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• Single Cell Genome Sequence for DLP+ library A110660A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA610 passage 3 on DLP+ library A110660A

  Dataset EGAD00001009430

• Single Cell Genome Sequence for DLP+ library A118357B

  Single Cell Genome Sequence for Immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 cell line SA1188 on DLP+ library A118357B

  Dataset EGAD00001009431

• Single Cell Genome Sequence for DLP+ library A98181A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA919 passage 7, patient-derived xenograft SA1050A passage 1 on DLP+ library A98181A

  Dataset EGAD00001009479

• Single Cell Genome Sequence for DLP+ library A95632C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 6 on DLP+ library A95632C

  Dataset EGAD00001009322

• Single Cell Genome Sequence for DLP+ library A95628A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1162SB on DLP+ library A95628A

  Dataset EGAD00001009319

• Single Cell Genome Sequence for DLP+ library A95652B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A95652B

  Dataset EGAD00001009327

• Panel amplicon sequencing data of COVID-19 patients

  Amplicon sequencing data for 90 patients hospitalized for COVID-19. to general ward. Patients had a median age of 60.5 (52.0 – 69.3) years and were overweighted (Body mass index: 28.4 (24.4 – 32.6) kg/m2). 35.6% of the cohort were female. The following genes were sequenced on a NovaSeq600 instrument with an Enrichment based library preparation (IDT-xGEN) with a median coverage of 2000x: ABL1, ASXL1, ATRX, BCOR, BCORL1, BRAF, CALR, CBL, CBLB, CBLC, CDKN2A, CEBPA, CSF3R, CUX1, DNMT3A, ETV6, EZH2, FBXW7, FLT3, FLT3-ITD, GATA1, GATA2, GNAS, GNB1, HRAS, IDH1, IDH2, IKZF1, JAK2, JAK3, KDM6A, KIT, KMT2A, KRAS, MPL, MYD88, NOTCH1, NPM1, NRAS, PDGFRA, PHF6, PPM1D, PTEN, PTPN11, RAD21, RUNX1, SETBP1, SF3B1, SMC1A, SMC3, SRSF2, STAG2, TET2, TP53, U2AF1, WT1, ZRSR2

  Dataset EGAD00001009416

• 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. Exomes were enriched for using hybridisation selection and subject to DNA-sequencing. This datasets is formed of two batches as they were sequencing at different times. Batch-1 exomes were selected for using Nimblegen capture (4-plex) and sequenced on Illumina Hiseq 4000 and batch-2 was exome selected using Agilent SureSelect Human All Exon v6 and sequenced on the Illumina NovaSeq 6000. All samples within the same family were processed within the same batch. This dataset is comprised on BAM files mapped using cgpMAP v3.2.0 (bwa-mem) using the GRCh38.

  Dataset EGAD00001008671

• Cholangiocarcinoma

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting two datasets that contain NGS files from gastrointestinal rare cancers (n=119): - Dataset 2 (87 patients): Intra-hepatic cholangiocarcinoma (n=47), Extra-hepatic, cholangiocarcinoma (n=16), Not specified Cholangiocarcinoma (n=9), Small bowel adenocarcinoma (n=6) and other rare GI cancer (n=9)

  Dataset EGAD00001008968

• An IL-1β driven neutrophil-stromal cell axis fosters a BAFF-rich microenvironment in multiple myeloma

  This depository contains data from two bulk RNA sequencing experiments: 1) Bulk RNA sequencing data of peripheral blood neutrophils from healthy donors cultured with a) human adipose-derived stromal cells (ADSC) as a model for mesenchymal stromal cells (MSC), and b) IL-1β stimulated ADSC as a model for inflammatory MSC as found in multiple myeloma (MM). 2) Bulk RNA sequencing data from ADSCs cultured a) without stimuli, b) with recombinant human IL-1β, c) with supernatant from iMSC-like cells, d) with neutrophils previously cultured with MSC, e) with neutrophils previously cultured with iMSC, f) with neutrophils previously cultured with iMSC in the presence of anti-human IL-1β or g) with neutrophils previously cultured with iMSC in the presence of an isotype control.

  Dataset EGAD00001010080

• Timing chromosomal amplification events using patterns of somatic mutations in high hyperdiploid acute lymphoblastic leukemia

  This dataset included 19 paired diagnostic and remission samples with high hyperdiploid acute lymphoblastic leukemia (ALL) that were collected from four different cohorts: the Division of Clinical Genetics, Lund University, Sweden. All samples were subjected to whole genome sequencing using the Illumina HiSeqX platform. Paired-end sequencing (2x150bp) was done to ~60x coverage for diagnostic samples and ~30x coverage for remission samples. The paired-end reads were aligned to the human reference genome GRCh37 (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/vertebrate_mammalian/Homo_sapiens/all_assembly_versions/GCF_000001405.25_GRCh37.p13/GCF_000001405.25_GRCh37.p13_genomic.fna.gz) by the Burrows-Wheeler Aligner tool (version 0.7.17). Duplicate reads marking and local realignment were performed by GATK (version 4.0.11.0).

  Dataset EGAD00001010103

• Acral Melanoma PDXs from the admixed Brazilian Population - Patient Derived Xenograft samples VCF files with somatic SNV and INDELs - Whole exome sequencing data

  Raw, flagged and annotated VCF files with somatic calls made with CavEMan and Pindel for Patient Derived Xenograft samples. Variant effect prediction was run with Ensembl VEP v103. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015749

• RNA Expression in Diverse Donor Derived Dermal Fibroblasts Correlates with Reprogramming to Pluripotency

  The cohort used in this study includes 36 African American (17 female, 19 male) and 36 White American (19 female, 17 male) individuals. The total cohort has a median age of 32 years, with a range of 20-64 years. The African American cohort has a median age of 34, with a range of 21-52 years. The White American cohort has a median age of 31, with a range of 20-64 years. Primary dermal fibroblast lines were derived from skin biopsies obtained from adult individuals at the NIEHS under institutional review board approved protocol human subjects 10-E-0063, "Sample Collection Registry for Quality Control of Biological and Environmental Specimens and Assay Development and Testing protocol" (ClinicalTrials.gov #NCT01087307). All participants gave written informed consent for tissue donation. Donor sex, age, and ancestry were voluntarily self-reported. Fibroblast cells were reprogrammed via lentiviral transduction using six transcription factors contained in three plasmids (ADDGENE/PSIN4-EF2-N2L, ADDGENE/PSIN4-EF2-O2S and ADDGENE/PSIN4-CMV-K2M). Reprogramming efficiency was determined by alkaline phosphatase staining of triplicate 10cm reprogrammed dishes containing colonies, which were then scanned. The saved images were analyzed with ImageJ 1.51h (Wayne Rasband, National Institutes of Health, USA) to count colonies, using color threshold adjusted and binary converted images of each dish. Triplicate plates were averaged and reported as colony counts or percent reprogramming efficiency ((# of colonies/250,000) x100). The African American cohort had reprogramming efficiencies ranging from 0.06-1.37%, with a median of 0.655%. The White American cohort had reprogramming efficiencies ranging from 0.02-1.13%, with a median of 0.455%. Our goal was to define transcriptomic heterogeneity that could be contributing to differences in reprogramming efficiency between individuals and between groups. Total RNA was obtained from dermal fibroblasts and matched iPSCs. For each sample, 500 ng total RNA was used as input for preparation of whole transcriptome rRNA depleted libraries. An adapter-ligated library was prepared with the KAPA HyperPrep Kit (KAPA Biosystems, Wilmington, MA) using Bioo Scientific NEXTflex™ DNA Barcoded Adapters (Bioo Scientific, Austin, TX, USA) according to KAPA-provided protocol. Sequencing was performed using an Illumina HiSeq 2500 following Illumina-provided protocols for 2x150 bp paired-end sequencing. Each transcriptome was sequenced to a target depth of 125 million reads. The following mean raw reads were obtained: African American dermal fibroblasts= 129,571,450; White American dermal fibroblasts= 131,939,505; African American iPSCs= 132,501,335; White American iPSCs= 134,394,164. Raw reads were aligned to hg19 using the STAR alignment tool (https://github.com/alexdobin/STAR). The following mean aligned reads were obtained: African American dermal fibroblasts= 123,315,343; White American dermal fibroblasts= 125,178,035; African American iPSCs= 123,148,312; White American iPSCs= 123,886,992. Reprinted from L. C. Mackey et al., Epigenetic Enzymes, Age, and Ancestry Regulate the Efficiency of Human iPSC Reprogramming. Stem Cells 36, 1697-1708 (2018), with permission from Wiley. Reprinted from L. S. Bisogno et al., Ancestry-dependent gene expression correlates with reprogramming to pluripotency and multiple dynamic biological processes. Science Advances 6 (47) (2020) (PMID: 33219026), with permission from AAAS.

  Study phs002341

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Gene Discovery in Autosomal Dominant Focal Segmental Glomerulosclerosis (FSGS)

  Focal segmental glomerulosclerosis (FSGS) is a frequent cause of end-stage renal disease. The pathogenesis of FSGS has not been precisely defined and there are no consistently effective treatments. Recent studies identifying causal genes in rare, inherited FSGS, including our own study, have associated mutations in at least six genes with familial FSGS, and each discovery has clarified molecular mechanisms of glomerular injury. To build on this productive line of inquiry, we have ascertained and carefully characterized 118 families with familial FSGS. We have screened the remainder of our families for mutations in genes known to cause FSGS and identified the causal mutations in an additional 6 kindreds; the genetic basis of disease in the remaining 111 families is unknown. The objective of this proposal is to use this valuable and unique family resource to systematically identify causal genes for familial FSGS. Limitations of current conventional linkage and positional cloning approaches include their requirement for large, multiplex families. In addition, narrowing candidate areas in traditional linkage analysis can be difficult due to large regions that lack recombination events and hence these regions have required cumbersome and lengthy screening for causative mutations. Powerful new genetic tools can facilitate this screening process and improve variant discovery in smaller families. In particular, efficient whole-exome sequencing, the targeted capture of protein-coding gene sequences, should be particularly useful in our studies since most Mendelian disorders are caused by mutations affecting exomes of the target gene. Thus, by combining genome-wide linkage analysis (GWLS) and whole-exome sequencing, we can maximize impact of our family data and accelerate identification of novel mutations in FSGS. In preliminary studies, we have used this combination to identify a novel variant in the WT1 (Wilms' Tumor-1) gene in one FSGS family, and we have evidence suggesting it is the causal mutation. This success provides proof-of-concept and provides a roadmap of how genes will be identified and evaluated in the proposed studies. Our hypothesis is that causes of inherited FSGS in our cohort of families will be sequence variants in the coding region of genes not previously associated with familial FSGS. We aim to: 1) Use GWLS and whole-exome sequencing to identify genetic variants associated with familial FSGS. 2) Characterize functional consequences of candidate causative mutations and 3) Determine the prevalence in the Duke FSGS dataset of these new causative mutations identified in Aim 2. Any genes found to have causative mutations will be sequenced in the remaining families and take full advantage of our family resource. By combining genome-wide linkage analysis (GWLS), whole-exome sequencing, and characterization of variants' functional consequences, we will significantly improve understanding of normal glomerular biology and of the pathogenesis of FSGS and related glomerular diseases. Moreover, our discoveries are likely to reveal new opportunities to improve therapy for a disease that currently has few effective treatments.

  Study phs000777

• Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectivesHypertension Study: To determine whether treatment with a calcium channel blocker or an angiotensin-converting enzyme inhibitor lowers the incidence of coronary heart disease (CHD) or other cardiovascular disease (CVD) events vs treatment with a diuretic.Lipid Study: To determine whether pravastatin compared with usual care reduces all-cause mortality in older, moderately hypercholesterolemic, hypertensive participants with at least an additional CHD risk factor. BackgroundHypertension Study: Antihypertensive therapy is well established to reduce hypertension-related morbidity and mortality, but the optimal first-step therapy is unknown.Lipid Study: Studies have demonstrated that statins administered to individuals with risk factors for coronary heart disease (CHD) reduce CHD events. However, many of these studies were too small to assess all-cause mortality or outcomes in important subgroups.ParticipantsHypertension Study: A total of 33,357 participants. Lipid Study: A total of 10,355 participants. Baseline mean total cholesterol was 224 mg/dL; LDL-C, 146 mg/dL; high-density lipoprotein cholesterol, 48 mg/dL; and triglycerides, 152 mg/dL. Mean age was 66 years; 49% were women, 38% black and 23% Hispanic, 14% had a history of CHD, and 35% had type 2 diabetes. DesignHypertension Study: A randomized, double-blind, active-controlled clinical trial conducted from February 1994 through March 2002. Participants were randomly assigned to receive chlorthalidone, 12.5 to 25 mg/d (n = 15,255); amlodipine, 2.5 to 10 mg/d (n = 9048); or lisinopril, 10 to 40 mg/d (n = 9054) for planned follow-up of approximately 4 to 8 years. The primary outcome was combined fatal CHD or nonfatal myocardial infarction, analyzed by intent-to-treat. Secondary outcomes were all-cause mortality, stroke, combined CHD (primary outcome, coronary revascularization, or angina with hospitalization), and combined CVD (combined CHD, stroke, treated angina without hospitalization, heart failure (HF), and peripheral arterial disease).Lipid Study: Multicenter (513 primarily community-based North American clinical centers), randomized, non-blinded trial conducted from 1994 through March 2002 in a subset of participants from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). The interventions in the trial were pravastatin, 40 mg/d, vs usual care. The primary outcome was all-cause mortality, with follow-up for up to 8 years. Secondary outcomes included non-fatal myocardial infarction or fatal CHD (CHD events) combined, cause-specific mortality, and cancer.ConclusionsHypertension Study: Thiazide-type diuretics are superior in preventing one or more major forms of CVD and are less expensive. They should be preferred for first-step antihypertensive therapy.Lipid Study: Pravastatin did not reduce either all-cause mortality or CHD significantly when compared with usual care in older participants with well-controlled hypertension and moderately elevated LDL-C. The results may be due to the modest differential in total cholesterol (9.6%) and LDL-C (16.7%) between pravastatin and usual care compared with prior statin trials supporting cardiovascular disease prevention.

  Study phs004021

• Transcriptomic analysis of liver CD8+ T cells

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS The liver is bathed in bacterial products including LPS transported from the intestinal portal vasculature, but maintains a state of tolerance exploited by persistent pathogens and tumours1,2,3,4. The cellular basis mediating this tolerance, yet allowing a switch to immunity or immunopathology, needs to be better understood for successful immunotherapy of liver diseases. Here we show that a variable proportion of CD8+T-cells compartmentalised in the human liver co-stain for CD14 and other prototypic myeloid membrane proteins; CD14+CD8+T-cells preferentially accumulate within the donor pool in liver allografts, amongst hepatic virus-specific and tumour-infiltrating responses, and in cirrhotic ascites. CD14+CD8+T-cells exhibit increased turnover, activation and constitutive immunomodulatory features with high homeostatic IL-10/IL-2 production directly ex vivo, and an enhanced capacity to rapidly produce antiviral/anti-tumour cytokines upon TCR engagement. This CD14+CD8+T-cell profile can be recapitulated by acquisition of membrane proteins, including the LPS receptor complex, from mononuclear phagocytes, resulting in augmented tumour killing by TCR-redirected T-cells in vitro. CD14+CD8+T-cells express integrins and chemokine receptors favouring interactions with the local stroma, which can promote their induction through CXCL12. LPS can also increase the frequency of CD14+CD8+T-cells in vitro and in vivo, and skew their function towards the production of chemotactic and regenerative cytokines. Thus, bacterial products in the gut-liver axis and tissue stromal factors can tune liver immunity by driving myeloid instruction of CD8+T-cells with immunomodulatory capacity. For the analysis of the single cell transcriptome two intrahepatic perfusate samples were isolated and frozen at -80 'C for storage prior to transportation to Newcastle, UK. Once thawed in pre-warmed HBSS containing 0.001% DNaseI, intrahepatic leukocytes were sorted by FACS to index classical mononuclear phagocytes (MNP) defined as Singlets, CD3-CD56-CD19-CD14hiHLA-DR+ or CD14± CD8+T-cells as follows: Singlets, CD3+CD56-CD19-CD4-CD8+V7.2- and split in to CD14± based on an isotype control. Single cells were sorted into 96-well skirted LoBind plates (Eppendorf) containing 5 µL lysis buffer (TCL buffer [Qiagen], supplemented with 1% b-mercaptoethanol [Sigma Aldrich; Merck]) on a BD Bioscience FACSFusion. The sorted plates were subsequently immediately sealed, centrifuged, and placed on dry ice to flash-freeze the cell lysate and stored at -80 'C. A modified SMART-seq2 protocol57 was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Study EGAS00001006885

• Regulatory and Effector T cells in Oral Immunotherapy for Food Allergy

  This study consisted of a clinical trial for peanut oral immunotherapy (OIT) and a follow-up project (see below). Patients were included from 2013-2015, and samples from the last timepoints were collected in 2017. The study focused on peanut-specific CD4+ T cell responses before, during, and after OIT with peanut protein. We analyzed T cell gene expression, cytokine production, and T cell receptor β (TCRβ) and TCRα clonotypes, both in bulk T cell populations and single cells, and sought to correlate these data with differences in clinical sensitivity between peanut-allergic patients before OIT, and with differences in clinical outcome after OIT. The goal was to better understand the role of peanut-specific effector and regulatory T cells in peanut allergy and tolerance, which may inform more effective therapies (e.g., OIT combined with biologicals, probiotics, or adjuvants) in the future. Tolerance Following Peanut Oral Immunotherapy (PNOIT2, NCT01750879): The unifying objective of this project is to determine whether peanut oral immunotherapy (PNOIT)-induced clinical tolerance in the context of food allergy is significantly associated with the expansion of a specific regulatory T cell subset (CD45RA-, CD25++, FoxP3+ +) that is thought to be inducible in the gut-associated lymphoid compartment and associated with immunological tolerance. The hypothesis of the study is that the induction of Treg cells will be associated with clinical tolerance. The investigators will measure the change from baseline of induced Treg cells as a frequency of total CD4+ T cells during active treatment and compare that between participants who achieve significant clinical tolerance and those who do not. High Threshold Peanut Challenge Study (PAID-UP, NCT02698033): This protocol was designed to better characterize a sub-population of peanut-sensitized individuals who may be non-allergic, despite significant sensitization, or who may be allergic, but at high threshold doses. By specifically targeting participants who met the initial screening criteria of an earlier study, NCT01750879, but failed to react during the pre-treatment 443 mg challenge to peanut, the investigators anticipate that they will identify individuals who have become spontaneously tolerant, despite persistent sensitization. The investigators might also find that clinical sensitivity persists but only with higher thresholds, or that sensitivity has increased (or is variable) since the previous allergen exposure. By repeating food challenges through to a full serving dose (7.4 gram), the investigators will distinguish participants who react only at higher doses from those who were not truly peanut-allergic, address whether their sensitivity has changed, and have the opportunity to further investigate their immune response to peanut allergen. Methods: Peripheral blood mononuclear cells were isolated from patient blood samples, and stimulated with peanut protein. Peanut-activated CD4+ T cells were sorted based on the activation marker CD154. For a more recent study, the activation marker CD137 was used as well. Total RNA from peanut-activated CD154+ and resting CD154- CD69- T cells was used for cDNA synthesis and amplification (SMARTer ultra low input RNA kit for sequencing - v3; Clontech Laboratories). Libraries were prepared and sequenced on the Illumina HiSeq platform, at a read depth of approximately 30 million reads per sample. Genomic DNA from CD154+ and CD154- CD69- T cells was used to amplify and sequence the TCRβ CDR3 regions (immunoSEQ assay; Adaptive Biotechnologies). The immunoSEQ approach generates an 87 base-pair fragment capable of identifying the VDJ region spanning each unique CDR3. Amplicons were sequenced using the Illumina NextSeq platform. Using a baseline developed from a suite of synthetic templates, primer concentrations and computational corrections were used to correct for the primer bias common to multiplex PCR reactions. Raw sequence data were filtered on the basis of TCRβ V, D, and J gene definitions provided by the IMGT database (www.imgt.org) and binned using a modified nearest-neighbor algorithm to merge closely related sequences and remove both PCR and sequencing errors. For single-cell analysis, we aimed to recover TCR variable sequences from high-throughput single-cell libraries generated by popular platforms such as SeqWell and DropSeq. We paired TCR information with T cell single-cell RNA sequencing results from patients undergoing peanut OIT to show clonal expansion-related T cell phenotypes.

  Study phs001897

• Spit for Science

  Spit for Science™ is a university-wide research opportunity with the scientific goal of understanding how genetic and environmental factors come together to influence substance use and emotional health across the college years and beyond. To address this goal, we have comprehensively and longitudinally studied eligible incoming freshmen (18 years or older) from a diverse urban university, assessing a wide range of risk and protective factors, including both biological susceptibility and environmental risk, and a variety of outcome measures, particularly alcohol use and other substances, and difficulties with emotional health. Our goal is to assess how risk and protective factors dynamically interact to contribute to behavior health outcomes over time and plan to use findings from the project to inform prevention and intervention efforts and aid in university policy and programming in ways that can support and promote student success. Methods: In the fall of their freshman year, first-time college students over the age of 18 are invited to complete an online survey containing broad questions about personality and behavior, as well as family, friends, and experiences growing up. Students can also provide a saliva sample and participate in the DNA component of the project (participation in the DNA component is not a requirement for participation in the survey). Each subsequent spring students are asked to complete a follow-up survey, enabling researchers to study patterns of substance use and emotional health across the college years.

  Study phs001754

• 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

• The Genetics of Type 2 Diabetes Consortium (GoT2D): Low-Pass Sequencing and High-Density SNP Genotyping for Type 2 Diabetes

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (EGA), by virtue of the project specific funding requirements.

  Study phs000840

• Risk Factors for Asymptomatic Diverticulosis

  Data for this analysis came from a prospective study of colonic diverticulosis at the University of North Carolina Hospital in Chapel Hill, North Carolina (NIH R01DK094738). This is a case-control genetic and transcriptomic study to identify the genetic and cellular determinants underlying colonic diverticulosis and the relationship with other gastrointestinal disorders. The study inclusion and exclusion are described below. DNA and RNA sequencing were performed on colonic tissue from 404 patients with (N=172) and without (N=232) diverticulosis. We assessed variation in the transcriptome associated with diverticulosis and integrated this variation with human intestine single-cell RNA-seq data. We integrated our expression quantitative trait loci with GWAS using Mendelian Randomization. A polygenic risk score analysis examined associations between severity of diverticulosis and other gastrointestinal disorders. We identified 38 genes with differential expression and 17 genes with varied transcript usage linked to diverticulosis. Our results suggest tissue remodeling as a primary mechanism for diverticula formation. The presence of diverticulosis was linked to stromal and epithelial cells in the colon including endothelial cells, myofibroblasts, fibroblasts, goblet, tuft, enterocytes, neurons, and glia. MR highlighted five genes including CCN3, CRISPLD2, ENTPD7, PHGR1, and TNFSF13. In diverticulosis cases, ENTPD7 upregulation was confirmed. A greater burden of diverticula was positively correlated with genetic predisposition to diverticulitis. The data related to the study including total RNA-Seq, SNP array and imputed genotypes will be available through dbGaP.

  Study phs003556

• UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

  Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

  Study phs002504

• 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

• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• deep-learning-powered tissue deconvolution for cfDNA

  Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

  Study EGAS00001007213

• NIPT samples for systematic evaluation of BinDel, a software tool for detecting clinically significant microdeletions in low-coverage WGS-based NIPT samples

  This dataset contains three sets of samples. The first sample set contains euploid fetus pregnancies reported by NIPTIFY screening test and postnatal evaluation. Dataset was processed similarly to previously published guidelines from KU Leuven, with modifications [1]. Briefly, peripheral blood samples were collected in cell-free DNA BCT tubes (Streck, USA), and plasma was separated with standard dual centrifugation. Cell-free DNA was extracted from 3 ml plasma using MagMAX Cell-Free DNA Isolation Kit (ThermoFisher Scientific). Whole-genome libraries were prepared using the FOCUS (Fragmented DNA Compact Sequencing Assay, Competence Centre on Health Technologies, Estonia) NIPT method protocol with 12 cycles for the final PCR enrichment step. In the following quantification, equal amounts of 36 samples were pooled, and the quality and quantity of the pool were assessed on Agilent 2200 TapeStation (Agilent Technologies, USA). Whole genome sequencing was performed on the NextSeq 550 instrument (Illumina Inc.) with an average coverage of 0.32× (minimum 0.08 and maximum 0.42) and producing 85 bp single-end reads. The second sample set contains a single NIPT sample postnatally diagnosed with Prader-Willi syndrome. The sample was sequenced with Illumina NextSeq 500 platform, producing 85 bp single-end reads with an average per-sample coverage of 0.32× at the University of Tartu, Institute of Genomics Core Facility, according to the manufacturer’s standard protocols, as described previously [2]. The third sample set contains samples SC005 (SeraCare Life Sciences Inc lot #10446565), SC0042 (#10571706), and SC016 (#10560229). These are SeraCare Life Sciences Inc circulating cell-free DNA (ccfDNA) like mixture of human genomic DNA that consists of matched maternal and fetus. SC005 and SC0042 consist of matched DNA of maternal and fetus with DiGeorge Syndrome. SC016 is a custom-ordered DNA Mix with fetus DNA having a pathogenic loss of the terminal region of 20p13 and a pathogenic 3q29 duplication. SC016 was processed as the first sample set was processed, and SC0042 was processed as the second sample set was processed. Sample SC005 was processed once as was sample set 1 and once as was sample set 2 processed. This study was performed with the approval of the Research Ethics Committee of the University of Tartu (#352/M-12). 1. Bayindir B, Dehaspe L, Brison N, Brady P, Ardui S, Kammoun M, et al. Noninvasive prenatal testing using a novel analysis pipeline to screen for all autosomal fetal aneuploidies improves pregnancy management. Eur J Hum Genet. 2015;23: 1286– 1293. doi:10.1038/ejhg.2014.282 2. Žilina O, Rekker K, Kaplinski L, Sauk M, Paluoja P, Teder H, et al. Creating basis for introducing noninvasive prenatal testing in the Estonian public health setting. Prenat Diagn. 2019;39: 1262–1268. doi:10.1002/pd.5578

  Dataset EGAD00001009512

• COVID-19 Exome Sequencing DAC policy

  This is the DAC policy for exome sequencing data from COVID-19 patients from EASI genomics and NIMgentics and belonging to the study "Variability in immune response genes and prediction of severe SARS-CoV-2 infection(INMUNGEN-Cov2 project)"

  Dac EGAC50000000065

• Identification of genetic mutations characteristic for recurrence of serous ovarian cancer.

  Establishment of novel therapeutic strategy to overcome intractable cancer by molecular profiling of serous ovarian cancer

  Study JGAS000104

• Massachusetts General Hospital Cancer Center DAC for single cell RNA-seq data from small cell lung cancer primary tumors and CTCs

  single cell RNA-seq data from 10 small cell lung cancer primary tumors and circulating tumor cells of three small cell lung cancer patients

  Dac EGAC50000000808

• TRACERx NSCLC - whole genome sequencing for ctDNA study

  An ultra-sensitive and specific ctDNA assay provides novel pre-operative disease stratification in early stage lung adenocarcinoma

  Study EGAS50000000313

• cell-free Methylated DNA by Immunoprecipitation and Sequencing (cfMeDIP) of human meningioma samples.

  Raw data for cell-free Methylated DNA by Immunoprecipitation and Sequencing (cfMeDIP) of human meningioma samples.

  Dataset EGAD50000002214

• Clonal hematopoiesis detection in the INSPIRE trial cohort of Pembrolizumab in patients with metastatic solid tumours

  Targeted DNA sequencing bam files from pre-treatment peripheral blood mononuclear cells collected from patients on the NCT02644369 Phase II trial of Pembrolizumab for metastatic solid tumours

  Dataset EGAD50000001696

• Long-read RNA-sequencing of three adult human neural retina samples for 17 lncRNA loci.

  Long-read direct cDNA sequencing (Oxford Nanopore Technologies) of three independent post-mortem human retina samples of 17 lncRNA loci.

  Dataset EGAD50000001402

• Khoe-San whole genome sequencing

  High-coverage (>30X) whole genome data (FASTQ) for 25 southern African Khoe-San individuals (from five populations). These are the same individuals as in Schlebusch et al. 2020 (EGAD00001006183), but different data.

  Dataset EGAD50000001559

• Bulk RNA-sequencing data from 9 cHL cell lines

  The dataset contains raw data of 27 bulk RNA-sequencing data from 9 cHL cell lines. Paired-end fastq with polyA capture are available for each cell line.

  Dataset EGAD50000001271

• Peripheral T cell lymphoma (PTCL) Shallow Whole Genome Sequencing

  Shallow Whole Genome Sequencing (sWGS) of 148 FFPE DNA samples from peripheral T cell lymphoma (PTCL) samples. Assoicated with the "Molecular biomarkers for stratification peripheral T cell lymphoma" study.

  Dataset EGAD50000001146

• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• Whole exome sequencing of two BPDCN patients for tracing clonal evolution

  Whole exome sequencing data was mapped to GRCh38 using bwa-mem2 as implemented in the nfcore sarek workflow.

  Dataset EGAD50000000309

• SECRETO Oral metagenome

  The dataset comprises data for n=329 participants who underwent saliva sampling. Shotgun metagenomic paired-end sequencing was conducted using the Illumina NovaSeq 6000 platform, and the resulting files are in FASTQ format.

  Dataset EGAD50000000283

• banfora_20150706_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - autosomes.

  Dataset EGAD00010002581

• OncoScan SNP data set for localized follicular lymphoma (lFL)

  149 unpaired initial tumor samples (133/149 FFPE and 16/149 fresh frozen samples) of lFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002593

• P50_P681_P763_PTC209_DMSO_24h_48h_72h_Illumina HT12v4_Gene_Expression.xlsx

  Expression dataset for DAC+PTC209 treated CD34 sorted primary CML bone marrow samples

  Dataset EGAD00010002210

• SNPArray_Thai

  The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 452 individuals generated and analyzed in Kutanan, Liu et al 2021 study of 33 ethnolinguistic groups in Thailand and Laos.

  Dataset EGAD00010002285

• Oncoscan SNP arrays for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 82 Oncoscan SNP tumor initial samples, zipped Affymetrix CEL file types, Oncoscan CNV FFPE Assay Kit, Thermo Fisher Scientific GeneChipTM Scanner 3000 7G

  Dataset EGAD00010001978

• Buccal Sample Methylation for Breast Cancer Detection

  This study encompasses buccal sample DNA methylation (IlluminaMethylationEPIC array) from breast cancer cases and healthy age-matched controls.

  Study EGAS00001007658

• Identifying new diagnostic and treatment pathways for patients with unclassifiable sarcomas

  Whole genome sequencing of tumour normal pairs of human undifferentiated sarcomas.

  Dataset EGAD00001003216

• TSG knock-out in hiPSCs (2017-08-10)

  We will perform RNAseq to evaluate the effects of the loss of a list of TSGs on the transcriptome. This dataset contains all the data available for this study on 2017-08-10.

  Dataset EGAD00001003556

• Exome - MBD4-deficient AML

  Exome sequencing for WEHI-AML-1 and WEHI-AML-2. Exome capture was performed with the Human All Exon v5_UTR Capture Library and the Agilent Technologies SureSelectXT2 Target Enrichment System, with sequencing on an Illumina HiSeq2500.

  Dataset EGAD00001003570

• RNA Sequencing of human fetal brain (FBSeq)

  FastQ files with paired-end RNAseq data for human fetal brain homogenate from 120 samples (12-19 post-conception weeks).

  Dataset EGAD00001004363