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• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005990

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005991

• Maastricht IBS 16S data

  Maastricht IBS cohort with biobank aims to identify subgroups of IBS according to phenotypical and genotypical characterization. This dataset represents 16S amlicon sequencing of the gut microbiome of case samples and matched controls. Fecal DNA was extracted using the Qiagen AllPrep kit with bead-beating step. Sequencing of bacterial 16S gene, domain V4, was performed using the Illumina MiSeq platform.

  Dataset EGAD00001007074

• Inherited MUTYH mutations cause elevated somatic mutation rates and distinctive mutational signatures in normal human cells

  Cellular DNA damage caused by reactive oxygen species is repaired by the base excision repair (BER) pathway which includes the DNA glycosylase MUTYH. Inherited biallelic MUTYH mutations cause predisposition to colorectal adenomas and carcinoma. However, the mechanistic progression from germline MUTYH mutations to MUTYH-Associated Polyposis (MAP) is incompletely understood. Here, we sequenced normal cell DNAs from 10 individuals with MAP and study the somatic mutation burden and mutational signatures.

  Dataset EGAD00001007997

• 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

• Pre-activated anti-viral innate immunity in the upper airways controls early SARS-CoV-2 infection in children

  We investigated 10 female and 14 male SARS-CoV-2 positive children (age range: 0.8 to 18 years). Based on the WHO guidelines, 15 patients were classified as having mild COVID-19, while 7 children were classified as moderate COVID-19 cases. Two children were asymptomatic. 8 female and 10 male SARS-CoV-2 negative children were included as controls (age range: 4 to 16). 12 SARS-CoV-2 positive female and 9 male adults were included ( age range: 27 - 76) together with 13 female and 10 male SARS-CoV-2 negative adult controls (age: 24 - 77). 10 adult COVID-19 patients had mild disease, while 12 had moderate COVID-19. We performed single-cell RNA sequencing experiments.

  Dataset EGAD00001007969

• Resequencing candidate genes for male spermatogenic impairment

  This study aims to identify novel candidate variants from human Y-chromosomal genes DAZ, BPY2 and CDY1/2 by resequencing the coding regions of these genes from male patients with spermatogenic impairment. The coding regions of the genes plus a selection of phylogenetically informative Y-chromosomal markers have been amplified by standard PCR, amplicon lengths range from 178 to 486 bp. Amplicons were quantified by gel electrophoresis and pooled in approx. equimolar concentrations per patient. For each of the 480 submitted samples, approx. 1 microgram of amplified DNA pool was provided in a total volume of 120 microlitres. The samples were indexed and libraries prepared for PE250bp Illumina MiSeq runs. 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 EGAD00001006784

• Single nuclei sequencing of early, late-term, and early-onset pre-eclamptic decidua and villi.

  Hypertensive disorders in pregnancy, of which the multisystem syndrome pre-eclampsia is the most severe, leading to preterm delivery, maternal mortality, and life-long complications. To elucidate early disease dynamics, we present the first spatio-temporal study comparing single-nuclei transcriptomes of human preterm pre-eclamptic placentae and healthy controls, contextualizing this in a comprehensive study including early and late gestational placentae. This study includes early placentae samples from the fetal part (villi; n=10), maternal part (Decidua; n=3), late placentae samples from healthy pregnancies, villi (n=6), decidua (n=4), and late placentae samples from early-onset preeclamptic pregnancies, villi (n=5) and decidua (n=5).

  Dataset EGAD00001008273

• Full blood mRNA sequencing of myotonic dystrophy type 1 patients after cognitive behavioural therapy

  This dataset consists of 60 mRNA sequencing runs from full blood of 31 myotonic dystrophy type 1 patients, of which for 27 patients reliable data is available before and after 10 months of cognitive behavioural therapy. >30 million 150 bp paired end reads were obtained with UMI-labeled adapters to facilitate filtering of PCR duplicates. Via UMI-analysis we found samples with the aliases sample_01 and sample_02 to contain a very high number of PCR duplicates and recommend the use of these samples only with highest caution or not at all.

  Dataset EGAD00001008383

• WGS of cell-free DNA derived from plasma of CRC patients and healthy controls, and WGS of matched tumor tissue and saliva

  This dataset contains: 1.) Whole-genome sequencing (WGS) data (~6x) of 259 cfDNA samples obtained from 50 colorectal cancer (CRC) patients and 61 healthy controls. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38). 2.) WGS data (~1x) of 50 tumor biopsy and 45 saliva samples from CRC patients. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009309

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  We provide whole exome DNA sequening data in fastq format for 23 clinical samples of chronic myeloid leukemia stem cells (CML-SC) plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed hematopoietic stem cells (HSC) at remission were selected from bone marrow samples by FACS, according to newly identified genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform.

  Dataset EGAD00001009847

• scRNAseq of distal colon biopsies from patients with ulcerative colitis and healthy controls

  scRNAseq dataset of colonic epithelium from distal colon biopsies from 4 patients with ulcerative colitis and 4 healthy individuals. Includes 11 samples split into three conditions: healthy, healthy margin and ulcerated. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into 4 lanes and into index (I1) and read (R1, R2) files. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Cell Ranger (v3.0.1) software from 10x Genomics was used to process the output and align the reads. The refdata-cellranger-GRCh38-3.0.0 reference was downloaded from the 10x Genomics website. First, cellranger mkfastq function was used to demultiplex raw base call files into FASTQ files. Then, the FASTQ files were aligned and filtered with cellranger count function.

  Dataset EGAD00001010167

• Estimating transcription factor variability in PC-9 cells using scRNA-seq

  PC-9 cells were barcoded following protocol from Chang et al. Nature Biotech. 2021, which does not affect downstream analysis. PC-9 cells were trypsinized into single-cell suspensions and processed using Chromium Single Cell Gene Expression 3’ Library and Gel Bead Kit V2.0 following the manufacturer’s instructions (10X Genomics). Cells were counted and checked for viability using Vi-CELL XR cell counter (Beckman Coulter), and then injected into microfluidic chips to form Gel Beads-in-Emulsion (GEMs) in the 10X Chromium instrument. Reverse transcription was performed on the GEMs, and RT products were purified and amplified. Expression libraries were made from the cDNA and profiled using the Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified with Kapa Library Quantification Kit (Kapa Biosystems). Illumina HiSeq2500 (Illumina) was used to sequence the libraries.

  Dataset EGAD00001011041

• An MTOR mutation hitchhikes through renal embryogenesis, driving multifocal, multiphenotypic tumours - WGS

  Embryogenesis is a vulnerable time. Mutations in developmental cells can result in the seeding of cells predisposed to disease within mature organs, creating a field effect. We characterise an embryonic cancer mutation that drives multifocal, multiphenotypic renal tumours in a 14-year-old girl. Their shared MTOR mutation, absent from normal tissues, increases protein flexibility which enables a FAT domain hinge to dramatically increase mTORC1 activity. Developmental mutations, not usually detected in traditional genetic screening, have vital clinical importance in guiding prognosis, targeted treatment, and family screening decisions for paediatric tumours.

  Dataset EGAD00001011645

• An MTOR mutation hitchhikes through renal embryogenesis, driving multifocal, multiphenotypic tumours - RNA

  Embryogenesis is a vulnerable time. Mutations in developmental cells can result in the seeding of cells predisposed to disease within mature organs, creating a field effect. We characterise an embryonic cancer mutation that drives multifocal, multiphenotypic renal tumours in a 14-year-old girl. Their shared MTOR mutation, absent from normal tissues, increases protein flexibility which enables a FAT domain hinge to dramatically increase mTORC1 activity. Developmental mutations, not usually detected in traditional genetic screening, have vital clinical importance in guiding prognosis, targeted treatment, and family screening decisions for paediatric tumours.

  Dataset EGAD00001011646

• An MTOR mutation hitchhikes through renal embryogenesis, driving multifocal, multiphenotypic tumours - scRNA

  Embryogenesis is a vulnerable time. Mutations in developmental cells can result in the seeding of cells predisposed to disease within mature organs, creating a field effect. We characterise an embryonic cancer mutation that drives multifocal, multiphenotypic renal tumours in a 14-year-old girl. Their shared MTOR mutation, absent from normal tissues, increases protein flexibility which enables a FAT domain hinge to dramatically increase mTORC1 activity. Developmental mutations, not usually detected in traditional genetic screening, have vital clinical importance in guiding prognosis, targeted treatment, and family screening decisions for paediatric tumours.

  Dataset EGAD00001011647

• Combination Immune Checkpoint Inhibition in Australian Rare Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Dataset EGAD00001015465

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• Transcriptomic profiling of Hedgehog-high and Hedgehog-low HPV-negative HNSCC

  This study investigates transcriptomic differences between Hedgehog-high and Hedgehog-low HPV-negative head and neck squamous cell carcinoma (HNSCC). Tumors were stratified based on pathway-level genomic alteration scores and imaging-associated Hedgehog activity. RNA sequencing was performed on archival FFPE tumor samples to assess pathway activation and transcriptional programs associated with Hedgehog signaling. The dataset supports integrative radiogenomic and functional analyses of tumor-intrinsic signaling pathways.

  Study EGAS50000001549

• Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification in gynecological cancer based on whole-exome sequencing and epigenomic analysis

  We collected 157 oral MPA-treatment samples from 66 cases (53 endometrial hyperplasia from 31 cases, 19 atypical polypoid adenomyoma from 14 cases, 1 normal endometrium from 1 case, and 84 endometrial carcinoma from 53 cases) and matched normal tissues/whole blood. The purpose of this study is to develop actionable molecular targets and/or biomarkers for prognostication and patient stratification.

  Study JGAS000813

• Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional associated phenotype information is available for all individuals included in this study directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04.

  Study EGAS00001006033

• The Gut Microbiome of liver transplant recipients – Cross-sectional + Longitudinal (renal and liver)

  TransplantLines is designed as a single-center, prospective cohort study and biobank including all different types of solid organ transplant recipients as well as living organ donors. In the TransplantLines gut microbiome study the gut microbiome of solid organ transplant recipients is characterized and linked to clinical phenotypes. This batch contains the cross-sectional data from liver transplant recipients and longitudinal data from renal and liver transplant recipients.

  Study EGAS00001006258

• SEARCH for Diabetes in Youth Study - Genetic Risk Score

  Genetic risk scores (GRS) quantify polygenic disease risk into a single measure and can aid in disease classification. GRS studies have focused primarily on adult populations of recent European ancestry. We aimed to assess the utility of GRS in classification of diabetes type among racially/ethnically diverse youth in the United States. We used data from SEARCH baseline visits and follow up visits for which key data elements were available. 2260 participants are included. Phenotypic Data to be submitted here include: Self-reported sex, race and ethnicity Diabetes type determined by provider Etiologic diabetes type T1D (antibody positive, or antibody negative/missing and insulin sensitive) T2D (antibody negative and insulin resistant) Diabetes duration (years) Age at diagnosis (years) Measures from baseline, SEARCH 3 (follow-up) and SEARCH 4 (follow-up): Age Height Weight Waist circumference HbA1c Fasting/non-fasting glucose C-peptide Triglycerides HDL LDL Systolic Blood Pressure Diastolic Blood Pressure Measures from SEARCH 3 and 4:Arterial stiffness as characterized by PWVRetinopathy Measures from SEARCH 4 only: LV structure and diastolic function measurements from echocardiogram GAD autoantibody IAD autoantibody ZnT8 autoantibody We performed genotyping using the Illumina Multi-Ethnic Global Array (MEGA) array with 1,697,069 genotyped variants including 748,291 with minor allele frequency <0.01. Genotyping and preliminary quality control checks were performed at the Colorado Center for Personalized Medicine. After additional quality control, 2,238 samples and 900,743 variants remained for analyses. Samples genotyped on the MEGA array were categorized using SEARCH etiologic type and consisted of predominantly type 1 diabetes cases (n=2,051) but also those with other diabetes (n=133 type 2 diabetes, n=52 other diabetes including monogenic diabetes; genetic confirmation with either a genetic clinical test or test performed as an ancillary study to SEARCH). The median reported age at DNA collection was 11.2 years (interquartile range 7.6 – 14.1) with a minimum age of 1.9 years and maximum of 21.9 years. We used additional data genotyped on the Affymetrix 500K imputation scaffold chip with 239,279 genotyped variants. This cohort consisted of predominantly type 2 diabetes cases (n=417) but also those with type 1 (n=104), and other diabetes types (n=16). After additional quality control, 537 samples and 235,967 variants remained. The median reported age at collection was 11.2 years (quartile range 8.1 – 14.2) with a minimum of 2.0 years and a maximum of 21.1 years. About 100 type 2 diabetes cases were also genotyped using the MEGA chip to ensure concordance between the data sets and facilitate strand alignment between the two chips before genotypic imputation. The data sets had n=230,228 genotyped variants in common and concordance between the genotypes was high (mean correlation r2 for SNPs used in GRS=0.95). We used the 1000 Genomes reference panel to impute each data set separately, resulting in a total of 34.5M and 27.8M well-imputed variants (r2>0.8) for the MEGA and Affymetrix data sets respectively. We combined high quality imputed variants for analysis.

  Study phs002703

• HBCC Postmortem Psychiatric Molecular Studies

  This postmortem study examines molecular, genetic and epigenetic signatures in the brains of hundreds of subjects with or without mental disorders conducted by the DIRP NIMH Human Brain Collection Core (HBCC). The brain tissues are obtained under protocols approved by the CNS IRB (NCT00001260), with the permission of the next-of-kin (NOK) through the Offices of the Chief Medical Examiners (MEOs) in the District of Columbia, Northern Virginia and Central Virginia. Additional samples were obtained from the University of Maryland Brain and Tissue Bank (contracts NO1-HD-4-3368 and NO1-HD-4-3383) (http://www.medschool.umaryland.edu/btbank/ and the Stanley Medical Research Institute: http://www.stanleyresearch.org/brain-research/). Clinical characterization, neuropathological screening, toxicological analyses, and dissections of various brain regions were performed as previously described (Lipska et al. 2006; PMID: 16997002). All patients met DSM-IV criteria for a lifetime Axis I diagnosis of psychiatric disorders including schizophrenia or schizoaffective disorder, bipolar disorder and major depression. Controls had no history of psychiatric diagnoses or addictions. SNP array: Array-based genotyping was performed on most samples published in this collection. The number of SNPs assayed via Illumina chips varied between 650,000 and 5 Million. Cerebellar tissue was generally used for genotyping studies. # Diagnosis SNP Array 1 Anxiety Disorder 1 2 Autism Spectrum Disorder 13 3 Bipolar Disorder 114 4 Control 387 5 Eating Disorder (ED) 2 6 Major Depressive Disorder (MDD) 186 7 Obsessive Compulsive Disorder (OCD) 5 8 Post-Traumatic Stress Disorder (PTSD) 0 9 Schizophrenia 220 10 Other 7 11 Tic Disorder 3 12 Undetermined 1 13 Williams Syndrome 2 Table: Numbers of samples in each diagnostic category. DNA extraction: 45-80 mg of cerebellar tissue was pulverized for DNA extractions. The QIAamp DNA mini Kit (Qiagen) method was employed for tissue DNA extraction. The tissue was initially lysed using Tissue Lyser (Qiagen) and extractions were accomplished according to manufacturer's protocol. The DNA was captured in 500uL elution buffer. The concentrations were measured using Thermo Scientific's NanoDrop 1000/NanoDrop ONE. The mean yield was 128.85 uG (+/- 79.48), the mean ratio of 260/280 was 1.87 (+/- 0.105), and the mean ratio of 260/230 was 2.48 (+/-1.75). Genotyping methods: Three types of Illumina Beadarray chips were used: HumanHap650Y, Human1M-Duo, and HumanOmni5M-Quad (San Diego, California). The genotyping was done according to the manufacturer's protocol (Illumina Proprietary, Catalog # WG-901-5003, Part # 15025910 Rev.A, June 2011). Approximately, 400ng DNA was used and each DNA sample was QC tested for 260/280 ratio by nanodrop and DNA band intactness on 2% agarose gel. Briefly, the samples were whole-genome amplified, fragmented, precipitated and resuspended in appropriate hybridization buffer. Denatured samples were hybridized on prepared Bead Array Chips. After hybridization, the Bead Chip oligonucleotides were extended by a single fluorescent labeled base, which was detected by fluorescence imaging with an Illumina Bead Array Reader, iScan. Normalized bead intensity data obtained for each sample were loaded into the Illumina Genome Studio (Illumina, v.2.0.3) with cluster position files provided by Illumina, and fluorescence intensities were converted into SNP genotypes. Microarray: We generated RNA expression data using array technology for psychiatric subjects compared to non-psychiatric subjects as controls. We used tissues from three different brain regions i.e. hippocampus, dorsolateral prefrontal cortex (DLPFC), and dura mater for a large cohort of individuals (total number 552 subjects for hippocampus, 800 for DLPFC and 146 for dura). Total RNA was extracted from ~100 mg of tissue using the RNeasy kit (Qiagen) according to the manufacturer's protocol. RNA quality and quantity were examined using the Bioanalyzer (Agilent, Inc) and NanoDrop (Thermo Scientific, Inc), respectively. Samples with RNA integrity number (RIN) # Diagnosis DLPFC Hippo Dura 1 Anxiety Disorder 1 0 0 2 Autism Spectrum Disorder 14 6 0 3 Bipolar Disorder 90 49 0 4 Control 336 270 75 5 Eating Disorder (ED) 2 1 0 6 Major Depressive Disorder (MDD) 144 87 0 7 Obsessive Compulsive Disorder (OCD) 5 3 0 8 Post-Traumatic Stress Disorder (PTSD) 6 0 0 9 Schizophrenia 192 125 71 10 Other 5 6 0 11 Tic Disorder 3 3 0 12 Undetermined 1 1 0 13 Williams Syndrome 2 1 0 Table: Numbers of samples in each diagnostic category. RNA-Seq of Dorso-lateral prefrontal cortex: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. RNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. RNA isolation: Total RNA from 468 HBCC samples was isolated from approximately 100 mg homogenized tissue from each sample by TRIzol/chloroform extraction and purification with the Qiagen RNeasy kit (Cat#74106) according to manufacturer's protocol. Samples were processed in randomized batches of 12. The order of extraction for schizophrenia, bipolar, and MDD disorders and control samples was assigned randomly with respect to diagnosis and all other sample characteristics. The mean total RNA yield was 24.2 ug (+/- 9.0). The RNA Integrity Number (RIN) was determined by 4200 Agilent TapeStation System. Samples with RIN DLPFC RNA-Seq quantified expression data are provided for 364 samples. Data were generated, QC'd, processed and quantified as follows: RNA library preparation and sequencing: All samples submitted to the New York Genome Center for RNAseq were prepared for sequencing in randomized batches of 94. The sequencing libraries were prepared using the KAPA Stranded RNAseq Kit with RiboErase (KAPA Biosystems). rRNA was depleted from 1ug of RNA using the KAPA RiboErase protocol that is integrated into the KAPA Stranded RNAseq Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. Schizophrenia Bipolar Control 89 65 210 Table: Numbers of samples in each diagnostic category. RNA-Seq of subgenual anterior cingulate cortex (sgACC): All the 200 post-mortem brain samples (61 controls; 39 bipolar disorder; 46 schizophrenia; 54 major depressive disorder) were collected by the HBCC, DIRP, NIMH. RNA Extraction and Quality Assessment: Tissue from sgACC was pulverized and stored at -80°C. Total RNA was extracted from 50-80 mg of the tissue using QIAGEN RNeasy Lipid Tissue Mini Kit (QIAGEN, Cat. # 74804) with DNase treatment (QIAGEN, Cat. # 79254). The RNA Integrity Number (RIN) for each sample was assessed with high-resolution capillary electrophoresis on the Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, California). The concentration of RNA and their 260/280 ratio (2.1+/- 0.032 SD) were determined with NanoDrop (Thermo Scientific). RNA sequencing: Stranded RNA-Seq libraries were constructed after rRNA depletion using Ribo-Zero GOLD (Illumina). RNA sequencing was performed at National Institute of Health Intramural Sequencing Center (NISC). Schizophrenia Bipolar Control MDD 46 39 61 54 Table: Numbers of samples in each diagnostic category. Whole Genome Sequencing: All brains were collected and dissected at the HBCC, DIRP, NIMH. This study generates whole genome sequencing data using sequencing of DNA in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) or cerebellum of 443 individuals with schizophrenia, bipolar disorder and major depressive disorder and non-psychiatric controls. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. DNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. All specimens were dissected from right or left hemisphere of frozen coronal slabs. DNA Library Preparation and Sequencing: All samples submitted to the New York Genome Center for WGS were prepared for sequencing in randomized batches of 95. The sequencing libraries were prepared using the Illumina PCR-free DNA sample preparation Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. A quantitative PCR assay (KAPA), with primers specific to the adapter sequence, was used to determine the yield and efficiency of the adaptor ligation process. Performed on the Illumina HiSeqX with 30X coverage. Schizophrenia Bipolar Control 115 78 230 Table: Numbers of samples in each diagnostic category. ChIP-Seq: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. This study generates epigenetic data using sequencing of DNA after chromatin immunoprecipitation (ChIP-Seq) for marks H3K4me3 and H3K27ac in the dorsolateral prefrontal cortex (DLPFC). Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029,6574. Chromatin precipitation, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. Chromatin immunoprecipitation (ChIP) assays for histone marks H3K4me3 and H3K27ac were carried out using Native ChIP. Micrococcal Nuclease (MNase) (Sigma, N3755) treatment was used to digest chromatin into mononucleosomes. The following antibodies were used for chromatin pull-down: anti-H3K4me3 (Cell Signaling, Cat# 9751BC, lot 7) and anti-H3K27ac (Active Motif, Cat# 39133, Lot # 31814008). Histone modification-enriched genomic DNA fragments were recovered using Protein A/G magnetic beads (Thermo Scientific, 88803-88938 or Millipore 16-663), and then washed, eluted, and treated with RNAse A and proteinase K. Final ChIP DNA products were isolated using phenol-chloroform extraction followed by ethanol precipitation. The efficiency of each ChIP assay was validated using Qubit concentration measurement and qPCR for positive (GRIN2B, DARPP32) and negative (HBB) control genomic regions. Only ChIP assays that passed quality control were further processed for library preparation and sequencing; this included ChIP DNA that was not detectable on Qubit but showed a good signal and expected enrichment patterns in qPCR. HISTONE_MARK H3K27ac H3K4me3 Input Bipolar 56 4 7 Control 158 11 24 Schizophrenia 79 11 12 Table: Numbers of individuals in each assay grouped by histone mark or input.Long-Read Whole-Genome Sequencing (WGS) Cohort Description: Brain specimens were obtained from the Human Brain Collection Core (HBCC), part of the NIH NeuroBioBank. Samples were collected under protocols approved by the NIH CNS Institutional Review Board (IRB) (NCT03092687), with informed consent from next-of-kin (NOK). Collection was coordinated through the Offices of the Chief Medical Examiners (MEOs) in Washington, D.C., Northern Virginia, and Central Virginia. Clinical metadata and documentation are publicly available via the NIMH Data Archive (NDA) (Collection #3151) https://nda.nih.gov/edit_collection.html?id=3151 Eligibility Criteria No clinical diagnosis of major neuropsychiatric or neurodegenerative diseaseNo diagnosis of cognitive impairment during life All individuals were confirmed to be neurologically normal at time of deathDemographics Initial cohort size: 155 individuals Ancestry: All individuals self-identified as African or African-admixed Mean age at death: 44.2 years (range: 18–85 years) Sex distribution: 36.4% femaleSample Processing: Frozen frontal cortex tissue was dissected and processed according to the public protocol: https://www.protocols.io/view/processing-human-frontal-cortex-brain-tissue-for-p-kxygxzmmov8j/v2. High-molecular-weight DNA was extracted and libraries were prepared using the Oxford Nanopore Technologies (ONT) LSK-114 kit. Sequencing was performed using ONT PromethION flow cells (R10.4.1 chemistry) Data Processing and Quality Control: Basecalling: Conducted using Guppy v6.38 Read Alignment: Reads were aligned to the GRCh38 reference genome using minimap2 Sample Identity Verification: Sample identity was validated by comparing ONT-derived SNP calls with matched short-read WGS genotypes to ensure concordance and prevent sample swaps Variant Calling and Phasing: Reads were base-called with Guppy v6.38. Reads were aligned to GRCh38 using minimap2. We verified sample identity by cross-checking ONT SNV calls with the existing short-read WGS genotypes, confirming no sample switches. The napu pipeline (https://github.com/nanoporegenomics/napu_wf) produced; haplotype-resolved assemblies, joint small-variant (SNV/indel) calls, and multi-caller structural-variant sets, all reported on GRCh38 and phased where possible. Raw signal data were basecalled to obtain 5-methyl-cytosine (5mC) status; methylation tags were added to the phased BAM files. Genome-wide methylation summaries are provided in BED format.Dataset Filtering and Exclusions: All 155 samples underwent sequencing and SNP-based ancestry inference 8 samples were excluded due to ancestry inconsistent with African or African-admixed background 1 sample was excluded due to insufficient sequencing quality Final Sample Set: 146 high-quality samples from individuals of African or African-admixed ancestry were retained for downstream analyses See PMID: 39764002 for further analysis detailsDiagnosis#SamplesControl155Table: Diagnostic Summary.Note: The data derived from HBCC resources were removed from dbGAP and are now available in the NIMH Data Archive (NDA). They include genotypes, short read whole genome sequencing (WGS), epigenetics (DNA methylation, ChIP-seq for histones), RNA expression (qPCR, microarray, RNA-seq, single nucleus RNA-seq) of various brain regions in cases with schizophrenia, bipolar disorder, major depression, substance use disorders and normative controls. Please access our NDA collection (https://nda.nih.gov/edit_collection.html?id=3151) for further detail.

  Study phs000979

• Responses to Varicella Zoster Virus Vaccination

  The study sequenced antibody heavy chain gene rearrangements from 4 identical twin pairs undergoing vaccination with Varicella Zoster viral vaccine.

  Study phs000817

• 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

• BIH COVID-19 airway single-cell, long-read RNA-seq

  We performed single-cell, long-read RNA-seq on nine nasopharyngeal swabs from patients hospitalized at Charite to study splicing alterations induced by SARS-CoV-2 infection. Additionally, three samples from healthy controls were included.

  Dac EGAC50000000757

• Repertoire sequencies from three different protocols

  This dataset contains sequencing data from Bulk RNAseq, PCR-based RepSeq and SMRT sequencing to compare immunoglobulin repertoire profiling strategies using matched human B-cell samples

  Dataset EGAD50000002217

• FOCUS study

  Shallow whole genome sequencing of adavanced colorectal tumors from patients included in the FOCUS clinical trial. Performed to calculate assocations of irinotecan with copy-number alterations. Copy number aberration analysis of 349 enroled patients.

  Dataset EGAD50000001007

• 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

• PCA Atlas donor genotyping arrays (Axiom UK Biobank v2.0)

  Raw Axiom v2.0 UK Biobank Array CEL files for PCA Atlas donor buffy-coat DNA, used to generate SNP genotypes for demultiplexing single-cell and spatial transcriptomics libraries.

  Dataset EGAD00010002818

• H3Africa EPIGEN EWAS

  Data from 59 whole blood samples from pregnant mothers, unexposed and exposed to the Rwandan genocide, was generated using Infinium MethylationEPIC BeadChip Kit.

  Dataset EGAD00010002383

• HSP90 inhibitor resistant cells

  K562 cells were treated with different HSP90 inhibitors (PuH71 and Coumermycin A1) and the CNV profil was compared to the parental K562 (untreated). In addition, the CNV profile of HSP90AB1 knockout K562 cells was analyzed.

  Dataset EGAD00010002336

• RNA sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000285

• 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

• Anaplastic Thyroid Cancer somatic variants (SomaticSniper)

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with SomaticSniper. Somatic variant calls are in VCF format. In total there are 94 tumour samples, each with a matched normal.

  Dataset EGAD00001004128

• BASIS RNAseq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001264

• Xenograft BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001336

• Whole exome sequencing of Finnish hereditary breast cancer families

  Dataset contains Whole Exome Sequencing(WES) data from 37 individuals as aligned bam-files. The reads have been aligned using bowtie2 to human genome hg19 build.

  Dataset EGAD00001002133

• 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

• Exome_Sequencing_of_Human_myeloid_malignancies

  This study involves exome sequencing of blood/bone marrow DNA from patients with myeloid malignancies. Blood DNA samples have been taken from patients at different timepoints of disease phenotype. We hope to elucidate mechanisms of clonal evolution in these patients.

  Dataset EGAD00001002213

• subset of WES data from umbrella study EGAS00001004338, used in EGAS00001004786

  linking 82 samples/82 runs of WES from EGAS00001004338 Umbrella study to EGAS0001004786 study

  Dataset EGAD00001006613

• 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

• Germline WES data of children with pathogenic mutations in cancer predisposing genes

  This data set includes bam files (aligned to hg38) from the germline of children who have pathogenic mutations in cancer predisposing genes

  Dataset EGAD00001009854

• Germline WES data of parents whose children have germline CHEK2 mutations

  This data set includes bam files (aligned to hg38) from the germline of parents whose children have CHEK2 germline mutations.

  Dataset EGAD00001009516

• Multimodal Immune Profiling to Determine Mechanisms of COVID-19 Clinical Trajectory in Uganda

  We conducted a prospective cohort study of adults (RESERVE-U-C19) admitted to Entebbe Regional Referral Hospital (ERRH), a national COVID-19 referral center, across three viral variant-driven phases of the pandemic in Uganda. In this cohort, which reflects the entire spectrum of SARS-CoV-2 infection, we integrated clinical data with serum proteomics (N=306) and whole-blood transcriptomics (N=100) to determine a range of host responses associated with COVID-19 severity, SARS-CoV-2/HIV co-infection, and circulating viral variants. Beyond the prognostic importance of myeloid cell-driven immune activation and lymphopenia, we show that multifaceted impairment of host protein synthesis and extensive redox imbalance define core metabolic signatures of severe COVID-19, with central roles for IL-7, IL-15, and lymphotoxin-α in COVID-19 respiratory failure. While prognostic signatures were generally consistent in SARS-CoV-2/HIV-coinfection, type I interferon responses uniquely scaled with COVID-19 severity in persons living with HIV. Throughout the pandemic, COVID-19 severity peaked during phases dominated by A.23/A.23.1 and Delta B.1.617.2/AY variants, with Delta phase COVID-19 distinguished by exaggerated pro-inflammatory myeloid cell and inflammasome activation, NK and CD8+ T-cell depletion, impaired host protein synthesis, and upregulation of viral cell entry and trafficking pathways. Data from this study available through dbGaP include raw RNA-Seq data from whole-blood of adult participants (N=100).

  Study phs003246

• Targeting the p53 pathway to treat Malignant Rhabdoid and High-Risk Atypical Teratoid Rhabdoid Tumors

  Rhabdoid tumors (RTs) predominantly affect young children and are among the deadliest pediatric solid tumors. Despite multimodal therapy consisting of surgery, radiation, and chemotherapy, children with these tumors have median survival of less than one year. RTs can arise throughout the body, including the central nervous system (CNS) where they are called atypical teratoid rhabdoid tumors (AT/RTs), and in extra-CNS locations such as the kidneys and other soft tissues where they are designated malignant RTs (MRTs). We previously identified MDM2 and MDM4 as therapeutic vulnerabilities in RTs and showed that treatment with the MDM2 inhibitor idasanutlin increased survival in mice bearing MRT xenografts. However, the therapeutic potential of idasanutlin in CNS RT tumors is unknown. Single agent therapies are prone to resistance and show limited clinical benefit on their own. Therefore, we sought to identify combination strategies incorporating idasanutlin that would be effective in both CNS and extra-CNS RTs. Here, we show that the XPO1 inhibitor selinexor increased nuclear retention of p53 and potentiated idasanutlin-induced p53 pathway activation and cytotoxicity in AT/RT and MRT cell lines in vitro. Importantly, combination therapy limited acquired resistance through TP53 mutation. In vivo, combination therapy was well-tolerated, reduced tumor burden, and increased survival in orthotopic models of both AT/RT and MRT. Our results demonstrate that combining idasanutlin with selinexor is a promising therapeutic strategy for children with rhabdoid tumors.

  Study EGAS00001007680

• NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study

  Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia.

  Study phs001598

• 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