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• BAM files: Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  cDNA depleted RNA (500ng total RNA input) was fragmented to 150-200 nucleotides in first strand buffer for 3 minutes at 94°C. Random hexamer primed first strand was generated in presence of dATP, dGTP, dCTP and cTTP. Second strand was generated using dUTP instead of dTTP to tag the second strand. Subsequent steps to generate the sequencing libraries were performed with the KAPA HTP Library Preparation Kit for Illumina sequencing with minor modifications, i.e., after indexed adapter ligation to the dsDNA fragments, the library was treated with USER enzyme (NEB_M5505L) in order to digest the second strand derived fragments. After amplification of the libraries, samples with unique sample indexes were pooled and sequenced paired-end 2x50bp on a HiSeq2500 system following standard Illumina guidelines.

  Dataset EGAD00001003806

• Miseq (18S) analysis of spiked placental tissue samples

  We spiked a small number of placental tissue samples with different combinations of Candida albicans, Plasmodium falciparum, Toxoplasma gondii, Human Cytolomega virus and Salmonella bongori (various combination of the equivalents of 1, 10, 100, 1000 and 10000 genome copies). A DNA isolation was performed on these spiked samples and the resulting DNA was subsequently sequenced by MiSeq (18S). These same samples were also analysed by X Ten to allow for a sensitivity comparison of the two methods of the eukaryotic spiked signals (Candida albicans, Plasmodium falciparum and Toxoplasma gondii). In addition, non-spiked placental samples from 50 cases of Fetal Growth Restriction (FGR) (+ matched healthy controls) and 49 cases of Preeclampsia (+ matched healthy controls) and 100 preterm cases were analyzed for their non-human eukaryotic content.

  Dataset EGAD00001004197

• Autozygosity pilot - QMUL

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing British-Pakistani cohort samples will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consists of low coverage whole exome sequencing on these samples.

  Dataset EGAD00001001027

• Genome Diversity in Africa Project - ancient samples - standard libraries

  Given the central importance of Africa to studies of human origins, genetic diversity and disease susceptibility, large-scale and representative characterisation of genetic diversity in Africa is needed. Analyses of ancient DNA from Africa would complement sequencing of modern African populations and provide unique opportunities to transform our understanding of the pre-history of the region. This approach would greatly refine our understanding of population structure and gene flow in Africa and globally, including genetic signatures of ancient admixture. This low coverage sequencing experiment will allow us to test and refine our pipeline for ancient DNA sequencing. 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/

  Dataset EGAD00001002211

• single cell RNA-seq of bone marrow from infants with MLL-rearranged Acute Lymphoblastic Leukemia by single cell RNA-sequencing

  This dataset contains two experiments. 1) Single cell RNA-seq of diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not). For some of the patients, multiple indipendent plates were produced (each plate is a sample). 2) in vitro prednisolone exposure experiment. diagnostic bone marrow samples from patient 4662R were cultured for three days with and without prednisolone. Single cell experiments were conducted according to Muraro et al (cell systems, 2016, doi:10.1016/j.cels.2016.09.002). Cell barcodes and UMI sequences are embedded in the header of each fastq entry. Cell barcodes irrelevant to this experiment were removed before submission.

  Dataset EGAD00001005461

• WES

  Exome Sequencing. 3 ug of genomic DNA from each lymph node sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001005424

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  It was a single-cell RNA sequencing study on the PBMC samples from four Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Single-cell analysis confirmed some of the signatures obtained from the bulk data. It identified that high IL32 in case samples in the bulk RNA-seq was contributed mainly by activated T cells and NK cells. Trajectory analysis of the scRNA-seq data suggested that IL32 expression increased as the T cells moved towards activated state.

  Dataset EGAD00001005768

• Profiling heterogeneity in Human derived IPSC-neurons (2020-05-18)

  The impact of genetic variants on molecular pathways that give rise to neurodegenerative diseases such as Alzheimer's and Parkinson's is best elucidated in the appropriate cell types and molecular contexts. Existing studies have focused on bulk profiling of mixed cell types, but have ignored assaying genetic effects across development and cell differentiation. At the core of this proposal is the idea to use single-cell assays to study genetic effects during differentiation of dopaminergic and cortical neurons to identify the sequence of molecular events from variants to healthy and diseased cell states in a cell-specific manner. 1) 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 please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2020-05-18.

  Dataset EGAD00001006157

• WGS and Avenio Surveillance Panel data to previously submitted data under study number EGAS00001004276 of ALK-rearranged lung cancer

  Some data was previously submitted data under study number EGAS00001004276. In this new dataset we provide additional WGS and Avenio Surveillance Panel data. We utilized 43 ALK+ NSCLC patients receiving targeted ALK therapy to evaluate ctDNA levels based on matched panel-based targeted next generation sequencing (tNGS) and untargeted shallow whole genome sequencing (sWGS). For the Avenio panel the sequencing was done on Illumina NextSeq 550 paired end 150 bp, for WGS the sequencing was done on Illumina HiSeq 4000, partly with KAPA_Hyper_Prep_Kit. In this dataset there are 132 WGS tumor samples and 134 panel sequencing data of plasma.

  Dataset EGAD00001007818

• Induction of trained immunity by influenza vaccine: impact on COVID-19

  Cryopreserved PBMCs from 10 individuals before and after vaccination were used to perform single cell RNA sequencing. Equal number of cells per individual were pooled together (5 individuals per pool) and single-cell RNA sequencing was performed in paired-end mode on NovaSeq 6000 (Illumina) with a depth of 50,000 reads per cell. DNA was isolated from PBMCs and then used for genotyping by Illumina GSA Beadchip. This dataset contains the fastq sequence files, genotypes of the donors used for demultiplexing the pools and files indicating the linkages between individuals, pools and fastq files. The number of samples listed by EGA does not match the actual number of samples due to limitations on the upload scheme used.

  Dataset EGAD00001007827

• RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC

  RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC. CD34+ hematopoietic stem cells (HSC) were isolated from healthy controls before transduction with WT-SRC and E527K-SRC lentiviral vectors in triplicate and differentiation to MK. Three replicates each of two pools were generated for both WT and E527K SRC transduced cells, resulting in 3 WT pool 1 samples, 3 WT pool 2 samples, 3 E527K pool 1 samples and 3 E527K pool 2 samples for a total of 12 samples. RNA was extracted and sequenced with following parameters: Platform: Illumina HiSeq4000, Library Prep Kit: TruSeq stranded mRNA, Sequencing Kit: Illumina HiSeq4000 100 cycles (76-8-8-7), Fragments: single end / fr-firststrand.

  Dataset EGAD00001008356

• 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

• 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

• Single Cell Genome Sequence for DLP+ library A108847B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1182E passage 1 on DLP+ library A108847B

  Dataset EGAD00001009429

• 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

• 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

• 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

• 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

• 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

• 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

• NKI-AvL CRC-OVC RNA-seq

  The dataset “NKI-AvL CRC-OVC RNA-seq" includes 4 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004341

• 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

• GIS-LUNGTCR1-2016_VAL-BAM

  This dataset contains BAM files of targeted Amplicon deep-sequencing data, for validation of the mutations found in WES. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors.

  Dataset EGAD00001001980

• Analysis of somatic mutations in normal blood, AML and MDS samples

  Targeted pulldown of genes known to be recurrently mutated in AML & MDS from patient and normal samples using Agilent Sureselect and for some cases also using Illumina Truseq technology.

  Dataset EGAD00001002180

• Lymphocyte RNA profiling

  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/

  Dataset EGAD00001002183

• Set of Structural Variants and Indels for GoNL samples

  These files contain indels and structural variants on 769 GoNL samples (SV release 6, 2016-05-25).

  Dataset EGAD00001002261

• eFORGE software tool BLUEPRINT dataset

  DNase accessibility data for BLUEPRINT consortium immune cells included in eFORGE software tool

  Dataset EGAD00001002713

• Expression profiling of pediatric brain tumors Embryonal Tumor with Multilayered Rosettes (ETMR)

  RNA was prepared using the IlluminaTruSeq RNA sample preparation kit for poly-adenylated mRNA with an average of 97.64 million reads per sample respectively

  Dataset EGAD00001004803

• IL2 data set including 59 samples

  The dataset is referenced by EGA Study ID EGAS00001003605, which includes the short-reads data for 59 samples. All short-reads data files are in fastq format.

  Dataset EGAD00001004967

• FASTQ Files for Human LV H3K27ac ChIP-seq

  This dataset contains 70 human LV H3K27ac ChIP-seq paired-end FASTQ files. The sequencing was performed using Illumina Hiseq 4000.

  Dataset EGAD00001004945

• ChIP-seq for GOF p53

  This dataset includes ChIP-seq data from two cell lines (HKCI-11 (GOFp53) and MIHA(WT p53)). All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005449

• Whole Genome Sequencing of Normal Singaporean Volunteers

  Whole-genome sequencing (WGS) data for 546 Singaporean volunteers used to estimate WGS-LTL in the study. Samples were sequenced using Illumina Hiseq X to a mean coverage of 30X.

  Dataset EGAD00001005480

• Whole Exome Data for two affected individuals in a family with severe congenital neutropenia (SCN).

  Raw Whole Exome Sequencing data from Blood samples drawn from related Female participants presenting severe congenital neutropenia.

  Dataset EGAD00001005937

• RNAseq for brainstem glioma

  RNAseq on Illumina HiSeq X Ten of brainstem glioma primary tumor sample

  Dataset EGAD00001006094

• long RNA data

  long RNA data for 27 CLL samples (8 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005968

• Therapeutic vulnerabilities in the DNA damage response for the treatment of ATRX mutant neuroblastoma

  Whole genome sequencing data of isogenic ATRX/TP53 knockout clones of the neuroblastoma cell line SK-N-SH

  Dataset EGAD00001006294

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

• Clinical dataset (new)

  ctDNA guiding adjuvant immunotherapy in urothelial carcinoma (Nature 2021). ABACUS clinical data cut (2020) used in 2021 paper: Clinical data include PCR, RFS_months, RFS_event, and OUTCOME for 40 patients in ABACUS with ctDNA data.

  Dataset EGAD00001007578

• Hypoxia acts as an environmental cue for the human TRM differentiation program

  Dataset consists of 19 bam files from RNA sequencing experiments batch1 and batch2.

  Dataset EGAD00001007692

• GCAT| PCAs GCATcoreSpain V2

  First 20 principal components of 4988 genotyped GCAT Cohort individuals with Infinium Multi-Ethnic Global (MEGAEX2) array, with data for Cr1-22. Plink files with QC and imputed (SHAPEIT+IMPUTE).

  Dataset EGAD00001007730

• Sequencing files for 7 melanoma patients

  Files from whole exome sequencing of matched normals and multiple tumors from 7 melanoma patients. The tumors include primary tumors and distant metastases.

  Dataset EGAD00001006410

• B15PON dataset

  Organoid cultures derived from normal colon and/or colorectal adenomas and/or colorectal carcinomas. RNA and DNA was isolated from these cultures for genome wide profiling.

  Dataset EGAD00001008411

• SNP array data in Massim study

  The compressed file contains plink format file for the Illumina MEGA SNP array data of 255 individuals generated and analyzed in Liu et al study of genom-wide variation of the Massim region.

  Dataset EGAD00001008545

• Genomic determination for Homologous Recombination Deficiency (HRD) by shallow Whole Genome Sequencing (sWGS)

  Homologous recombination deficiency (HRD) score in a large cohort of 55 triple-negative breast cancer PDX

  Dataset EGAD00001008839

• Dataset for Stromal-induced epithelial-mesenchymal transition induces drug resistance in acute lymphoblastic leukemia

  RNA-seq was performed to compare gene expression profiles between 11 patient adherent ALL samples and nonadherent ALL samples.

  Dataset EGAD00001009056

• Clinical data

  Clinical data from AVANT: Clinical data include race, age, sex, baseline ecog, tumor stage, node status, treatment arm, KRAS and BRAF mutation status, tumor location, concensus molecular subtype, overall survival and disease free survival for 797 patients across AVANT.

  Dataset EGAD00001009727

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Dataset EGAD00001009427

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult Spatial (2025-07-31)

  Spatial transcriptome analysis of the human heart . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015666

• 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

• 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

• 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

• 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

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study

  This is a case-control study of primary open angle glaucoma (POAG). POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. For this study we have formed a collaborative consortium contributing 2170 POAG cases and 2347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition has also been harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The NEIGHBOR consortium has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). The consortium includes eleven different centers where data collection and analysis take place. The eleven sites and investigators are: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman, D. Zack); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Eye Institute (X01HG005259).

  Study phs000238

• Starr County Health Studies' Genetics of Diabetes Study

  An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented and also a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies. The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls. In the first instance we have identified a subset of unrelated cases from the total cases that we have identified. Where multiply affected sibships were available, the youngest onset case with detailed phenotyping (including assessment of diabetic retinopathy) was selected. Controls came from a recent survey to establish a representative sample of the Starr County population. Blocks were randomly selected, households on selected blocks enumerated and one individual randomly selected from each household for a detailed examination. The examination included an oral glucose tolerance test. Those included as controls are those with no prior diagnosis of diabetes and a negative oral glucose tolerance test. This collection of cases and controls provides the opportunity to identify susceptibility loci for type 2 diabetes and its complications, specifically diabetic retinopathy and albuminuria. The data set also allows the examination of impaired fasting glucose and impaired glucose tolerance. The samples are split between those born in the United States and those born in Mexico and this gives a natural contrast for examining genotype and environmental interactions. It is anticipated that the understanding that will come will lead to strategies for delaying and preventing the onset of diabetes and its complications.

  Study phs000143

• Genome-Wide Association of Native and Post Aspirin Platelet Function Phenotypes

  The goal of this study was to identify genetic variants in a genome-wide association study (GWAS) that are associated with previously obtained platelet function phenotypes measured in each individual under baseline conditions and following 2 weeks of low dose aspirin (ASA). During this study we performed a high density 1 million-SNP genome scan on subjects from GeneSTAR (representing 800 2-generational families with a family history of premature coronary artery disease, 60% white and 40% African American, N=3232). We identified genomic loci associated with quantitative platelet phenotypes prioritized for their biological interest, determined associations between genomic loci and baseline platelet phenotypes (primary phenotypes are platelet aggregation in platelet rich plasma induced by collagen, adenosine diphosphate (ADP), arachidonic acid (AA), and epinephrine (Epi), determined associations between genomic loci and post-ASA platelet phenotypes, ie, measures of ASA "resistance" (primary phenotypes are as above, plus urinary levels of the prostaglandin metabolite, 11-dehydro-thromboxane B2 ), and compared peaks of association between genomic loci and three common baseline platelet phenotypes (collagen-, epinephrine-, and ADP-induced aggregation in platelet rich plasma) with associations found for these same phenotypes in the Framingham Heart Study. We also determined whether any significant genotype-phenotype associations in the 1 million SNP genome scan could be localized to any specific genes or potential genes of interest using publicly available databases and further examined whether candidate genes previously associated with a specific platelet phenotype are located in a genomic region of interest as determined from the SNP genome scan. We conducted replications of our findings, and are presently involved in larger scale meta-analysis of findings for pre-aspirin and post-aspirin associations. The study population is constituted of full siblings (SIBS) (ages 35-78 years) identified from The Johns Hopkins Sibling Study, now called GeneSTAR, the spouses of the SIBS, and their adult offspring (>21 years of age). They include 3200 individuals from approximately 300 African American and 500 white extended families. "Spouse" refers to the other parent of any SIB offspring, independent of marital status. Sibship sizes among families range from 1 to 16 (excluding index cases). On average, each SIB has 2 potentially eligible offspring. A family for this study is defined by all of the full sibships and the total numbers of offspring that come from all SIBS, rather than just the nuclear family.

  Study phs000375

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on >600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children’s Oncology Group (COG) Biopathology Center.

  Study phs002304

• De Novo Mutation Rates at the Single-Mutation Resolution in the Human Genome

  We developed a method to measure the origination rates of target mutations of choice and applied it to the HbS and nearby mutations in the human beta-globin (HBB) gene, as well as to the equivalent mutations in the nearly identical delta-globin (HBD) gene in sperm cells from African and European donors. Specifically, after extracting DNA from the sperm of the donors, each sample is enriched for the HbS mutation and nearby mutations by the restriction enzyme Bsu36I, which cleaves the wild-type (WT) sequence CCTGAGG at positions 16–22 of HBB and the homologous positions of HBD while leaving the HbS mutant and other mutants in these positions intact. Next, unique barcodes are attached to the DNA fragments from these Bsu36I-treated samples in order to reduce error by consensus sequencing of copies originating from the same original fragment. To determine how many target WT sequences have been removed (scanned) by Bsu36I digestion and hence to be able to calculate the de novo mutation rate, we run a second reaction in parallel for each donor. This reaction involves the same steps as the former reaction except for digestion by Bsu36I (Bsu36I-untreated). Spiking into the Bsu36I-treated and untreated samples known amounts of mock HBB-like DNA molecules that are fully resistant to Bsu36I digestion allows to calculate in the sequence analysis stage the Bsu36I-enrichment score based on the change in their frequency between the two treatments, which in turn is used to calculate the number of scanned WT sequences. Our results show significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than Europeans in the HBB region studied. Finally, the rate of the 20A>T mutation, called the “HbS mutation” when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations, and no instances were observed in the European HBB ROI or in the European or African HBD ROI.12 consented subjects; samples from two subjects were pooled

  Study phs002391

• Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

  With the development of triple combination antiretroviral therapy, routine HIV treatment eliminates nearly all actively infected cells. Nevertheless, the small reservoir of latently infected cells, which can remain dormant for long periods of time before becoming active and producing new virus particles, represents a crucial barrier to completely curing the disease. Identifying markers that identify latently infected cells or the biochemical factors that control latency activation could enable the effective use of a “shock and kill” strategy, where specific targeting or activation of latently infected cells eliminates the viral reservoir. Our recent work suggests that the global transcriptomic and epigenomic changes during hematopoietic differentiation affect viral latency and activation. Additionally, we recently found that global inhibition of histone deacetylase activity increases viral activation in these cells, further implicating epigenomic changes during activation. These results raise fundamental questions: What are the markers of latently infected cells? How do the transcriptomic and epigenomic states of a cell affect latency and activation? How does the differentiation state relate to viral latency? Here, we leverage our experimental platform for identifying latently and actively infected cells, single-cell transcriptome and epigenome sequencing, and our recently developed computational integration methods to investigate these questions. Our interdisciplinary team combines expertise in HIV basic science, HIV clinical treatment, and bioinformatics to develop an experimental and computational framework for integrated gene expression, chromatin accessibility, and lineage into a single picture of viral latency and activation. Specifically, this project will (1) use single-cell RNA-seq and single-cell ATAC-seq to map the diversity of infected cells, (2) investigate the relationship between hematopoietic differentiation state and viral activation, (3) determine viral integration sites through single-cell RNA-seq, (4) computationally integrate single-cell transcriptome and epigenome profiles, and (5) computationally infer cell lineage relationships among viral genomes and infected cells. To accomplish these goals, we will carry out the following aims: (1) Characterize lineage, transcriptomic and epigenomic diversity of single latently and actively infected primary cells. (2) Investigate latency and activation during in vitro differentiation. (3) Survey single cell diversity of re-activated and in vitro infected cells from cART-suppressed patients. Together, these aims will produce a comprehensive, integrated transcriptomic and epigenomic atlas of the HIV reservoir, identify DNA and RNA biomarkers of latency, and characterize clonal expansion patterns. Our work also develops a broadly applicable experimental and computational framework, laying a foundation for the discovery of novel insights into HIV latency and activation.

  Study phs002915

• Single-Cell Mitochondrial Mutation Lineage Tracing of Non-Dysplastic and Dysplastic Barrett's Esophagus

  This study addresses a critical knowledge gap in understanding Barrett's esophagus (BE), a common metaplastic condition and precursor to esophageal adenocarcinoma, by identifying lineage connections and cell states underlying its development and malignant transformation. We collected biopsies from 13 Barrett's esophagus patients undergoing routine surveillance endoscopy, sampling metaplastic tissue alongside normal squamous esophagus and gastric cardia tissues when clinically appropriate. Our novel approach integrated single-cell RNA sequencing of nearly 180,000 cells with mitochondrial DNA mutation analysis for lineage tracing, coupled with spatial transcriptomics and comprehensive whole-exome sequencing. For one patient with high-grade dysplasia, we performed detailed whole-exome sequencing analysis at 100x coverage on dissociated Barrett's esophagus cells alongside matched normal esophagus and gastric cardia tissues. This genomic profiling revealed critical genetic drivers of malignant transformation, including a truncating mutation in the mutation cluster region of APC (a negative WNT regulator), mutations in the tumor suppressor genes CDKN2A and TP53, and significant copy number alterations including loss of CDKN2A on chromosome 9. These genetic alterations corresponded with the transcriptional changes observed in our single-cell data, particularly WNT pathway dysregulation and the expansion of LGR5-expressing stem cells, providing molecular evidence for how single clones can initiate the dysplastic transformation. Data deposited in dbGaP consist specifically of the whole-exome sequencing raw files, processed variant calls, and copy number analyses from the single patient with high-grade dysplasia and matched normal esophagus and stomach control tissue. Whole exome sequencing was performed on an Illumina NovaSeq 6000. Sequencing data was preprocessed following the Genome Analysis Toolkit's (GATK) Best Practices. Sequencing data was analyzed with Mutect2 (GATK, v4.2.5.0) to identify short somatic mutations including single-nucleotide polymorphisms and insertions and deletions. The Barrett's esophagus sample was run with the two matched normals, as well as the publicly available germline resource somatic-hg38_af-only-gnomad.hg38.vcf.gz (GATK). Somatic variant calls were filtered using FilterMutectCalls (GATK) and loaded into the Integrative Genomics Viewer (v2.12.3) for identification of high-quality variants in known esophageal adenocarcinoma regulators. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9). CNV, Mutect2, and SVC analyses will be made available through dbGAP. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9) with the default run settings; a pooled reference was generated from the normal esophagus and stomach samples. Copy number results were plotted directly within CNVkit using the function scatter.

  Study phs003949

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Study EGAS50000000156

• Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain

  These data are derived from iterative data collection and analysis partly reported in three primary publications (Gibbs et al., 2010, PMID: 20485568, Hernandez et al. 2011, PMID: 21216877, Hernandez et al. 2012, PMID: 22433082). This study includes an assessment of common genetic variability across the genome, chip based gene expression analysis and array based methylation analysis, across a series of 150 subjects from whom we had cerebellum, frontal cortex, pons, and temporal cortex tissue (600 tissue samples). In each tissue we assessed 27,578 DNA methylation sites and the expression level of 22,184 genes. This work was then expanded to include assessment of 232 additional subjects and two tissues (cerebellum and frontal cortex) for whom we collected genotype, RNA expression and DNA methylation data.

  Study phs000249

• DNA Methylation Analysis of Peripheral Blood Cells from Siblings Discordant for ASD

  Autism is a common disorder whose causes are poorly understood. Both genetic and environmental influences are thought to act together causing autism. Epigenetics is an area that bridges genetic and environmental influencing and commonly is studied by examining dynamic methylation changes to the DNA. We have screened a total of 78 autistic boys and their fathers by this method in 807 genes and find 116 methylation changes that together can correctly identify nearly 80% of the affected boys from their fathers. We propose to confirm these exciting data in a much larger set of genes in 1,200 autistic boys and their families, including unaffected brothers. These data not only could provide new insight into the causes of autism but could also result in a screening test for autism.

  Study phs000619

• Developing Targeted Therapy for Patients with Multiple Myeloma and Gain or Amplification of Chr1q (1q+)

  Multiple myeloma (MM) frequently presents with gain or amplification of chr1q (1q+), which is associated with inferior response to treatment and poor outcomes. To develop targeted therapy for MM with 1q+, we leveraged external and in-house dependency screens and drug screens, along with single-cell sequencing of patient tumors with subclonal 1q+. We demonstrated that MM with 1q+ exhibits higher sensitivity to MCL1 and PI3K inhibitors, which may be synergistic and act through established and novel mechanisms. Two human MM cell lines with 1q+, KMS12BM and KMS11, were profiled with either single-cell RNA-sequencing (scRNA-seq) alone (KMS12BM, KMS11) or both scRNA-seq and whole-genome sequencing (WGS; KMS12BM) to understand the factors that determine response to MCL1 and PI3K inhibitors and how these inhibitors work.

  Study phs003886

• Truncated FOS impairs osteogenic differentiation and induces prostaglandin and NFkB signalling in an in vitro cell-of-origin model for osteoid osteoma and osteoblastoma

  The effect of FOS truncation on osteogenic differentiation and proliferation was investigated in an in vitro model for osteoid osteoma and osteoblastoma. In this model, truncated FOS (FOSΔ) was overexpressed in human foetal mesenchymal stem cells through a lentiviral vector. Osteogenic differentiation - assessed by measuring mineralization, ALPL expression and ALP activity - and proliferation rate were reduced in cells overexpressing FOSΔ compared to mesenchymal stem cells with an empty lentiviral vector (pLV). Transcriptome-sequencing and differential gene expression analysis revealed decreased gene expression of genes in pathways involving cell cycling and mitosis, and osteogenic differentiation, including WNT signalling, extracellular matrix (ECM) organization and matrix metalloproteinases (MMPs), in FOSΔ as compared to empty vector cells, indicating decreased proliferation and osteogenesis.

  Study EGAS50000001291

• Head and neck tumor organoid biobank for modelling individual responses to radiation therapy according to the TP53/ HPV status

  Head and neck cancers (HNC) represent an extremely heterogeneous group of diseases with a poorly predictable therapy outcome. Here, we have established a comprehensive molecularly and functionally characterized head and neck organoid biobank recapitulating the clinically relevant subtypes of TP53 mutant and human papillomavirus type 16 (HPV 16) infection-driven HNC. Organoids were exposed to radiotherapy and genetically engineered normal and tumor organoids were used for testing the direct functional consequences of TP53-loss and HPV infection. We identified subtype-associated transcriptomic signatures and pathological features, including sensitivity to TP53 stabilization by the MDM2 inhibitor Nutlin-3. TP53 loss-of-function alone was insufficient to promote radiation resistance, whereas HPV 16 oncogenes E6/E7 mediated radiosensitivity via induction of cell cycle arrest.

  Study EGAS50000001219

• Microbiota 16S sequencing study in NSCLC patients eligible for surgery without neoadjuvant treatment

  18 non-small cell lung cancer patients eligible for surgery without neaodjuvant treatment were included in the study at Centre Jean Perrin (France). Patients did not take any antibiotics, food supplements or immunostimulants 2 months prior to inclusion. During surgery, patients underwent partial or complete lobectomy where samples of non-malignant lung tissue, peritumoural tissue and tumour were resected from the removed lobe. This was preceeded by the washing of the removed lobe and obtaining the broncho-alveolar lavage fluid. These four sample types were analysed by 16S sequencing in 17 from 18 patients. The study is a part of the project "Characterization of Microbiota (Intestinal, From Lungs, and Upper Airways) in Patients With Non-small Cell Lung Carcinoma: Exploratory Study " which is registered under ref. NCT03068663 (clinicaltrials.gov).

  Study EGAS00001004728

• Identification of the underlying causal variant in a multi-generational family with autosomal dominant common variable immunodeficiency

  Common variable immunodeficiency (CVID) is the most common form of primary immunodeficiency with an estimated incidence of 1:10,000. It has been apparent for many years that CVID has a genetic component, occurs frequently in families and can have both a recessive or dominant mode of inheritance. In recent years, 4 genes underlying CVID have been identified; however, mutations within in them are estimated to account for no more than 10% of all cases of CVID. We have identified a multi-generational family with autosomal dominant CVID. Genome-wide linkage analysis has mapped the locus underlying CVID in this family to an approximately 9.2 Mb interval on chromosome 3q27.3-q29, between the markers D3S3570 and D3S1265. This locus is distinct from any of the previously mapped susceptibility loci suggesting a novel genetic variant is responsible for disease in this family. The aim of this study is to use exome sequencing of affected (n = 4) and unaffected (n = 4) individuals, in tandem with the available genetic mapping data, to identify the causal variant underlying CVID in this family.

  Dataset EGAD00001000363

• WGoxBS and SureSelect data of the POPS placenta samples

  We carried out whole-genome oxidative bisulfite sequencing (WGoxBS) in the placentas of two healthy female and two healthy male pregnancies generating an average genome depth of coverage of 25x. The sex-specific differential methylation pattern observed in this region was validated in additional 8 healthy placentas (including 2 from the WGoxBS) using SureSelect in-solution target capture. For WGoxBS, placental genomic DNA (4 µg) from 4 healthy pregnancies was processed to achieve 10 kb fragments with the g-Tube (Covaris), according to the manufacturer's instructions. To increase the number of uniquely sequenced reads, two independent libraries were generated for each individual. Multiplexed sequencing was carried out on the Illumina MiSeq, HiSeq 2000, and HiSeq 2500 instruments with 2x100, 2x50 and 2x125 cycles using MiSeq Reagent Kit v3, HiSeq SBS Kit v3 and HiSeq SBS Kit v4, respectively. For SureSelect in-solution capture, placental genomic DNA (3.5 µg) from 8 healthy pregnancies (including 2 from the WGoxBS) was fragmented by the Covaris S220 system according to the SureSelect Methyl-Seq target enrichment protocol (Agilent). All 8 libraries were pooled and sequenced on the Illumina HiSeq 2500 instrument with 2 × 125 cycles using HiSeq SBS Kit v4 and a single lane of the Illumina HiSeq 4000 instrument with 2 × 150 cycles using HiSeq 3000/4000 SBS Kit following Illumina's guidelines (Illumina Application Note: Epigenetics February 2016).

  Dataset EGAD00001003136