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• Whole exome genome sequencing data to study "A biobank of patient-derived pediatric brain tumor models"

  Whole exome sequencing data to 30 PDOX models (28 early passages, 3 late passages (1 overlap)), 3 cell lines, and 20 matching human tumors

  Dataset EGAD00001003544

• CRISPR screen M14, NCI-H3122 (2019-08-28)

  Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung . This dataset contains all the data available for this study on 2019-08-28.

  Dataset EGAD00001005296

• 5WGS and 35WES sample pairs belongs to COCA-CN

  There are 5WGS and 35WES sample pairs from the first affiliated hospital of kunming medical university, which belongs to ICGC projects COCA-CN.

  Dataset EGAD00001003456

• Raw data for "Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse"

  FASTQ files from Illumina sequencing of 10x Visium experiments.

  Dataset EGAD00001010260

• MP-WGS and WES from CCND1-negative MCL

  BAM files from 5 CCND1-negative MCL cases. 4 BAM files corresponded to long insert size Mate Pair-WGS and 3 to WES. In 2 of the cases both technologies were performed.

  Dataset EGAD00001004161

• Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Dataset EGAD00001001210

• Comparison of the treated celiac disease microbiome to that of controls

  Coeliac disease (CeD) is an immune-mediated disorder primarily affecting the small intestine, characterised by an inflammatory immune reaction to dietary gluten. CeD onset results from a multifaceted interplay of genetic and environmental factors. While recent data show that alterations in gut microbiome composition could play an important role, many current studies are constrained by small sample sizes and limited resolution. To address these limitations, we analysed faecal gut microbiota from two Dutch cohorts, CeDNN (128 treated CeD patients (tCeD), 106 controls) and the Lifelines Dutch Microbiome Project (24 self-reported tCeD, 654 controls), using shotgun metagenomic sequencing. Self-reported IBS (570 cases, 1710 controls) and IBD (93 cases, 465 controls) were used as comparative conditions of the gastrointestinal tract. Interindividual variation within the case and control groups was calculated at whole microbiome and strain level. Finally, species-specific gene repertoires were analysed in tCeD patients and controls. Within-individual microbiome diversity was decreased in patients with self-reported IBS and IBD but not in tCeD patients. Each condition displayed a unique microbial pattern and, in addition to confirming previously reported microbiome associations, we identify an increase in the levels of Clostridium sp. CAG:253, Roseburia hominis, and Eggerthella lenta, amongst others. We further show that the observed changes can partially be explained by gluten-free diet adherence. We also observe increased interindividual variation of gut microbiome composition among tCeD patients and a higher bacterial mutation frequency in tCeD that contributes to higher interindividual variation at strain level. In addition, the immotile European subspecies of Eubacterium rectale, which has a distinct carbohydrate metabolism potential, was nearly absent in tCeD patients. Our study sheds light on the complex interplay between the gut microbiome and CeD, revealing increased interindividual variation and strain-level variation in tCeD patients. These findings expand our understanding of the microbiome’s role in intestinal health and disease. Note that some of the data in this study belong to the Lifelines cohort. Access to this dataset can be requested via the page of the EGA data access committee EGAC00001001996. The phenotype data can be requested, for a fee, by filling the application form at https://www.lifelines.nl/researcher/how-to-apply/apply-here.

  Study EGAS50000000959

• Conjunctival fibrosis and the innate barriers to Chlamydia trachomatis intracellular infection: a genome wide association study

  This data comes from a genome-wide association study in 1090 cases of scarring trachoma and 1531 controls from a non-selected multi-ethnic sampling of The Gambia. The data constitutes hard base calls at 1457295 features from the HumanOmni2.5-8 (Omni2.5) BeadChip. Three genotype-calling algorithms were used : Illuminus (Bioinformatics 2007, 23:2741–6), GenCall (Patent US7035740, 2006) and GenoSNP (Bioinformatics 2008, 24:2209–14). Data from each calling algorithm was filtered to retain only SNPs with a call rate ≥ 0.98. To obtain a merged set of SNPs, all genotypes that matched across call-sets were retained, whilst those that mismatched between call-sets were set to missing. Genotypes that were present in one call set and missing in others were also retained. The merged SNP set contained 1467876 SNPs, which were filtered for call rate ≥ 0.99 and Hardy-Weinberg equilibrium P value < 5 x 10-8. The case and control groups were approximately equivalent with respect to gender and ethnicity. 70% of cases and 63% of controls were female. Self-described ethnic composition of the cases was 29% Jola, 27% Mandinka, 21% Wolof, 10% Fula and 13% other/no data. In controls the composition was 25% Jola, 24% Mandinka, 21% Wolof, 8% Fula and 22% other/no data. Median age was 49 (range 32-60) in cases and 37 (range 12-52) in controls (t = -3.6019, P = 0.0003). This data set has substantial levels of population structure, which reflects extensive networks of pairwise kinship between participants. First pass tests of association in EMMAX (Nat Genet 2010, 42:348–54) led to genome-wide deflation of the test statistics (λ = 0.982 SE = 1.74e-05) that could be directly attributed to the differing age and gender distributions between cases and controls. Modelling the phenotype to adjust for age and gender successfully controlled for this and no genome-wide deviation from the null was subsequently observed (λ = 1.001, SE = 8.7 x 10-7). Neither principal components analysis (PCA) nor tests of proportional identity by state (IBS) variance in PLINK identified significant levels of within or between group genetic variance. The phenotypes submitted in the phenotypes file include both uncorrected (case/control status) and corrected (age and gender corrected case/control status) phenotypes, as well as age and self-described ethnicity.

  Study EGAS00001001516

• TRanscriptomic ANalySis of left ventriCulaR gene Expression (TRANSCRibE)

  Myocardial ischemia occurs when there is a mismatch between coronary oxygen delivery and metabolic requirements of the myocardium, which may be clinically manifested during angina, coronary angioplasty or cardiopulmonary bypass (CPB). Myocardial ischemia may lead to a spectrum of myocardial stunning, hibernating myocardium, and ultimately cell death if the ischemic insult is severe. In the human heart, irreversible damage begins after approximately 20 to 40 minutes of oxygen deprivation. Observed molecular and cellular changes of myocardial ischemia are characteristic of an inflammatory response, but the exact mechanisms that underlie this pathological process are unclear and may not be full emulated by animal models of ischemia or infarction. Thus, we felt it valuable to investigate a human ischemia model. During cardiac surgery, CPB with aortic cross-clamping (AoXC) and cardioplegic arrest is associated with excellent clinical outcomes and suitable operative conditions. However, despite the use of cardioprotective strategies, AoXc during CPB is accompanied by a variable, yet obligate ischemic period lasting 1 to 3 hours, resulting in hypoxia, metabolic substrate depletion, reperfusion injury, apoptosis, and necrosis. Cardiac specific biomarkers of ischemia and infarction, including troponin, are elevated even after routine coronary artery bypass graft surgery and correlate with the duration of ischemia from AoXc.This process of CPB provides us with the ability to examine the transcriptional profile before and after an expected, consistent, and reproducible human ischemic event, albeit induced by cold cardioplegic arrest and not coronary occlusion. In addition, the absence of reperfusion in this time period allows us to examine the transcriptomic response to intermittent ischemia, without having to account for the perturbations of reperfusion injury. Although various animal models have been used to examine the effects of ischemia on cardiac function, no human data exist which examine the early transcriptomic response to a left ventricular (LV) ischemic insult. We therefore characterized the effect of cold cardioplegia induced acute ischemia on the transcriptional profile of the LV by performing whole transcriptome next-generation RNA-sequencing (RNA-seq) in patients undergoing cardiac surgery by sampling human LV tissue prior to, and after, the obligate ischemia during AoXC. We hypothesized that the cold cardioplegia induced ischemic injury will dramatically alter transcription in the human myocardium, and that we would identify genes and pathways, which will identify interventional targets for pharmacological therapy. Methods:We have collected left ventricle tissue samples and blood sample from patients undergoing heart surgery. We obtained punch biopsies (~3-5μg total RNA content) from the site of a routinely placed surgical vent in the anterolateral apical left ventricular wall of patients undergoing elective aortic valve replacement surgery with cardiopulmonary bypass. After an average of 79 minutes of aortic cross-clamping with intermittent cold blood cardioplegia for myocardial protection every 20 minutes, a second biopsy was obtained in the same manner. Tissue samples were immediately placed in RNAlater® (Ambion, ThermoFisher Scientific, Waltham, MA), and after 48 hours at +4°C were stored at -80°C until RNA extraction. Total RNA was isolated with Trizol and RNA quality was assessed using the Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA). Libraries were prepared by poly(A) mRNA isolation and reverse transcription Polymerase Chain Reaction (RT-PCR), then sequenced on the Illumina HiSeq2000 or HiSeq2500 (Illumina, San Diego, CA). As samples were analyzed at different times, different read lengths were employed, initially using single-end reads (n=20) and then transitioning to paired end reads (n=216), ranging from 36 - 100 base pairs. Raw sequencing files were processed using Sickle, Skewer, and STAR software, and aligned to GrCh37 or UCSC Hg19. DNA was isolated from whole blood using standard methods. SNP genotyping was performed using the Illumina Omni2.5Exome-8 BeadChip array with additional exome content (Illumina, San Diego, CA) chip, version 1.1. We first phased and imputed 93 subjects using a phasing tool called SHAPEIT and an imputation tool called MINIMAC, with 1000 Genomes phase 1 version 3 for the reference panel. We then phased and imputed 26 more subjects using SHAPEIT, an imputation tool called IMPUTE2, and 1000 Genomes phase 3 version 5.

  Study phs001679

• Genetic Basis of Early Onset Bicuspid Aortic Valve Disease

  The study protocol was approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston (HSC-MS-11-0185). Study recruitment began on July 1, 2017, and concluded on March 30, 2022. After written informed consent, we enrolled probands with early onset BAV disease (EBAV), which we defined as individuals with BAV who were under the age of 30 at the time of first clinical event. Clinical events were defined as aortic replacement, aortic valve surgery, aortic dissection, moderate or severe aortic stenosis or aortic regurgitation, large aneurysm (Z > 4.5), or intervention for BAV-related conditions. Those with hypoplastic left heart, known genetic mutations, genetic syndromes, or complex congenital heart disease were excluded. Samples were collected and genotyped as previously reported. For comparison, we analyzed a cohort of older individuals of European ancestry with sporadic BAV disease selected from the International BAV Consortium (BAVGWAS). Phenotypes were derived from record review with confirmation of image data whenever possible [25-26]. The computational pipeline for CNV analysis of Illumina single nucleotide polymorphism (SNP) array data included three independent CNV detection algorithms.GenomeStudio was used to exclude samples with indeterminate sex or more than 5% missing genotypes, and single nucleotide polymorphisms (SNPs) with GenTrain = 0. Principal component analysis was used to remove outliers that did not cluster with European ancestry. Prior to CNV analysis, each dataset was trimmed by selecting a common set of 650,000 SNPs that were genotyped on each of the microarrays used in this study.Three independent algorithms (PennCNV, cnvPartition, and QuantiSNP) were used to generate CNV calls and sample-level quality statistics from SNP intensity data. PennCNV and QuantiSNP were run on Unix clusters and cnvPartition data were exported from GenomeStudio. The analysis was run using default configurations. PennCNV was used to generate QC data and remove CNV calls that intersect with polymorphic genomic regions. Samples that met any of the following criteria were excluded, standard deviation of the LogR ratio (obtained from PennCNV) > 0.35 or number of CNVs > 2 standard deviations above the mean for each data set. CNV calls less than 20 Kilobases in length and/or spanned by fewer than 6 probes were excluded. The overlap function for rare CNVs in PLINK was used to construct CNV regions (CNVRs) after adjacent regions were merged using PennCNV. LogR ratio (LRR) and B allele frequency (BAF) data at CNVRs and calls of interest were visualized in GenomeStudio for validation. For segregation analysis, GenomeStudio was used to determine the presence of CNVs in relatives.A total of 22,014 unselected control Illumina Genotypes obtained from the Database of Genotypes and Phenotypes were analyzed using identical methods (S1 Table). The Wisconsin Longitudinal Study (WLS) includes data on a cohort of 10,300 individuals who graduated from Wisconsin high schools in 1957. The Health and Retirement Study (HRS) includes data on 37,000 individuals aged 50 above from 23,000 households across the United States. Principal component analysis was used to select European ancestry genotypes from these datasets for analysis. Datasets were paired for case-control analysis based on the concordance of log-transformed sample-level quality control statistics (number of CNV calls and standard deviation of logR ratios). Chi-squared or Fisher exact tests were used to compare CNV frequencies in cases and controls.Rare CNV functions in PLINK (v1.7) were used to perform permutation-based burden tests or gene set-based enrichment tests. Case control burden tests were restricted to CNVs that were longer than 110 Kb and less than 0.1% in frequency. CNV overlap functions in PLINK were used to identify rare CNVs that intersect between datasets or involve specific BAV or CHD genes . The list of candidate genes included 190 CHD genes that have strong cumulative evidence to cause BAV or related congenital malformations from human or animal model data. Genome Reference Consortium Human Build 37 was used for CNV annotation [34].

  Study phs003705