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• Reference Standards for Mosaic Variant Detection

  After conception, postzygotic mutations continuously occur throughout life in humans, causing somatic mosaicism in an individual. The variant type, time of origination, and locations of the mosaic mutations result in unique mosaic patterns in a combinatorial manner and further affect phenotypes, including various noncancerous diseases. Several efforts have, thus, been made to identify the mutational landscape and mechanisms underlying the mosaic mutations. From a technical aspect, the accurate detection of mutations is at the core of the mosaicism research, and the construction of a standard reference is a critical first step to serve as the basis for analytical validation and benchmarks for germline and somatic mutation detection. Furthermore, a reference standard for mosaic mutations is urgently needed to enable more advanced research.Herein, we generated robust, large-scale, and cell line mixture-based reference standards that contain abundant mosaic SNVs and INDELs along with wild-type sites and germ line variants. Moreover, the whole reference standard set mimics the cumulative aspect of mosaic variant acquisition in the early developmental stage through a progressive cell line mixing with confirmed genotypes. It can be used for optimizing the current use of mosaic variant detection strategies, as well as developing algorithms for future improvements.We previously generated an NCBI BioProject (PRJNA758606) to release much of these data. Only the data that are subject to authorized access constraints have been included in this submission to dbGaP. The two data sources are thus, complementary to each other.

  Study phs003399

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Study EGAS00001003661

• Platelet RNAseq data for SLFN14 K219N patients

  Pathogenic missense variants in SLFN14, which encodes an RNA endoribonuclease protein that regulates rRNA degradation, are known to cause inherited thrombocytopenia with impaired platelet aggregation and ATP secretion. Despite rather mild laboratory defects, these patients display an obvious bleeding phenotype. The function of SLFN14 in megakaryocyte (MK) and platelet biology is unknown. This study aims to characterize the platelet transcriptome in patients with a SLFN14 K219N variant and model the disease in the immortalized megakaryocyte cell line imMKCL. Total platelet RNA was sequenced for two patients and 19 healthy controls. Differential gene expression analysis yielded a total of 2999 and 2888 significantly (|log2FC|>1, FDR<0.05) up- and downregulated genes, respectively. Remarkably, these downregulated genes were not enriched for any biological pathway while upregulated genes were enriched for pathways involved in (mitochondrial) translation and transcription with a significant upregulation of 134 ribosomal protein genes (RPG). Heterozygous and homozygous SLFN14 K219N imMKCL showed a defect in MK differentiation that aggravated during cell passaging of undifferentiated cells and in proplatelet formation. SLFN14 defective platelets and MK showed signs of rRNA degradation while this was absent in undifferentiated imMKCL cells. Upregulation of RPG through increased mTOR signaling in SLFN14 K219N MK seems to be a compensatory response for rRNA degradation. Indeed, mTOR inhibition with rapamycin resulted in further enhanced rRNA degradation in SLFN14 K219N MK. Taken together, our study indicates dysregulation of mTOR-regulated ribosomal biogenesis as the disease mechanism for SLFN14-related thrombocytopenia.

  Study EGAS00001006339

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

  Study EGAS00001007573

• Preclinical Pediatric Molecular Analysis for Therapy Choice (MATCH)

  Purpose: Pediatric solid tumors arise from diverse tissues during development and exhibit a wide range of molecular, cellular and genetic features. This diversity, combined with the low incidence of pediatric cancer makes it increasingly difficult to personalize therapy for individual patients based on the unique features of their tumors. Therefore, well-credentialed preclinical models that capture the diversity and heterogeneity of pediatric solid tumors are essential for identifying molecular targeted therapeutics for precision medicine. Experimental Design: Here, we report 281 orthotopic patient derived xenografts (O-PDXs) from 224 patients representing 24 different types of pediatric solid tumors. We have performed genomic characterization of the O-PDXs and compared them to their corresponding patient tumors. To demonstrate the feasibility and utility of using such a diverse collection of O-PDXs in preclinical studies, we performed a preclinical pediatric precision medicine trial based on the NCI-COG Pediatric MATCH trial enrollment criteria. We also tested molecular targeted therapy for a novel oncogenic fusion recently reported in pediatric melanoma and precision drug delivery using nano-liposomal irinotecan. Results: In the preclinical match study, we identified one specific single agent response to LY3023414 in an osteosarcoma model with a TSC2 variant of unknown significance. Combinations of nano-liposomal irinotecan were effective in treating both Ewing sarcoma and rhabdomyosarcoma xenografts. Conclusion: Our studies demonstrate the value of large, well-credentialed preclinical models for future precision medicine in pediatric oncology using single agents, drug combinations and novel drug formulations.

  Study EGAS00001008011

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• Privacy Notice for the Account User

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

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

• Genome-Wide Approach to Measure Variant-Based Heritability of Drug Outcome Phenotypes

  Current pharmacogenetic approaches often use a few large-effect alleles to predict drug outcomes. However, many drug outcome phenotypes are determined by complex pathways that may be influenced by common single-nucleotide variants (SNVs) across the genome. We ascertained how much variation in drug response is explained by common SNVs for pharmacokinetic (drug levels) and pharmacodynamic phenotypes (highest creatinine) for 4 drugs: vancomycin, gentamicin, cyclosporine and tacrolimus.

  Study phs002506

• Cellular Heterogeneity in Early Human Development at Stage CS16

  In this study, we applied 10x Genomics Multiome assays for single-nucleus profiling of gene expression and chromatin accessibility simultaneously to a Carnegie stage 16 (37-42 days) specimen. These data can be used to identify and characterize diverse human cell types and annotate them with respect to marker genes, expression, and regulatory modules. These data comprise a rich resource for the exploration of human biology.

  Study phs003532

• RNA-seq following miR-130a knock-down (KD) in Flag-tag AML1-ETO Kasumi-1 cells

  We performed RNA-seq on Flag-tag AML1-ETO Kasumi-1 cells transduced with Control or miR-130a KD lentiviruses to identify differentially expressed genes. Kasumi-1 cells were transduced in 3 independent replicates for control and miR-130a KD samples with lentiviruses containing GFP reporter gene. GFP+ cells were sorted 3 days post-transduction and RNA was harvested for library preparation and sequencing.

  Study EGAS00001005866