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• RNA sequencing of Ewing sarcoma and CIC-DUX4 sarcoma

  RNA sequencing of a collection of 6 Ewing sarcoma and 3 CIC-DUX4 sarcoma tumoroids plus 3 matched patient tumors. Tumoroids were established from digested patient tumor material as 3D culture in Matrigel. After 2-3 month of growth, RNA was isolated from individual tumoroid models using the RNeasy Kit (Qiagen) and used for whole exome sequencing. RNA from corresponding patient tumors was tested in parallel, if available.

  Dataset EGAD50000000557

• Whole Genome DNA Methylation MPI

  Whole Genome Bisulfite Sequencing on normal primary human uveal melanocytes. WGBS libraries were prepared using the Accel-NGS Methyl-Seq DNA Library Kit (Swift Biosciences, Catalog No. 30024), the EZ DNA Methylation-Gold Kit (Zymo, D5005) and DNA Clean & Concentrator-5 (Zymo, D4013), following the instruction manual Accel-NGS® Methyl-Seq DNA Library (Revision 160510). Paired-end libraries (2 × 150 bp) were sequenced on a NovaSeq 6000 instrument.

  Dataset EGAD50000001139

• Single-cell Transcriptome Analysis of Plasma Cells Across the Disease Spectrum of Multiple Myeloma

  This dataset includes FastQ files of single-cell RNA sequencing data of 5' GEX and VDJ libraries from CD138+ plasma cells enriched from 72 bone marrow aspirates from patients diagnosed with a monoclonal gammopathy from the multiple myeloma spectrum, including MGUS (n=13), SMM (n = 22), NDMM (n = 17), RRMM (n = 15) and PCL (n = 2); and 3 controls.

  Dataset EGAD50000001179

• Low-input RNA-seq libraries from FFPE samples using TaKaRa SMARTer kit

  Using the TaKaRa SMARTer Stranded Total RNA-Seq Kit v2, RNA-seq libraries were generated from 5 ng of RNA extracted from FFPE tissue. A low-input workflow was applied with 5 PCR cycles for the first amplification and 16 for the second. Library quality was assessed by Bioanalyzer and Qubit, and libraries were sequenced (2×150 bp) on the Illumina NextSeq 550 platform.

  Dataset EGAD50000001552

• Immunoglobulin Heavy-Chain locus in Multiple Sclerosis (n=4)

  Peripheral-blood or monocyte DNA from two healthy donors and two individuals with multiple sclerosis were sequenced on a PromethION-2 Solo (P2 Solo) instrument using R10.4.1 flow-cells and the Ultra-Long DNA Sequencing Kit (SQK-ULK114). For each participant we provide FASTQ reads (on-target), and haplotype-resolved assemblies of the complete IGH locus (~1.3 Mb) in FASTA format.

  Dataset EGAD50000001517

• Longitudinal ctDNA in Uveal Melanoma

  This dataset contains data from 11 uveal melanoma patients. Plasma samples were collected at baseline, 2-weeks, 3-, 6-, and 12-months post treatment (surgery/radiation). Samples underwent targeted panel, shallow whole genome, and cfMeDIP sequencing. A total of 46 plasma samples, 7 tumours, 11 buffy coats, and 10 healthy controls are included.

  Dataset EGAD00001008998

• FIT interval CRCs versus Screen-detected CRCs

  Formalin-fixed, paraffin-embedded samples from 27 FIT interval CRC and 54 screen-detected CRCs collected in a pilot-program of FIT-based CRC screening in the southwest and northwest regions in the Netherlands, were used in this study. DNA was extracted for 1) Shallow Sequencing (copy number analysis) and 2) TSACP Amplicon Cancer Gene Panel (mutations) of 22 FIT Interval CRCs and 45 screen-detected CRCs.

  Dataset EGAD00001006409

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in late severe COVID-19

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of late severe COVID-19. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001008161

• GenomeDenmark Phase 2 - whole genome variants called using BayesTyper

  Variants and genotypes called in 50 danish parent-offspring trios from 80x Illumina sequencing data using BayesTyper. Data was produced using different insert size libraries of the sizes 180, 500, 800, 2000, 5000, 10000 and 20000 bp. The sample IDs for the fathers and mothers are TrioID-01 and TrioID-02, respectively, and the IDs for the children are TrioID-0x, where x is a number between 3 and 7

  Dataset EGAD00001003188

• RNAseq_pituitary_adenoma

  Total RNA was extracted using RNAble (Eurobio), cleaned-up with RNeasy columns (Qiagen) and sequenced. The libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq Stranded mRNA protocol (Illumina), starting from 1 µg of high quality total RNA. Paired end (2 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on hg19 (GRCh37) human reference genome with STAR (v.2.5.2a)

  Dataset EGAD00001004996

• WGS data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - MUMC

  The dataset includes cram files from WGS of 2 NEN tumors and matched PDTOs. For all tumors, cram files from WGS of matched normal tissue from the corresponding patients are included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009988

• Evolution of four ER+ breast cancers

  The evolution of four breast cancers was analyzed using longitudinal samples collected over 2-15 years. Whole-genome sequencing and single-cell RNA-Seq were used to analyze evolution. We have deposited VCF files for SNV, indel, and structural variant calls from WGS data, and a text file showing transcripts per million (TPM) expression for the single-cell RNA-Seq data.

  Dataset EGAD00001003303

• GoNL release 5 raw SNV calls

  These files contain a total of 20.4M SNVs and the complete information output by the GATK UnifiedGenotyper v1.4 on all 767 GoNL samples. These calls are not trio-aware and all genotypes were reported regardless of their quality. Both filtered and passing calls are reported in these files. Filtered calls include (1) calls failing our VQSR threshold and (2) calls in the GoNL inaccessible genome.

  Dataset EGAD00001000743

• AT-AML samples dataset

  Serial samples from one AT-AML patient as described in publication Goldgraben et al Pediatric Blood & Cancer 2020. Whole exome sequencing of a AT-'germline' blood sample, one bone marrow sample (at AML diagnosis) and 3 AML blood samples. Library preped using the Illumina Nextera Rapid Capture Exome Enrichment Kit, and sequenced as PE150 on HiSeq4000. Provided: 5 BAM files (GRCh37); 2 VCF analyses (germline and somatic)

  Dataset EGAD00001006090

• Prognostic and immunomodulatory consequences of ERV expression in ovarian cancer

  The dataset contains transcriptional data obtained using total RNA sequencing on a Illumina machin. 59 samples are from the Hammersmith Hospital (HH) cohort of human primary ovarian tumours and 20 samples are from ovarian cancer cell lines Kuramochi (3 replicates) and Ovsaho (2 replicates) treated with 1 uM DNMTi guadecitabine or vehicle, at an early (day 5) or late (day 8) timepoint.

  Dataset EGAD00001006589

• Single-cell RNA and TCR sequencing of 37 PBMC pools of advanced HCC patients.

  scRNAseq and scTCRseq of serial peripheral blood mononuclear cell (PBMC) samples (n=72) taken at various timepoints before and during treatment (Week 0 (W0), Week 3 (W3), Week 6 (W6)). PBMC samples were pooled together into 37 pools, loading 2 or three samples per lane in the 10X Genomics chip, in equal proportions, according to a pre-designed pooling matrix.

  Dataset EGAD00001011345

• Nicotine Addiction Genetics and Correlates

  Ascertainment: Families were ascertained through panels of adult Australian twins, and a sample of spouses of Australian twins. Families with at least one offspring who was identified as a current or former smoker in an earlier survey. Screening telephone interviews were conducted with index cases to provide confirmation of a history of heavy cigarette smoking, to obtain confirmation of a history of heavy cigarette smoking, and to obtain additional information on the history of cigarette use and the survival status of other family members, and their full siblings and parents. Index cases were the affected spouse of a twin, or the affected twin from pairs discordant for a history of heavy smoking, or a randomly chosen twin from pairs where both have a history of regular smoking (i.e., has smoked at least 100 cigarettes lifetime), and at least one live biological parent to identify sibships with at least one affected sib pair (ASP) concordant for heavy smoking, and at least one living parent. If permission was granted by the index case, eligible family members were contacted and invited to provide a blood sample and to complete a telephone diagnostic interview. In families with just one available biological parent, and additional unaffected sibling who had never smoked on a regular basis (i.e., has smoked fewer than 100 cigarette lifetime, but has experimented with cigarettes once or twice) was included (when available) to help compensate for the loss of information due to missing parental phenotypes. (Target N=400 Australian families with approximately 600 ASPs; and 600 TDT trios comprised of a nicotine dependent index case and both biological parents). Diagnostic Assessment: The telephone diagnostic interview assessed DSM-IV and modified DSM-IIIR diagnoses (i.e., without time clustering) for nicotine dependence, alcohol and other drug dependence and abuse, major depression, and childhood conduct disorder. Most diagnostic assessments were based on the SSAGA/SSAGA-II, developed for the multi-site gene-mapping alcoholism study (the Collaborative Study on the Genetics of Alcohol. An exception was the tobacco section, which was developed directly from the CIDI and DIS (as the original SSAGA did not include a diagnostic section on nicotine dependence). In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001299

• Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

  IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

  Study phs002686

• Genetic Associations in Idiopathic Talipes Equinovarus (Clubfoot) - GAIT

  Isolated clubfoot or idiopathic talipes equinovarus (ITEV) is one of the five most common birth defects, affecting approximately 4,000 newborns each year in the US. While the orthopedic care of these children has improved, long-term problems persist and the health care costs are significant. Studies suggest that clubfoot is a complex disorder with segregation analyses and family studies indicating that genetic factors play an important etiologic role in the development of clubfoot. Only one environmental factor, maternal smoking during pregnancy, has been implicated. We postulate that a small number of genes account for a substantial fraction of clubfoot and that these genes can be identified in a defined population. The challenge now is to identify the genetic loci and, later, the effect of environmental exposures. To accomplish this task, it is important to have a well-defined population and the methodology to detect linkage with and without association. Towards these goals, we have identified and characterized multiplex clubfoot families, including two large clubfoot families, a resource which is among the largest ITEV populations in existence. We will perform a high-density SNP genome scan (GWAS) on our clubfoot dataset to identify chromosomal regions that may harbor clubfoot genes with subsequent interrogation of these regions and candidate genes. We are in a position with our unique clubfoot population and with the methodology in place to undertake this study. The study phases are: 1) continued ascertainment of multiplex and simplex families and 2) GWAS and characterization of identified chromosomal regions and candidate genes. The results of this study will provide data essential to the identification of the gene(s) contributing to the clubfoot phenotype. Identification of high-risk genotypes can lead to the development of prevention programs in selected populations and may suggest gene-based prevention strategies.

  Study phs000314

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Human Gene Expression Patterns Associated with Experimental P. falciparum Infection

  Description: Experimental exposure to malaria parasites can lead to development of protective immunity, providing a foothold for the development of a malaria vaccine. The goal of this study is to investigate immune transcriptional profiles associated with malaria protective immune responses induced by experimental Chemo-Prophylaxis and Sporozoites (CPS) immunization of P. falciparum-naive human volunteers. Samples for this study were obtained from a CPS-immunization study conducted in 2011 (ClinicalTrials.gov Identifier: NCT01218893), where healthy volunteers received CPS-immunization with bites from different numbers of P. falciparum-infected mosquitoes (three times 15 (n=5), 10 (n=9) or 5 (n=10)). Five control subjects received uninfected mosquito bites under chloroquine prophylaxis. Fifteen weeks after discontinuation of chloroquine prophylaxis, all volunteers were challenged by exposure to infected mosquito bites. Study Design: A maximum of 30 volunteers were divided into four groups. All volunteers received weekly chloroquine prophylaxis for a period of 13 weeks (91 days). During these 13 weeks, on days 8, 36 and 64 they were exposed to the bites of 15 mosquitoes. Group 1 (n=5, positive control) received three CPS immunizations by 15 mosquitoes infected with P. falciparum sporozoites. Group 2 (n=10) received three times 10 bites from infected mosquitoes and 5 bites from uninfected mosquitoes. Group 3 (n=10) received three times 5 bites from infected mosquitoes and 10 bites from uninfected mosquitoes. Group 4 (n=5), the negative control, received three placebo immunizations with 15 bites of uninfected mosquitoes. Fifteen weeks after discontinuation of chloroquine prophylaxis, all 30 volunteers were challenged at day 196 by the bites of 5 infectious mosquitoes and followed for 21 days. All subjects were treated with chloroquine 21 days after challenge or whenever they had a positive thick smear during that period.

  Study phs001346

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• mutation analysys of Gorlin syndrome

  Gorlin syndrome is a genetic disorder of autosomal dominant inheritance that predisposes the affected individual to a variety of disorders that are attributed largely to heterozygous germline patched1 (PTCH1) mutations. PTCH1 is a hedgehog (Hh) receptor as well as a repressor, mutation of which leads to constitutive activation of Hh pathway. Hh pathway encompasses a wide variety of cellular signaling cascades, which involve several molecules; however, no associated genotype?phenotype correlations have been reported. Recently, mutations in Suppressor of fused homolog (SUFU) or PTCH2 were reported in patients with Gorlin syndrome. These facts suggest that multi-layered mutations in Hh pathway may contribute to the development of Gorlin syndrome. We demonstrated multiple mutations of Hh-related genes in addition to PTCH1, which possibly act in an additive or multiplicative manner and lead to Gorlin syndrome. High-throughput sequencing was performed to analyze exome sequences in four unrelated Gorlin syndrome patient genomes. Mutations in PTCH1 gene were detected in all four patients. Specific nucleotide variations or frameshift variations of PTCH1 were identified along with the inferred amino acid changes in all patients. We further filtered 84 different genes which are closely related to Hh signaling. Fifty three of these had enough coverage of over ?30. The sequencing results were filtered and compared to reduce the number of sequence variants identified in each of the affected individuals. We discovered three genes, PTCH2, BOC, and WNT9b, with mutations with a predicted functional impact assessed by MutationTaster2 or PolyPhen-2 (Polymorphism Phenotyping v2) analysis. It is noticeable that PTCH2 and BOC are Hh receptor molecules. No significant mutations were observed in SUFU. Multi-layered mutations in Hh pathway may change the activation level of the Hh signals, which may explain the wide phenotypic variability of Gorlin syndrome.

  Study JGAS000099

• The light chain IgLV3-21 defines a new poor prognostic subgroup in Chronic Lymphocytic Leukemia: results from a multicenter study

  Purpose: Unmutated (UM) immunoglobulin heavy chain region (IgHV) status or IgHV3-21 gene usage is associated with poor prognosis in chronic lymphocytic leukemia (CLL). Interestingly, IgHV3-21 is often co-expressed with light chain IgLV3-21 which is potentially able to trigger cell-autonomous BCR-mediated signaling. However this light chain has never been characterized independently of the heavy chain IgHV3-21.Experimental Design: we performed total RNA sequencing to characterize IgLV3-21 patients (n=32) and investigated IgLV3-21 prognostic impact in terms of treatment-free (TFS) and overall (OS) survival in 3 other independent cohorts for a total of 813 patients where IgLV3-21 presence was tested by real-time PCR and confirmed by Sanger sequencing.Results: Using total RNA sequencing to characterize 32 patients with high-risk CLL, we found a high frequency (28%) of IgLV3-21 rearrangements. Gene set enrichment analysis revealed that these patients present higher expression of genes responsible for ribosome biogenesis and translation initiation (P<0.0001) and MYC target genes (P=0.0003). Patients with IgLV3-21 rearrangements displayed a significantly shorter TFS and OS (P<0.05), in particular in IgHV mutated patients. In each of the 3 independent validation cohorts (n=813), we showed that IgLV3-21 rearrangements -similar to UM IgHV status- conferred poor prognosis compared to mutated IgHV (P<0.0001). Importantly, we confirmed in multivariate analysis that this was independent of IgHV mutational status or subset #2 stereotyped receptor (P<0.0001). Conclusions: We therefore demonstrate for the first time that a light chain can impact on CLL prognosis and that IgLV3-21 light chain usage defines a new poor prognostic subgroup in CLL.

  Study EGAS00001002894

• Transcriptional_profiling_of_tauopathies_in_human_IPS_derived_neurons

  This project is a pilot study, in collaboration with Maria Grazia Spillantini and Mariangela Iovino (Cambridge Centre for Brain Repair), to investigate the utility of IPS-derived neurons for the study of neurodegenerative disorders. Our aim is to characterise the transcriptional consequences of tauopathies using neurons derived from differentiated IPSCs as a model system. We will use IPS cells derived from six individuals, four with known mutations in the tau protein, 2 without. RNA will be extracted at Day 0 and Day 65 of differentiation by which time the neuronal tauopathy is apparent. RNA will be extracted and the transcriptome of each line characterised using RNAseq. We will then search for genes that are differentially expressed between the transcriptomes of individuals with tau mutations versus those in controls. My lab will analyse the RNAseq data, comparing both affected and controls and both time-points, to establish candidate genes. Darren Logan’s lab, along with our collaborators, will experimentally verify and further investigate these genes in additional lines and animal models. From this analysis we will generate a list of candidate genes that are differentially expressed between cases and controls. This study will not only help us understand the molecular basis of tauopathies, but also identify gene candidates for biomarkers of neurodegenerative disease. It will serve as a proof of principle for future planned studies into generating and transcriptomically analysing an allelic series of Tau mutations in IPSCs with a controlled genetic background.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 EGAS00001000382