Study was designed to probe the likely hereditary basis for risk or resilience to develop PTSD and other trauma spectrum disorders. The overall guiding hypothesis was that genomic variation gives rise to risk/susceptibility traits that, when actuated by traumatic environmental stimuli, such as combat, give rise to PTSD and other stress-related phenotypes. Two studies designed to identify risk and resilience factors for combat-induced, stress-related symptoms are being conducted by our group: The Marine Resiliency Study (MRS) is a prospective PTSD study with longitudinal follow-up (pre- and post-exposure to combat stress) of US Marines bound for deployment to Iraq or Afghanistan. Extensive phenotyping includes 3 domains: Psychosocial, Psychophysiologic, and Biophysiologic. The biological and physiological measures collected were chosen in part due to their potential to serve as intermediate phenotypes for stress-related disorders. A second, cross-sectional study involves a cohort of combat-exposed active duty or previously deployed service members (CAVC), including PTSD cases and controls with comparable psychosocial and clinical phenotypes. Little information is available about the factors that explain why some trauma survivors develop stress disorders and some do not. It is hoped that the insights gained from this approach will improve understanding of the genetic contributors to PTSD, and potentially provide novel diagnostic tests and therapeutic approaches to this currently enigmatic and difficult-to-manage condition.

  Study phs000864

• Genomics of Relapsed Small Cell Lung Cancer Progression

  Small cell lung cancer (SCLC) accounts for nearly 15% of all patients with lung cancer. Though the response to initial therapy is favorable in many patients, a majority of patients go on to develop recurrent disease which is very difficult to treat. The response rates to chemotherapy are very low and most patients succumb to relapsed SCLC within a few months. Virtually no progress has been made in the treatment of SCLC in the last three decades. In order to better understand the molecular alterations in relapsed SCLC, we have generated exome and RNA sequence from normal, primary tumor and relapse tissues of SCLC patients.

  Study phs001049

• Single_Cell_Sequencing_of_Sperm__scSperm_

  The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

  Study EGAS00001000935

• Genetics of Glucose Regulation in Gestation and Growth (Gen3G) Cohort - Placenta Transcriptomics RNA Sequencing

  The overarching goals of Genetics of Glucose regulation in Gestation and Growth (Gen3G) are to increase our understanding of biological, environmental, and genetic determinants of glucose regulation during pregnancy and their impact on fetal/child development. Gen3G is a prospective cohort study: we initially recruited 1,024 pregnant women between 2010-2013 at Blood Sampling in Pregnancy Clinic during the first trimester of pregnancy (median 9 weeks of gestation) in Sherbrooke, Québec, Canada. We assessed 898 pregnant women at second trimester (median 26 weeks of gestation), when participants completed a 75g oral glucose tolerance test (OGTT) as clinically indicated for screening of gestational diabetes mellitus (GDM). We collected data for 854 mother-child dyads at delivery (from medical records), in addition to placenta and/or cord blood samples in majority of newborns.The overall goal of the grant that supported data that is included in this dbGaP submission was to discover novel placental factors that regulate glucose metabolism in pregnancy and predict GDM by conducting genome-wide transcriptomics (RNA and miRNA) in carefully collected placenta samples from Gen3G.

  Study phs003151

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at: mfreeberg@ebi.ac.uk , or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addressesDate and time of a visit to the service website Operating systemAmount of data transmittedBrowserEmail address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the serviceTo better understand the needs of the users and guide future improvements of the serviceTo monitor website activities according to and in compliance with the Terms of UseTo better understand the needs of the website visitors and guide future improvements of the serviceTo conduct and monitor website security activitiesTo create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you.Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data.Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. 9. CookiesWe use cookies and similar technologies that are strictly necessary for the correct functioning and security of the EGA website (for example, to enable core site features and to help protect the service). These cookies do not store information that directly identifies you.You can set your browser to block or delete cookies. Please note that if you disable strictly necessary cookies, parts of the website may not function properly.Published on February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• All counts

  This dataset is the expression profiling by high throughput sequencing, including all counts of genes for all samples in two groups. It includes 26 samples totally (Lean healthy group includes 12 samples: s001/SR01_Bright, s002/SR01_Dim, s004/SR02_Bright, s005/SR04_Dim, s006/SR04_Bright, s007/SR05_Dim, s008/SR05_Bright, s009/SR06_Bright, s011/SR07_Dim, s012/SR07_Bright, s013/SR08_Bright, s014/SR08_Dim; DM2 group includes 14 samples: s015/SR201_Bright, s017/SR202_Bright, s018/SR202_Dim, s019/SR203_Bright, s020/SR203_Dim, s021/SR204_Bright, s022/SR204_Dim, s023/SR205_Dim, s025/SR206_Dim, s026/SR206_Bright, s027/SR207_Dim, s028/SR207_Bright, s029/SR208_Bright, s030/SR208_Dim). It is a TAB file.

  Dataset EGAD50000001715

• MicroRNAs, Hypertension and End Organ Damage in Humans

  Study 1) Profiling of microRNAs in plasma of patients with hypertension complicated or not by metabolic syndrome or chronic kidney disease Hypertension (HTN) or high blood pressure is associated with subclinical target organ damage such as cardiac, vascular and kidney injury, which may lead to complications and death. In this study, we investigated circulating microRNAs as biomarkers of target organ damage in HTN patients. We profiled circulating microRNAs by RNA sequencing in platelet-poor plasma of normotensive subjects and patients with HTN complicated or not by metabolic syndrome (MetS) or chronic kidney disease (CKD) (n=15 each group). Differentially expressed microRNAs were identified with a threshold of false discovery rate <0.1. Differentially expressed microRNAs were identified uniquely to associate with HTN (8), MetS (1) or CKD (13), and 8 were similarly differentially expressed in different groups. This study identified the association of differentially expressed circulating microRNAs with target organ damage in HTN patients, which could have some pathophysiological and therapeutic implications. Study 2) Profiling of microRNAs in gluteal subcutaneous small arteries of patients with hypertension complicated or not by chronic kidney disease Hypertension (HTN) is associated with vascular damage characterized by endothelial dysfunction and vascular remodeling and stiffening, which contributes to kidney injury leading to chronic kidney disease (CKD). MicroRNAs are short non-coding RNAs which repress/degrade target mRNAs. The microRNA role in vascular injury in HTN remains unclear. In this study, we aimed to identify differentially expressed microRNAs in small arteries of patients with HTN associated or not with CKD, in order to shed light on the pathophysiological molecular mechanisms. Normotensive subjects and HTN patients associated or not with CKD grades 3-4 were studied (n=15-16). Small arteries were isolated from subcutaneous gluteal biopsies, RNAs were extracted, and small and total RNA sequencing was performed by Illumina HiSeq-2500. Differentially expressed genes were identified with a P<0.05 and fold change (FC) >1.3. Differentially expressed microRNAs and mRNAs were identified uniquely to associate with HTN (microRNAs: 10, mRNAs: 68), CKD (microRNAs: 68, mRNAs: 395), and both groups (microRNAs: 2, mRNAs: 32). This study identified differentially expressed microRNAs and mRNAs in small arteries with target organ damage in HTN, which could have some pathophysiological and therapeutic implications.

  Study phs002389

• Early on-treatment changes in circulating tumor DNA fraction and response to enzalutamide or abiraterone in metastatic castration-resistant prostate cancer

  On-treatment circulating tumor DNA (ctDNA) quantification is touted as a surrogate biomarker for understanding metastatic cancer response to systemic therapy, but there is relatively little supporting data from standardized patient cohorts. Here, in a prospective observational cohort, we demonstrate that 4-week on-treatment changes in plasma ctDNA levels can accurately identify metastatic castration-resistant prostate cancer that will progress within 6 months of initiating first-line abiraterone or enzalutamide treatment. On-treatment ctDNA measurements outperformed existing clinical variables for predicting disease response and were also closely associated with differential overall survival. Although optimal timing of blood collections and thresholds for ctDNA detection will require further testing, our data highlights the potential for sequential ctDNA measurements to provide an early and reliable read-out for therapy response. The high accuracy of this information suggests that ctDNA could be useful for guiding clinical trials of therapy changes in initially non-responsive metastatic cancers.

  Study EGAS00001006856

• Aspirin and Inflammation: Mutations, Genes, Pathways and Prevention in Barrett's Esophagus

  Background: Use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to protect against tetraploidy, aneuploidy, and chromosomal alterations in the metaplastic condition Barrett's esophagus (BE) and to lower the incidence and mortality of esophageal adenocarcinoma (EA). The esophagus is exposed to both intrinsic and extrinsic mutagens resulting from gastric reflux, chronic inflammation and exposure to environmental carcinogens such as those found in cigarettes. Here we test the hypothesis that NSAID use inhibits accumulation of point mutations/indels during somatic genomic evolution in BE. Methods: Whole exome sequences were generated from 82 purified epithelial biopsies and paired blood samples from a cross-sectional study of 41 NSAID users and 41 nonusers matched by sex, age, smoking, and continuous time using or not using NSAIDs. Results: NSAID use reduced overall frequency of point mutations across the spectrum of mutation types, lowered the frequency of mutations even when adjusted for both TP53 mutation and smoking status, and decreased the prevalence of clones with high variant allele frequency. Never smokers who consistently used NSAIDs had fewer point mutations in signature 17, which is commonly found in EA. NSAID users had on average a 50% reduction in functional gene mutations in nine cancer-associated pathways and also had less diversity in pathway mutational burden compared to nonusers. Conclusions: These results indicate NSAID use functions to limit overall mutations on which selection can act and supports a model in which specific mutant cell populations survive or expand better in the absence of NSAIDs. Galipeau PC, et al. Genome Med. 2018 Feb 27;10(1):17. PMID: 29486792.

  Study phs001654

• Male Infertility: Genetics of Spermatogenic Failure

  Spermatogenesis is a complex biological process that requires the coordination of thousands of genes. Perhaps because of the large number of genes involved, spermatogenic failure occurs frequently and affects approximately 1% of men. While environmental and genetic factors likely contribute to this disorder, it is thought that the majority of cases have an underlying genetic basis. The two most common genetic causes are deletions on the Y chromosome and cytogenetic abnormalities (/e.g./ Klinefelter syndrome, XXY), which each account for roughly 10-15% of cases of complete spermatogenic failure. Point mutations in several other genes have also been linked to spermatogenic failure, but their collective prevalence is very low. Thus, for approximately 70% of men with spermatogenic failure, the genetic cause remains unknown. We hypothesize that a disproportionate number of these remaining genetic variants reside on the sex chromosomes because they are hemizygous in males and contain a disproportionate number of genes expressed in the testis. To identify genes that are required for spermatogenesis, we have performed capture-based targeted sequencing in 301 men with azoospermia (complete absence of sperm) and 300 fertile controls. Our sequencing is focused on coding genes and conserved, non-coding sequences of the X and Y chromosomes. In addition, we have targeted ~497 autosomal genes that display exclusive or predominant expression in the testis. The total sequence space targeted is 21.3 Mb, and we require >70% of targets reach an average coverage of 20X.

  Study phs001023

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• WES of der(1;7)(q10;p10) myeloid neoplasms

  The study examined WES of der(1;7)(q10;p10) myeloid neoplasm cases. BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10) were used to identify key driver genes in patients with der(1;7)(q10;p10). This study is one of the largest WES for der(1;7)(q10;p10)(+) myeloid neoplasm cases.

  Study EGAS50000000704

• Genome-Wide Association Study of Genetic Susceptibility for Graft-vs-Host Disease Cohort 1

  Allogeneic hematopoietic stem cell transplantation (Allo-HSCT) is the only curative therapy for many advanced hematologic malignancies. Allo-HSCT is associated with significant morbidities and mortality, mainly because of the graft-versus-host disease (GVHD) caused by donor T cells recognizing antigens present in recipient tissues, and initiating an alloimmune response resulting in damage to many organs including the skin, gastrointestinal (GI) tract, and liver in recipient. More than half of all Allo-HSCT recipients develop different degrees of GVHD (grades I-IV). About 20% of recipients develop severe GVHD (grades III-IV) that is associated with a very high morbidity and mortality. The most important factor determining the severity of GVHD is the genetic disparities between donors and recipients, as is reflected in human leukocyte antigen (HLA) haplotypes that are routinely checked for donor selection. Even when donors and recipients are HLA-identical, many recipients develop severe GVHD. As a result, non-HLA antigens are important determinants of acute GVHD. An interesting and unique aspect of GVHD is that it is the consequence of an interaction between antigens present in one individual with the immune system of another individual. As a result, genotypes of both donor and recipient, and their interactions affect the pathogenesis of GVHD. To determine the genetic risk factors for GVHD, in the first aim (discovery phase), we will conduct Genome-Wide Association Studies (GWAS) in 3,000 patients who underwent Allo-HSCT and in their respective donors (6000 DNA samples) that are provided to us by the Center for International Blood and Marrow Transplant Research (CIBMTR), a research collaboration between the NMDP and Medical College of Wisconsin. In the second aim, we will validate the association between high risk genotypes detected in the first aim and severe GVHD in 1,750 donors and 1,750 recipients of Allo-HSCT, and perform the joint analysis with the discovery samples. In the third aim, we will investigate the functional effect of SNPs detected and validated to be significantly correlated with the severity of acute GVHD in mixed lymphocyte reaction (MLR), as an ex vivo surrogate for an alloimmune response.

  Study phs002185

• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• DAC-2020-03-26-Lemola (DAC-039))

  This is only the location. For the raw data and any check if the dataset may be relevant please refer to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/lemola).

  Study EGAS50000000635

• Targeted sequencing of head and neck squamous cell carcinomas

  Overall survival remains very poor for patients diagnosed with head and neck squamous cell carcinoma (HNSCC). Identification of additional biomarkers and novel therapeutic strategies are important for improving patient outcome. Patient-derived xenografts (PDXs), generated by implanting fresh tumor tissue directly from patients into immune-deficient mice, recapitulate many of the features of their corresponding clinical cancers, including histopathological and molecular profiles. Using a large collection of PDX models of HNSCC we demonstrate that rapid engraftment into immune-compromised mice is highly prognostic, and show that genomic deregulation of the G1/S checkpoint pathway correlates with engraftment. Furthermore, CCND1 and CDKN2A genomic alterations are predictive of response to the CDK4/6 inhibitor abemaciclib. Overall, our study supports the pursuit of CDK4/6 inhibitors as a therapeutic strategy for a substantial proportion of HNSCC patients, and demonstrates the potential of using PDX models to identify novel targeted therapies for those patients who have the poorest outcomes.

  Study EGAS00001002979

• Whole genome sequencing of 25 South African individuals with myasthenia gravis

  This study investigated the genetic basis of an ophthalmoplegic subphenotype of MG (OP-MG) which occurs in a proportion of myasthenics with juvenile symptom onset and African genetic ancestry. This OP-MG subphenotype is characterised by treatment resistant weakness of the extraocular muscles (EOMs) and the pathogenetic mechanism(s) underlying its development is unknown. The aim of this study was to use a hypothesis-generating genome-wide case-control analysis to identify candidate OP-MG susceptibility genes and pathways. Whole genome sequencing (WGS) was performed on 25 AChR-antibody positive myasthenic individuals of African genetic ancestry sampled from the phenotypic extremes: 15 with OP-MG (cases) and 10 individuals with control MG (EOM treatment-responsive).

  Study EGAS00001003462

• PCGP Ph-like ALL

  Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

  Study EGAS00001000654

• How mitochondrial DNA research can benefit from data reuse through EGA?

  Mitochondria are the only cellular organelles harbouring their own DNA, which encodes for proteins essentials in its respiration process. Despite its discovery in 1960, Mitochondrial DNA is often overlooked compared to nuclear DNA. Indeed, not all sequencing technologies capture a good representation of mtDNA (mitochondrial DNA). Recently, Ed Reznik's team (The Ed Reznik Lab | Memorial Sloan Kettering Cancer Center) carried out a massive analysis and reanalysis of single cells WGS (whole genome sequencing) produced with an amplification-free protocol (Direct library prep, DLP). As they demonstrated in the paper Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes - PMC, DLP is more effective in catching mtDNA compared to classical single-cell sequencing. These data allowed the team to unravel mtDNA dynamics in tumoral and normal samples, highlighting how mtDNA and nuclear DNA are co-regulated and their ratio is critical for phenotype. Data reuse to achieve the greatest results For this project, Reznik's team re-used data from 3 studies stored at the European Genome-phenome Archive (EGAS00001006343, EGAS00001004448 and EGAS00001003190) that comprised a total of 602 datasets. All of them were initially produced by the teams of Sam Aparicio and Sohrab P. Shah at the Memorial Sloan Kettering Cancer Centre, where Ed Reznik is a promising group leader. This demonstrates, once again, that networking, collaboration and data sharing can achieve the greatest results when coupled with innovative and smart ideas. At the EGA we are proud to provide the scientific community with an infrastructure to enable all those very smart ideas out there to find the right data to be tested.

  Blog mitochondrial-dna-research

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• The Proteogenomic Subtypes of Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is an aggressive blood cancer with poor prognosis. We report a comprehensive proteogenomic analysis of bone-marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none are exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is only captured in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival upon treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired towards stronger complex I dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

  Study EGAS00001005950

• EGA submission account terms

  Submission account terms Each EGA submission account has a dedicated submission box. To ensure continued service to all submitters EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. Those that are near to or exceeding this value will be monitored on a weekly basis by the helpdesk team and the submitter will be contacted and guidance provided accordingly on completing their metadata registration. You will be able to register your metadata associated with the files in your submission account via EGA Submitter Portal, Webin or the EGA REST API. EGA also requests that metadata is submitted within 60 days of upload data to a submission box. When we detect files that are over 60 days old in a submission box we will notify the submitter requesting that metadata be submitted or the files removed from the submission box. It is important to note that data is not archived at the EGA until the metadata describing the files has been associated and the archival process has completed. It is only when associated metadata has been submitted that the archival process into EGA is fully triggered. EGA removes files from the submission box once they have been successfully archived, so no action is required by a submitter to remove successfully archived files. Files over 90 days old will be deleted from the submission box unless EGA Helpdesk has been contacted and confirmed an exemption with the submitter.

  Documentation submission/terms

• Relationship between low LDL cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: a US-based cross-sectional observational study using electronic medical records

  Lipid lowering therapy using HMG-CoA reductase inhibitors (statins) is associated with an approximately 9-12% increase in the risk of new-onset type 2 diabetes (T2DM). The risk of diabetes could be increased by statins directly; however, genetic approaches have also implicated low LDL cholesterol (LDL-C) concentrations as a risk factor for T2DM. Mendelian randomization studies using functional variants in both HMGCR (GeneID:3156) and PCSK9 (GeneID:255738) genes found a higher risk of T2DM in individuals with variants associated with lower LDL-C concentrations. Since PCSK9 and HMGCR are involved in lipid metabolism through distinct molecular pathways, the altered glycemic effect associated with variants in both genes is likely to be the result of their common effect on LDL-C concentrations. Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations with increased risk of T2DM. Individuals who have very low LDL-C concentrations not due to lipid lowering therapy can provide insights into the relationship between low LDL-C concentrations and T2DM. Here, we used de-identified electronic health records (EHRs) to test the hypothesis that low LDL-C concentrations are associated with T2DM.

  Study phs001588

• Single Cell Sequencing of Sperm (scSperm)

  The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

  Dataset EGAD00001001216

• Organ_maturation_in_preparation_for_birth__Peds_RFA__to_develop_a_tissue__resource_and_a_single_cell_atlas_of_organ_development_and_maturation_for__dissemination_among_the_scientific_and_clinical_community__RNA

  Knowledge about abnormal organ development is important to understand pathology and to develop novel treatment approaches for individuals with congenital and acquired disease. Most of our current understanding is based on examination of tissues from the embryo and early foetus, collected from women undergoing termination of pregnancy in the first trimester (third) of pregnancy. There is very little known about normal and abnormal organ development from a developmental perspective during the crucial last two-thirds of pregnancy when much remodelling of foetal tissues occurs. This study will generate a single-cell atlas of late-foetal lungs, blood, heart, bone and immune organs.

  Study EGAS00001008256

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• Homozygous Duplication Identified by Whole Genome Sequencing Causes LRBA Deficiency

  In more than one third of primary immunodeficiency (PID) patients, extensive genetic analysis including whole exome sequencing (WES) fails to identify the genetic defect. Whole genome sequencing (WGS) is able to detect variants missed by other genomics platforms, enabling the molecular diagnosis of otherwise unresolved cases. Here, we report two siblings, offspring of consanguineous parents, who experienced similar severe events encompassing early onset of colitis, lymphoproliferation and hypogammaglobulinemia, typical of lipopolysaccharide (LPS)-responsive and beige-like anchor protein (LRBA) or cytotoxic T-lymphocyte-associated protein 4 (CTLA4) deficiencies. WGS of these patients detected a 12.3 kb homozygous tandem duplication that was absent in control cohorts and is predicted to disrupt the reading frame of the LRBA gene.

  Study phs002557

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

  Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002237

• Whole exome sequencing on primary retinoblastoma tissues and matching lymphocyte DNA.

  Retinoblastoma is a rare childhood cancer initiated by RB1 mutation or MYCN amplification, while additional alterations may be required for tumor development. However, the view on single nucleotide variants is very limited. To better understand oncogenesis, we determined the genomic landscape of retinoblastoma. We performed exome sequencing of 71 retinoblastomas and matched blood DNA. Next, we determined the presence of single nucleotide variants, copy number alterations and viruses. Aside from RB1, recurrent gene mutations were very rare. Only a limited fraction of tumors showed BCOR (7/71, 10%) or CREBBP alterations (3/71, 4%). No evidence was found for the presence of viruses. Instead, specific somatic copy number alterations were more common, particularly in patients diagnosed at later age. Recurrent alterations of chromosomal arms often involved less than one copy, also in highly pure tumor samples, suggesting within-tumor heterogeneity. Our results show that retinoblastoma is among the least mutated cancers and signify the extreme sensitivity of the childhood retina for RB1 loss. We hypothesize that retinoblastomas arising later in retinal development benefit more from subclonal secondary alterations and therefore, these alterations are more selected for in these tumors. Targeted therapy based on these subclonal events might be insufficient for complete tumor control.

  Study EGAS00001001690

• A novel subset of human CD33+ haematopoietic stem cells characterized at single-cell resolution

  Elucidation of the identity and diversity of mechanisms that sustain long-term human blood cell production remains an important challenge. Previous studies indicate that, in adult mice, this property is ultimately vested in cells uniquely identified by their ability to clonally regenerate detectable levels of mature blood cells in serially transplanted recipients. We now present a combined multi-parameter analysis of the molecular features of very primitive human cord blood cells that display different cell output activities in vitro and in vivo. These analyses identified a new, prospectively separable, but still functionally heterogeneous, subset of long-term human blood-forming cells. Single-cell measurements of their transcriptional, DNA methylation and 40-protein content and of closely related phenotypes revealed numerous subtle, but consistent differences both within and between each subset analyzed. These results suggest that multiple regulatory mechanisms underlie the functional heterogeneity exhibited by clonally tracked human blood cell precursors with long-term output abilities.

  Study EGAS00001002826

• The epigenomic response of skeletal muscle in life-long high-level trained and untrained men and women after acute exercise

  To investigate the influence of lifelong exercise training on the response of skeletal muscle to a bout of acute exercise we generated targeted epigenomic data from long-term endurance (8 men) and strength (8 men) trained individuals and healthy age-matched untrained controls (8 men). Skeletal muscle biopsies were taken from M. vastus lateralis before, directly after, and 3hrs following acute exercise. Control subjects completed one bout of acute endurance exercise and one bout of acute resistance exercise, separated by 4-8 weeks, athletes completed one bout in their respective form of sports. All 96 samples were used for DNA extraction and targeted library construction using a custom Twist Biosciences panel and following EM-methylation tranformation were sequenced (2x150bp paired end) on the Illumina NovaSeq 6000.

  Dataset EGAD50000000512

• The scRNA dataset for TIGIT in MCL with CART

  We collected longitudinal samples from 15 patients with MCL at various clinical time points before and after CAT-T therapy brexucabtagene autoleucel (BA) infusion. The patients were grouped into three categories based on their clinical responses after BA treatment: 1) responsive (n = 9), 2) relapsed (n = 5), and 3) refractory (n = 1). All patients in category #1 and #2 had initially attained a complete response (CR) after BA therapy. The responsive group maintained CR with no relapse at the time of last follow up, while the relapsed group achieved initial CR but eventually relapsed. The 10x Chromium™ Single-Cell 5′ Reagent Kit v2 (PN-1000190, 10x GENOMICS) and Chromium Single-Cell Human TCR amplification Kit (PN-1000252, 10x GENOMICS) were used to perform single-cell separation, cDNA amplification, and library construction for gene expression and TCR repertoire following the manufacturer’s guidelines. Thirty-nine samples passed quality control and underwent single-cell transcriptome profiling with simultaneous single-cell T-cell receptor (TCR) repertoire analysis.

  Dataset EGAD00001010180

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  Study on RNA-seq data from tumor tissue samples of primary tumors of advanced clear cell renal cell carcinoma patients enrolled in the NIVOREN GETUG-AFU-26 trial who consented to and participated in the translational program. The goal of this study was to assess previously published gene expression signatures and evaluate their association with the benefit and/or resistance to nivolumab, as well as their association with circulating soluble factors.

  Study EGAS50000001057

• Targeted sequencing of Burkitt lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  The UK’s Haematological Malignancy Research Network (www.HMRN.org) was established in 2004 to provide robust generalizable data to inform clinical practice and research. HMRN is a collaboration between researchers in the Epidemiology & Statistics Group (ECSG) at the University of York, a unified Clinical Network operating across 14 hospitals, and an integrated Haematological Malignancy Diagnostic Service (HMDS) in Leeds. Covering a population of around 4 million, HMRN collects detailed information about all patients diagnosed with a haematological malignancy within the HMRN region, accruing around 2,400 new diagnoses each year. The population has a similar socio-demographic profile to the country as a whole, and HMRN’s maturing data present an increasingly valuable resource to address real questions of concern to haematologists, commissioners and health service researchers – locally, nationally and internationally. This study forms part of a larger project employing targeted exome sequencing on tumour samples from patients diagnosed with a variety of both lymphoid and myeloid malignancies. The results for samples collected from 39 Burkitt lymphoma patients, diagnosed within HMRN from 2005 to 2012, are provided.

  Study EGAS00001004649

• Uveal melanoma patient with germline MBD4 nonsense mutation

  There is currently no effective treatment for metastasised uveal melanoma (UM). Recently, it was reported that a UM patient was responsive to checkpoint inhibitor (CI) treatment, due to a high tumour mutation burden correlated with a germline loss-of-function MBD4 mutation. Here, we report on another UM patient who carried an MBD4 germline nonsense variant (p.Leu563Ter) and her tumour showed a 5-fold higher than average mutation burden. We confirmed the association between germline loss-of-function variant in MBD4 and CI response. The patient experienced stable disease (10 months) and survived two years with metastatic disease, which is twice as long as median survival. Additionally, the frequency of MBD4 loss-of-function variants in reported UM cohorts was >20 times higher than in an aggregated population genome database (P < 5x10-5), implying a potential role as UM predisposition gene. These findings provide a strong basis for the inclusion of MBD4 in screening of potential UM-prone families as well as stratification of immunotherapy.

  Study EGAS00001003362

• Single-cell RNA-seq of celiac disease-specific plasma cells

  Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGP) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls, and performed RNA-sequencing with clonal inference and transcriptomic analysis of 3251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy-chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific vs non-disease-specific PCs and between short-lived vs long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

  Study EGAS00001004623

• 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.

  Study EGAS00001003427

• WGS datasets of pediatric glioblastoma

  WGS with linked reads of pediatric glioblastoma. For each patient, blood and tumor tissue were sequenced. For two patients, we also provide sequencing data for the blood of their parents.

  Dataset EGAD00001005212

• Cell types of the human retina and its organoids at single-cell resolution. Cowan et al

  Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers, and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas.

  Dataset EGAD00001006350

• Identifying autosomal recessive mutations causing neurological disorders

  The objective of this study is to resequence of targeted intervals containing autosomal recessive variants causing neurological disorders in consanguineous pedigrees. Using homozygosity mapping, three intervals of very different sizes have previously been unambiguously mapped for three different neurological diseases: 2.4Mb, 8Mb and 14.3Mb in size, for Microlissencephaly, Severe Mental Retardation and Complicated hereditary spastic paraplegia respectively. This study is a pilot to assess how well custom targeted resequencing performs across a broad size range of intervals. The study design is to use a different custom capture probe set for each interval, pulldown from a single patient from each family, and sequence 1 lane using Illumina paired-reads for each sample. Candidate variants will be followed up in the families themselves, and in patients with similar phenotypes from outbred populations.

  Study EGAS00001000023

• Somatic_Variation_Angiosarcoma

  Through whole genome sequencing, this study will explore the mutational profiles and signatures within an angiosarcoma tumour from a patient with xeroderma pimentosum. Very little information is known about this tumour type and it has not previously been studied within the context of xerogerma pigmentosum.

  Study EGAS00001002610