11951 results for "division 2 coins fc 26 Visit Buyfc26coins.com Kupiłem(a) duży pakiet monet FC 26 i dostałem(a) dodatkowy rabat. Świetnie!.fXzt"

in 27.49 milliseconds.

• Novel regional age-associated DNA methylation changes within human common disease-associated loci

  Background: Advancing age progressively impacts on risk and severity of chronic disease. It also modifies the epigenome, with changes in DNA methylation, due to both random drift and variation within specific functional loci. Results: In a discovery set of 2,238 peripheral-blood genome-wide DNA methylomes (MeDIP-seq) aged 19-82 years, we identified 71 age-associated Differentially Methylated Regions (a-DMRs, p < 1.85 x 10-8) within the Linkage Disequilibrium (LD) blocks of the NIH Catalogue of published GWAS SNPs. This included 52 novel regions, 29 within loci not covered by 450k or 27k Illumina array, and with marked enrichment for Poised Promoters and Enhancers across multiple cell types. In a replication set of 2,084 DNA methylomes, 95.7% of the a-DMRs showed the same direction of ageing effect, with 80.3% and 53.3% replicated to p < 0.05 and p < 1.85 x 10-8, respectively. Conclusion: By analysing the functionally enriched disease and trait-associated regions of the human genome, we identified novel epigenetic ageing changes, which could be useful biomarkers or provide mechanistic insights into age-related common diseases.

  Study EGAS00001001910

• Genome-wide cell-free DNA fragmentation in patients with cancer

  Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

  Study EGAS00001003611

• Germline mutations in the transcription factor IKZF5 cause thrombocytopenia.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4 T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Study EGAS00001003736

• RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

  Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

  Study EGAS00001000610

• Whole genome and transcriptome analysis of medullary thyroid cancer

  Medullary thyroid cancer is the neoplasm of the calcitonin-producing parafollicular cells of the thyroid gland. The hormone calcitonin acts to lower the blood calcium level, counteracting the effects of the parathyroid hormone; it can also serve as a biomarker for the presence or recurrence of medullary thyroid cancer. Surgery is the only curative treatment for this cancer. Targeted therapeutics vandetanib and cabozantinib are approved for the treatment of aggressive and metastatic tumors that are not amenable to surgery. The use of these multikinase inhibitors are supported by the observed overactivation of the RET oncoprotein in a large sub-population of medullary thyroid cancers; however, not all patients carry oncogenic alterations of this kinase. Hence, there is a need for molecular characterization of medullary tumors on the genomic scale with the aim of identifying targetable mutations. Here, we describe the genomic profiles of two medullary thyroid cancers and report the presence of a putative oncogenic BRAF fusion in one. Such alterations previously observed in other malignancies and known targets of available drugs, can benefit patients who currently have no therapy options.

  Study EGAS00001001473

• Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers

  Infiltration of human cancers by T cells is generally interpreted as a sign of immune recognition, and there is a growing effort to reactivate dysfunctional T cells at such tumor sites. However, these efforts only have value if the intratumoral T cell receptor (TCR) repertoire of such cells is intrinsically tumor-reactive, and this has not been established in an unbiased manner for most human cancers. To address this issue, we analyzed the intrinsic tumor-reactivity of the intratumoral TCR repertoire of CD8+ T cells in ovarian and colorectal cancer – two tumor types for which T cell infiltrates form a positive prognostic marker. Data obtained demonstrate that a capacity to recognize autologous tumor is limited to approximately 10% of intratumoral CD8+ T cells. Furthermore, in two out of four patient samples tested, no tumor-reactive TCRs were identified, despite infiltration of their tumors by T cells. These data indicate that the intrinsic capacity of intratumoral T cells to recognize adjacent tumor tissue can be rare and variable, and suggest that clinical efforts to reactivate intratumoral T cells will benefit from approaches that simultaneously increase the quality of the intratumoral TCR repertoire.

  Study EGAS00001003119

• UAMS Smoldering Myeloma Myeloma Sequencing

  Identifying high risk smoldering myeloma patients and progression mechanism is a prerequisite to implement effective inception strategies and curve myeloma related morbidity and mortality. We hypothesize that genomics may help identify determinants of progression that may help predict outcome and offer effective chemo preventive targets. Eighty-two patients underwent a custom targeted panel sequencing with an additional capture for the translocation loci. These results were compared to 223 newly diagnosed patients (EGAS00001003223 and EGAD00001004117) and 17 MGUS and 10 early myeloma patients. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads. Overall, these data highlight the importance of dysregulation of the MAPK pathway in the progression to MM.

  Study EGAS00001003629

• The proliferative history shapes the DNA methylome of B-cell tumor and predicts clinical outcome

  Here, we provide access to CLL and DLBCL DNA methylation and gene expression data in the context of a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. This approach showed that differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.

  Study EGAS00001004640

• Monitoring of leukemia clones in B-cell acute lymphoblastic leukemia at diagnosis and during treatment by single-cell DNA amplicon sequencing

  Acute lymphoblastic leukemia (ALL) is characterized by the presence of chromosomal changes, including numerical changes, translocations and deletions, which are often associated with additional single nucleotide mutations. In this study we used single-cell targeted DNA sequencing to determine the clonal heterogeneity of B-cell ALL at diagnosis and during chemotherapy treatment. With a customly designed DNA amplicon library targeting the most common mutations (in 110 genes) present in ALL, we analyzed bone marrow samples and/or blood samples from 12 B-ALL cases at diagnosis. For 4 cases where we detected multiple mutational clones at diagnosis, we also studied blood samples during the first weeks of chemotherapy treatment. This study shows that B-ALL cases with either a ETV6-RUNX1 or a BCR-ABL1 fusion have a low mutational burden, while cases with PAX5 alterations or hyperdyploidy have multiple clones at diagnosis, often with mutations in the JAK-STAT signaling pathway and the RAS signaling pathway. As expected, it can be observed that these clones disappear during treatment of the leukemia with almost no mutated cells left after two weeks of treatment.

  Study EGAS00001005029

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• Clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancers defined by genomic analysis

  Ductal Carcinoma In Situ (DCIS) is the most common form of pre-invasive breast cancer and despite treatment a small fraction (5-10%) of DCIS patients present with invasive disease many years later. A fundamental biologic question is whether the invasive disease recurring in the same breast is established by tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial pure DCIS lesion and paired invasive recurrent tumors in 95 patients together with single cell DNA sequencing in a subset of cases. Our data shows that in 75% the invasive recurrence was clonally related to the initial DCIS, suggesting that the tumor cells were not eliminated during the initial treatment with surgery +/- radiotherapy. Surprisingly however, 18% were clonally unrelated to the DCIS, representing new independent lineages, and 7% of cases were ambiguous. Our findings show that although DCIS is often the precursor of invasive recurrence, a significant fraction of invasive recurrences are unrelated to the initial DCIS. This knowledge is essential for accurate risk evaluation of DCIS treatment de-escalation strategies and the identification of predictive biomarkers.

  Study EGAS00001005784

• Clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancers defined by genomic analysis

  Ductal Carcinoma In Situ (DCIS) is the most common form of pre-invasive breast cancer and despite treatment a small fraction (5-10%) of DCIS patients present with invasive disease many years later. A fundamental biologic question is whether the invasive disease recurring in the same breast is established by tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial pure DCIS lesion and paired invasive recurrent tumors in 95 patients together with single cell DNA sequencing in a subset of cases. Our data shows that in 75% the invasive recurrence was clonally related to the initial DCIS, suggesting that the tumor cells were not eliminated during the initial treatment with surgery +/- radiotherapy. Surprisingly however, 18% were clonally unrelated to the DCIS, representing new independent lineages, and 7% of cases were ambiguous. Our findings show that although DCIS is often the precursor of invasive recurrence, a significant fraction of invasive recurrences are unrelated to the initial DCIS. This knowledge is essential for accurate risk evaluation of DCIS treatment de-escalation strategies and the identification of predictive biomarkers.

  Study EGAS00001006306

• PDAC organoid genomic heterogeneity

  The establishment of patient-derived pancreatic cancer organoid culture in recent years creates an exciting opportunity for researchers to perform a wide range of in vitro studies on a model that closely recapitulates the tumor. Among the outstanding questions in pancreatic cancer biology are the causes and consequences of genomic heterogeneity observed in the disease. However, to use pancreatic cancer organoids as a model to study genomic variations, we need to first understand the degree of genomic heterogeneity and its stability within organoids. Here, we used single-cell whole-genome sequencing to investigate the genomic heterogeneity of two independent pancreatic cancer organoids, as well as their genomic stability with extended culture. Clonal populations with similar copy number profiles were observed within the organoids, and the proportion of these clones was shifted with extended culture, suggesting the growth advantage of some clones. However, sub-clonal genomic heterogeneity was also observed within each clonal population, indicating the genomic instability of the pancreatic cancer cells themselves. Furthermore, our transcriptomic analysis also revealed a positive correlation between copy number alterations and gene expression regulation, suggesting the “gene dosage” effect of these copy number alterations that translates to gene expression regulation.

  Study EGAS00001006782

• DNA methylation landscape of prostate cancer

  Metastases from primary prostate cancers to rare locations, such as the brain, are becoming more common due to longer life expectancy thanks to improved treatments. Epigenetic dysregulation is a feature of primary prostate cancer, and distinct DNA methylation profiles are associated with the mutually exclusive SPOP mutant or TMPRSS2-ERG fusion genetic backgrounds. Using a cohort of 42 patients with prostate cancer brain metastases (PCBM), with matched primary samples available for 17 patients, we carried out DNA methylation analysis using Illumina EPIC array. We examined the epigenetic distinction between primary PCa and PCBM, the association between epigenetic alterations and mutational background, and particular epigenetic alterations that may be associated with PCBM in particular. Multiregion sampling of PCBM revealed epigenetic heterogeneity in metastases. We found aberrant methylation in PCBM is associated with mutational background, PRC2 complex activity and upregulation of EZH2, an effect that is particularly pronounced in SPOP mutant PCBM. While we detected a hypermethylator phenotype in PCBM, we also observed hypomethylation occurring at the promoters of genes involved in neuroactive ligand-receptor interactions or the calcium signalling pathway, such as GABRB3 and GRM5, a change not observed in non-brain prostate cancer metastases.

  Study EGAS00001006670

• Transgenerational transmission of reproductive and metabolic dysfunction in the male progeny of polycystic ovary syndrome

  The transgenerational maternal effects of PCOS in female progeny have been revealed. As there are evidence that a male equivalent of PCOS may exist, we asked whether sons born to mother with PCOS (PCOS-sons) transmit reproductive and metabolic phenotypes to their male progeny. Here, in a Swedish nationwide register-based cohort and a clinical case-control study from Chile we found that PCOS-sons are more often obese and dyslipidemic. Their serum miRNAs are found to potentially regulate PCOS-risk genes. Our prenatal androgenized PCOS-like mouse model with or without diet-induced obesity confirmed that reproductive and metabolic dysfunctions in F1 male offspring are passed down to F3. Small non-coding RNAs (sncRNAs) sequencing of F1-F3 sperm revealed distinct differentially expressed (DE) sncRNAs across generations in the androgenized, obese, and obese and androgenized lineages, respectively. Notably, common targets between transgenerational DEsncRNAs in mouse sperm and in PCOS-sons serum indicate similar effects of maternal hyperandrogenism. These findings strengthen the translational relevance highlighting a previously underappreciated risk of reproductive and metabolic dysfunction via the male germline transmission and potential molecular markers to study in future generations.

  Study EGAS00001007079

• Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

  Immunotherapy with chimeric antigen receptor T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify cancer specific exon targets, we analyze 1,532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We find 2,933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n=148) or the alternatively spliced isoform (n=9) level. Expression of selected alternatively spliced targets, including the EDB domain of fibronectin 1, and gene targets, such as COL11A1, are validated in pediatric patient derived xenograft tumors. We generate T cells expressing chimeric antigen receptors specific for the EDB domain or COL11A1 and demonstrate that these have antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

  Study EGAS00001007766

• H3Africa - Identification and characterization of novel hereditary neurological disease genes in Mali.

  Despite the vast diversity of its populations, genetic studies in Africa have been limited. African populations, Malians in particular, have a high rate of intra-ethnic and consanguineous marriage, resulting in increased prevalence of autosomal recessive diseases. Family-based genetic studies can be limited in developed countries due to small sibships. The average fertility rate in Mali is over 6 births per woman, offering a unique opportunity to find new disease genes or mutations that can then be studied in other populations. Hereditary neurological diseases are very debilitating diseases, and developing countries, particularly in Africa, pay a high price in terms of disability-adjusted life years. Although most are currently untreatable, increasing awareness about hereditary neurological disorders can reduce this burden. This study will help to identify and characterize novel hereditary neurological disease genes in Mali. These genes are likely to be important in the normal function of the nervous system and to have important pathophysiological implications for African and other populations. This study will also train physicians and students in the characterization of neurodegenerative diseases as well as in genetic technology and molecular biology, and build a suitable research environment that will retain them.

  Study EGAS00001003016

• Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response

  The study 'Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response' reports the genomic characterization at the single allele level upon Whole Exome Sequencing of Bladder Cancer (BLCa) Patient Tumor (PT) samples obtained from 18 patients and corresponding Patient Derived Organoids (PDOs), implementing the SPICE pipeline (Ciani Y et al). Our cohort included 21 PTs and 22 PDOs. In this study, we generated a unique biobank resource of BLCa organoids that encompasses a broad spectrum of disease stages. We demonstrated that PDOs retain cancer heterogeneity and mutational burden. Furthermore, we observed that BLCa PDO can have different morphologies which may reflect tumor-specific features. Indeed, a solid morphology may be associated with more advanced tumors, as supported by the high PDO genomic burden and high primary tumor stage. Moreover, with our drug screening pipeline, we demonstrated the clinical relevance and feasibility of using a BLCa PDO-based drug assay for comparing the standard of care (SOC) drugs with compounds not currently in use for BLCa. Response to SOC was highly heterogeneous with approximately 50% of non-muscle invasive bladder cancer and 33% of muscle invasive bladder cancer PDOs showing no or minimal response. The most effective targeted therapy was lapatinib. We used an integrative analysis of drug response profiles with matched PDO genomic analysis to determine enrichment thresholds for candidate markers of therapy resistance and sensitivity. Importantly, by assessing the clinical history of longitudinally sampled cases, the clonal evolution of the disease could be determined and matched with PDO drug response profiles.

  Study phs003149

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets. Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis. Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended. We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced. 

  Study phs002856

• A catalog of the genetic causes of Hereditary Angioedema in the Canary Islands (Spain)

  Hereditary angioedema (HAE) is a rare disease where known causes involve C1 inhibitor dysfunction or dysregulation of the kinin cascade. The updated HAE management guidelines recommend performing genetic tests to reach a precise diagnosis. Unfortunately, genetic tests are still uncommon in the diagnosis routine. Here, we characterized for the first time the genetic causes of HAE in affected families from the Canary Islands (Spain). Whole-exome sequencing data was obtained from 41 affected patients and unaffected relatives from 29 unrelated families identified in the archipelago. The Hereditary Angioedema Database Annotation (HADA) tool was used for pathogenicity classification and causal variant prioritization among the genes known to cause HAE. Manual reclassification of prioritized variants was used in those families lacking known causal variants. We detected a total of eight different variants causing HAE in this patient series, affecting essentially SERPING1 and F12 genes, one of them being a novel SERPING1 variant (c.686-12A>G) with a predicted splicing effect which was reclassified as likely pathogenic in one family. Altogether, the diagnostic yield by assessing previously reported causal genes and considering variant reclassifications according to the American College of Medical Genetics guidelines reached 66.7% (95% Confidence Interval [CI]: 30.1-91.0) in families with more than one affected member and 10.0% (95% CI: 1.8-33.1) among cases without family information for the disease. Despite the genetic causes of many patients remain to be identified, our results reinforce the need of genetic tests as first-tier diagnostic tool in this disease, as recommended by the international WAO/EAACI guidelines for the management of HAE.

  Study EGAS00001006547

• 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

• INCLUDE Data Hub: NDA GUIDs for Down Syndrome Research

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality of life for people with Down syndrome. The INCLUDE Project Data Coordinating Center (DCC) and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions. The INCLUDE Data Hub includes an innovative researcher data repository, a portal, and a cloud-based platform for data analysis. The portal provides access to de-identified demographics and clinical metadata, as well as multi-omics datasets, including whole genome sequences, transcriptomes, proteomes, and metabolomes. The INCLUDE Data Hub uses a 'registered access' model, whereby users can access the portal and associated data after agreeing to terms of use. From the Data Hub, users can also reach 'controlled access' data (e.g., whole genome sequences) only for those studies for which they have obtained approval by an NIH Data Access Committee through the corresponding dbGaP study. A thoughtful linkage strategy to identify duplicate participants across studies enables researchers to merge multiple datasets and data types to create richer datasets and reduce costly redundancies in large-scale data generation (e.g., -omics) while mitigating potential risks introduced by linkage.Based on recommendations from the NICHD Office of Data Science and Sharing, which completed a comprehensive assessment of existing Privacy Protecting Record Linkage (PPRL) and associated data governance solutions, the INCLUDE DCC and the associated NIH Steering Committee have implemented NIMH Data Archive Global Unique Identifiers (NDA GUIDs) in the INCLUDE Data Hub. The NDA GUID Tool is a government-owned and operated PPRL technology that enables researchers to link data from multiple sources to the same individual without revealing personally identifiable information (PII). With the NDA GUID Tool, the same participant information will return the same GUID whenever or wherever it is entered. The GUID itself is not personally identifiable information or protected health information. Sharing data with NDA GUIDs allows approved researchers to link together data on a single participant, even if the data were collected at different locations or through different studies or are distributed from different data repositories. This dbGaP study enables researchers to access an INCLUDE GUID Mapping File that includes all available NDA GUIDs and their associations to study-specific Participant IDs across studies in the INCLUDE Data Hub. This dbGaP study only distributes NDA GUIDs associated with the INCLUDE Data Hub datasets. To access the associated controlled-access datasets, add the corresponding dbGaP studies to your Data Access Request. A list of these studies is available on the INCLUDE Data Hub Portal: https://portal.includedcc.org/studies.

  Study phs003678

• A common single nucleotide variant in T is strongly associated with chordoma

  Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics.

  Dataset EGAD00001000226

• LCCC 1108: Development of a Tumor Molecular Analyses Program and Its Use to Support Treatment Decisions (UNCseqTM)

  The primary objective of this specimen correlative study was two-fold: to provide a mechanism for the association of known molecular alterations with clinical outcomes, and to provide rapid genetic profiling of alterations with known clinical utility using tumor and germline specimens to support treatment decisions.

  Study phs001713

• Osteosarcoma WGS on multiple tissue samples from six patients

  Osteosarcoma is a primary bone tumor that exhibits a complex genome characterized by gross chromosomal abnormalities. Osteosarcoma patients often develop metastatic disease, resulting in limited therapeutic options and poor survival rates. To gain knowledge on the mechanisms underlying osteosarcoma heterogeneity and metastatic process, it is important to obtain a detailed profile of the genomic alterations that accompany osteosarcoma progression. Therefore, in this study we performed WGS on multiple tissue samples from six patients with osteosarcoma, including the treatment naïve biopsy of the primary tumor, resection of the primary tumor after neoadjuvant chemotherapy, local recurrence and distant metastases.

  Dataset EGAD50000000475

• BELLINI clinical trial single-cell RNA-Seq and TCR data: cohorts A & B

  Single-cell RNA-Seq data and TCR sequencing data (both by 10X Genomics) of 51 TNBC primary tumors obtained from 29 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (16 patients, 28 samples) received nivolumab for 4 weeks, patients in cohort B (13 patients, 23 samples) received nivolumab + ipilimumab for 4 weeks. The included sequencing data was generated from frozen material for cohort A and from fresh material for cohort B.

  Dataset EGAD50000000807

• WES data from 438 tumor/germline samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 876 BAM files corresponding to the full WES dataset. Tumor and matched germline DNA were sequenced to a mean coverage of 132x (35x-338x) and 128x (31x-302x), respectively.

  Dataset EGAD50000000730

• Bulk TCRseq data from 149 patients with bladder cancer

  For this dataset we performed bulk TCRseq on tumor and serial blood samples from patients with muscle invasive bladder cancer (n patients = 119, n blood = 209, n tumor = 28) or non-muscle invasive bladder cancer (n patients = 30, n blood = 56, n tumor = 19) for a total of 149 patients and 312 samples. Each sample consists of a paired fastq file. Sequenced on the Ilumina NovaSeq6000 platform using SP and S1 flow cells (v1.5, 2x101 cycles), with a mean yield of 42 million reads covering the CDR3β region.

  Dataset EGAD50000001382

• Autosomal dominant macular dystrophy sequencing

  Inherited retinal dystrophies (IRD) are a group of rare diseases that cause a large disability rate. THRB (MIM*190160), located on 3p24.2, encodes the thyroid hormone receptor beta (TRβ). THRB mutations may be associated with human cone disorders, as this gene regulates the expression of red cone opsins. The aim of this work is to refine the ophthalmologic phenotype and describe a novel variant in THRB associated to IRD, thus confirming the role of this gene in tiopathogenesis of IRD.

  Dataset EGAD50000001255

• Single-cell RNA-Seq analysis of thymic ILC1 progenitors and NK cell differentiation This analysis involved a multiplexed sequencing run to study thymic innate lymphoid cells (ILCs) and NK progenitors. The generated data requires a demultiplexing file to separate and identify the individual sample tags for downstream analysis.

  This dataset contains multiplexed single-cell RNA sequencing (scRNA-seq) data from human thymic tissue, focusing on ILC1 progenitors and NK cell differentiation. The data were generated using the BD Rhapsody system and sequenced on the Illumina NovaSeq S4 platform. A demultiplexing file is required to assign sample identities.

  Dataset EGAD50000001157

• Prevalence and association of microsatellite instability and Lynch syndrome Pan-Cancer and development of a personalized cancer risk prediction tool for Lynch syndrome carriers in India

  The study aimed to systematically study MSI/ MMRd status in tumour DNA and germline mutations in mismatch repair (MMR) genes across a unique, large and heterogeneous group of commonly observed non-colorectal gastrointestinal and genitourinary tumours in the Indian population.

  Study EGAS50000001449

• Intractable Cancer Therapy Development through a New Target Identification by Molecular Profiling

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent / metastatic breast cancer, and the purpose of this study is to find the characteristics of recurrent / metastatic breast cancers by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000075

• RNA-Seq Profiles from the CheckMate-577 Clinical Trial

  The dataset contains RNAseq profiles of 386 patients from the CheckMate-577 (CA209-577) clinical trial whose ICF allows data deposition into a public repository. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNA was analyzed using the Illumina TruSeq RNA Access method for library preparation, followed by sequencing on the Illumina NovaSeq platform with a 50bp paired-end strategy and a target read depth of 50M per sample. Fastq files are included.

  Dataset EGAD50000002394

• VCF file from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by HPAH

  VCF file from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by hereditary pulmonary arterial hypertension (HPAH). Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). BAM files were processed at the CNAG (Barcelona) with their pipeline, including GATK v3.6 for genotyping and other tools such as snpEff for annotating variants, to produce this VCF file with a total of 9,643,070 variants, out of which 7,891,370 are SNVs.

  Dataset EGAD00001005758

• Whole genome sequencing

  This dataset contains whole genome sequencing data from 22 samples of FACS-purified bone marrow CD34+ haematopoietic stem and progenitor cells and matched hair follicle controls collected from individuals undergoing hip replacement surgery. Additionally, it contains whole genome sequencing data from unseparated bone marrow mononuclear cells, CD3-CD34- bone marrow mononuclear cells, and peripheral blood granulocytes of the same 14 samples. Haematopoietic samples were sequenced to a target coverage of 90-120x; 19 of them were re-sequenced to a total target coverage of 270x. Hair follicle controls were sequenced to a target coverage of 30x.

  Dataset EGAD00001015178

• National Institute on Aging - Late Onset Alzheimer's Disease Family Study: Genome-Wide Association Study for Susceptibility Loci

  Alzheimer disease is the most common neurodegenerative disorder of the elderly affecting an estimated five million Americans. Genetic factors contribute to the risk for disease with heritability estimates ranging from 57% to 79%. More than a decade ago, the ε4 variant of APOE was identified and remains the most consistently replicated genetic variant influencing the risk of late onset Alzheimer disease. A segregation analysis suggests there may be four additional genes influencing the age-at-onset of Alzheimer disease. In 2007 there were 968 association studies in 398 candidate genes reported, but none replicated consistently. There are many reasons for the lack of consistency, but one important reason for the lack of progress is the paucity of a sufficient number of well characterized families and patients available to the entire scientific community. The extensive effort and expense required to ascertain such a population has been addressed by the NIA-LOAD Family Study. Its goal is to identify and recruit families with two or more siblings with the late-onset form of Alzheimer's disease and a cohort of unrelated, non-demented controls similar in age and ethnic background, and to make the samples, the clinical and genotyping data and preliminary analyses available to qualified investigators world-wide. Genotyping by the Center for Inherited Disease Research (CIDR) was performed using the Illumina Infinium II assay protocol with hybridization to Illumina Human 610Quadv1_B Beadchips. This genotyping represents the largest collection of families ever assembled with Alzheimer's disease combining the NIA-LOAD Genetics Initiative Multiplex Family Study, the National Cell Repository for Alzheimer's Disease (NCRAD) with additional controls from the University of Kentucky. These genotyping results will serve as a focal point for future research that will identify all of the remaining genetic variants in Alzheimer's disease.

  Study phs000168

• Childhood Cancer Data Initiative (CCDI): Enhancement of Data Sharing in Pediatric, Adolescent and Young Adult Cancers

  NCI's Childhood Cancer Data Initiative (CCDI) is building a community centered around childhood cancer care and research data. Through enhanced data sharing, we can improve our understanding of cancer biology to improve preventive measures, treatment, quality of life, and survivorship, as well as ensure that researchers learn from every child with cancer. While childhood cancers represent the leading cause of death in children over the age of 1, they are collectively rare, comprising approximately 1%‒3% of cancers diagnosed annually in the United States. Information on diagnosis, treatment, and outcomes is often stored at the hospital or institution where a child is treated, making it difficult to answer scientific questions about childhood cancer. Sharing clinical care and research data generated by children's hospitals, clinics, or networks broadly with the community can help us learn faster and, on a scale much larger than any single institution caring for children can learn on its own. To exploit the rapid advances in high-throughput DNA sequencing technologies and realize the goals of precision cancer medicine, the UMICH Cancer Center established the Michigan Oncology Sequencing Center (MI-ONCOSEQ). This UMICH Cancer Center provisions genomic data derived from the Michigan Oncology Sequencing Center (MI-ONCOSEQ) clinical sequencing assay for patients that fall within the inclusion criteria of the CCDI data sharing initiative. An "integrative sequencing approach" carried out in a CLIA-certified laboratory is utilized to provide a comprehensive landscape of the genetic alterations in individual tumor specimens for the purpose of identifying informative and/or actionable mutations. Using a number of computational pipelines that we have developed in-house or have adapted from the public domain, candidate molecular aberrations are nominated and then analyzed by scientists for clinical significance and/or relevance. This approach enables the detection of point mutations, insertions/deletions, gene fusions and rearrangements, amplifications/deletions, and outlier expressed genes. Furthermore, we can identify certain germline alterations that may also be relevant.

  Study phs002431

• Structure and Diversity of Urinary Cell-Free DNA Informative of Host-Pathogen Interactions in Human Urinary Tract Infection

  The risk of acquiring urinary tract infection (UTI) is very high for patients who have received kidney transplants; nearly half will develop bacteriuria and an eighth viruria via BK polyomavirus in the first three years following transplantation. Current methodology for diagnosing viral and bacterial infections, while well practiced, is often limited in scope. The advent of next generation sequencing of cell-free DNA has shown promise in its ability to capture multiple perspectives of human health from discovering the origin of cell-free DNA in plasma; such a diagnostic has not been readily applied to urinary cell-free DNA. In this study, we selected 141 urine samples from a cohort of kidney transplant patients, which were collected and stored at Weill Cornell Medical College - New York Presbyterian Hospital. Of these samples, 43 samples were determined to be culture positive (> 10,000 CFU) for one or more bacterial species, including E. coli, Enterococcus, Klebsiella, Haemophilus, and Raoultella. A separate 23 samples were confirmed for BK virus nephropathy, with presence of BK polyomavirus confirmed via qPCR. We also included 29 samples from 14 patients who did not develop UTIs in the first three months following transplantation, and 11 samples that were negative for BK virus nephropathy. For a full description of samples, please see the Supplementary Data 1 in https://pubmed.ncbi.nlm.nih.gov/29925834/. From these urine samples, we aimed to capture and sequence urinary cell-free DNA using a single-stranded library preparation. In addition, we performed whole-genome bisulfite sequencing to 170 plasma samples collected from 27 hematopoietic cell transplant patients who developed graft-versus host disease and BK polyomavirus infection. We also performed Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) on 196 cell-free DNA (cfDNA) samples (154 plasma and 42 urine) collected from five groups of subjects. For a full description of samples, please see publications in PMID: 35864089 and PMID: 35058359.

  Study phs001564

• Genomic features of Helicobacter pylori-na��ve diffuse-type gastric cancer.

  Helicobacter pylori (HP) is a major etiologic driver of diffuse-type gastric cancer (DGC). However, improvements in hygiene have led to an increase in the prevalence of HP-na��ve DGC; that is, DGC that occurs independent of HP. Although multiple genomic cohort studies for gastric cancer have been conducted, including studies for DGC, distinctive genomic differences between HP-exposed and HP-na��ve DGC remain largely unknown. Here, we employed exome and RNA sequencing with immunohistochemical analyses to perform binary comparisons between 36 HP-exposed and 27 HP-na��ve DGCs from sporadic, early-stage, and intramucosal or submucosal tumor samples. Among the samples, 33 HP-exposed and 17 HP-na��ve samples had been preserved as fresh-frozen samples. HP infection status was determined using stringent criteria. HP-exposed DGCs exhibited an increased single nucleotide variant burden (HP- exposed DGCs; 1.97 [0.48���7.19] and HP-na��ve DGCs; 1.09 [0.38���3.68] per megabase; p=0.0003) and a higher prevalence of chromosome arm-level aneuploidies (p<0.0001). CDH1 was mutated at similar frequencies in both groups, whereas RHOA���ARHGAP pathway misregulation was exclusive to HP-exposed DGCs (p=0.0167). HP-exposed DGCs showed gains in chromosome arms 8p/8q (p<0.0001), 7p (p=0.0035) and 7q (p=0.0354), and losses in 16q (p=0.0167). Immunohistochemical analyses revealed a higher expression of intestinal markers such as CD10 (p<0.0001) and CDX2 (p=0.0002) and a lower expression of the gastric marker, MUC5AC (p=0.0305) among HP-exposed DGCs. HP-na��ve DGCs, on the other hand, had a purely gastric marker phenotype. This work reveals that HP-na��ve and HP-exposed DGCs develop along different molecular pathways, which provide a basis for early detection strategies in high incidence settings.

  Study JGAS000575

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• Genomic Landscape of Human Skin at a Single-Cell Resolution

  Every cell in the human body has a unique set of somatic mutations, yet it remains difficult to comprehensively genotype an individual cell. Here, we developed solutions to overcome this obstacle in the context of normal human skin, thus offering the first glimpse into the genomic landscapes of melanocytes at single-cell resolution. We comprehensively genotyped 133 melanocytes from 19 sites across 6 donors. As expected, sun-shielded melanocytes had fewer mutations than sun-exposed melanocytes. However, within sun-exposed sites, melanocytes on chronically sun-exposed skin (e.g. the face) displayed a lower mutation burden than melanocytes on intermittently sun-exposed skin (e.g. the back). Melanocytes from donors with a history of skin cancer had higher mutation burdens than melanocytes from donors without skin cancer, implying that the mutation burden of normal skin can be harnessed to measure cumulative sun damage and skin cancer risk. Moreover, melanocytes from healthy skin commonly harbor pathogenic mutations, likely explaining the origins of the melanomas that arise in the absence of a pre-existing nevus. Phylogenetic analyses identified groups of related melanocytes, suggesting that melanocytes spread throughout skin as fields of clonally related cells, invisible to the naked eye. Overall, our study offers an unprecedented view into the genomic landscapes of individual melanocytes, revealing key insights into the causes and origins of melanoma.

  Study phs001979

• Mid-pass Whole-genome Sequencing in a Malagasy Cohort Uncovers Body Composition Associations

  The majority of human genomic research studies have been conducted in European-ancestry cohorts, reducing the likelihood of detecting potentially novel and globally impactful findings. Here, we present mid-pass whole-genome sequencing data and a genome-wide association study in a cohort of 264 self-reported Malagasy individuals from three locations on the island of Madagascar. We describe genetic variation in this Malagasy cohort, providing insight into the shared and unique patterns of genetic variation across the island. We observe phenotypic variation by location, and find high rates of hypertension particularly in the Southern Highlands sampling site as well as elevated self-reported malaria prevalence in the West Coast site relative to other sites. After filtering to a subset of 214 minimally-related individuals, we find a number of genetic associations with body composition traits, including many variants that are only observed in African populations or populations with admixed African ancestry from the 1000 Genomes Project. This study highlights the importance of including diverse populations in genomic research for the potential to gain novel insights, even with small cohort sizes. This project was conducted in partnership and consultation with local stakeholders in Madagascar and serves as an example of genomic research that prioritizes community engagement and that has potential impacts on our understanding of human health and disease.

  Study EGAS50000000496

• A comprehensive DNA methylation landscape of human and mouse cell lines derived from hematological malignancies

  Human cancer cell lines constitute useful models to study the primary disease and many relevant findings in tumor biology have been originated from them since the first immortalized cell line (HeLa) was obtained. The easy experimental intervention, the purity of the transformed cells and their versatility to undergo high-throughput screenings represent advantageous features of the established cancer cell lines. In recent years, major efforts have characterized in detail the multiomics make-up of hundreds of cancer cell lines and studied their association with sensitivity to anticancer drugs. Most of these studies have been genetic-centric and have not characterized in detail the epigenetic profiles underlying the characteristics of these cells or their impact on the efficacy of antitumoral compounds. In this regard, a past version of a DNA methylation microarray or a less accessible and more time-consuming such as reduced representation bisulfite sequencing have been used in those attempts to interrogate the epigenetic setting. Herein, we have obtained the DNA methylation profiles of 210 cell lines derived from hematological malignancies utilizing comprehensive DNA methylation microarrays that interrogates more than 850,000 and 285,000 CpG sites from human and mouse genomes, respectively. Importantly, we also provide a pharmacoepigenetic example of the potential use of this resource by showing how DNA methylation can predict response to nucleoside analogues.

  Study EGAS50000000627

• DUX4 activates novel intergenic transcripts and isoforms in a tissue-specific context

  DUX4, a transcription factor driving zygotic genome activation during the embryonic cleavage stage in mammals, regulates the expression of genic and non-genic elements and modulates chromatin accessibility. Its misexpression in skeletal muscle causes Facioscapulohumeral muscular dystrophy (FSHD). The sporadic expression of DUX4 in FSHD muscle and the limitations of short-read RNA sequencing challenge, however, a comprehensive grasp of its consequences on the muscle transcriptome. Here, leveraging full-length isoform RNA sequencing with short-read RNA sequencing on DUX4-inducible myoblasts, we elucidated DUX4-induced transcriptomic changes within a myogenic context. DUX4 yields a complex transcriptome featuring numerous unannotated isoforms from known and novel loci. Moreover, we observed distinct isoform usage of DUX4 target genes between myogenic and embryonic cleavage states highlighting the distinct differences between DUX4 transcription factor activity in skeletal muscle and during the cleavage stage. We also identified ~1,400 unannotated intergenic isoforms predominantly originating from repetitive elements such as LTRs, LINEs, and SINEs. Integration with available datasets delineates the transcriptional and epigenetic landscape of these loci across myogenic and embryonic backgrounds. Like the cell type-specific isoform production, the usage of DUX4 binding sites at these intergenic loci is in part cell type-specific. Collectively, these findings demonstrate substantial and context-specific transcriptomic alterations induced by DUX4 further enriching our understanding of DUX4-induced muscle pathology.

  Study EGAS50000000503

• What is metadata?

  What is metadata? Data represents units of information and metadata can be seen, simply put, as data about other data. For example, in a simple experiment in which a patient genome was sequenced, there are multiple and diverse fields of metadata: from the biological sex of the patient to the sequencing platform used. Another way to understand metadata, following our genomic experiment example, is going through the different layers of (meta)data: One of the basic units of information (data) would be the sequence of nucleotides (e.g. GCTGG and GCCGG). This DNA sequence can be contextualised within a chromosome by providing its locus (e.g. β-globin gene). This data, the locus, is about other data, the sequence of nucleotides, which would render it metadata. We can go one step further, and provide more context, by giving the associated phenotype of each of these sequences: GCTGG corresponds to a healthy individual, while GCCGG corresponds to a person with β-thalassaemia. Once again, this data is contextualising the data we have provided up to this point, which makes it metadata. With this simple example, what we are doing is adding layers of data that describe the ones below. Had we given the sequences alone, little would be possible from the researchers' point of view. But, now that the data has its accompanying metadata, a researcher could compare both sequences and their phenotypes to infer a possible cause of the disorder. Each layer of information broadens the possible applications of the data. Now that we know what metadata is, it is time to emphasise the importance of submitting good quality metadata. The quality of the metadata will determine whether the data is usable, discoverable, and interpretable by researchers and clinicians. One example that highlights the importance of good quality metadata is the description of biological sex of a patient: while the terms "female," "girl," or "woman" all represent the same concept, they are not harmonised. These different representations of a concept can create confusion and errors in data analysis. By applying standard definitions and terminologies to biological sex metadata, we can avoid misunderstandings and facilitate the integration of different datasets.  In order to comply with the FAIR principles and, more specifically, to allow for the (meta)data to be interoperable (i.e. used universally and unambiguously), we need to place some standards onto the (meta)data EGA  archives. These can be as simple as asserting that the given patient's biological sex is one of the correct terms (e.g. female or male); or as complex as multiple layers and combinations of validation steps with existing records. You can find further details on how EGA manages these standards on our metadata model page.

  Documentation submission/metadata/what-is-metadata

• A Cancer Cell-Line Titration Series for Evaluating Somatic Classification

  Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300x. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1,500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. Our cell-line titration series dataset, along with the associated verification results, is effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development.

  Study EGAS00001001016

• Double mutant DNMT3A AML: a unique subtype

  Mutation of DNMT3A, encoding a de novo methyltransferase essential for cytosine methylation, is a common early event in clonal hematopoiesis (CH) and adult acute myeloid leukemia (AML). Spontaneous deamination of methylated cytosines damages DNA, which is repaired by the base excision repair (BER) enzymes MBD4 and TDG. Congenital MBD4-deficiency has been linked to early-onset CH and AML, and is marked by exceedingly high levels of DNA damage and mutation of DNMT3A. Strikingly, wildtype (WT) DNMT3A binds TDG, thereby potentiating its repair activity. Since TDG is the only remaining BER enzyme in MBD4-deficient AML patients capable of repairing methylation damage, we investigated whether mutant DNMT3A negatively affects the repair function of TDG. We found that, whereas WT DNMT3A stimulates TDG function, mutant DNMT3A impairs TDG-mediated repair of DNA damage in vitro. In light of this finding and to extrapolate our observations to the broader AML patient population, we investigate here the genetic profiles and survival outcomes of AML patients with single (SM) versus double mutant (DM) DNMT3A. DM DNMT3A AML patients show a characteristic driver mutation landscape and reduced overall survival when compared to SM DNMT3A AML patients. Importantly, whole-genome sequencing showed a trend for increased DNA damage in primary DM DNMT3A AML samples, especially when DNMT3A mutations are located at the DNMT3A-TDG interaction interface.

  Study EGAS00001007966

• Effects of interferon-gamma treatment on human small intestinal organoids generated from healthy donors

  The intestine is vulnerable to interferon-gamma as intestinal epithelial stem cells undergo cell death when exposed to interferon-gamma. Here, we developed a novel human intestinal organoid-based 3D model system to study the effects of interferon-gamma-induced intestinal epithelial damage at the RNA level. We treated organoids with 10 ng/mL for either 6 or 18h. Knowledge generated with this dataset is relevant for a variaty of intestinal pathologies with an immune component, for instance graft-versus-host disease.

  Study EGAS50000000083

• SARS-CoV2 mRNA-vaccination-induced Immunological Memory in Human Non-Lymphoid and Lymphoid Tissues

  SARS-CoV2 mRNA vaccination-induced CD4+ Th cells were isolated based on activation marker expression from human bone marrow (n=3), lung (n=5), liver (n=4) and paired blood samples (to liver donors, n=4) of virus-naive vaccinees after Spike peptide mix stimulation in vitro. The 10X platform was used for single cell transcriptome analysis, along with T cell receptor clonotype analysis in a total of 1985 cells. Samples were sequenced on a NovaSeq 6000 (Illumina).

  Study EGAS50000000045

• International Multi-Center ADHD Gene Project (IMAGE) II Case Sample

  This sample represents a collection of cases across a range of sites. All of these samples were ascertained for ADHD with most meeting criteria for combined type ADHD. The collection sites span Europe and America. Further details on the source and inclusion and exclusion information can be found in Neale et al. "Case-Control Genome-Wide Association of Attention-Deficit / Hyperactivity Disorder" J Am Acad Child Adolesc Psychiatry. 2010 September; 49(9): 906-920 PMID20732627. For online access to this manuscript see: PMC2928577.

  Study phs000407