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• FEGA Sweden Helpdesk

  FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

  Dac EGAC50000000077

• Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

  Gastric cancer (GC) is a major cause of global cancer mortality with high levels of heterogeneity, and intratumoral heterogeneity (ITH) represents a significant barrier to GC patient outcomes. In this study, we applied GeoMx DSP technology to identify ITH in GC. We found spatially colocalized RNA-based intratumor subgroups within samples, each correlated with distinct spatially oriented TME and immune profiles. The findings broadening our understanding of the spatial and molecular complexity of GC ITH and offering a valuable data resource for future exploration and discovery.

  Study EGAS50000000345

• Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023

  Synthetic - This submission contains a subset of a synthetic dataset derived from the project Heilsa Tryggvedottir - a Nordic collaboration on sharing sensitive human data. Heilsa Tryggvedottir is funded by the Nordic e-Infrastructure Collaboration (NeIC), the ELIXIR nodes of Finland, Norway, and Sweden, Computerome in Denmark, and the Estonian Scientific Computing Infrastructure (ETAIS). In the synthetic data creation process, it was attempted to strike a fine balance between the usability of the datasets (e.g. technical FEGA development, testing, user training, and basic bioinformatics) and compliance with GDPR. File names and file content (e.g. headers in fastq) are anonymized. Moreover, the X, Y, and mitochondrial sequences have been discarded from the original data since these data can be used for maternal, paternal, or ethnic origin tracing. The dataset does not follow natural haplotype distribution (inherent to imputation panels). The only inputs derived from real sequence data are variant distribution density per chromosome and learning sequencing error models. The synthetic dataset consists of two fastq files, a cram file, a vcf file, and two index files.

  Dataset EGAD50000000119

• Genome-wide NanoRCS of cfDNA from plasma of healthy individuals

  Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We adapted a new technique, NanoRCS, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to plasma of healthy controls.

  Study EGAS50000000695

• Splicing signature analysis of RNU4-2, RNU5A-1 and RNU5B-1

  Pathogenic variants in the snRNA RNU4-2 were recently described as a frequent cause of neurodevelopmental disorders. In our study we further delineate the phenotype associated with RNU4-2 and we also identify pathogenic variants in RNU5A-A and RNU5B-1. Capture-based RNA-Seq were performed to compare splicing pattern between affected and control individuals. A strong signature based on alternative 5' splice site usage was found for RNU4-2 patients, and we suggest an either 5' or 3' signature depending on the variant's localiztion in U5 genes.

  Study EGAS50000000889

• Copy Number Abnormalities of Chr1 in Multiple Myeloma at the Single Cell Level

  Single-cell whole genome sequencing (scWGS) provides a tool to gain deeper insights into the clonal relationships of Chr1 copy number changes. Here, we study Chr1 copy number alteration (CNA) using Direct library preparation plus (DLP+), a scalable scWGS platform implemented by image-based object recognition, and open-source computational methods. We report scWGS of 2,046 cells with 400-650 single-cells per patient from 5 Multiple Myeloma patients selected from our biobank with chr1q gains identified by iFISH using a CKS1B probe (IRB S21-01218 and I19-01384)

  Study phs004109

• WES of Mino-VEN-R Mantle Cell Lymphoma Cells

  This project investigates the genetic basis of therapy resistance in mantle cell lymphoma (MCL) using whole exome sequencing (WES) of the Mino_VEN_R cell line, a model of resistance to pirtobrutinib, a non-covalent BTK inhibitor. Our study suggested that drug-tolerant persister (DTP) cells evade therapy through metabolic and phenotypic reprogramming. By analyzing the exome profile of resistant cells, this study aims to identify mutations associated with treatment escape and cellular plasticity. The findings will contribute to a better understanding of resistance mechanisms and support the development of more effective therapeutic strategies.

  Study EGAS50000001088

• Sequencing Study in COPD cases and controls

  Since smokers with COPD have a higher risk of developing lung cancer than those without, we hypothesized that they carry more mutations in affected tissue. We called somatic mutations in airway brush samples from medium-coverage whole genome sequencing data from healthy never and ex-smokers (n=8), as well as from ex-smokers with variable degrees of COPD (n=4). Owing to the limited concordance of resulting calls between the applied tools we built a consensus, a strategy that was validated with high accuracy for cancer data.

  Study EGAS00001003406

• Celiac disease meta-analysis

  Celiac disease (CeD) is a common immune-mediated disease of the small intestine that is triggered by exposure to dietary gluten. While the HLA locus plays a major role in disease susceptibility, 39 non-HLA loci were also identified in a study of 24,269 individuals. We now build on this earlier study by adding 4,125 additional Caucasian samples including an Argentinian cohort genotyped on the Immunochip. In doing so, we not only confirm the previous associations, we also identify two novel independent genome-wide significant associations.

  Study EGAS00001003805

• Understanding_Society_GWAS

  The UK Household Longitudinal Study (Understanding Society https://www.understandingsociety.ac.uk/) aims to create and enhance a resource for a wide range of scientists, both social and biological, by combining the collection of biomarkers and psychosocial information with high quality longitudinal social and economic data about individuals and families. 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 EGAS00001001232

• Whole_exome_sequencing_of_young_onset_Primary_Sclerosing_Cholangitis

  Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence =10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWASand immunochip experiments to identify loci underlying PSC susceptibility. Through ourcollaborators at the University of Calgary we have access to DNA from three parent-offspringtrios where the children required liver transplants due to PSC before the age of 9. These areextremely rare cases indeed and we believe that exome-sequencing represents a powerfulmeans of identifying the causal mutation underlying this severe phenotype.

  Study EGAS00001000388

• Germline alterations of acute myeloid leukemia

  Germline variants may increase the risk of cancer. A systematic analysis was conducted of a consecutive series of primary and secondary adult acute myeloid leukemia (AML) patients. Exome sequencing was performed on leukemic blasts (somatic) and a skin biopsy (germline) followed by analysis on 35 acute myeloid leukemia or cancer predisposition candidate genes. Exome data were available from 68/80 (85%) patients, and full clinical history was available from all patients. The analysis revealed 34 rare single-nucleotide variants or short indels in 16 genes to be functionally adverse in silico.

  Study EGAS00001002760

• Placebo-only arm transcriptomic analysis of the phase 3 PROTECT clinical trial

  It is poorly understood how the tumor immune microenvironment influences disease recurrence in localized clear cell renal cell carcinoma (ccRCC). Here we perform whole-transcriptomic profiling of 236 tumors from patients assigned to the placebo-only arm of a randomized, adjuvant clinical trial for high-risk localized ccRCC. Unbiased pathway analysis identifies myeloid-derived interleukin-6 (IL-6) as a key mediator. Furthermore, a novel myeloid gene signature strongly correlates with disease recurrence and overall survival on uni- and multivariate analysis and is linked to TP53 inactivation across multiple datasets.

  Study EGAS00001006344

• Cystic fibrosis multi-omics study

  Cystic fibrosis (CF) is a genetic disorder affecting approximately 1 in 2,500 people in the UK. Here, we generated a number of high-throughput sequence data sets for monocytes and neutrophils from CF patients and matched healthy volunteers (HV); including ChIP-Seq (H3K27Ac), chromatin accessibility (ATAC-Seq), and transcript/gene expression (RNA-Seq) data. Analysis of gene expression and epigenetic profiles demonstrates a robust innate immune gene expression profile that distinguishes CF and HV during periods of disease exacerbation. Upregulation of pathways responsible for the production of proinflammatory cytokines is described.

  Study EGAS00001006421

• Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

  This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

  Study EGAS00001004942

• Single-cell RNA and ATAC sequencing data analysis of human postmenopausal fallopian tube and ovary

  In this study, we used a combination of technologies, including Drop-seq, 10X single-cell RNA-seq (scRNA-seq), and single-cell assay on transposase accessible chromatin (scATAC-seq) to generate  a high-quality cell atlas that consists of four tissue sites from the reproductive tract of postmenopausal women. This atlas, by far the most comprehensive map of the postmenopausal female reproductive system to date, will pave the way to a better understanding of the pathophysiology of many diseases affecting older women.

  Study EGAS00001006780

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• Single cell transcriptional evolution of myeloid leukaemia of Down syndrome – WGS

  Abstract: Children with Down syndrome have a 150-fold increased risk of developing myeloid leukaemia (ML-DS). Unusually for a childhood leukaemia, ML-DS arises from a preleukaemic state, termed transient abnormal myelopoiesis (TAM), and via a conserved sequence of mutations. Here, we examined the relationship between the genetic and transcriptional evolution of ML-DS from a rich collection of primary patient samples through single cell mRNA sequencing, complemented by phylogenetic analyses in progressive disease. We distilled the transcriptional consequence of each genetic step in the evolution of ML-DS, showing that TAM-defining GATA1 mutations account for most of the ML-DS transcriptome, including those of progressive disease. This transcriptional backbone may thus represent a common vulnerability in ML-DS. We extracted the transcriptional difference between TAM and ML-DS which, unexpectedly, reflected features shared across childhood leukaemia. Our approach delineates the transcriptional evolution of ML-DS and provides an analytical blueprint for distilling consequences of mutations directly from patient samples.

  Dataset EGAD00001015453

• Mitochondrial DNA sequencing in samples of Huntington’s disease patients

  Mitochondrial dysfunction is found in the brain and peripheral tissues of Huntington’s disease (HD) patients, which connects many pathological features of HD. In this project, we conducted a large-scale study of mtDNA variations with a sensitive mtDNA-targeted sequencing method called STAMP, at a median coverage of 4000-fold, in lymphoblast and blood samples of HD patients. mtDNA sequence variations and copy numbers were compared between samples from HD patients and healthy control individuals, and were assessed in relation to HD stages, and changes of HD phenotypes in longitudinal samples.

  Study EGAS00001004092

• A novel recurrent mutation in MITF predisposes to familial and sporadic melanoma

  We conducted whole-genome sequencing of probands from several melanoma families, identifying one individual carrying a novel germline variant (c.G1075A, NM_000248.3; p.E318K, NP_000239.1; rs149617956) in the melanoma lineage-specific oncogene MITF. While the variant cosegregated with melanoma in some, but not all cases in the family, linkage analysis of 31 families subsequently identified to carry the variant generated a LOD score of 2.7 under a dominant model, suggesting E318K as a possible intermediate risk variant. Consistent with this, E318K was significantly associated with melanoma in a large Australian case-control sample, giving an odds ratio (OR) of 2.33, 95% CI 1.21-4.70 (case and control carrier frequency, 0.0165 and 0.0072, respectively; P=0.008). Likewise, it was similarly associated in an independent case-control sample from the United Kingdom (UK P=0.012; combined P=0.0003, OR 2.19, 95% CI 1.41-3.45). In the Australian sample, the variant allele was significantly over-represented in cases with a family history of melanoma (OR 2.95, 95% CI 1.23-6.92), multiple primary melanomas (OR 4.22, 95% CI 1.52-10.91), or both (OR 8.37, 95% CI 2.58-23.80). The variant allele was also associated with increased nevus count (combined P=0.002, OR 2.54, 95% CI 1.42-4.55) and non-blue eye color (combined P=0.008, OR 2.01, 95% CI 1.11-3.81). Functional analysis of E318K showed that MITF encoded by the variant allele had impaired sumoylation and differentially regulated several MITF targets. These data indicate that MITF is a melanoma predisposition gene and highlights the utility of whole-genome sequencing to identify novel rare variants associated with disease susceptibility.

  Study phs000419

• A Missense SNP in the Tumor Suppressor SETD2 Reduces H3K36me3 and Mitotic Spindle Integrity in Drosophila

  While examining DNA from renal cell carcinoma (RCC) patients we observed a single nucleotide polymorphism (SNP; rs58906143,chr3:47163422 C→G (hg19); E902Q*) within SETD2 that was overrepresented in kidney cancer patients compared to control patients. This original study utilized directed sequencing of 14 genes. In an expanded study using a Taqman assay to study the specific SNP, a G allele was found in 72/493 cases (14.6%) and 24/356 (6.7%) controls. Analysis by ancestry revealed that there was there was a G allele in 50/119 (42.0%) cases and 21/71 (29.6%) controls in patients with African Ancestry while there was a G allele in 19/335 cases (5.7%) and 3/269 (1.1%) controls in patients with European Ancestry. These differences did not reach statistical significance. Concurrently, we studied the functional effect of this SNP in a Drosophila model. The homologous amino acid substitution at E741Q reduces H3K36me3 levels which could be rescued by wild type Set2. Additionally, the mutation resulted in significant defects in spindle morphogenesis, consistent with a role for SETD2 in alpha-tubulin methylation during mitosis. Data available through dbGAP include the 14 gene sequence files of 52 control and 128 RCC patients, the results of Taqman SNP (rs58906143) analysis in text files for 221 controls and 357 RCC patients, and compiled phenotype data including age and assigned race. Due to data use limitations, genotyping data for 8 RCC patients and 83 controls as well as GWAS data for ancestry determination will not be available on dbGaP, but will be made available on request.

  Study phs003474

• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - WXS

  B-PLL is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003275

• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - RNA-seq

  B-cell prolymphocytic leukemia (B-PLL) is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003274

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• 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