4075 results for "*geneti*"

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• A single-cell multi-omic atlas of the human pancreas reveals latent plasticity across development, health, and disease

  The pancreas plays a central role in major human diseases, yet our understanding of its cellular diversity and plasticity remains incomplete. Here, we present a single-cell multiomics atlas of the human pancreas, profiling over four million cells and nuclei from 57 donors across fetal development, adult homeostasis, and type 2 diabetes (T2D). Integrating sc/snRNA-seq, snATAC-seq, VASA-seq, spatial transcriptomics (Xenium), and multiplexed proteomics (CODEX), we resolve gene expression, chromatin accessibility, and spatial organization at high resolution. We identify transcriptionally plastic centroacinar-like cells (pCACs) in adults with fetal-like features, delineate endocrine and exocrine lineage trajectories during development, and uncover HNF1A-defined beta cell epigenetic states. In T2D, we observe shifts in beta cell subtypes and altered regulatory programs. Glucose perturbation of healthy islets reveals cell-type-specific adaptation and stress responses. This atlas provides a foundational framework to understand pancreas biology and the role of cellular plasticity in regeneration and disease.

  Study EGAS50000001872

• Investigating Host Genetic Risk Factors for Tuberculosis in Highly Endemic South African Populations

  It is apparent from our recent population genetic and admixture mapping work 1–3 that a substantial part of the ancestral input into the South African Coloured (SAC) population is from the San or Khoe groups, which are not well represented in publicly available genetic databases. It is a reasonable assumption that the SAC population in the Western Cape may have derived more genetic input from the present KhoeSan population in the Northern Cape than the San residing in Namibia. It was concluded by our group that it is indeed the southern African KhoeSan group, the ≠Khomani, that best represent the KhoeSan contribution seen in the SAC 4. More recently, it has been shown that there are ancestry related increases in TB susceptibility, especially with increased Bantu-speaking African and KhoeSan ancestry 5. We aim to elucidate the epidemiological and human-host genetic risk factors for TB and the immunological pathways modulating TB infection. The proposed sub-study will enroll people evaluated for TB at Northern Cape community health clinics and their contacts from their households and/or community. We will conduct a demographic interview, collect saliva, which will be used for genetic analysis, and blood to determine latent TB infection status and capture immunological responses to mycobacterial infections at the cellular level and RNA sequencing.

  Study EGAS00001007850

• Genetic control of naive T cell receptor gene usage in celiac disease

  We have characterized the TCR repertoire of naïve CD4+ T cells in 103 individuals with CeD and 103 control subjects by undertaking gene usage quantitative trait loci analyses based on repertoire sequencing and single nucleotide polymorphism genotyping. Variants within the TCR alpha and beta loci and HLA region as well as HLA-DQ allotypes and alleles were tested for association with TCR gene usage.

  Study EGAS50000001882

• Genetic control of naive B cell receptor gene usage in celiac disease

  We have characterized the BCR repertoire of naïve B cells in 102 individuals with CeD and 102 control subjects by undertaking gene usage quantitative trait loci analyses based on BCR repertoire sequencing and single nucleotide polymorphism genotyping within the IGH, IGK and IGL loci.

  Study EGAS50000001881

• CSF PBAT methylome profiling in multiple sclerosis - shallow seq

  This study contains shallow-depth post-bisulfite adaptor tagging (PBAT) whole-genome bisulfite sequencing data generated from cerebrospinal fluid (CSF) cells from individuals with relapsing-remitting multiple sclerosis and neurological disease controls. The shallow-sequencing dataset includes lower-depth technical replicate sequencing of discovery-cohort samples and an independent validation cohort. These data were generated to assess the reproducibility of candidate MS-associated DNA methylation differences identified by deep PBAT-seq and to support validation of methylation signatures in CSF immune cells. The study contributes to the characterization of immune regulatory, adhesion, migration and protocadherin-associated epigenetic changes in multiple sclerosis.

  Study EGAS50000001940

• mRNA-seq of paired Follicular Lymphoma (FL) patient samples before and after high-grade transformation to DLBCL (FL vs. tFL) from FFPE tissues

  The aim of this study was to analyze transcriptional changes in paired samples of follicular lymphoma (FL) and its histological transformation (tFL). Transformation of FL is an adverse event in the course of the disease and is associated with poor outcome. Several genetic aberrations have been linked to tFL pathogenesis, but gene expression changes and microenvironmental interactions have not been well characterized. We performed RNA profiling of FL and paired tFL samples transformed to DLBCL (n=11 pairs). For RNA profiling, we utilized libraries prepared using RNA isolated from archival FFPE tissues.

  Study EGAS50000000941

• Rhabdoid tumors WGS from Sánchez-Guixé et al. "Variable latency between the founder genetic event and rhabdoid tumor expansion" 2026

  Whole Genome Sequencing from tumors and normal blood samples from 16 cases diagnosed with rhabdoid tumors in SJD hospital and 1 case from Princess Maxima Center (PMC) (total 17 cases)

  Study EGAS50000002082

• After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

  CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

  Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

• The EGA at the International Congress of Human Genetics

  Today is the start of the International Congress of Human Genetics (ICHG). This event, hosted by the African Society of Human Genetics (AfSHG) and the Southern African Society for Human Genetics (SASHG), will reunite international experts to highlight how genomic technologies are being managed to address challenges generated by the current status of Human Health and Genomics. The European Genome-phenome Archive (EGA) will be at the Congress participating in workshops, meetings and talks where topics such as data access and discovery as well as the Federated EGA will be present. Data access and discovery In the context of the “Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. Data access and discovery In the context of the “ Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. During the last four years, CINECA has been identifying gaps in data sharing between Africa, Canada and Europe in order to build a federated solution for data access. Thomas Keane will present the project within the sessions happening the 24ᵗʰ. The Federated EGA at the ICHG A Federated EGA poster will be shown during the Poster Session 1 that will take place the 23ʳᵈ. The objective is to bring awareness of the European Genome-phenome Archive as a resource for permanent archive and secure data sharing. In this context, the network generated by the Federated EGA is key for cases where research data cannot be shared outside local jurisdictions. The Federated EGA was officially launched on 2022 with research institutes from five countries becoming the first nodes of this network. Nowadays, with more than 20 nodes preparing to join, it aims to become the largest human omics data sharing initiative towards understanding human health and disease. The H3Africa Initiative and the African research represented in the EGA 1.1% of the EGA studies include samples from African populations. Countries such as South Africa, Kenya, Uganda or Egypt, among others, are present in the 72.577 samples from African individuals archived at the EGA. 23 EGA datasets are managed by the Human Heredity and Health in Africa Initiative (H3Africa). This Initiative will celebrate its Consortium Meeting the 27ᵗʰ and 28ᵗʰ, back-to-back with the ICHG. H3ABioNet, the Pan African Bioinformatics Network for the H3Africa consortium, will also take this context to celebrate its 10-Year Symposium during the Congress. Members of the EGA team will attend both of them, as the H3ABioNet works in conjunction with H3Africa projects, to submit data to the European Genome-Phenome Archive.

  Blog the-ega-at-the-international-congress-of-human-genetics

• Shedding light over COVID-19 susceptibility and severity

  “One of the most remarkable features of SARS-CoV-2 infection is the variation in consequence ranging from asymptomatic to life-threatening” state the authors of the majestic Nature paper released in accelerated pre-view on July 2021. This variation in consequences represent not only an issue of burning medical relevance, but also a scientific and intellectual challenge for scientists around the globe. Researchers are known to be easily triggered by a challenge, and they recently demonstrated to be even better at double their efforts to focus on an urgent societal need. In this work led and coordinated by the COVID-19 Host Genetics Initiative (COVID-19 HGI), researchers gathered data from 49,562 cases and two million controls from 46 studies performed worldwide. The majority of the data has been deposited at the EGA, where 29 datasets have been collected under the study number EGAS00001005304. Data gathered from diverse sources conferred a huge robustness to the results. Genetic data from different ancestry origin were included in the analyses, even though data from patients with European origin was highly predominant (approx. 75%). Separated analysis of the different ancestries gave rise to relevant differences in the results, highlighting how important it is to take this aspect in consideration for future studies. Data from the individual studies was compiled into three categories according to COVID-19 severity for a meta-analysis: (a) critically ill cases (b) moderate or severe cases (c) all cases. They were paired with non-COVID-19-reported controls. All three analysis resulted in a total of 13 genetic loci associated with COVID-19 severity. Out of those, 9 loci associated specifically with critical illness, while 6 (a few overlapped) associated with moderated illness. Some genomic position matched previous findings. Interestingly, working with such an enormous amount of data allowed the depth to discriminate association with disease susceptibility vs severity, an issue of large medical relevance. Several loci mapped into biological relevant genes, like TYK2, PPP1R15A and FOXP4, previously implicated in immune response and/or lung functions. Researchers participating in the COVID-19 Host Genetics Initiative have worked in an unprecedented time-tight collaboration, prioritizing data sharing and collective results to tackle the pandemic affecting the world. The scientific community won’t miss any of the lessons to learn from this, and the EGA is ready to keep working to enable safe data sharing and fruitful collaborations.

  Blog covid-19-susceptibility-and-severity

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

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

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

  Blog providing-access-to-covid-19

• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

  Blog the-last-addition-to-the-list-of-clonal-evolution-studies-in-the-ega

• 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

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• 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

• New review highlights how data reanalysis is transforming rare disease diagnosis

  A newly published review, Advancing the diagnosis of rare neuromuscular and neurological diseases through the collaborative Solve-RD research framework, reflects on one of Europe's largest collaborative efforts to improve the diagnosis of rare diseases through systematic genomic reanalysis. Rather than focusing on generating new sequencing data alone, the review highlights a simple but powerful idea: genomic data continue to gain value over time. As disease knowledge expands, analytical methods improve, and new technologies become available, datasets that once yielded no diagnosis can help “solve families” - that is, identify the genetic cause of disease in families who had previously remained without an answer - years after they were first generated. It is a compelling reminder that the diagnostic journey does not necessarily end with an initial negative result. Solve-RD: a collaborative approach to unsolved rare diseases Launched in 2018, Solve-RD brought together clinicians, researchers and data scientists across Europe to systematically revisit genomic data from patients with previously unsolved rare diseases. By combining expertise across the European Reference Networks (ERNs) with complementary approaches such as RNA sequencing and other multi-omics technologies, the consortium created a framework for large-scale collaborative reanalysis. The results demonstrate the value of this approach. In one of the consortium's largest studies, 506 of more than 6,000 previously unsolved families received a genetic diagnosis through systematic reanalysis, as reported in the consortium's flagship Nature Medicine publication. More recently, a complementary RNA sequencing study released in MedRxiv provided diagnoses for 19 of 248 families whose DNA analyses had previously been inconclusive, while also identifying several novel candidate disease genes. From archived data to new diagnoses These achievements depended on more than new analytical methods—they relied on the continued availability of genomic data. Throughout the Solve-RD project, datasets were securely archived at the European Genome-phenome Archive (EGA), enabling long-term preservation and controlled access for future research and reanalysis. More than 750,000 files, representing over 800 TB of data, were deposited in the archive. Today, the Solve-RD collection remains the second largest collection of datasets at the EGA and discoverable under study EGAS00001003851, allowing authorised researchers to request access through the project's Data Access Committee. Looking ahead While the review reflects on the achievements of Solve-RD, its message extends beyond a single project. It shows how systematic reanalysis, collaborative interpretation and the responsible reuse of existing data can continue generating diagnoses long after those data were first produced. Building on the collaborative foundations established through RD-Connect, Solve-RD and EJP RD, the European Rare Diseases Research Alliance (ERDERA) is now expanding this model across Europe. ERDERA has already brought together 10,000 harmonised genomic and phenotypic datasets from unsolved rare disease cases into a secure European resource, with the long-term ambition of integrating 100,000 genomic and multi-omics datasets to accelerate rare disease research and diagnosis. The EGA is actively working with ERDERA partners to support the operation of this large-scale effort: from aiding in coordinating and processing data submissions to enabling their secure archival and controlled reuse. This support extends across genomic, transcriptomic and other multi-omics data, including emerging technologies such as long-read sequencing, optical genome mapping and novel omics approaches. By helping centres submit and manage increasingly diverse datasets at scale, the EGA supports their integration into a sustainable resource that can be revisited as technologies evolve and new research questions emerge.

  Blog data-reanalysis-is-transforming-rare-disease-diagnosis

• Whole-genome sequences of Korean populations generated by using long- and short-read sequencing technologies.

  We newly sequenced whole-genome of Korean participants by using long- and short-read sequencing platforms (n = 3 and n = 100 for long- and short-read sequencing, respectively). With these data, generated by Sequel II HiFi system (Pacific Bioscience) and DNBSEQ-T7 (MGI) sequencers, we identified a set of structural variations common in Korean population as well as the genetic features distinct from other ethnicities.

  Study EGAS50000000375

• Epigenetic Heterogeneity in Breast Tumors with Implications for Disease Diagnosis and Monitoring

  This study investigates epigenetic heterogeneity in human breast cancer using complementary single-cell and bulk epigenomic approaches. Human breast tumor samples were profiled using whole-genome bisulfite sequencing, enzyme-mediated methylation sequencing of sorted tumor-cell populations, single-nucleus CUT&Tag, and single-cell RNA and chromatin-accessibility multiome profiling. These data were used to characterize recurrent epigenetic cell states and intra-tumor heterogeneity in breast cancer.

  Study EGAS50000002070

• NGS in FACSorted populations from AML patients

  FACS-enriched bone marrow cell populations from 22 AML patients were analyzed using a custom panel targeting 56 genes recurrently mutated in myeloid neoplasms. DNA was released from a median of 60,000 sorted cells by incubation with 2.5 μL proteinase K and 2 μL RNase A (Thermo Fisher Scientific) for 30 minutes at 37°C, purified using 2× AMPure XP beads (Beckman Coulter, Brea, CA), and stored in pH 8 elution buffer at −20°C. DNA quantity was measured using the Qubit dsDNA BR Assay on a Qubit 3.0 fluorometer (Thermo Fisher Scientific), and quality was assessed using the Genomic DNA ScreenTape assay on a 4200 TapeStation system (Agilent Technologies, Santa Clara, CA). Libraries were prepared from at least 20 ng of DNA according to the SOPHiA GENETICS protocol and sequenced on an Illumina MiSeq using 2 × 251-cycle paired-end reads. At least 95% of target bases achieved ≥1,000× coverage. FASTQ files were analyzed in SOPHiA DDM using the GRCh37/hg19 reference genome for alignment, variant calling, and annotation. Variants were retained when the variant allele frequency was ≥2%, coverage was ≥100 reads, and the alternate allele was supported on both strands. Synonymous, intronic, intergenic, 5′ untranslated-region, and recurrent panel-artifact calls were excluded. The remaining variants were classified according to Association for Molecular Pathology and American College of Medical Genetics and Genomics guidance using VarSome, ClinVar, COSMIC, and dbSNP. Only pathogenic or likely pathogenic variants were analyzed. All retained calls were visually confirmed in Integrative Genomics Viewer v2.11.3, and only variants previously reported as somatic in hematopoietic or myeloid neoplasms were retained.

  Study EGAS50000002132

• Single-Cell Multiomic and Whole-Genome Profiling of Primary and Metastatic Colorectal Cancer

  This study contains controlled-access single-cell multiomic sequencing (scRNA-seq and scATAC-seq) data generated from patients with colorectal cancer, including 33 primary tumours, 11 metastatic lesions, and 7 adjacent normal tissue samples. Whole-genome sequencing (WGS) data are available for the tumour samples. These data were generated to investigate the genomic and epigenomic landscape of colorectal cancer and to identify recurrent regulatory alterations associated with tumour progression and metastasis.

  Study EGAS50000002048

• NNI ET Imaging Genetic DAC

  Dac EGAC50000001134

• Weizmann Breast Cancer Epigenetics Data Access Committee

  Data Access Committee responsible for reviewing requests for controlled access to human sequencing data generated in the study "Epigenetic Heterogeneity in Breast Tumors with Implications for Disease Diagnosis and Monitoring".

  Dac EGAC50000001136

• Large-scale single-cell phylogenetic mapping of clonal evolution in the human aging esophagus

  SMART-PTA single-cell whole-genome and full transcriptome sequencing form normal esophagus samples

  Dataset EGAD50000002573

• Long-read whole genome sequencing of gastric cancer

  Gastric cancer (GC) remains a significant health challenge globally, with a particularly high incidence in Asia, including Singapore. Understanding the genomic landscape of normal gastric and the different GC subtypes along with its precursor lesions such as intestinal metaplasia (IM) as well as GC metastatic sites is crucial for advancing diagnostics, prognostics, and therapeutics. Long-read sequencing technologies offer an opportunity to delve deeper into the genomic and epigenetic alterations underlying these conditions and to complement existing short-read omics data. By integrating these data with previously generated in-house multi-omics data (such as RNA sequencing and whole exome sequencing), we hope to better elucidate the molecular mechanism underlying GC initiation and progression.

  Study EGAS50000001607

• TMEM259 alleles modulate respiratory syncytial virus infection and ER-stress-triggered apoptosis

  Whole Exome Sequencing data for the IRIS1, IRIS2, and IRIS3 cohorts. Abstract: Respiratory syncytial virus (RSV) is a main cause of infant morbidity and mortality. Susceptibility factors for severe RSV bronchiolitis in previously healthy children are unclear. We analyze genetic variants in 5,141 genes involved in virus sensing, interferon (IFN) signaling and effector functions in a population of n=101 previously healthy infants with severe RSV bronchiolitis. Comparing the allele frequencies of the patient cohort with the Exome Aggregation Consortium (ExAC) dataset our analysis reveals 94 non-synonymous coding single nucleotide polymorphisms (SNPs) mapping to 79 potential risk genes. Follow up of genes expressed in human lung cells show that TMEM259 (also known as membralin), a protein involved in regulating endoplasmic reticulum (ER) stress and neuronal cell survival, restricts RSV infection. Analysis of engineered human airway cells endogenously expressing the TMEM259 major allele or the rs77868901 minor variant shows allele-dependent modulation of RSV infection and ER-stress induced apoptosis, but not IFN activity nor induction of IFN stimulated genes. TMEM259 abundance and polymorphisms modulate RSV infection likely by modulating the ER stress response and apoptosis. This data may aid future risk stratification and development of prevention and treatment strategies for RSV.

  Study EGAS50000001971

• Direct identification of de novo mobile element insertions from single molecule sequencing of human sperm

  Mobile element insertions (MEIs) are a significant source of human genetic variation, yet the rates and properties of de novo MEIs are poorly characterized due to technical limitations in sequencing technology. Here, we directly sequenced individual gametes from sperm samples of 19 donors (aged 27-62) using highly accurate PacBio long-read sequencing to identify de novo retrotransposition events without familial inference. We developed a “self-alignment” strategy using personalized genome assemblies that enables high-precision, single-read detection of de novo MEIs. Using this method, we identified 43 de novo Alu insertions, revealing >9-fold variation in Alu retrotransposition rates between individuals (ranging from 0 to 0.148 insertions/gamete). We found a significant increase in Alu activity with paternal age, yielding a 4.67% increase in insertions per gamete per year of additional paternal age, representing a direct observation of age-associated increases in structural variant (SV) mutation rates. De novo Alu insertions predominantly represent evolutionarily young AluYa5 and AluYb8 subfamilies and bear characteristic molecular signatures of target-primed reverse transcription (TPRT). Our population-averaged rate of 4.52 insertions per 100 gametes aligns well with previous population genetic estimates, validating both direct observation and population approaches for estimating de novo MEI rates. These results establish direct gamete sequencing as a powerful method for characterizing germline mutation processes and reveal age as a significant determinant of de novo retrotransposition in the male germline.

  Study EGAS50000002110

• Integrating transcriptional regulatory networks with chromatin accessibility as markers of survival outcome and drug response in triple-negative breast cancer

  Patients with triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous breast cancer subtype, have limited effective targeted therapy options and frequently develop resistance to chemotherapy. Transcription regulators (TRs) guided precision medicine, namely anti-estrogen receptor therapy, has proven successful in hormone-dependent breast cancer, but remains a challenge in TNBC. Here, we identified key TRs underlying TNBC identity by combining a transcriptional interaction network with chromatin accessibility and defined TR activity score metrics. We show that the activity scores of these TRs independently discriminate patient outcome across different clinical endpoints. Matching TR activity scores to drug sensitivity identified drug-TR pairs across independent datasets, including NFE2L3 and CBFB activity associated with sensitivity to mTOR inhibition, which we validated using a cohort of TNBC patient-derived xenografts. Collectively, we present methodology to promote TR-guided precision medicine that captures inter-tumor heterogeneity in TNBC and nominates drug sensitivities according to TR activity scores inferred from expression and chromatin accessibility data.

  Study EGAS50000001691

• scATAC-seq of CD4+ T cells from blood, lymph nodes and tumors of NSCLC patients

  This study explore the CD4+ T cells diversity in paired blood, lymph nodes and tumors of 2 different NSCLC patients. After FACS-sorted of Tregs (DAPI- CD45+ CD4+ CD25hi CD127lo) and Tconvs (DAPI- CD45+ CD4+CD25lo CD127lo/hi), cells were mixed in equal proportion (fifty/fifty ratio) and procesed with 10X Chromium (10X Genomics) scATAC kit and sequenced using Illumina platforms.

  Study EGAS50000000294

• Germline whole-genome sequencing (WGS) of colorectal cancer patients

  Whole-genome sequencing (WGS) data generated from matched germline blood DNA samples obtained from patients with primary or metastatic colorectal adenocarcinoma (n=37). These data were generated as part of a multiomic study integrating whole-genome sequencing with single-cell multiome profiling to investigate recurrent epigenetic alterations in colorectal cancer evolution and the tumour microenvironment.

  Dataset EGAD50000002942

• Whole Genome Sequencing (WGS) of Tumour Samples of Primary and Metastatic Colorectal Cancer

  WGS samples of primary (n=33) and metastatic (n=11) colorectal cancer tissues related to Livanova et al. manuscript 'Epigenetic evolution of colorectal cancer and its microenvironment reveals new vulnerabilities'

  Dataset EGAD50000002943

• Single-cell 10x Genomics Multiome ATAC-seq data from primary and metastatic colorectal cancers and normal colon tissues

  This dataset contains single-cell 10x Genomics Multiome ATAC-seq data from 33 primary colorectal cancer, 11 metastatic colorectal cancer, and 7 matched normal colon tissue samples generated as part of the study "Epigenetic evolution of colorectal cancer and its microenvironment reveals novel vulnerabilities."

  Dataset EGAD50000002944

• Single-cell 10x Genomics Multiome RNA-seq data from primary and metastatic colorectal cancers and normal colon tissues

  This dataset contains single-cell 10x Genomics Multiome RNA-seq data from 33 primary colorectal cancer, 11 metastatic colorectal cancer, and 7 matched normal colon tissue samples generated as part of the study "Epigenetic evolution of colorectal cancer and its microenvironment reveals novel vulnerabilities."

  Dataset EGAD50000002945

• Human breast cancer epigenetic sequencing data

  Controlled-access sequencing data generated from human breast tumor samples in the study "Epigenetic Heterogeneity in Breast Tumors with Implications for Disease Diagnosis and Monitoring". The dataset includes whole-genome DNA methylation sequencing, enzyme-mediated methylation sequencing of sorted tumor-cell populations, single-nucleus CUT&Tag, and single-cell RNA and chromatin-accessibility multiome sequencing. Raw sequencing data are provided as FASTQ files.

  Dataset EGAD50000002972

• Genetic Effects on the Skin Methylome in Healthy Older Twins

  Study EGAS00001007816

• Multi-omic data of subjects of FUSION study

  Finland-United States Investigation of NIDDM Genetics (FUSION) Study has sought to understand the genetic basis of type 2 diabetes (T2D) and diabetes-related traits including glucose, insulin, lipid levels, and obesity. We have performed extensive multi-omic characterization of the study subjects, including SNP array genotyping, whole genome/exome DNA sequencing of blood/tissue/iPSC cells generated from fibroblast, as well as RNAs. The study has provided crucial data for understanding molecular and cellular mechanisms of the disease-causing variants and their respective target genes. This set of data will be a valuable resource to the T2D community.

  Study EGAS00001008440

• VLAIO DenMark Project Data Access Committee

  The VLAIO DenMark Project Data Access Committee is responsible for reviewing and approving controlled-access requests for human genetic, immunological, omics, and associated phenotype data generated within the VLAIO O&O project HBC.2022.0988, titled “Use of multimodel omics technologies to study Dengue host response markers”. The project is a collaboration between Janssen Pharmaceutica NV, Universiteit Gent, and the Institute of Tropical Medicine Antwerp, covering dengue host-response data generated from human challenge, natural infection, and related biomarker studies. The DAC evaluates whether proposed data use is consistent with participant consent, applicable ethics approvals, data protection requirements, institutional policies, and the data access policy linked to the relevant EGA dataset. Access decisions should be made by the project representatives from Janssen, ITG, and UGent, including Ole Lagatie, Kevin Ariën, and Filip Van Nieuwerburgh. EGA will distribute controlled-access data only upon approval granted by this DAC.

  Dac EGAC50000001078

• Plasma Nucleosome Profiling Reports on Tumor Burden and Molecular Subtypes in Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is an aggressive malignancy with dismal prognosis and marked transcriptional heterogeneity that drives distinct therapeutic vulnerabilities. The clinical translation of these molecular insights is limited by limited access to tumor biopsies. Here, we apply chromatin immunoprecipitation of cell-free nucleosomes carrying active histone modifications followed by sequencing (cfChIP-seq) to 441 plasma samples from individuals with advanced SCLC, other neuroendocrine carcinomas (NEC), non-SCLC cancers, and healthy controls. cfChIP-seq faithfully captured the epigenetic and transcriptional landscape of tumor-derived cfDNA, including SCLC tissue/cell-of-origin signatures, and yielded a quantitative score of tumor fraction that tracked radiographic burden and prognosis. Integrating plasma cfChIP-seq with matched tumor transcriptomes (n = 73, including 41 time-matched pairs), we show that cfChIP-seq levels at promoters of lineage-defining transcription factors (ASCL1, NEUROD1, POU2F3, and ATOH1) correlate strongly with tumor RNA and support noninvasive inference of SCLC transcriptional subtypes directly from plasma. These findings establish cfChIP-seq as a practical liquid-biopsy platform that reports real-time tumor state and subtype, enabling precision monitoring and laying the groundwork for subtype-informed therapeutic stratification in SCLC.

  Study EGAS50000001916

• A functional genomic links differential sperm methylation from overweight men to transposable element regulation in paternal origins of disease risk in children

  The occurrence of childhood neurodevelopmental disorders has been steadily increasing for decades yet we have little understanding of modes of inheritance implicated in these diseases. Epidemiology studies have revealed an association between an elevated paternal BMI and an increased risk for neurodevelopmental disorders in children, suggesting non-genetic modes of inheritance may be involved. Epigenetic marks –like DNA methylation at cytosines– are especially susceptible to environmental, diet and lifestyle changes. Yet, whether a man’s weight influences the sperm methylome and potentially impacts offspring development remains unresolved. Using MethylC capture (MCC)-sequencing, we identified over 38000 differentially methylated CpG (DMCs) in the sperm of men with an elevated BMI, with many occurring in regions that were enriched for neural gene and disease ontologies. Differentially methylated regions (DMRs) were enriched at transposable elements that can act as active enhancers during human zygotic genome activation, and at gene promoters for early lineage specification. These results suggest that sperm methylome alterations that are linked to elevated BMI may influence key embryonic transcriptional process, notably associated with trophectoderm and placental development.

  Study EGAS50000001028

• Cell-free DNA methylation profiling in classic Hodgkin lymphoma using cfEM-seq

  Genome-wide DNA methylation profiling using cfEM-seq and Ultima Genomics sequencing in classic Hodgkin lymphoma. The study includes plasma-derived cell-free DNA from patients with classic Hodgkin lymphoma together with classic Hodgkin lymphoma and anaplastic large cell lymphoma cell lines. The deposited data comprise original sequencing CRAM files and associated sequencing-provider QC metadata.

  Study EGAS50000002038

• Alterations of whole genome and extrachromosomal circular cell-free DNA fragmentomes across the cancer care continuum

  The origins and properties of cancer-associated genetic changes in cell-free DNA (cfDNA) are not fully understood. Through genome-wide analyses of 1,807 samples from 1,064 patients across eight common cancer types, we identified extrachromosomal circular DNA (eccDNA) as a source of cfDNA fragments. Characterization of eccDNA-derived cfDNA fragments along with single base substitutions, small insertions and deletions, rearrangements, and phased variants in single cfDNA molecules, revealed differences between tumor tissues and cfDNA, with an increase in tumor-derived cfDNA alterations at epigenetically repressed regions and a decrease at active promoters. Combination of variant characteristics with individual error rates and machine learning analyses enabled tumor-informed and tumor-independent measures of circulating tumor DNA for early detection, detection of minimal residual disease, and for monitoring patients during therapy. The universal nature of eccDNA and other tumor-derived characteristics of cfDNA may be broadly useful for cancer detection.

  Study EGAS50000001331

• Cryptic mRNA Splicing in FLT3 Internal Tandem Duplications

  NGS analyses of genetic material from Acute Myeloid Leukemia cases harboring FLT3 Internal Tandem Duplications to investigate the occurrence of cryptic mRNA splicing.

  Study EGAS50000002156

• A nationwide prospective randomized trial for diagnosing developmental disorders demonstrates whole-genome sequencing outperforms whole-exome sequencing.

  Whole-exome (WES) or whole-genome (WGS) sequencing are recommended as first- or second-tier molecular tests for patients with developmental disorders (DD), but the clinical utility of WGS continues to be debated. This prospective randomized trial involving all Belgian Human Genetics centers compared the standard of care (SoC) - combining WES and microarray or shallow WGS - with WGS for 567 individuals with unexplained DD. The diagnostic yield of WGS was 39.8% (113/284) vs 30% for SoC (85/283) (p=0.015), mainly due to an increased detection of single nucleotide variants and indels (+8.7%). WGS also enabled the detection of three non-coding (potential) pathogenic variants. Diagnostic yield was higher for females (45.5%, 97/213) compared to males (28.5%, 101/354) (p<0.001). De novo variants were found for 23.6% of patients. Analysis of inherited variants in genes associated with autosomal dominant phenotypes contributed more to the diagnostic yield (3.9%) than X-linked variants (1.9%), and to a similar extent as autosomal recessive variants (4.1%). This nationwide study demonstrates WGS outperforms WES for the diagnosis of patients with DD in a decentralized hospital setting and well-characterized cohort. The results also highlight the importance of evaluating autosomal dominant inherited variants in genomics analyses for DD.

  Study EGAS50000002018

• Distinct immune and genomic signatures predict resistance to ibrutinib therapy in Waldenström macroglobulinemia

  In this study, we investigate the complex interplay between tumour-acquired genetic features and the composition of the microenvironment in the promotion of ibrutinib resistance in WM patients by integrating single-cell RNA sequencing (scRNAseq) and whole-genome sequencing (WGS), to examine bone marrow tumour and immune compartments from 37 symptomatic WM patients treated with ibrutinib.

  Study EGAS50000001586

• Characterization of cell types, positional codes, and enhancers contributing to human facial individuality and pathology

  Human genetic diversity generates an astonishing variety of facial shapes, and craniofacial anomalies rank among the most common birth defects. This study generated a multimodal atlas of human embryonic craniofacial development across embryonic weeks 6–11, including single-cell transcriptomics, chromatin accessibility, and spatial transcriptomics. The dataset characterizes cell states, mesenchymal subtypes, and their gene-enhancer cis-regulatory landscapes in space and time. These data provide a resource for studying normal human facial development, craniofacial abnormalities, and the genetic mechanisms underlying facial individuality.

  Study EGAS50000002001

• Cryptic mRNA Splicing in FLT3-ITD mutated Acute Myeloid Leukemia

  NGS analyses of genetic material from Acute Myeloid Leukemia cases harboring FLT3 Internal Tandem Duplications to investigate the occurrence of cryptic mRNA splicing. DNA extracted from diagnostic bone marrow sample was used for library preparation and then NGS was performed using Sophia DDMTM Myeloid Solution Panel, Thermofisher ION S5 Platform.

  Dataset EGAD50000003093

• BeSolveRD : a nationwide randomized trial comparing whole exome vs whole genome sequencing in developmental disorders

  Whole-exome (WES) and whole-genome (WGS) sequencing of 567 patients with developmental disorders for which a prospective randomized trial involving all Belgian Human Genetics centers was done to compare the standard of care - combining WES and microarray or shallow WGS - with WGS.

  Dataset EGAD50000002905

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an AND operator when a space is inserted between two words. Include OR (capitalised) between the keywords in your search in order to show pages containing either term or both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• 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? 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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. 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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