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• Peripheral immunoprofiling of stratifies COVID-19 patients based on disease-specific neutrophil signatures

  The SARS-CoV-2 pandemic has led to increasing numbers of COVID-19 patients all over the world. Aetiopathologies range from no symptoms, mild flu-like to severe cases succumbing to respiratory failure. Reports on a dysregulated immune system in the severe cases, showing similarities to cytokine release syndrome, calls for better characterization and understanding of the changes in the immune system as well as their variance across COVID-19 patients in order to be able to design according to host-directed therapies. Here, we profiled blood transcriptomes of 39 COVID-19 patients and 10 control donors. Enriched granulocyte signatures in whole blood samples were verified in granulocyte samples from 49 COVID-19 patients in a second cohort.

  Dataset EGAD00001006326

• Peripheral immunoprofiling of stratifies COVID-19 patients based on disease-specific neutrophil signatures

  The SARS-CoV-2 pandemic has led to increasing numbers of COVID-19 patients all over the world. Aetiopathologies range from no symptoms, mild flu-like to severe cases succumbing to respiratory failure. Reports on a dysregulated immune system in the severe cases, showing similarities to cytokine release syndrome, calls for better characterization and understanding of the changes in the immune system as well as their variance across COVID-19 patients in order to be able to design according to host-directed therapies. Here, we profiled blood transcriptomes of 39 COVID-19 patients and 10 control donors. Enriched granulocyte signatures in whole blood samples were verified in granulocyte samples from 49 COVID-19 patients in a second cohort.

  Dataset EGAD00001006671

• Genome_Diversity_in_Africa_Project__Uganda

  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

  Study EGAS00001002523

• WES_of_adult_intellectual_disabilities_with_co_morbid_psychiatric_disorders

  ost adults with intellectual disabilities (ID) do not undergo genetic diagnostic investigation as part of their clinical care and have 'missed the boat' with regard to the WES and WGS genetic testing that is now being provided for children with ID. There is a dramatically increased risk of psychistric disorders in adults with ID, e.g. the risk of psychoses is 10X higher than in the general population. It remains an open question as to how much of adult ID is genetic in origin and how similar the genetic forms of adult ID are to those being diagnosed in children, in part due to survivor bias. There is also the opportunity to identify adults with treatable forms of ID, of which over 80 have been described, thus improving their clinical management. Furthermore, analysis of medical records of adults with genetic forms of ID can help to characterise the 'natural history' of individual disorders, resulting in more accurate prognoses for diagnosed children and identifying opportunities for improved management and possibly therapeutic intervention (e.g. optimal anti-epileptic therapy). Here we propose to exome sequence (to ~50X coverage) 200 adults with ID and co-morbid psychiatric disorders. This cohort has previously been assayed with chromosomal microarrays (Wolfe et al 2017 EJHG, 25, 66–72) identifying a diagnostic yield of ~11% which is comparable to the CNV diagnostic yield in various child ID cohorts (10-15%). The authors observed no substantive biases in diagnostic yield between different psychiatric diagnostic classes. The WES data will be analysed using the diagnostic workflows developed in the DDD study to ensure comparability between child and adult ID datasets. This study is intended as a pilot study to demonstrate the value of WES in adults with ID. 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 EGAS00001002962

• Whole exome and RNA sequencing of organoid samples derived from TRACERx patients

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘hot’) and non-evading (‘cold’) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008092

• Raw bulk TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008118

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• This committee is composed on individuals who have access to the data corresponding to this project: Gut microbiome modulates response to anti PD-1 immunotherapy in melanoma patients

  Dac EGAC00001000758

• Netherlands Cancer Institute (NKI-AVL) general DAC

  Data is available under reasonable request. All data requests will be reviewed by the NKI IRB and must be supported by the Principal Investigator of the study. The researcher will need to sign a data access agreement with the NKI after approval. Go to https://ega.nki.nl to fill out the form to request access.

  Dac EGAC50000000055

• Whole exome sequencing, RNA sequencing and single-cell RNA sequencing of 4 melanoma patients

  We perfomed whole exome sequencing and RNA sequencing of 4 melanoma patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

  Study JGAS000285

• DNA sequencing of sgRNAs enriched from the CRISPR-Cas9 screened HCC organoids

  There are 12 samples. The project aims to find enriched or depleted sgRNAs to identify functional genes in HCC progression and lenvatinib resistance

  Study EGAS50000001130

• Kidney_Single_Cell_Study

  We intend to use single cell transcriptome analysis to explore the heterogenity of different cell types within the kidney.

  Study EGAS00001002325

• The landscape of LAM disease

  Tumor biopsies from LAM disease were retrospectively analyzed by multiple techniques to characterize the alterations in patients ,to elucidate the landscape of genetic/genomic alterations.

  Study EGAS00001003534

• Exome and transcriptome sequencing of Desmoplastic Small Round Cell Sarcoma

  To conduct exome and transcriptome profiling to identify secondary recurrent mutations, multi-site phylogenetic analyse and immune characterization of Desmoplastic Small Round Cell Sarcoma.

  Study EGAS00001004575

• Genomics analysis of mucinous tumours of the ovary and related neoplasms

  To perform genetic and gene expression analyses on mucinous ovarian tumours to determine a progression model, cell of origin and novel therapeutic targets.

  Study EGAS00001003545

• Sequencing data for CLL patients

  Single-cell RNA-sequencing and other genome-wide approaches were applied to a cohort of CLL patients receiving Venetoclax treatment to study mechanisms of resistance.

  Study EGAS00001005815

• Whole exome sequencing study of cholesteatoma patients from affected families

  This study used whole exome sequencing on 21 patients with cholesteatoma from 10 families in order to identify variants that may attribute to cholesteatoma aetiology.

  Study EGAS00001006147

• Rifaximin stimulates nitrogen detoxification by PXR-independent mechanisms in human small intestinal organoids

  To study the effects of rifaximin on human small intestinal (hSI) organoids, we performed RNAseq in PXR knockdown hSI compared to control hSI.

  Study EGAS00001006857

• Possible DNA Damage after paternal exposure to ionizing radiation in Radar technicians

  This dataset contains whole genome sequences from Illumina NovaSeq Devices sequenced at the WGGC Bonn to study effects of prolonged paternal exposure to ionizing radiation. Here we provide the reads, mapped to the hg19 reference genome of all samples.

  Dataset EGAD00001011043

• Identification of Putative Neoantigens in Stage III Melanoma

  This study of three metastatic melanoma patients utilized exome sequencing and RNA sequencing to help identify putative neoantigen peptides that could be further validated by standard immunological assays before design of a personalized vaccine. For each set of neoantigens identified and verified by standard assays, we designed GMP peptides that correspond to the top neoantigens, then used these to condition dendritic cell isolates from each patient. The conditioned dendritic cells were used as the vaccine in three rounds of vaccination, followed by monitoring for T cell memory response to each of the neoantigens.

  Study phs001005

• Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

  This observational study was designed to determine the cellular tropism of Influenza A and B Viruses (IAV, IBV) from samples taken from the upper respiratory tract collected during routine nasal washes during the 2017-2018 season. Using single-cell RNA sequencing (scRNA-seq) we sought to determine which cell types could be infected, what the cellular response was to infection in both infected and bystander cells, and to compare the intra/inter-host variability of IAV and IBV during a single season at a single healthcare provider location.

  Study phs002039

• Gastrointestinal Cancer Treatment Responders

  Comprehensive genomic profiling of colon adenocarcinomas has revealed multiple recurrent alterations that may inform new treatment strategies. Clinical trials of these agents are ongoing, although the mechanisms of response and resistance to these agents are not well characterized. The goal of this study is to perform comprehensive profiling of pre-treatment and post-resistance tumor and germline samples obtained from patients with colon cancer who receive these agents by carrying out whole exome sequencing and RNA sequencing, and to use these data to identify mechanisms of response and resistance.

  Study phs000803

• NHLBI TOPMed - NHGRI CCDG: AF Biobank LMU in the context of the MED Biobank LMU

  The Atrial Fibrillation Biobank Ludwig Maximilian University (AFLMU) Study contributes to the spectrum of disease by adding carefully characterized patients with atrial fibrillation. Atrial fibrillation, one of the most common human arrhythmias confers major morbidity, mortality and health care cost, and has been demonstrated to be caused and influenced by genetic and -omics factors. Particularly, AFLMU enrolled patients with an early onset of atrial fibrillation to increase the genetic burden on disease pathophysiology. All patients were recruited applying standardized protocols to maintain homogeneity in data and DNA quality.

  Study phs001543

• Multivalent State Transitions Shape the Intratumoral Composition of Small Cell Lung Carcinoma

  Small cell lung carcinoma (SCLC) is an aggressive, tobacco-associated tumor characterized by rapid growth, early metastases, and initial response followed by almost invariable resistance to chemotherapy. Studies to date have not resolved the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. We combined patient-derived xenograft (PDX) (n = 64) resources with multi-omic profiling, single-cell fluorescence tracking of ex vivo tumor cells, and mathematical and statistical models to study the topology of the SCLC transcriptional state space and its plasticity.

  Study phs003102

• Nanopore whole-genome sequencing of sample RK067 and variant-call data (SNVs and intermediate-sized deletions) of 174 Japanese samples.

  We performed whole-genome sequencing of a human samples using Oxford Nanopore MinION sequencer, so as to be able to establish methods to detect and identify structural variations in Japanese individuals. Intermediate-sized deletions were identified from 174 Japanese samples��� short-reads whole-genome sequencing data. Variant call information of these intermediate-sized deletions were joined with SNVs identified in a previous study (Fujimoto, A et al., Nat Genet, 2016) to create a reference panel for use in imputation.

  Study JGAS000180