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• Breakpoint detection using long insert whole genome sequencing

  In this study, we hypothesize that shallow long insert whole genome sequencing (LI-WGS) increases our power for detecting breakpoints compared to shallow short insert WGS. We performed a priori analyses to demonstrate the benefits of LI-WGS, developed a long insert library preparation protocol based off Illumina's protocol, and compared LI-WGS against short insert WGS on test samples. We then used long insert WGS to identify translocations and copy number changes in tumor and germline samples collected from cancer patients with different malignancies.

  Study phs000646

• 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.

  Study EGAS50000000086

• Multiomic Landscape of Multiple Myeloma Precursor and Relapsed Disease

  Multiple myeloma (MM) is a treatable, though incurable, plasma cell malignancy. The molecular mechanisms driving disease onset and the emergence of drug resistance remain elusive. To better characterize the mutational, transcriptional, and epigenetic alterations that accompany MM disease evolution, we accessed molecular data from MM patients treated at Moffitt Cancer Center, with bone marrow biopsies collected between 2011 and 2023.We performed scMultiome (single-cell, paired RNA/ATAC-Seq, 10x Genomics) on 18 CD138+-selected bone marrow aspirate samples, including: 2 healthy donors, 3 patients with monoclonal gammopathy of undetermined significance (MGUS), 4 with smoldering myeloma (SMM), 3 with newly diagnosed MM (NDMM), 1 with early relapse MM (ERMM, 1 to 3 lines of therapy), and 5 with late relapse MM (LRMM, 4 or more lines of therapy). Our dataset includes a sequential sample: a patient with a premalignant condition ("scMultiome_SMM_4") that progressed to active myeloma ("scMultiome_NDMM_3"). These data allow for the assessment of transcriptional and epigenetic dysregulation at the cellular level. Our findings illustrate the dynamic epigenetic and transcriptional landscapes that accompany MM disease progression.We also conducted CUT&Tag analysis on 4 NDMM and 4 LRMM samples to map histone modifications, specifically H3K27ac, to investigate their role in transcriptional reprogramming observed in advanced stages of MM. This analysis revealed sample heterogeneity in terms of super-enhancer-regulated genes associated with active transcription.This cohort also includes samples from the clinical trial NCT04151667, “Daratumumab-Based Response-Adaptive Therapy for Older Adults With Newly Diagnosed Multiple Myeloma.” We performed scRNAseq (single-cell RNA sequencing, 10x Genomics) on 30 CD138+-selected bone marrow aspirate samples and 31 pre-sort samples featuring bone marrow mononuclear cells of various cell types from 5 healthy donors and 11 patients with newly diagnosed MM (NDMM). Our dataset includes sequential samples for all 11 NDMM patients, both prior to induction therapy (denoted by ‘a') with Daratumumab and Dexamethasone, and at cycle 2 day 22 (C2D22, i.e., 60 days after induction therapy start, denoted by ‘b'). For three NDMM patients, we also have samples at relapse (denoted by ‘c'). These data allow for the assessment of transcriptional dysregulation at the single-cell level in both the tumor and immune-tumor microenvironment, associated with Daratumumab treatment in NDMM patients.In addition to the molecular data, demographic, and phenotypic information for all samples is provided.

  Study phs003892

• Single-cell ATAC-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006559

• Single-cell RNA-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006560

• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• HiDEF-seq Single-Molecule Sequencing of Single-Strand Mismatches and Damage

  Our study sought to resolve, with single-molecule resolution, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detected base substitutions when present in either one or both DNA strands. We compared the fidelity for dsDNA mutations to that of the same samples profiled by NanoSeq duplex sequencing. We also detected cytosine deamination, a common type of DNA damage, with single-molecule resolution. We profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.The data available via dbGaP includes raw HiDEF-seq sequencing files (Pacific Biosciences subreads in BAM format), raw NanoSeq sequencing files (Illumina FASTQ format), and raw germline sequencing files (Illumina FASTQ format).The HiDEF-seq main publication contains a supplementary table with a list of accession IDs for each sample's files.

  Study phs003604

• Establishment of an iPSC Repository Derived from Healthy Volunteers

  Understanding the interaction between genetic variation and epigenetic variation remains a challenge due to the confounding role of environmental factors. We propose that human induced pluripotent stem cells (iPSCs) are an excellent model to study the relationship between genetic variation and epigenetic variation while controlling for consistent environmental factors. In this study, we have created a comprehensive resource of high-quality genomic, epigenomic, and transcriptomic data of six iPSC lines and three iPS-derived cell types (NSC, Motor Neuron, Monocyte) from three healthy donors. We found that epigenetic variation is most strongly associated with genetic variation at the iPSC stage, and that relationship weakens as epigenetic variation increases in the differentiated cells. Additionally, cell-type is a stronger source of epigenetic variation than genetic variation, highlighting that humans are far more similar than they are different, regardless of genetic background. Further, we have elucidated a utility of studying epigenetic variation in iPSCs and their derivatives for identifying important loci for GWAS studies and the cell-types in which they may be acting.

  Study phs003649

• Whole genome sequencing of pancreatic cystic fluid for early detection and diagnosis of pancreatic cancer

  Pancreatic cancer (PC) is a leading cause of cancer-related deaths globally. Accurate PC detection at early or premalignant stage, when surgery is effective, would increase survival rates and prevent unnecessary surgery or surveillance. Molecular diagnostic attempts using PCy fluid (PCyF), as a liquid biopsy, to analyze common mutations associated with PC development are yet to contribute to early diagnosis. Whole genome sequencing (WGS) is utilized in various cancers, PC inclusive, for detecting genetic changes associated with carcinogenesis, but not in PCyF due to technical limitations, including isolated DNA purity. The goal of the study was to achieve high quality of WGS from PCyF from 9 patients to enable development of signatures of malignancy. The WGS was performed using Illumina sequencing. Experimental design was at a 50x depth.

  Dataset EGAD50000000869

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Study

  The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits. The initial effort involved linkage analysis of affected-sibling-pair (ASP) families based on over 5,000 individuals living in Finland, and association fine mapping based on these family members and additional T2D cases and controls. We completed a genome-wide association scan on 1161 T2D cases and 1174 normal glucose tolerant (NGT) controls. Individual-level data is available for the 919 T2D cases and 787 NGT controls who reconsented to the use of their data or are deceased (phs000100). In addition, we selected these 919 T2D cases and a matched set of 919 NGT controls (774 overlapping with GWAS) for targeted sequencing of 78 genes associated with glucose, insulin, and/or lipids. 400 of these T2D cases were also chosen for whole-exome sequencing (phs000702).

  Study phs000867