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• CD49f single-cell methylomes

  Single-cell DNA methylation has emerged as a powerful tool to study molecular heterogeneity within cellular populations. We report the development of a bisulfite based whole genome protocol suitable for use on single index sorted primary mammalian cells. Application of this protocol to human hematopoietic stem cells provided quantitative DNA methylation measurements of up to 5.7 million CpGs in a single cell. Analysis of cis CpG methylation states in single cells revealed a loss of concordance beyond 2kb, which supported the development of a new analytical framework (PDclust) for single-cell DNA methylation datasets that considers heterogeneity of methylation states at single CpG resolution. PDclust identified epigenetically distinct subpopulations within highly purified and functionally defined human stem cell populations. In silico merging of the methylation states from the single cells allowed us to ascribe function to these epigenetically distinct subpopulations on the basis of their epigenetic states.

  Study EGAS00001002789

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

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

  Study EGAS00001003600

• ALK_inhibitors_in_the_context_of_ALK_dependent_cancer_cell_lines

  Anaplastic lymphoma kinase (ALK) has recently been found to be a critical cancer gene in cases of lung cancer, neuroblastomas and lymphomas. ALK inhibitors have recently shown significant activity in lung cancer patients with tumours that harbour the EML4-ALK gene rearrangement, but already drug-resistance is emerging. We have taken a lung cancer cell line H3122 (with the EML4-ALK rearrangement) and generated clones resistant to a small molecule inhibitor of ALK by serial exposure to the drug over 8 weeks. We now wish to characterise at the exome level whether the acquisiton of resistance has been accompanied by the development of new mutations that we can take forward for further study as the potential mechansims underlying the resistance. We therefore propose to exome sequence the parental NCI-H3122 cell line as well as drug-resistant clones.

  Study EGAS00001000082

• Acquisition_of_additional_mutations_drives_accelerated_progression_of_NPM1_positive_CMML_to_AML_

  This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/We performed exome sequencing on serial samples from a patient with CMML who progressed to AML. The exome sequencing suggests that NPM1, TET2 and DNMT3a mutations were present in the dominant clone in the CMML sample and that NRAS is a new subclonal mutation in the AML sample. Diagnostic data shows the presence of a FLT3-ITD mutation in the AML sample, which is likely to have driven progression. Here we are performing re-sequencing of the putative driver and some passenger mutations which appear to be in the same clone to validate these mutations and to verify the relative quantification of these abnormalities .

  Study EGAS00001000619

• Glioblastoma initiating cells are sensitive to histone demethylase inhibition due to epigenetic deregulation

  Tumor-initiating cells are a subpopulation of cells that have self-renewal capacity to regenerate a tumor. Here, we identify stem cell-like chromatin features in human glioblastoma initiating cells (GICs) and link them to a loss of the repressive histone H3 lysine 9 trimethylation (H3K9me3) mark. Increasing H3K9me3 levels by histone demethylase inhibition led to cell death in GICs but not in their differentiated counterparts. The induction of apoptosis was accompanied by a loss of the activating H3 lysine 9 acetylation (H3K9ac) modification and accumulation of DNA damage and downregulation of DDR genes. Upon knockdown of histone demethylases KDM4C and KDM7A both differentiation and DNA damage was induced. Thus, the H3K9me3-H3K9ac equilibrium is crucial for GIC viability and represents a chromatin feature that can be exploited to specifically target this tumor subpopulation.

  Study EGAS00001003750

• The genomic and radiomic complexity of multifocal prostate cancer

  Multiparametric magnetic resonance imaging (mpMRI) and molecular prognostic tests are emerging to guide screening and prostate cancer (PCa) diagnosis, however their efficacy and cross validation requires further assessment in the context of intraprostatic heterogeneity and patient prognosis. To evaluate the molecular features that make prostate tumors visible to mpMRI, we established an mpMRI-blind multicore collection and performed low pass whole genome, exome, transcriptome and methylation profiling of 14 lesions and 23 representative cores from 6 PCa patients. Our results show that diagnosis based on mpMRI does not capture the genomic complexity of tumors, and reveal that commercial prognostic signature results based on single-biopsy assessments are insufficient to define risk of progression. Altogether, our study supports the use of a multi-biopsy assessment in both mpMRI visible and non-visible areas in order to provide a truly personalised diagnosis

  Study EGAS00001002767

• SudanMitoSeq: Sudanese mitochondrial sequencing

  In various contexts, mitochondrial function or dysfunction can be linked to mitochondrial genome variations. The use of mitochondrial genetics thus promises personalized diagnostics and treatments. In order to devise specific precision medicine approaches based on mitochondrial genetic variation and to test them within clinical studies, control data is indispensable. Such control data needs to comprehensively cover genetic variation commonly observed and thus expected. In the context of this study we assessed whether current, world-wide mitochondrial data sufficiently represents the region of North and East Africa, that is, whether current reference data is ready for precision medicine in this region. Towards this, we sequenced mitochondrial genomes of 159 Sudanese individuals provided as part of this EGA study and analyzed them together with various other, publicly available data concerning mitochondrial variation. For details, please refer to the publication.

  Study EGAS00001005669

• Human breast transcriptome analysis

  Obesity is a risk factor for the development of post-menopausal breast cancer and is associated with a worse breast cancer prognosis. Here we carried out transcriptome profiling on nontumorous breast tissue to define the molecular changes that occur related to excess body fat and adipose inflammation. A second goal was to determine if blood biomarkers reflect molecular changes in the breast. Increases in a variety of pathways linked to tumor development and progression were found. Moreover, increased expression of several drug targets including aromatase, the rate-limiting enzyme for estrogen biosynthesis, and PD-1 was observed. Various blood biomarkers that are associated with either elevated risk of breast cancer or worse prognosis were altered and correlated with molecular changes in the breast. Collectively, this study helps to explain both the link between obesity and breast cancer and the utility of blood biomarkers for determining risk and prognosis.

  Study EGAS00001004665

• 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

• Impaired HLA Class I Antigen Processing and Presentation as a Mechanism of Acquired Resistance to Immune Checkpoint Inhibitors in Lung Cancer

  Mechanisms of acquired resistance to immune checkpoint inhibitors (ICIs) are poorly understood. The purpose of this study was to investigate whether alterations in genes encoding components of the HLA Class I antigen processing and presentation machinery or interferon signaling pathways play a role in acquired resistance to PD-1 or PD-L1 antagonistic antibodies. Whole exome sequencing was performed on tumor samples collected from patients with advanced non-small cell lung cancer at the time of resistance to PD-1 axis inhibitors and on available matched pre-treatment and normal samples. Patient-derived xenografts successfully established from the ICI-resistant samples were also exome sequenced. Additionally, RNA sequencing was performed on cases with sufficient tissue.

  Study phs001464