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• CIDR Whole Exome Sequencing in Joubert Syndrome

  The purpose of this study is to identify new genetic causes of neurodevelopmental diseases (NDDs) in the Joubert syndrome (JS) spectrum. Joubert syndrome is a recessive disease characterized by cerebellar vermis hypoplasia. Our currently funded NINDS award entitled "Molecular characterization of Joubert syndrome" seeks to identify new genetic causes through a variety of molecular strategies. Although our previous strategies involved whole genome SNP-scans, followed by candidate gene sequencing to arrive at identification of new JS causes, we have recently moved to Whole Exome Sequencing (WES) as a highly efficient methodology that is optimized for recessive disease. In this pilot project, CIDR has sequenced DNA on probands from 20 inbred families with JS spectrum disorders in which known causes have been excluded, that have not previously undergone genome-wide SNP scans. These paired end reads will be subject to our established bioinformatics pipeline including HOMOZGYOSITY, SNP and INDEL callers in our lab to identify potentially deleterious sequence changes (PDSC). This is followed by analysis to include testing each PDSC for segregation in the whole pedigree, for occurrence in a ethnically-matched cohort, as well as a defined patient cohort patients, in order to validate new NDD genes.

  Study phs000382

• Integrated Analysis of Multimodal Single-Cell Data

  The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

  Study phs002315

• Genomics of Circulating Tumor Cells

  Comprehensive analyses of cancer genomes in clinical settings promise to inform prognoses and guide the deployment of precise cancer treatments. A major barrier, however, is the inaccessibility of adequate metastatic tissue for accurate genomic analysis in prostate and other cancers. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming multiple technical hurdles. Here, we report an integrated process to isolate, qualify, and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of over 99.995% of the territory accessible in bulk exome sequencing is possible in CTCs. We validated our sequencing process in two prostate cancer patients including one for whom we compared CTC-derived mutations to mutations found in a lymph node metastasis and nine cores of the primary tumor. 51 of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early trunk mutations and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

  Study phs000717

• Detecting and Subtyping Lung Cancer Through Analysis of Circulating Tumor DNA

  Small cell lung cancer (SCLC) is among the most aggressive tumors with poor clinical outcomes. Tumors are rarely resected, which is a major barrier to molecular profiling of tumor tissue; therefore, non-invasive approaches using circulating tumor DNA (ctDNA) from liquid biopsies are needed to help advance research and clinical care for patients with SCLC. We developed a targeted capture panel that profiles SCLC genes and transcriptional regulation sites, including transcription start sites (TSS) and transcription factor binding sites (TFBS). This is a single assay that detects genomic mutations and transcriptional regulation activity based on ctDNA fragment patterns reflecting epigenetic nucleosomal positions. We applied this assay to sequence patient-derived xenograft (PDX) and patient plasma samples. We also performed whole genome sequencing (WGS) for a subset of the PDX plasma samples to validate the capture data. We developed new algorithms to quantify activity of key SCLC marker genes of ASCL1, NEUROD1, POU2F3, and ATOH1 and to classify SCLC subtypes based on activity of these markers. Furthermore, we developed a model to classify SCLC from non-small cell lung cancer (NSCLC), which has potential important applications for monitoring transdifferentiation and tumor plasticity.

  Study phs003570

• CSER: Exome Sequencing in Diverse Populations in Colorado and Oregon/CHARM Cancer Health Assessments Reaching Many

  The CHARM (Cancer Health Assessment Reaching Many) study, part of the Clinical Sequencing Evidence-Generating Research (CS.ER2) effort, aimed to assess the utility of clinical exome sequencing and how it affects care in diverse populations. The study population included adults at risk for hereditary cancer syndromes. The primary objective was the implementation of a hereditary cancer risk assessment program in healthy 18-49 year-olds in primary care settings within a vertically integrated health delivery system (Kaiser Permanente) and a federal qualified health center (Denver Health). The investigators aimed to assess clinical exome sequencing implementation and interpretation, as well as tailored interactions for low health literacy including a contextualized consent process, and a modified approach to results disclosure and genetic counseling. The investigators were also assessing the clinical utility (healthcare utilization and adherence to recommended care) and personal utility of primary and additional results from clinical exome sequencing, and evaluate the ethical and policy implications of considering personal utility of genomic information decisions for health care coverage.Sequencing and analysis for CHARM was conducted at the Northwest Clinical Genomics Laboratory, University of Washington, Seattle (https://nwgc.gs.washington.edu/).

  Study phs002111

• Induction of fetal meiotic oocytes from embryonic stem cells in cynomolgus monkeys

  Human in vitro oogenesis provides a framework for clarifying the mechanism of human oogenesis. To create its benchmark, it is vital to promote in vitro oogenesis using a model physiologically close to humans. Here, we establish a foundation for in vitro oogenesis in cynomolgus (cy) monkeys: cy female embryonic stem cells harboring one active and one inactive X chromosome (Xa and Xi, respectively) differentiate robustly into primordial germ cell-like cells, which in xenogeneic reconstituted ovaries develop efficiently into oogonia and, remarkably, further into meiotic oocytes at the zygotene stage. This differentiation entails a comprehensive epigenetic reprogramming, including Xi reprogramming, yet, as partly observed in vivo, Xa and Xi remain epigenetically asymmetric with incomplete Xi reactivation. In humans and monkeys, the Xi epigenome in pluripotent stem cells functions as an Xi-reprogramming determinant. We further show that developmental-pathway over-activations with suboptimal up-regulation of relevant meiotic genes impede in vitro meiotic progression. Cy in vitro oogenesis exhibits critical homology with the human system, including with respect to bottlenecks, providing a salient model for advancing human in vitro oogenesis.

  Study JGAS000573

• Cryptic Relatedness in the Singapore Living Biobank Project

  The Singapore Living Biobank is a collection of healthy population-based Chinese and Malay individuals, for the purpose of phenotype recall study of high-impact variant carriers. These individuals are sampled from two studies: Multi-Ethnic Cohort (MEC), and the Singapore Health 2012 (SH2012). The MEC is a population-based cohort initiated in 2007 to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as diabetes and cardiovascular outcomes in the three ethnic groups (Chinese, Malays, and Indians). The SH2012 study is a population-based cross-sectional survey conducted in Singapore between 2012 and 2013, with over-sampling of Malays and Indians. Participants in MEC and SH2012 completed a similar set of questionnaire components, health examination, and biochemisty panels. Description of the MEC and SH2012 studies can be found at http://blog.nus.edu.sg/sphs/. We generated whole-exome sequencing data and Illumina OmniExpress array genotyping data for 1,299 Chinese and 1,229 Malays from the Singapore Living Biobank. This study includes a subset of 762 individuals that were found to be closely related (≤3rd degree), including 263 Chinese and 499 Malays.

  Study EGAS00001002619

• Development and first-in-human CAR T therapy targeting the pathognomonic MiT-fusion driven protein GPNMB

  Summary: CAR T therapy for solid tumors is constrained by the scarcity of safe, uniformly expressed cell-surface targets. Here we identify GPNMB, a MiT fusion-driven protein, as highly, homogeneously, and stably expressed in primary and relapsed translocation-positive alveolar soft part sarcoma (ASPS) and renal cell carcinoma (tRCC). We develop a GPNMB-directed CAR T cell product, GCAR1, which demonstrates potent activity against patient-matched cells, organoids and xenograft models. In a first-in-human treatment of two patients with relapsed/refractory, metastatic ASPS, GCAR1 is well tolerated and induces stable disease for up to 6 months, accompanied by resolution of many non-target lesions. GCAR1 T cells expand in peripheral blood as a polyclonal population and remain detectable for up to 6 months. Spatial transcriptomics identify multiple immunosuppressive niches adjacent to T cells infiltrating treatment-resistant lesions; biological PDL1 blockade or PD1 and TIGIT double knockout overcomes this resistance and shows synergistic activity with GCAR1 in xenograft models. Taken together, these data provide clinical proof-of-concept for treating solid tumors with CAR T cells targeting a surface antigen driven by an oncogenic gene fusion.

  Study EGAS50000001696

• Increased mutation accumulation during fetal development in Down syndrome

  Children with Down syndrome (DS) show a high incidence of leukemia, which is preceded by transient myeloproliferative disorder (TMD) in neonates. TMD is characterized by mutations in GATA1 that accumulate during fetal development, indicating that additional mutagenesis is required for leukemogenesis. Abnormalities in chromosome numbers can result in a mutator phenotype. However, it is unknown whether a trisomy of chromosome 21 (T21) results in enhanced mutation accumulation during human development. Here, we determined the mutational consequences of a constitutive T21 in DS fetuses compared to disomy 21 cells (D21) of D21 fetuses. We found that D21 fetal HPSCs had a higher somatic mutation rate compared to healthy adults HSPCs. Moreover, we observed an increase in somatic mutation load in T21 cells of DS fetuses, which was already apparent during the first cell divisions of embryogenesis. The mutation load could be explained by processes that are active during normal fetal development and were similar to those observed in TMD blast cells. Our study shows that T21 causes an increase in somatic load in fetal cells of DS fetuses, which may contribute to leukemia development early in life.

  Study EGAS00001003982

• Pan Prostate Cancer Group data

  The Pan Prostate Cancer Group intends to provide breakthrough advances from the analysis of a very large series of Whole Genome DNA data, contributed by many of the leading scientists and clinicians working in prostate cancer genomics generating Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The accumulated data, collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals, are presented in this series. This project will provide a global framework for the future analysis of even larger series of genomes as costs of DNA sequencing, storage, and sequence analysis decrease. In addition to these WGS data from different clinical categories, ethnicities, levels of aggressiveness, and disease managed by different treatments with information linked to long-term clinical follow up, we intend to add additional layers of data, including transcriptome and methylation data. The current data series focuses primarily on the analysis of WGS data. For further information, please refer to https://panprostate.org/, and The Pan Prostate Cancer Group Data Sharing Policy, EGAP00001003712.

  Study EGAS00001002876

• Study on the proliferation history of colorectal adenomas

  Mismatch repair (MMR) deficient colorectal adenomas are composed of transformed cells that descend from a common founder and progressively accumulate genomic alterations but their proliferation history is still largely unknown. Here we rebuilt the proliferation history of four MMR deficient colorectal adenomas from male individuals by deep sequencing the X chromosome and mapping the somatic mutations that were progressively acquired during tumor growth. We developed a novel method to call high and low frequency mutations, to cluster them according to their frequencies and rebuild the proliferation trees directly from these mutation clusters using a recursive algorithm. The trees of all four lesions were formed of a dominant subclone that coexisted with other genetically heterogeneous subpopulations of cells. Despite this similar hierarchical organization, however, the growth dynamics varied among and within tumors, likely depending on a combination of tumor-specific genetic and environmental factors. Our study provides insights into the biological properties of individual MMR deficient colorectal adenomas that may influence their growth and also the response to therapy. Extended to other solid tumors, our approach could inform on the mechanisms of cancer progression, thus providing insight into the best choice of cancer treatment methods.

  Study EGAS00001000883

• Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors

  Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of various cancers but its utility in renal cell cancer (RCC) has not been well established. A combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n=90) with various renal tumour subtypes, were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of ~33% for both cohorts. A highly sensitive personalised approach, applied to plasma and urine from select patients (n=22), improved detection to ~50%, including in patients with early stage and even benign lesions. A machine-learning based model, applied to untargeted data, predicted this detection, potentially offering a means of triaging patient samples for personalised analysis. We observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than a single tissue biopsy. Longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. These data highlight low ctDNA levels in RCC but indicate potential clinical utility provided improvement in isolation and detection approaches.

  Study EGAS00001003530

• Germline HAVCR2 mutations altering TIM-3 characterize subcutaneous panniculitis-like T-cell lymphomas with hemophagocytic lymphohistiocytic syndrome

  Sub-cutaneous panniculitis-like T-cell lymphomas (SPTCL), a non-Hodgkin lymphoma, can be associated with hemophagocytic lymphohistiocytosis (HLH), a life-threatening immune activation which adversely impacts survival1,2. T-cell-immunoglobulin mucin-3 (TIM-3) is a modulator of immune responses expressed on subgroups of T- and innate immune cells. We identify in ~60% of SPTCL cases germline, loss-of-function, missense variants in highly conserved residues of TIM-3, c.245A>G(p.Y82C) and c.291A>G(p.I97M), each with specific geographic distribution. Y82C-TIM-3 occurs on a potential founder chromosome in patients with East Asian and Polynesian ancestry, while I97M-TIM-3 occurs in Caucasians. Both variants induce protein misfolding and abrogate TIM-3’s plasma-membrane expression leading to persistent immune activation, increased production of inflammatory cytokines, including TNF-α and IL-1β, promoting HLH and SPTCL. Our findings highlight HLH/SPTCL as a new genetic entity and showcase TIM-3 mutations as the first causative genetic defect in SPTCL. While TIM-3-mutant HLH/SPTCL benefit from immunomodulation, therapeutic repression of the TIM-3 checkpoint may have adverse consequences.

  Study EGAS00001002765

• SINGLE_CELL_ANALYSIS_OF_IN_VITRO_ERYTHROPOIESIS

  We are developing a protocol to differentiate mouse and human induced pluripotent stem (IPS) and embryonic stem (ES) cells towards the haematopoietic pathway to generate erythrocytes in vitro. This system has many applications such as the study of the role of specific genes and human polymorphisms in infectious diseases such as malaria, as well as haematological diseases such as myelodysplastic syndrome. The nature of the in vitro differentiation process means that a heterogeneous population of cells is generated. In order to understand the types of cells produced with our protocol, we have performed a single cell analysis, which has the power to reveal the different populations of cells and their characteristics. For this, a cDNA library has been made that needs to be sequenced to obtain the gene expression profiles of the different cells. With this information we will be able to assess the quality of the differentiation protocol and improve it in order to produce better cells for the downstream applications.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/

  Study EGAS00001000764

• Defective T-cell expansion in RASGRP1 deficiency

  Inherited CTPS1- CD27- and CD70-deficiencies in humans have revealed key factors of T-lymphocyte expansion, that is a prerequisite for an efficient immunity to Epstein-Barr virus (EBV) infection. RASGRP1 is a T-lymphocyte specific nucleotide exchange factor known to activate the MAP kinases pathway. A deleterious homozygous mutation in RASGRP1 leading to the loss RASGRP1 expression was identified in two siblings who both developed a persistent EBV infection leading to Hodgkin lymphoma. RASGRP1-deficient T cells exhibited defective MAPK activation and impaired proliferation that was restored by expression of wild-type RASGRP1. Similar defects were observed in T cells from healthy individuals when RASGRP1 was downregulated. RASGRP1-deficient T cells also exhibited decreased CD27-dependent proliferation toward CD70-expressing EBV-transformed B cells, a crucial pathway required for expansion of antigen-specific T cells in anti-EBV immunity. Furthermore, RASGRP1-deficient T cells failed to upregulate CTPS1, an important enzyme required for DNA synthesis. These results show that RASGRP1 deficiency leads to susceptibility to EBV infection, and demonstrate the key role of RASGRP1 at the crossroad of pathways required for the expansion of activated T lymphocytes.

  Study EGAS00001002753

• The genomic basis of childhood T-lineage acute lymphoblastic leukemia

  T-lineage acute lymphoblastic leukemia (T-ALL) is a high-risk tumor that has eluded comprehensive genomic characterization, in part due to the high frequency of non-coding genomic alterations resulting in oncogenic dysregulation. Here we report integrated genome and transcriptome sequencing of T-ALL tumor and remission samples obtained from over 1300 uniformly treated children with T-ALL, coupled with epigenomic and single cell analysis of malignant and normal T cell precursors. Integrated analysis identified 15 subtypes with distinct genomic drivers, gene expression, developmental state and outcome. Integration with chromatin topology analyses enabled elucidation of multiple mechanisms of enhancer deregulation that involve enhancers and genes in a subtype-specific fashion. We show that the immunophenotypically-described, high-risk entity of early T-cell precursor ALL is superseded by a broader category of leukemias of variable immunophenotype with diverse genomic alterations of a core set of genes encoding regulators of hematopoietic stem cell development. Numerous genetic alterations and disease subtypes emerged as independent predictors of survival and treatment failure in univariable and multivariable outcome models. These findings provide a roadmap for the classification, risk stratification and mechanistic understanding of this disease.

  Study EGAS50000000016

• WNT-dependent interaction between inflammatory fibroblasts and FOLR2+ macrophages promotes fibrosis in chronic kidney disease

  Chronic kidney disease (CKD) is a public health problem driven by myofibroblast accumulation, leading to interstitial fibrosis. Heterogeneity is a recently recognised characteristics in kidney fibroblasts in CKD, but the role of different populations is still unclear. Here, we characterize a proinflammatory fibroblast population (named CXCL-iFibro), which corresponds to an early state of myofibroblast differentiation in CKD. By performing immunofluorescence studies and spatial transcriptomics analysis on 2 patients, we demonstrate that CXCL-iFibro co-localize with macrophages in the kidney and participate in their attraction, accumulation, and switch into FOLR2+ macrophages from early CKD stages on. In vitro, we cultured primary inflammatory fibroblasts that we characterized by using bulk RNAseq. We show that macrophages promote the switch of CXCL-iFibro into ECM-secreting myofibroblasts through a WNT/-catenin-dependent pathway, thereby suggesting a reciprocal crosstalk between these populations of fibroblasts and macrophages. Finally, the detection of CXCL-iFibro at early stages of CKD is predictive of poor patient prognosis, which shows that the CXCL-iFibro population is an early player in CKD progression and demonstrates the clinical relevance of our findings.

  Study EGAS50000000101

• Distinct immune cell infiltration patterns in PDAC exhibit divergent immune cell selection and immunosuppressive mechanisms

  Pancreatic ductal adenocarcinoma has a dismal prognosis. A comprehensive analysis of single-cell multi-omic data from matched tumour-infiltrated CD45+ cells and peripheral blood in 12 patients, and two published datasets, reveals a complex immune infiltrate. Patients have either a myeloid-enriched or adaptive-enriched tumour microenvironment. Lymphocyte enrichment is intrinsically linked with highly distinct B and T cell clonal selection, diversification, and differentiation. Using TCR data, we see the largest clonal expansions in CD8 effector memory, senescent cells, and highly activated regulatory T cells which are induced within the tumour from naïve cells. We identify pathways that potentially lead to a suppressive microenvironement, including targets of immunotherapy and checkpoints including TIGIT/PVR and SIRPA/CD47. PDAC patient tumors from the APACT clinical trial revealed that patients with myeloid enrichment had the shorter overall survival compared to those adaptive cell enrichment. We identify multiple therapeutic targets that should form the basis for rational design including boosting of B cell responses, targeting immunosuppressive macrophages, and specific Treg depletion approaches. The dataset is scRNA-seq data from PDAC patients.

  Study EGAS50000000726

• The molecular basis of T-PLL is an actionable perturbation of TCL1/ATM- and epigenetically instructed damage responses

  T-cell prolymphocytic leukemia (T-PLL) is a rare and poor-prognostic mature T-cell malignancy. To address its incomplete molecular concept, we integrated large-scale profiling data of alterations in gene expression, allelic copy number (CN), and nucleotide sequences in 111 well-characterized patients. Besides prominent signatures of T-cell activation and prevalent clonal variants, we also identified novel hot-spots for CN variability, fusion molecules, alternative transcripts, and progression-associated dynamics. The overall lesional spectrum of T-PLL is mainly annotated to axes of DNA damage responses, T-cell receptor/cytokine signaling, and histone modulation. We formulate a multi-dimensional model of T-PLL pathogenesis centered around a unique combination of TCL1 overexpression with damaging ATM aberrations as initiating core lesions. The effects imposed by TCL1 cooperate with compromised ATM towards a leukemogenic phenotype of impaired DNA damage processing. Dysfunctional ATM appears inefficient in alleviating elevated redox burdens and telomere attrition and in evoking a p53-dependent apoptotic response to genotoxic insults. As non-genotoxic strategies, synergistic combinations of p53 reactivators and deacetylase inhibitors reinstate such cell death execution.

  Study EGAS00001002744

• Cell-free DNA analysis reveals POLR1D-mediated resistance to bevacizumab in colorectal cancer

  Bevacizumab is an approved anti-angiogenic drug for patients with metastasized colorectal cancer (mCRC) targeting VEGF. The survival benefit of anti-VEGF therapy in mCRC patients is limited to a few months and acquired resistance mechanisms are greatly unknown. Using plasma DNA, we studied the evolution of tumor genomes in a cohort of patients with mCRC (n=150) and observed a recurrent focal amplification (8.7% of cases) on chromosome 13q12.2. Analysis of TCGA data (n=619) suggested an association with later stages, which we confirmed by longitudinal plasma analyses. We defined the minimally amplified region and studied the mechanistic consequences of copy number gain of the involved genes. The amplification of one gene, POLR1D, impacted cell proliferation, resulting in upregulation of VEGFA, an important regulator of angiogenesis which has been implicated in the resistance to bevacizumab. In several patients, we observed the emergence of this 13q12.2 amplicon under bevacizumab treatment, which was invariably associated with evolution of therapy resistance. Hence, we describe a novel resistance mechanism against a widely applied treatment in mCRC patients which will impact clinical management

  Study EGAS00001003791

• Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

  Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step towards clinical application of patient-tailored treatment regimens. Toward this goal, we have established a library of 139 gynecologic tumors including cervical, endometrial, and epithelial ovarian cancers (EOCs) and uterine sarcomas that were genomically and/or pharmacologically annotated and explored dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discovered lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identified TP53 mutation as a molecular determinant that elicit therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identified transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Together, our results demonstrate potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers.

  Study EGAS00001003556

• Massively parallel functional dissection of schizophrenia associated non-coding genetic variants

  Schizophrenia (SCZ) is a severe mental disorder affecting 1% of the world population. SCZ is characterized by an underlying genetic architecture that is highly polygenic. Genome wide association studies have identified thousands of genetic variants that are statistically linked to the disease. However, the translation of these associations into insights on the pathomechanisms has been challenging because the causal genetic variants, their molecular function, and their target genes remain largely unknown. To address these questions, we combined induced pluripotent stem cell technology with a massively parallel variant annotation pipeline (MVAP) to functionally characterize 35,000 SCZ associated non-coding genetic variants. This approach identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on the molecular level in a highly cell type and condition specific fashion. Subsequent multi-modal integration of epigenomic data combined with CRISPR screening in human neurons enabled us to systematically translate SCZ variant associations into target genes, biological processes, and ultimately alterations of neuronal physiology. These results provide a new high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulus dependent molecular processes modulated by SCZ genetic variation beyond statistical association.

  Study EGAS00001007542

• M116 Proteome Extracellular Vesicle Profiling

  For extracellular vesicles (ECV) extraction from plasma, 1M ammonium acetate was added to precipitate ECVs on ice for 45 min. Then, 100 mM ammonium acetate was added to the mixture, and ECVs were precipitated by centrifugation at 20,000g for 30 min. ECVs were washed with 50 mM ammonium bicarbonate (Sigma-Aldrich, Cat. 1066-33-7). Then, 600 µl of 1% ammonium deoxycholate (Sigma Aldrich, Cat. K2755-1MG) were added. The concentration of protein in each sample was measured using a bicinchoninic acid assay (BCA assay). Ammonium bicarbonate was used to dilute 500 µg of protein into a final volume of 500 µl. Next, dithiothreitol (Sigma-Aldrich, Cat. D9779) was added to obtain a final concentration of 20 mM, followed by iodoacetamide (Sigma-Aldrich, Cat. I6125) to a final concentration of 40 mM. Next, trypsin (Roche, Cat. RTRYP-RO) was added to the sample in a 1:25 protein ratio and incubated at 37°C overnight. Next day, formic acid (ThermoFisher Scientific, Cat. 28905) in a final concentration of 0.1% was added and extraction of proteins was done using Empore™ Solid Phase Extraction Cartridges (3M), following manufacturer’s instructions. The eluted samples were then centrifuged for 90 min. using a speed vacuum centrifuge (Thermo, RC1010), followed by snap freezing in liquid nitrogen. Then, the samples were kept in a freeze dryer (LyoDry Compact Benchtop, MechaTech) overnight. Next, the samples were reconstituted in 30 µl of 0.1% formic acid (FA) and an o-Phthaladehyde (Oparil) assay was performed to determine the concentration of each sample. After that, the sample was prepared in a concentration of 0.5 µg/µl using 0.1% FA and alcohol dehydrogenase (ADH). The samples were prepared in glass mass spectrometry vials for proteomic analysis using a Waters Synapt G2Si High-Definition Mass Spectrometry (Waters Corporation) operated by the MassLynx 4.1., 110 min. running time with 2 µl of an injection containing 1 µg of peptide. Quality controls were also run along with samples to guarantee consistency. Pooled quality controls were made from all samples, in which the samples were run at the beginning, middle and end of the mass spectrometry run. Samples were randomized before running the experiment. The proteomic data was then imported into Progenesis software 4.2 (Nonlinear Dynamic, UK) to identify and quantify peptides and proteins.

  Dataset EGAD50000001679

• Genome Diversity in Africa Project: Benin (2021-02-16)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics 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/ . This dataset contains all the data available for this study on 2021-02-16.

  Dataset EGAD00001006970

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

  Study phs003066

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): a Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study - for Samples Collected at Johns Hopkins

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI).The larger dataset for this study can be found in dbGaP study phs003066.

  Study phs003094

• STAT5 is a therapeutically targetable vulnerability in cutaneous T-cell lymphoma

  Cutaneous T-cell lymphomas represent a heterogeneous group of lymphoproliferative disorders characterized by the infiltration and expansion of mature malignant T-cells into the skin. The disease encompasses distinct variants such as mycosis fungoides a skin resident variant, in which the malignant cells are restricted to skin lesions, and leukemic variant sézary syndrome characterized by circulating malignant T-cells. Here we integrated shallow whole genome sequencing and whole exome sequencing, on samples from four sézary syndrome patients and two advanced mycosis fungoides patients with blood involvement, to characterize genetic alterations and assess their therapeutic actionability. We identified an elevated copy number of 17q, resulting in increased STAT5 expression and activation, as a key factor in the pathophysiology of the disease.

  Study EGAS00001004719

• Exome trios in patients with gastroschisis (2019-04-08)

  Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. 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/ . This dataset contains all the data available for this study on 2019-04-08.

  Dataset EGAD00001004942

• Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

  Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Study EGAS50000000679

• A Multiethnic Genome-wide Scan of Prostate Cancer

  Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

  Study phs000306

• Osteosarcoma_X10

  This is a continuation of the osteosarcoma work we have undertaken.

  Study EGAS00001002167

• Neuroblastoma sequencing data

  This study shares tumor and normal DNA for a patient with neuroblastoma

  Study EGAS00001005602

• Poly A transcriptom sequencing of mutifocal hepatocellular carcinoma

  Poly A transcriptome sequence of mutifocal hepatocelular carcinoma

  Dataset EGAD00001003231

• Whole-Genome Sequencing of a Healthy Aging Cohort.

  Whole-Genome Sequencing of a Healthy Aging Cohort.

  Dataset EGAD00001003941

• University of Utah Pelvic Organ Prolapse Disorder Study

  The overall purpose of this University of Utah Pelvic Organ Prolapse Disorder Study was to identify and localize predisposition genes contributing to pelvic organ prolapse (POP). POP cases recruited for this study were identified by one of three methods: high-risk POP pedigree cases, POP sister pairs, and surgically-treated POP cases reporting a family history of POP. High-risk POP pedigree cases were identified using the Utah Population Database (UPDB), a genealogy database of residents in Utah that has been linked to diagnostic ICD9 and CPT codes in medical records at the University of Utah and Intermountain Healthcare. We identified families with a significant excess number of POP cases compared to matched population rates and targeted these individuals for recruitment as well as any other POP cases in the family. POP sister pair cases were identified at the University of Utah Urogyncology clinic for women who had undergone POP surgery and also self-reported one or more sisters who were also surgically treated for POP. POP affection status of all sisters was confirmed either by physical examination or by chart review. Surgically treated-POP cases reporting a family history of POP were identified at the University of Utah Urogyncology clinic by self-report of a family history of POP. Efforts were made to recruit other affected family members and confirm affection status. To obtain DNA, subjects provided either a blood specimen or saliva. Medical records were reviewed by a urogynecologist and diagnostic information for pelvic organ prolapse and stress and overactive bladder were obtained. Collected DNA was genotyped and analyzed. To maintain confidentiality of the familial data, genetic data from only one subject per family has been submitted to dbGaP. Use of the University of Utah Pelvic Organ Prolapse Disorder Study data is limited to investigators studying pelvic floor disorders. These pelvic floor disorders include pelvic organ prolapse, urinary and anal incontinence, and other conditions related to weakening or injury to the muscles and connective tissue in the pelvis as a result of pelvic surgery, pregnancy, or vaginal delivery of a child. These data will be used only for research purposes related to pelvic floor disorders. They will not be used to determine the individual identity of any person or their relationship to another person or for research on non-disease traits.

  Study phs001439

• Target sequencing of a case of concurrent Langerhans Cell Histiocytosis and Acute Myeloid Leukemia

  We performed target sequensing of the bone marrow and lymph node samples to scrrening for driver mutations in a case of concurrent Langerhans Cell Histiocytosis and Acute Myeloid Leukemia.

  Study JGAS000558

• Whole-exome sequencing data from breast cancer recurrence, endometrial cancer, and colon tumor samples harboring a rare germline BARD1 variant

  This dataset comprises whole-exome sequencing data from tumor and matched blood samples of a patient with breast cancer recurrence and endometrial cancer carrying a germline BARD1 p.(Gly753Val) variant, as well as from the colon tumor of the proband's father

  Dataset EGAD50000002412

• Immunophenotype data for a subset of NSCLC cases in OAK

  The investigators would like to correlate NGS data from OAK to immunophenotype designation performed manually based on a panCK/CD8 immunohistochemistry stain for a subset of squamous cell carcinomas.

  Dataset EGAD50000001253

• RRBS data of 48 individuals of the Dutch Hunger Winter Families Study

  The dataset entails 48 RRBS libraries of 24 siblings. 24 individuals are conceived during the Dutch Famine, a severe 6 month famine at the end of World War 2. A same sex sibling was added as a control, allowing partial matching for (early) familial environment and genetics.

  Dataset EGAD00001000733

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441

• A prospective study identifies MisMatch Repair genes as candidate predisposing genes for uveal melanoma.

  Objective: The aim of this study is to identify new predisposing genes for uveal melanoma (UM), the most common intraocular malignancy in adults. Design: Prospective cohort study from Institut Curie. Participants: 381 unselected patients diagnosed with UM between July 2021 and February 2023 at Institut Curie. Methods: All patients received genetic counseling and consented to extended genetic testing. A panel of 122 genes was analyzed by targeted sequencing on germline DNA from these patients. Main outcomes measures: UM was diagnosed by ophthalmologists at Institut Curie, and a senior pathologist confirmed the diagnosis when tumor or biopsy was available. Classification of the germline genetic variants was performed according to the ACMG guidelines. Results: We identified at least one pathogenic variant (PV) in 79 patients. Among those variants, 20 were found in clinically relevant genes for the patient’s follow-up and genetic counseling. We found a significant enrichment of germline pathogenic variants in Mismatch Repair (MMR) MLH1, MSH2 and MSH6 genes in this UM cohort, suggesting that MMR germline alterations could predispose to UM. From this cohort, one tumor was available from a patient carrying a MLH1 germline mutation. The tumor was characterized by a monosomy 3, in line with a loss of heterozygosity (LOH) of MLH1, located on chromosome 3. Loss of expression of MLH1 and PMS2 was observed by immunohistochemistry, and MMR mutational signatures SBS6, ID1 and ID2 were identified from the whole genome sequencing of the tumor. These data suggest that MLH1 is implicated in the oncogenesis of this UM. Conclusions: This study is the largest prospective constitutional study performed on UM patients, and the first demonstrating that MMR germline alterations are significantly enriched among these patients. Further analyses will be needed to estimate the risk of developing UM for patients with Lynch syndrome

  Study EGAS50000000914

• Integrative analysis reveals a macrophage-predominant, immunosuppressive immune microenvironment and subtype-specific therapeutic vulnerabilities in advanced salivary gland cancer

  Background Salivary gland cancers (SGC) are rare and heterogeneous malignant tumors. Advanced SGC lack established treatment options and show poor response to immunotherapy. Here, an integrative multi-omics analysis in a large cohort of advanced SGC revealed insights into the tumor immune microenvironment (TIM) and distinct mechanisms of immune evasion. Methods A total of 104 patients with recurrent/metastatic SGC from the DKTK MASTER program were included in this study. Whole-exome or whole-genome sequencing and RNA-sequencing was performed on fresh frozen tumor tissue. The tumor immune microenvironment was analyzed using CIBERSORT deconvolution analysis and immune gene expression scores in bulk RNA-sequencing data. Single-nuclei sequencing and immunohistochemistry analyses were performed in selected samples. Results were validated in bulk RNA-sequencing data of a previously published independent dataset. Results Bulk transcriptome analysis revealed an immune-deserted TIM in the majority of advanced SGC samples. Immune exclusion was most prominent in adenoid cystic carcinoma (ACC) subgroup 1 exhibiting a downregulation of the antigen processing machinery. Only a small subset of advanced SGC, including few adenoid cystic carcinoma, exhibited T-cell inflammation, which was correlated with tumor mutational burden in Non-ACC samples. Subtype specific expression of immune checkpoints as well as cancer testis antigens were identified with prominent expression of VTCN1 in luminal cells within ACC. Single-cell RNA-sequencing and bulk RNA-seq deconvolution analysis validated immune cell exclusion and revealed a TIM that was dominated by M2 macrophages across SGC subtypes. Among evaluable patients treated with immune checkpoint inhibitors, a high T-cell to macrophage ratio was associated with clinical benefit. Conclusions These data support biomarker-based development of immune-checkpoint inhibition and the development of novel immune-checkpoint inhibitors and cellular therapies in SGC.

  Study EGAS50000000809

• Molecular Tumor Board to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer

  Purpose: Molecular profiling of cancer is increasingly common as part of routine care in oncology, and germline and somatic profiling may provide insights and actionable targets for men with metastatic prostate cancer. However, all reported cases are of deidentified individuals without full medical and genomic data available in the public domain. Patient and Methods: We present a case of whole genome tumor and germline sequencing in a patient with advanced prostate cancer, who has agreed to make his genomic and clinical data publicly available in an accompanying personal testimonial. Results: We describe an 84-year-old Caucasian male with a Gleason 10 oligometastastic hormone-sensitive prostate cancer. Whole-genome sequencing provided insights into his tumor’s underlying mutational processes and the development of an SPOP mutation. It also revealed an androgen-receptor dependency of his cancer which was reflected in his durable response to radiation and hormonal therapy. Potentially actionable genomic lesions in the tumor were identified through a personalized medicine approach for potential future therapy, but at the moment, he remains in remission, illustrating the hormonal sensitivity of his SPOP-driven prostate cancer. We also placed this patient in the context of a large prostate-cancer cohort from the PCAWG (Pan-cancer Analysis of Whole Genomes) group. In this comparison, the patient's cancer appears typical in terms of the number and type of somatic mutations, but it has a somewhat larger contribution from the mutational process associated with aging. Conclusion: We combined the expertise of medical oncology and genomics approaches to develop a molecular tumor board to integrate the care and study of this patient, who continues to have an outstanding response to his combined modality treatment. This identifiable case potentially helps overcome barriers to clinical and genomic data sharing.

  Study EGAS00001004648

• Exome Sequencing of Chordoma Cases

  Chordoma is a rare tumor that is believed to develop from notochord remnants. We previously identified germline duplication of the TBXT gene as a major susceptibility mechanism in several chordoma families. Currently, we are using whole exome sequencing to identify additional susceptibility genes in chordoma families without TBXT duplication as well as in sporadic cases.

  Study phs001280

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  This study evaluates integrated genomic models of response to immune checkpoint blockade for lung cancer patients. A computationally adjusted tumor mutation burden was combined with HLA class I genetic variation, mutational smoking signature and activating mutations in receptor tyrosine kinase genes to generate a prognostic classifier that outperforms tumor mutation burden.

  Study phs001940

• Epigenetic Moderators of Naltrexone Efficacy for Alcohol Use Disorder

  This study was a 16-week randomized controlled trial of oral naltrexone (50 mg daily) vs. placebo among adults with Alcohol Use Disorder. DNA was extracted from peripheral mononuclear cells isolated from a blood sample collected at baseline, prior to study medication ingestion. The Illumina MethylationEPIC BeadChip was subsequently used to analyze these extracted DNA samples.

  Study phs002424

• Family-Based Study on Ulcerative Colitis with Whole Exome Sequencing

  Genetic risk factors for ulcerative colitis are not well understood. We performed a family-based whole exome sequencing analysis to identify potential causal mutations. In the proband, we found a heterozygous de novo mutation in the gene HSPA1L. Our results indicate that the de novo mutation in HSPA1L is associated with ulcerative colitis.

  Study phs001251

• Exome Sequencing of Pleuropulmonary Blastoma

  Pleuropulmonary blastoma (PPB) is a rare, aggressive pediatric cancer arising from the lung or pleural cavity. In this study, we sequenced and analyzed the exomes of 15 PPB matched tumor and normal pairs. This study is part of a larger effort to characterize pediatric cancers as part of the Slim Initiative for Genomic Medicine (SIGMA) project.

  Study phs000543

• LungMAP: Molecular Atlas of Lung Development - Human Lung Tissue

  Mammalian fetal lung development is a complex biological process. Despite considerable progress, a comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. The purpose of this study as part of the LungMAP consortium (www.lungmap.net) is to understand the transcriptional changes in the process of mammalian lung development.

  Study phs001961

• RNA sequencing of genetically modified human iPSCs modeling patients with autism spectrum disorders (ASD)

  We generated two genetically modified iPSC lines. In each line, a single promoter variant identified in a patient with autism spectrum disorder (ASD) was introduced by using the CRISPR/Cas9 system. These mutant lines were analyzed by RNA-seq together with control lines to assess the impact of the introduced variant.

  Study JGAS000651

• Genomic evolution of pancreatic cancer at single-cell resolution

  This project assesses genomic evolution of pancreatic cancer using the Mission Bio Tapestri platform and Whole Exome Sequencing. The Mission Bio Tapestri platform is a single-cell DNA sequencing platform using a targeted gene panel to assess SNV/CNV. Several samples, including primary and metastatic tissue, were used to investigate changes at single-cell resolution.

  Study EGAS50000001351

• CAGEKID: Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001000083

• CAGEKID: Cancer Genomics of the Kidney - Targeted Sequencing

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001007004

• Comprehensive NGS Profiling to Enable Detection of ALK Gene Rearrangements and MET Amplifications in Non-Small Cell Lung Cancer

  We evaluate the analytical performance of the PGDx™ elio™ tissue complete assay, a 505 gene next-generation sequencing (NGS) tissue-based assay, that has now been FDA-cleared for use by physicians to help guide treatment decisions for cancer patients, using a NSCLC cohort of 38 patients.

  Study EGAS50000000010

• Ribosome_Profiling_of_Macrophages_during_Salmonella_Infection

  The aim of this study is to assess translational changes in macrophages over a time course of Salmonella infection. 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/

  Study EGAS00001001285

• Single-cell RNA-seq profiling of patient derived organoids

  The aim of this study was to profile developement of resistance to cancer treatments using organoids. Two patient derived colorectal cancer organoids were profiled using single cell RNAseq after treatment with a combination of different anticancer drugs. The organoids were profiled both after 4 weeks of treatment and after a drug holiday of 2 weeks.

  Study EGAS50000001025

• Evaluating potential drug candidates for the treament of Henamgiopericytoma on patient derived cell line models

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1. Potential drug candidates that could be repurposed for the treatment of SFT/HPC were screened.

  Study EGAS50000000027

• single nuclei multiomics (ATAC-RNA) of KOLF2.1J human induced pluripotent stem cells-derived differentiated dopaminergic neurons

  We processed nuclei from hIPSCs differentiated optimized protocols for generating dopaminergic neurons. Cells differentiated with a first iteration were RNA and ATAC-sequenced, to understand our protocol caveats to address for optimization. Cells differentiated with a second protocol and in vivo were RNA-sequenced to validate the identities of our cells.

  Study EGAS50000001418

• RNAseq and ATACseq on HGSC lines, pre- and post-treatment with an epigenetic drug

  This study looked to determine changes in gene expression and chromatin accessibility of five HGSC cell lines, following treatment with a novel epigenetic drug. The epigenetic drug, HKMTi-1-005, is a compound with dual activity against H3K27 and H3K9 methylation. The cell lines used were PEO1, PEO4, PEA2, OVCAR5, OVCAR8.

  Study EGAS50000000047

• Diagnostic yield and clinical utility of whole-exome sequencing in pediatric patients with rare and undiagnosed diseases in the Czech Republic

  In our single-center study, we have launched a pilot program for pediatric patients with undiagnosed diseases in the second-largest university hospital in the Czech Republic. WES was implemented as a first-line test after inclusion in the study as part of the diagnostic workflow.

  Study EGAS50000000442

• The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

  A surrogate marker based on the epigenome that captures these components in easily accessible epithelial tissue could potentially identify women at risk. The WID-BC-index identifies women with breast cancer based on a DNA methylation signature derived from cervical smear samples.

  Study EGAS00001005055

• Mutant_clone_mapping_in_normal_oesohagus_and_skin_2

  We will use targeted exome sequencing to examine normal appearing oesophageal epithelium and skin to determine the mutational burden. DNA will be extracted from epithelia of a defined size and we will overlay positional information from the epithelial pieces to give clone maps over a wide area. This will be done in both oesophageal epithelium and skin

  Study EGAS00001005659

• COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

  Through thorough exclusion criteria and deep phenotypic characterisation for a Madrid-based population we intend to find enrichment of gene mutations associated to severity. In addition we will look for statistically overrepresented annotation of particular phenotypes (a controlled vocabulary specifically developed for this project) that associate them to affected genes in our patient sample.

  Study EGAS00001005931

• Finding structural variation from the human skin fibroblast at the single-cell level

  Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their molecular consequences. We present a computational method, scNOVA, that integrates haplotype-resolved SV discovery with nucleosome occupancy analysis using Strand-seq, to functionally characterize SVs in single cells.

  Study EGAS00001006498

• Multiomics analyses of Parkinson's disease midbrains

  Understanding the key pathological mechanisms underlying Parkinson's Disease pathology is fundamental for the development of novel and more effective therapeutic strategies. In this study, post-mortem human midbrain tissue from a cohort of 13 PD patients and 10 controls was analyzed with a set of multi-omics technologies including small RNA sequencing, transcriptomics and proteomics profiling.

  Study EGAS00001004966

• PhIP-Seq data

  Inflammatory bowel diseases (IBD), e.g. Crohn’s disease (CD) and ulcerative colitis (UC), are chronic immune-mediated inflammatory diseases. A comprehensive overview of an IBD-specific antibody epitope repertoire is, however, lacking. We leveraged a high-throughput phage-displayed immunoprecipitation sequencing (PhIP-seq) workflow to identify antibodies against 344,000 antimicrobial, immune and food antigens in 497 IBD patients.

  Study EGAS00001007054

• Whole genome sequencing libraries from the study "Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study".

  Whole genome sequencing libraries from the study "Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study". These are libraries from 41 patients. Specifically: 15 transformed follicular lymphoma (TFL), 6 early progressers (PFL), and 20 non-early progressers (NPFL). For TFL and PFL patients, trios consisting of diagnostic (T1), transformed/progressed (T2) and a matching normal are available (n = 63 libaries in total). For NPFL patients, a tumor-normal pair are available (n = 40 libraries).

  Dataset EGAD00001002897

• Exome sequencing of matching primary tumor and venous tumor thrombus (VTT) renal cell carcinoma (RCC) samples

  We performed multiregion whole exome sequencing of a total of 37 samples from five consecutive patients (normal tissue, n=5; primary tumors, n=16; tumor thrombi, n=16) to >35-fold target coverage. Matching primary tumor and venous tumor thrombus samples were analyzed. Four patients had a clear cell RCC, one patient had a poorly differentiated type II papillary RCC (RCC-VTT-04). The latter patient had a friable thrombus, the others were of solid consistency.

  Dataset EGAD00001004887

• Whole Transcriptome Analysis + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the analysis of PBMCs' whole transcriptome and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011318

• Phase II Therapeutic Trial of Mexiletine in Non-Dystrophic Myotonia (IND #77,021)

  Non-dystrophic myotonias are a group of rare muscle disorders caused by abnormalities in different muscle cell membrane proteins. Patients experience delayed muscle relaxation that causes impaired physical activity, stiffness, and pain. Mexiletine has been shown to be beneficial for symptoms of myotonia in case reports of patients with non-dystrophic myotonia, however, current management of these patients primarily depends on individual practitioners' preference. This study is a placebo-controlled, double-blind, cross-over treatment trial using mexiletine in non-dystrophic myotonias. The results, if positive, will permit the identification of mexiletine as an effective therapy for myotonia, making it a first-line therapy for patients with non-dystrophic myotonia. The specific aim of this proposal is to perform a randomized, double-blind, placebo-controlled cross-over study to assess whether mexiletine improves both quantitative and qualitative measures of myotonia in patients with non-dystrophic myotonia. Given the rarity of non-dystrophic myotonia, large randomized controlled treatment trials in these disorders have not been feasible in the past. Primary Outcome Measure: Patient-assessed symptom: stiffness as measured by an Interactive Voice Response Diary (IVR). Secondary Outcome Measures: a) patient-assessed pain, weakness, and fatigue as measured by IVR; b) clinical myotonia assessment; c) quality of life as measured by INQoL, SF36; d) a quantitative measure of grip myotonia; e) measurement of CMAP after short and long exercise; f) grading of myotonia on needle EMG.

  Study phs001311

• National Cancer Institute (NCI) Genome-Wide Association Study (GWAS) of Renal Cell Carcinoma in African Americans

  The NCI GWAS of renal cell carcinoma (RCC) in African Americans was undertaken to provide insight into genetic loci affecting susceptibility to this malignancy in a racial group known to be at elevated risk. We genotyped 1,136,723 single-nucleotide polymorphisms (SNPs) among 255 cases and 375 controls of African ancestry from the NCI Kidney Cancer Study, and further investigated 16 SNPs in a replication set consisting of 140 cases and 543 controls from a case-control study conducted at the University of Texas MD Anderson Cancer Center. The variant rs10771279 located on 12p11, 77kb from a European-ancestry RCC risk marker, was associated with RCC risk in the GWAS (P=1.2 x 10-7) but did not replicate (P=0.99). The variant 7105934 on 11q13.3, previously associated with RCC in a GWAS using European-ancestry samples, was associated with risk in both studies [meta-analysis odds ratio (OR)=0.76, 95% confidence interval (CI)=0.64-0.91; P=0.0022]. The frequency of this allele was higher than that observed in the European-ancestry GWAS (0.56 and 0.07 respectively among controls). The rs7105934 association was stronger for clear cell RCC (ccRCC: OR=0.56; P=7.4 x 10-7) and absent for cases of other or unknown histology (OR=1.02; P=0.86). In conclusion, this study provides evidence that rs7105934 is a susceptibility locus for RCC, and clear-cell RCC in particular, among African Americans.

  Study phs000863

• QUANTitative Chest Computed Tomography UnMasking Emphysema Progression in Alpha-1 Antitrypsin Deficiency

  AAT deficiency is a genetic disorder associated with emphysema. Spirometry, the lung function test that measures how well the lungs exhale air, is used to diagnose and track the progression of emphysema. Some studies have suggested that forced expiratory volume in 1 second (FEV1) measurements, a type of spirometry test, may lack accuracy in detecting disease progression in cases of severe AAT deficiency. Another method, high resolution chest CT scans, may be more accurate at measuring the progression of emphysema. The purpose of this study is to determine if high resolution CT scans are better at detecting the progression of emphysema than lung function tests. Results from this study may lead to the development of a more accurate way to assess lung tissue loss and may improve the understanding of lung destruction in AAT deficiency. This study will last 4 years and will enroll people with AAT deficiency who have nearly normal lung function test results. Study visits, each lasting about 4 hours, will occur at baseline and months 6, 12, 18, 24, and 36. At each visit, participants will undergo lung function tests, a CT scan, blood collection, and a physical exam. Female participants will have urine collected for a pregnancy test. All participants will also complete questionnaires to assess health status and lung function. Study researchers will call participants every 2 months to collect information on lung disease symptoms and medication changes.

  Study phs000698

• Indexing Genes Impacted by Copy Number Variation in Developmental Disorders

  A challenge in clinical genomics is to predict whether copy number variation (CNV) affecting a gene or multiple genes will manifest as disease. Increasing recognition of gene dosage effects in neurodevelopmental disorders prompted us to develop a computational approach based on critical-exon (highly expressed in brain, highly conserved) examination for potential etiologic effects. Using a large CNV dataset, our updated analyses revealed significant (P < 1.64 x 10-15) enrichment of critical-exons within rare CNVs in cases compared to controls. Separately, we used a weighted gene co-expression network analysis (WGCNA) to construct an unbiased protein module from prenatal and adult tissues and found it significantly enriched for critical exons in prenatal (P < 1.15 x 10-50, OR = 2.11) and adult (P < 6.03 x 10-18, OR = 1.55) development. WGCNA yielded 1,206 proteins for which we prioritized the corresponding genes as likely to have a role in neurodevelopmental disorders. We compared the gene lists obtained from critical-exon and WGCNA analysis and found 438 candidate genes associated with CNVs annotated as pathogenic, or variants of uncertain significance (VOUS), from among 10,619 developmental delay cases. We identified genes containing CNVs previously considered to be VOUS, to be new candidate genes for neurodevelopmental disorders (GIT1, MVB12B and PPP1R9A) demonstrating the utility of this strategy to index the clinical effects of CNVs. Reprinted from Uddin et al, 2016, with permission from Scientific Reports.

  Study phs001154

• Whole genome and transcriptome sequencing of lung cancer patients and cell lines at Genentech

  Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

  Study phs000299

• Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

  Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

  Study phs001041

• Genome-Wide Association Study in Systemic Sclerosis

  The Scleroderma Family Registry and DNA Repository (Registry) was initially developed as a registry and bio-specimen repository of patients with systemic sclerosis (scleroderma), family members and unaffected healthy controls. A case-control design was later adopted due to the lack of availability of many parents in this adult-onset disease, which precluded a linkage approach. In addition to collecting demographic data, the registry included the collection of disease-pertinent, cross-sectional, clinical information from medical records of affected participants. Registry participants were >/= 18 years of age at enrollment. On the basis of medical record review, all cases were verified by the principal investigator to meet the eligibility criteria. 800+ blood samples from verified affected cases of European ancestry were selected for a Genome Wide Association Study (GWAS). These genetic data, as well as phenotypic data, are available in dbGaP. DNA, serum and plasma from Registry participants, which are currently being stored in the University of Texas Health Science Center - Houston, Scleroderma Registry Genetic Repository, are available for research purposes. However, not all of the 800+ registry participants who submitted a blood sample currently have DNA available due to depletion of some samples. In addition to including SNP data from the genome-wide (first study release) and immunochip (second study release) scan on the 800+ samples, the dbGaP database provides a set of data tables with phenotypic information collected from the participants in the registry.

  Study phs000357

• 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

• Targeted Linked-Read DNA-seq Analysis of Castration-Resistant Prostate Cancers

  Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, its efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. It is important to resolve the mechanisms of AR genomic rearrangements to develop new therapies and predictive biomarkers for PC. We developed a targeted linked-read DNA sequencing assay to interrogate alterations in AR and a panel of genes known to be amplified or mutated in CRPC. Linked-read DNA-sequencing libraries were generated using the 10X Genomics Chromium platform and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. This targeted linked-read DNA-seq assay was used to interrogate a set of 6 benchmarking samples harboring known AR gene rearrangements and other alterations in AR, as well a panel of 6 patient-derived xenograft CRPC tumors and 23 clinical CRPC tumors. In this cohort, we identified a subset of samples that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. The data that will be made available through dbGaP are raw FASTQ files.

  Study phs003343

• Center for Sub-Cellular Genomics

  A cell is a highly complex system with distributed molecular physiologies in structured sub-cellular compartments whose interplay with the nuclear genome determine the functional characteristics of the cell. A classic example of distributed genomic processes is found in neurons. Learning and memory require modulation of individual synapses through RNA localization, localized translation, and localized metabolites, such as those from dendritic mitochondria. Dendrites of neurons integrate distributed synaptic signals into both electrical and nuclear transcriptional response. Dysfunction of these distributed genomic functions in neurons can result in a broad spectrum of neuropsychiatric diseases such as bipolar and depressive disorders, autism, among others. The Center for Sub-Cellular Genomics' (CSG) mission is to develop new technologies to enable the dissection of complex genomic interactions within a single cell. New technologies include methods to target DNA and RNA sampling at sub-cellular resolution in live cells; high-throughput isolation and microfluidics chemistry for sub-cellular fractions; sub-cellular resolution mass-spectrometry; and computational tools for analysis of sub-cellular genomics data. The new technologies developed by CSG will enable the broader genomics community to associate sub-cellular processes to cell function and dysfunction. These technologies will be utilized in the center to generate a comprehensive atlas of genomic signatures of sub-cellular compartments in the mammalian neuron system. The technologies and neuron-focused data obtained here will be relevant to neurodegenerative and neuropsychiatric diseases including schizophrenia, depression, autism spectrum disorder, traumatic brain injury, and Alzheimer's.

  Study phs002120

• First datasets available in the Federated EGA Network

  In February 2024, a great milestone was reached for the human omics data community: the first datasets are now available in the Federated European Genome-phenome Archive (FEGA). These datasets - hosted by national nodes in Poland, Norway, and Sweden - are discoverable in the EGA portal and accessible according to national laws. These datasets include: From FEGA Poland - The Genomic Map Of Poland From FEGA Norway - CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling Also from FEGA Norway - Single cell transcriptomics in expanded Tregs of APS-1 patients From FEGA Sweden - A Combined Omics and Tissue Biobank for Paediatric Cancers The establishment of these datasets represents a significant step towards achieving the broader objectives of the FEGA; to facilitate the sharing of high-quality human genomic and phenotypic data across borders. “The value for users is twofold: it becomes easier to make data available securely compared to storing data locally, and data becomes easier to find for other researchers. The possibility of reuse improves the chances of both verifying scientific discoveries and reaching groundbreaking conclusions, of benefit to the research community and later also patients,” said Anna Hagwall, project manager and head of human data at FEGA Sweden, NBIS. About Federated EGA FEGA was launched in 2022 as a network to store and lawfully share sensitive human omics data safely. It relies on the technology originally developed by the EGA and support from ongoing collaborations with ELIXIR - a European life sciences infrastructure. FEGA has contributed to and benefitted from the implementation of community standards for sensitive data management including those developed by the Global Alliance for Genomics and Health (GA4GH). “The FEGA concept and the development of the Nordic FEGA nodes have been made possible thanks to several projects coordinated by NeIC,” said Kjell Petersen, FEGA Norway technical lead. Managing human omics data is challenging due to its sheer size and privacy concerns, often resulting in restrictions on how and where sensitive data can be shared. The FEGA network follows a federated data access model whereby sensitive data is stored securely within a local or national jurisdiction, while discovery across the network for data of interest is enabled via a central portal. As of February 2024, the FEGA network comprises seven European national nodes with tens of additional national partners working towards establishing a FEGA node. As the FEGA network continues to onboard nodes from around the world, populated with more and more data, we move closer to a vision of a truly global resource for discovery of and access to sensitive human omics data to accelerate disease research and improve human health. "The Federated EGA network is entering a key phase where the first research datasets are now available across the network. In coming years, we look forward to expanding these datasets to cover key areas such as cancer and rare diseases for the benefit of patients" said Thomas Keane, Group Leader at EMBL-EBI.

  Blog first-datasets-available-in-Federated-EGA

• The circulating cell-free DNA landscape in sepsis is dominated by impaired liver clearance

  Circulating cell-free DNA (cfDNA) is a promising molecular biomarker. However, its utility in severe infection remains poorly understood. Here, we isolated cfDNA from sepsis patients and controls, demonstrating a 41-fold increase in the amount of cfDNA in circulation during disease. We used sequencing to reconstruct cfDNA methylomes, fragmentation profiles, and nucleosome footprints across 58 samples. We observed no difference in cfDNA composition between patients and controls, challenging the idea that cfDNA increases due to higher immune cell death during sepsis. Instead, we suggest that liver dysfunction prevents efficient clearance of cfDNA during disease. This was supported by fragmentation and end-motif patterns, both of which showed evidence of cfDNA being exposed to circulating nucleases for a prolonged period, proportionally to the extent of liver dysfunction. Variation in cfDNA of megakaryocyte-erythroid progenitor origin was also a significant contributor in sepsis, increasing over time. Moreover, we showed that cfDNA retains nucleosome footprints with cell type-specific gene activity information. We developed a novel approach to study nucleosome phasing that successfully recovers tissue-specific signatures. By combining this with single-cell data, we demonstrated that sepsis patients with liver dysfunction have higher amounts of cfDNA derived from Kupffer cells and the liver parenchyma. In conclusion, we present the first high-throughput multi-modal study of cfDNA during sepsis, which will serve as a reference point for future studies on the role of this biomarker in critical illness.

  Study EGAS50000001033

• Whole exome sequencing of an invasive diffuse intrinsic pontine glioma sampled from different sites

  The lateral ventricle subventricular zone (SVZ) is a frequent site of high-grade glioma (HGG) spread and tumor invasion of the SVZ is a predictor of a worse clinical prognosis. A range of HGG types invade the stem cell niche of the SVZ, including both adult glioblastoma and pediatric high-grade gliomas such as diffuse intrinsic pontine glioma (DIPG). The cellular and molecular mechanisms mediating this frequent invasion of the SVZ are poorly understood. Here we demonstrate that neural precursor cell (NPC):glioma cell communication underpins the propensity of glioma to colonize the SVZ. SVZ NPCs secrete chemoattractant signals toward which glioma cells home. Biochemical and proteomic analyses of factors secreted by SVZ NPCs revealed a discrete list of candidate proteins. Necessity and sufficiency testing implicated the neurite outgrowth-promoting factor pleiotrophin, along with three required binding partners (secreted protein acidic and rich in cysteine (SPARC), SPARC-like protein 1, and heat shock protein 90B), as key mediators of this chemoattractant effect. Pleiotrophin protein expression is strongly enriched in the SVZ, and knockdown of pleiotrophin expression starkly reduced glioma invasion of the SVZ in the adult murine brain. Pleiotrophin, in complex with the three binding partners, activated the Rho/ROCK pathway in DIPG cells, and inhibition of ROCK resulted in decreased DIPG invasion toward SVZ neural precursor cell-secreted factors. These findings demonstrate a pathogenic role for neural precursor cell – glioma interactions and potential therapeutic targets to limit glioma invasion.

  Study EGAS00001002326

• Massively parallel nanowell-based single-cell gene expression profiling

  Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5184-nanowell-containing microchip to capture ~1300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

  Study EGAS00001002320

• 33 patients with Monoclonal Gammopathy of Undetermined Significance (MGUS) had whole exome sequencing performed. Cells were sorted by FACSAria using CD138, CD19 and CD56 to obtain a pure abnormal plasma cell population. Generated somatic variants were compared to a previous study of 463 multiple myeloma patients.

  Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor of multiple myeloma (MM) with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS genes mutations, little is known about molecular mechanism of malignant transformation. We have performed whole exome sequencing together with SNP array analysis in 33 flow-cytometry separated abnormal PC samples of MGUS patients to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations (NS-SNVs) and copy number alterations (CNAs) were present in 97.0% and in 63.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in MGUS compared to MM (p<10-4) and we have identified 6 myeloma significantly mutated genes which are KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB in the MGUS dataset. We also found a positive correlation with increasing chromosome changes and somatic mutations. IGH translocations were present in 27.3% of cases comprising t(4;14), t(11;14), t(14;16) or t(14;20) and were in a similar frequency to MM, which corresponded with primary lesion hypothesis. Data from this study showed MGUS is a genetically comprehensive disease, however overall genetic instability is significantly lower compared to MM.

  Study EGAS00001001658

• Small variants in mtDNA Canary Islands - WES Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005678

• Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005679

• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• Ultra-long sequencing for contiguous haplotype resolution of the human immunoglobulin heavy chain locus

  Genetic diversity within the human immunoglobulin heavy chain (IGH) locus influences the expressed antibody repertoire and susceptibility to infectious and autoimmune diseases. However, repetitive sequences and complex structural variation pose significant challenges for large-scale characterization. Here, we introduce a method that combines Oxford Nanopore ultra-long sequencing and adaptive sampling with a bioinformatic pipeline to produce haplotype-resolved, annotated IGH assemblies. Notably, our strategy overcomes prior limitations in phasing resolution, enabling single-contig haplotype assemblies that span the entire IGH locus. We applied this method to four individuals and validated the accuracy of the IGH assemblies using Pacific Biosciences HiFi reads, demonstrating near-complete sequence congruence, detecting only indels with a high degree of confidence. Moreover, when applied to the reference material HG002, our pipeline revealed no base differences and a limited number of indels compared with the Telomere-to-Telomere genome benchmark across the IGH region. Importantly, in the four individuals, our approach uncovered 30 novel alleles and previously uncharacterized large structural variants, including a 120 kb duplication spanning IGHE to IGHA1 and an expanded seven-copy IGHV3-23 gene haplotype. These findings underscore the power of our method to resolve the full complexity of the IGH locus and uncover previously unrecognized variants that may affect immune function and disease susceptibility. Thus, our method provides a strong basis for future immunological research and translational applications.

  Study EGAS50000001042

• SSBP1

  SSBP1 mutations cause a complex optic atrophy spectrum disorder with mitochondrial DNA depletion

  Study EGAS00001004003

• FEGA and European GDI: working together to improve human health

  The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

  Blog fega-and-gdi

• Genome-Wide Association Study of Celiac Disease

  Celiac disease (gluten-sensitive enteropathy, celiac sprue) is a common disease with significant morbidity and mortality. It is caused by sensitivity to the dietary protein gluten, resulting in a chronic enteropathy in the small intestine. Celiac disease is now recognized to be a common disease, with reports that the disease frequency is 1:133 in the United States, similar to European estimates. There is recent evidence to suggest that the incidence of the disease is rising. Occult disease is frequently present with minimal classic symptoms or signs. The ratio of symptomatic to asymptomatic celiac disease is estimated to be 1:7. Some complications of celiac disease include lymphoma, osteoporosis, anemia, miscarriages, seizures, vitamin deficiencies, and co-occurrence of other autoimmune diseases. The only treatment is a gluten-free diet, so that recurrence of symptoms and complications may occur after minor dietary indiscretions. Identifying the underlying genetic causes of celiac disease may allow us to identify susceptible individuals, as well as advance new ways to prevent the disease and to treat it once it occurs. Several genome-wide linkage studies and one genome-wide association study of celiac disease have been conducted. Other than the common locus at HLA, few putative celiac disease loci have been replicated between studies, suggesting that the disease is heterogeneous and complex. A portion of the genetic predisposition can be attributed to HLA, but the etiology is likely due to a number of rare, high penetrant genes (as would be identified in linkage analysis) and to more common, low penetrant genes (as would be identified in association studies). The objective of this study is to identify new loci that increase risk to develop celiac disease. We will capitalize on existing North American resources, including three large collections of celiac cases and controls (Aim 1) and an independent set of celiac cases and their families (Aim 3). We propose a comprehensive multi-stage approach, with the following specific aims. In Aim 1, we will conduct a genome-wide association (GWA) study of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). The GWA will include1900 disease cases and 3400 matched controls, genotyped using the Illumina Human 610-quad chip. Statistical analyses will be performed to test for associations with celiac disease. In Aim 2, we will conduct a combined analysis of our GWA dataset from Aim 1 and a previous GWA dataset to identify additional low-penetrance loci. In Aim 3, we will attempt to replicate significant findings from the GWA study in two independent sample sets. At the conclusion of this study, we expect to have validated a number of SNPs and CNPs from regions in the genome that alter the risk of developing celiac disease. These SNPs may prove useful at both the clinical and research level. The data from the study will be shared with the scientific community.

  Study phs000274

• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• Blood Somatic Mutations in TCGA Donors Suffering from Solid Tumors

  Blood somatic mutations identified across 8,530 solid tumor patients in TCGA cohort. We reasoned that low-coverage whole-genome sequencing of blood samples routinely carried out in cancer genomics projects may be repurposed to detect clonal hematopoiesis (CH). Thus, inspired by a previous approach to identify early mutations in the development of the hematopoietic system, we implemented a pipeline to systematically carry out this "reverse" somatic mutation calling on the paired blood/tumor samples. Blood somatic mutations were called using a 'reverse' approach, in which the tumor sample taken from each patient was used as control of their germline genome. Blood somatic mutations are thus detected as variants in the blood (with respect to the human reference genome) that are absent in the tumor sample. The variant calling was carried out in our in house cluster on downloaded blood/tumor BAM files. The matched blood and tumoral BAM files -- masked and deduplicated using GATK -- of 8,530 whole-exome patients were obtained as described above. The variant calling was carried out using Strelka2 (employing default parameters) with the blood sample as the tumoral input and the tumor sample as control (reverse calling). All variants with two or more supporting reads matching the caller PASS filter and with VAF<0.5 were kept. Mutations in lowly mappable regions as defined by the DUST algorithm (k=30) and UMAP68 (36-kmers) were excluded. Contiguous variants were merged into double-base substitutions. Variants with greater frequency across the cohorts than the DNMT3A R882H or JAK2 V617F hotspot in a cohort-specific Panel of Normals and in gnomAD v2.1 were removed. This was equivalent to discarding variants present in these datasets with an allele frequency greater than 0.008 in PoN TCGA and 0.0003 in gnomAD v2.1. Additionally, common SNPs as defined by the dbSNP 151 Common UCSC track and dbSNP were excluded. Mutations within segmental duplications, simple repeats and masked regions as defined in UCSC tracks were also removed. Finally, samples with the mutation count above the 97.5 percentile of the mutation burden across the cohort were deemed unreliable and excluded for further analyses. We call the set of variants obtained after the application of these filters the full set. A more conservative subset of somatic mutations was generated from the full set of blood somatic mutations. To this end, we applied MosaicForecast, a software designed to phase mutations to polymorphisms with the aim of identifying somatic mutations in a small number of cells and also predict mosaicism for the unphased ones with a random forest classifier. As a result, we obtained a subset of mosaic-phased mutations, and a subset of mutations likely to be somatic (mosaic set).In order to obtain access to this study, please first obtain access to TCGA study (phs000178).

  Study phs002867

• National Institute on Aging (NIA) Long Life Family Study (LLFS)

  The Long Life Family Study (LLFS) is an international collaborative study of the genetics and familial components of exceptional survival, longevity, and healthy aging. Families were recruited through elderly probands (generally in their 90s) who self-reported on the survival history of their parents and siblings, and on the basis of this information, families which showed clustering of exceptional survival were recruited. [Specifically, a Family Longevity Selection Score (FLOSS) ≥7 was required. The FLOSS measures the average excess Observed lifespan over that Expected based upon lifetables, while adding a bonus term for still-living individuals. Thus FLOSS is a useful tool for scoring and selecting families for inclusion in a research study of exceptional survival (Sebastiani et al., 2009, PMID: 19910380)]. Probands resided in the catchment areas of four Field Centers (Boston University, Columbia University, University of Pittsburgh, and University of Southern Denmark). Recruited family members were phenotyped through extensive in-home visits by teams of technicians who traveled all over the USA and Denmark. Blood assays were centrally processed at a Laboratory Core (University of Minnesota) and protocols were standardized, monitored and coordinated through a Data Management Coordinating Center (Washington University). We examined and extensively phenotyped in all major domains of healthy aging, 4,953 individuals in 539 families through comprehensive in-home visits. Of these, 4,815 gave dbGaP sharing permission and had sufficient quantity/quality of DNA for GWAS genotyping. This large collection of families, selected on the basis of clustering for exceptional survival, is a unique resource for the study of human longevity and healthy aging. We estimate that less than 1% of the Framingham Heart Study (FHS) families (a roughly random population family sample) would meet the minimal entrance criteria for exceptional survival required in the LLFS (Sebastiani et al., 2009, PMID: 19910380). Thus, the least exceptional LLFS families show more clustering for exceptional longevity than 99% of the FHS families. Although the LLFS pedigrees were selected on the basis of longevity per se in the upper generation (and the generation above that), the children's generation have significantly lower rates of many major diseases and have better healthy aging profiles for many disease phenotypes (Newman et al., 2011, PMID: 21258136). The participants had their first in-person visit between 2006 and 2009. After that visit, they were contacted annually by telephone to update vital status, medical history, and general health. Between 2014 and 2017, willing participants completed a second in-person visit. The second visit followed the same protocols and centralized training as the first visit. During the second visit, a portable carotid ultrasound exam was added. Again, participants were continuously contacted annually for telephone follow-up during the period of the second in-person visit and after that. Annual telephone follow-ups currently ongoing, and plans for a third in-person visit are in progress.

  Study phs000397

• Kids First: Whole Genome Sequencing in Structural Defects of the Neural Tube

  Myelomeningocele (aka meningomyelocele, MM) is the most severe form of spina bifida, a neural tube defect (NTD) in humans and the most common CNS birth defect. MM is considered a genetically complex disease, and occurs in 3.72/10,000 live US birth, and is partly preventable with prenatal folate, but the genetic basis and the mechanisms by which folate work to reduce disease incidence remain obscure. MM is associated nearly uniformly with prenatal hydrocephalus and the Arnold-Chiari malformation, as well as paraplegia and lifelong neuromotor disability. The genes for several rare syndromic forms of NTDs are known, but the causes for the majority with sporadic MM remain unknown. Despite the importance of MM, most previous research has been limited to targeted sequencing and association studies of folate metabolism genes, or very small-scale exome sequencing. We hypothesize that de novo mutations (DNMs) produce likely gene disrupting (LGD) events that contribution to MM risk. Using conservative estimates of between 50-100 recurrently mutated discoverable genes contributing to risk, and our preliminary data demonstrating an excess of LGD DNMs in MM compared with control individuals, we estimate that with a cohort size of 1000 trios, we should uncover between 5-20 new recurrently mutated genes underlying MM, with minimal false-discovery. With this in mind, we formed the Spina Bifida Sequencing Consortium, and established a platform for data and sample sharing. Preliminary analysis of our first batch of 100 trios analyzed by WGS from GMKF suggests a wealth of important gene mutations. We have embarked on a new recruitment effort of an additional cohort of 400 new simplex MM trios, in collaboration with the US Spina Bifida Association, consented trios to allow for data sharing, and have performed detailed sample quality control. We also have preliminary data that use of dried bloodspot DNA from trios performs comparably to whole blood DNA, so will be happy to swap saliva for bloodspot recruitment at NIH's preference. This cohort is now half-way assembled, with the remaining cohort to be ascertained in the next 6 months. We have established a workflow for de novo SNP/INDEL/SV detection from WGS and have ample computer storage and nodes to see the project to completion. We also plan to continue recruitment into the future with the goal of 2000 trios in the next 5 years. We propose a detailed bioinformatics workflow to identify gene mutations within a statistical framework, considering detailed scRNA expression profiling from developing mammalian neural tube, and have developed a robust functional validation workflow using Xenopus and mouse gene targeting. Our project has the potential to uncover a host of causes for this most common of the CNS birth defects, paving the way for future breakthroughs in detection, treatment, and prevention.

  Study phs002591

• Submitter Portal API

  Submitter Portal API The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. For those that want a more flexible and automated approach, we also provide a programmatic approach using the Submitter Portal AP in addition to the user interface of the Submitter Portal. With the help of our API, you can quickly include the submission of metadata into your own workflow for a more effective and individualised experience. Previous steps Create your EGA account To submit data you first need to create your EGA user. Then, once your account has been verified, you will have to request a submitter role and sign the EGA Data Processing Agreement (DPA). When the DPA is signed, you must send it to EGA Helpdesk for further validation. Please, note that if you already have an EGA account, or you have an ega-box (submission account), you can skip this step.  Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find the relevant information in the DAC Portal Guide. Programmatic submission All the calls to the API need to be Authenticated. We use the OpenID Connect protocol. API Usage Flow: Click here to check the API usage flow schema Obtain Access and Refresh Token: The first step to using the API is to obtain an access and refresh token. These tokens are required for authentication and authorisation of API requests. To obtain these tokens, you need to log in using your EGA credentials. Example: curl "https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token" \ -d "grant_type=password" \ -d "client_id=sp-api" \ -d "username=your-username" \ --data-urlencode "password=your-password" Use Access Token in API Calls: Once you have obtained the access token, you must use it in all the calls to the API. The access token is valid for a limited time period. When it expires, you will need to use the refresh token to obtain a new access token. Create Submission Object: After authentication, you can start creating a submission object. This object will be used to store all the metadata objects and files related to the submission. Example: curl "https://submission.ega-archive.org/api/submissions" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My submission title\", \"description\":\"My submission description\" }" Create EGA Metadata Objects: Within the submission object, you can create other metadata objects required for the submission. These objects may include information about the submitter, study, sample, experiment, and run. Example of study creation: curl "https://submission.ega-archive.org/api/submissions/{submisison-id}/studies" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My study title\", \"description\":\"My study description\", \"study_type\":\"Metagenomics\" }" If you would like to reuse already registered objects in new submissions, bear in mind that they must have an accession which you must use to reference them. You cannot reuse objects that have not been finalised and accepted yet.For example, when creating a new run which is reusing a previously submitted experiment, instead of using experiment_provisional_id, you must use experiment_accession_id. Enums There are some fields that only accept specific values, i.e. study_type. The API provides several enumerations to list these values. You can list all the enumerations, or a specific one, for example, study_types. Obtain IDs of files You can list the files available in your inbox and filter by a prefix by adding the prefix param, i.e. &prefix=/my_folder/abc Example: curl "https://submission.ega-archive.org/api/files?status=inbox&prefix=/my_folder/abc" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" To improve performance and manageability, we have limited the number of files that the Submitter Portal API can return in a response. If a given call exceeds this limit, user will be asked to narrow down the search by using the query parameters already available in this endpoint. Finalise Submission: Once all the metadata objects are created and linked to the submission, you can finalise the submission. Finalising the submission sends it to the Helpdesk team for review. Please, note that all files linked to the submission must be ingested, and all objects created in a submission must be linked before you can finalise the submission. API Reference: For a full API reference, please check our specification documentation.

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal-api

• Single Cell RNA-Sequencing of BCG Naive and Recurrent Non-Muscle Invasive Bladder Cancer Reveals a CD6/ALCAM-Mediated Immune-Suppressive Pathway

  Non-muscle invasive bladder cancer (NMIBC) represents 70–80% patients with newly diagnosed bladder cancer, and Bacillus Calmette-Guerin (BCG) remains a cornerstone treatment for intermediate- and high-risk NMIBC to prevent disease recurrence and progression. However, a significant number of patients experience recurrence after their first course of BCG, posing significant challenges in the management of the disease. We conducted single cell RNA sequencing (scRNA-Seq) on freshly collected NMIBC samples, distinguishing between those naive to BCG treatment and those that recurred post-BCG treatment. We observed a clear activation of inflammatory pathways across cell types during recurrence, but these were not associated with canonical immune checkpoint or T cell exhaustion phenotypes. Analysis of cell-to-cell communication revealed enhanced interactions between T cells and urothelial cells in BCG-recurrence, predominantly modulated by CD6 and activated leukocyte cell adhesion molecule (ALCAM). Furthermore, we found CD6hi T cells to be immunosuppressed and enriched in recurrent samples, suggesting a potential role for CD6 as an immune evasion signal in NMIBC.

  Study phs003742

• A multicenter study of susceptibility genes to type 1 diabetes

  The first genome-wide association study of fulminant type 1 diabetes mellitus was performed in Japanese individuals. As previously reported using a candidate gene approach, a strong association was observed with multiple SNPs in the HLA region, and the strongest association was seen for rs9268853 in the class II DR region (P=1.56 x 10-23, odds ratio [OR] 3.18). In addition, rs11170445 in CSAD/lnc-ITGB7-1 on chromosome 12q13.13 showed an association at a genome-wide significance level (P=7.58 x 10-9, OR 1.96). Fine mapping of the region revealed that rs3782151 in CSAD/lnc-ITGB7-1 showed the lowest P value (P=4.60 x 10-9, OR 1.97 [95% CI 1.57-2.48]). The risk allele of rs3782151 is a cis-expression quantitative trait locus (eQTL) for ITGB7 that significantly increases the expression of this gene. CSAD/lnc-ITGB7-1 was strongly associated with the susceptibility to fulminant, but not classical autoimmune, type 1 diabetes, implicating this locus in the distinct phenotype of fulminant type 1 diabetes.

  Study JGAS000144