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• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  We generated a dataset consisting of 79 VCF files, and respective FASTQ and CRAM files, methodically generated using the GLIMPSE1 imputation algorithm leveraging the 1000 Genomes Project Phase 3 dataset as the reference panel of haplotypes. In total this dataset is composed of approximately 325 GB of FASTQ data, 156 GB of CRAM data, and 6 GB of VCF data. Our samples were specifically derived from sequenced DNA from a highly selective cohort of patients, mostly comprised of Iberian Populations in Spain (IBS) individuals but also containing some individuals with other genetic backgrounds, who presented severe COVID-19 symptoms during the initial wave of the SARS-CoV-2 pandemic in Madrid, Spain. On average, each VCF file in this rich dataset contains 9.49 million high-confidence single nucleotide variants [95%CI: 9.37 million - 9.61 million].

  Dataset EGAD00001011363

• MultiOMICS study of a pair of infant monozygotic twins with concordant B-cell ALL (WGS)

  B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common cancer in childhood. Studying identical twins with B-cell ALL provides a unique and tractable model for deciphering the developmental timing of pre- and post-natal mutations contributing to clonal evolution. To date, this has mainly focused on major cytogenetic subgroups of childhood B-cell ALL, including MLL fusions, ETV6-RUNX1, hyperdiploidy, and BCR-ABL1. However, formal demonstration of the prenatal origin and “backtracking” the natural history of the leukemia remains understudied in “B-other”/Normal Karyotype (NK) B-cell ALL. To characterize the genetic landscape of this particular leukemia subtype, we performed whole genome DNA- and B-cell receptor (BCR)- on a pair of 8-month-old monozygotic twins diagnosed with concordant “B-other”/NK B-cell ALL.

  Dataset EGAD00001005017

• MultiOMICS study of a pair of infant monozygotic twins with concordant B-cell ALL (WGBS)

  B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common cancer in childhood. Studying identical twins with B-cell ALL provides a unique and tractable model for deciphering the developmental timing of pre- and post-natal mutations contributing to clonal evolution. To date, this has mainly focused on major cytogenetic subgroups of childhood B-cell ALL, including MLL fusions, ETV6-RUNX1, hyperdiploidy, and BCR-ABL1. However, formal demonstration of the prenatal origin and “backtracking” the natural history of the leukemia remains understudied in “B-other”/Normal Karyotype (NK) B-cell ALL. To characterize the epigenetic landscape of this particular leukemia subtype, we performed DNA bisulfite-sequencing on a pair of 8-month-old monozygotic twins diagnosed with concordant “B-other”/NK B-cell ALL.

  Dataset EGAD00001005018

• Summary Statistics GWAS SSNS

  Column 1 rsid: SNP identifier;Column 2 chromosome: name of chromosome on which the SNP is located;Column 3: position: base pair position on the chromosome;Column 4 minor_test_allele: the base that constitutes the minor allele;Column 5 major_allele: the base that constitutes the major allele;Column 6 maf: the frequency of the minor allele, indicated as a fraction of 1;Column 7 allele_freq_cases: the minor allele frequency in cases;Column 8 allele_freq_controls: the minor allele frequency in controls;Column 9 regression_pvalue: the p-value for the difference in allele frequency between cases and controls;Column 10 odds_ratio: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00010002316

• Summary Statistics GWAS SSNS

  Column 1 “rsid”: SNP identifier Column 2 “chromosome”: name of chromosome on which the SNP is located Column 3: “position”: base pair position on the chromosome Column 4 “minor_test_allele”: the base that constitutes the minor allele Column 5 “major_allele”: the base that constitutes the major allele Column 6 “maf”: the frequency of the minor allele, indicated as a fraction of 1 Column 7 “allele_freq_cases”: the minor allele frequency in cases Column 8 “allele_freq_controls”: the minor allele frequency in controls Column 9 “regression_pvalue”: the p-value for the difference in allele frequency between cases and controls Column 10 “odds_ratio”: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00001008782

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  We carried out WGS and RNAseq on a cohort of 48 children and young adults with induction failure in T-cell Acute Lymphoblastic Leukemia (T-ALL) to identify genomic drivers of treatment resistance. The study includes WGS for 33 tumour/normal pairs and 15 tumour-only samples. In addition, there is RNAseq data for 37 cases.

  Dataset EGAD00001009058

• Dynamics of multiple resistance mechanisms in plasma DNA and their clinical implications for NSCLC patients receiving EGFR-targeted therapies

  Background:The development of resistance mechanisms to targeted therapies is complicated by underlying tumour heterogeneity. When multiple resistance mechanisms co-exist, identifying the dominant driver(s) is critical for selection of treatment. Patients and methods:We studied the relative dynamics of multiple oncogenic drivers and resistance mechanisms in 50 patients with EGFR-mutant non-small cell lung cancer (NSCLC), during treatment with gefitinib and hydroxychloroquine (NCT00809237). We performed digital PCR and targeted deep sequencing of cell-free DNA from longitudinal plasma samples from all patients, and shallow whole genome sequencing of serial samples from three patients who underwent histological transformation to small-cell lung cancer (SCLC). ResultsEGFR activating mutations were assessed in tumour samples and accurately identified in plasma samples of 95% of patients (41/43). We identified additional mutations including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%), and PTEN (4/50, 8%), and tracked their relative levels in plasma. Patients with both TP53 and EGFR mutations detected in plasma pre-treatment tended to have worse overall survival than those where only EGFR was detected. The resistance-conferring EGFR T790M mutation was identified in 62% of the patients who progressed. Changes in relative levels of T790M and activating mutations in EGFR corresponded to clinical responses in two patients who were given sequential treatments. Patients who progressed without T790M detected in plasma had worse PFS during TKI continuation, and developed alternative resistance mechanisms, that could be identified in plasma DNA, including SCLC-associated copy number changes and TP53 mutations, that tracked with progression and response to subsequent therapies. Conclusion:Longitudinal analysis of multiple oncogenic drivers in ctDNA may help identifying dominant mechanisms of resistance to EGFR-targeted therapies, and highlight the importance of monitoring genetic events that are not direct drug targets but provide non-invasive molecular information that may guide clinical management.

  Study EGAS00001002908

• Emergence of oncofetal plasticity is ubiquitous in early colorectal cancers

  Metastasis formation is classically considered a late-stage event in colorectal cancer (CRC) evolution. Yet, the time and patterning by which metastatic competence is acquired remain poorly understood. Here, we show that metastasis-associated oncofetal cell states already emerge at the earliest stages of CRC, concurrent with invasive front formation. However, while necessary for metastasis, we detect them ubiquitously among early non-metastatic cancers, highlighting additional bottlenecks like immune evasion. To understand how oncofetal cells first emerge, we generated multiregional organoid models that reflect successive tumor progression stages within individual early-stage CRCs. Whole-genome sequencing and growth factor-dependency assays exclude tumor cell-intrinsic acquired traits. In contrast, single-cell spatial atlases of the tumor-microenvironment before and after malignant transformation revealed stereotypic patterning of fibroblast subtypes resembling normal tissue architecture, resulting in distinct regional microenvironments. At the onset of malignant growth into the submucosa, the first cancer-associated fibroblasts (CAFs) to appear strongly resemble submucosal trophocytes and colocalize with oncofetal cell states at invasive fronts. Functionally, fibroblast-organoid co-cultures confirm that these trophocyte-like CAFs induce plastic transitioning to oncofetal states. Thus, interactions between tumor and submucosal fibroblasts directly following malignant transformation dictate the timing and location at which oncofetal plasticity first occurs during CRC progression.

  Study EGAS50000001532

• Whole genome sequencing of AML samples at presentation, remission, and relapse

  Whole genome sequencing of AML blood or bone marrow at presentation and remission for 5 patients. Relapse samples are included for 2 patients, totaling 12 WGS BAM files.

  Dataset EGAD00001005120

• OncoCis: Annotation of cis-regulatory mutations in cancer

  RNA-seq dataset used for the validation of CDK6 cis-regulatory mutation annotated by OncoCis. NB bam files for manuscript A_Proteomic_Chronology_of_Gene_Expression_through_the_Cell_Cycle_in_Human_Myeloid_Leukemia_Cells are now available at the following link:http://www.ebi.ac.uk/ena/data/view/ERP008483

  Dataset EGAD00001001019

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• Reference Profiles of ExRNAs in Normal Human Pregnancy

  In this study, we did a comprehensive exRNA profiling of plasma and serum specimens from healthy pregnant women, sampled at different gestational time points, and including subjects with diverse geographical and ethnic backgrounds. This study also contains samples from male and female healthy donors to provide a baseline. The aim of this study is to identify miRNAs that can predict the gestation age and to build a miRNA profile across gestation using small RNA-seq data.

  Study phs003182

• Comparison Across Multiple Types of Sleep Deprivation

  This study is designed to assess neurobehavioral performance, as well as molecular and physiological changes associated with variations in timing and quantity of sleep. Gene expression changes associated with neurobehavioral (cognitive) performance were assessed in a time-series among individuals randomly assigned to four separate sleep conditions during a 10-day inpatient study: a well-rested control, sleep restriction with nighttime sleep, sleep restriction with daytime sleep to roughly simulate shiftwork schedules, and total (acute) sleep deprivation.

  Study phs003924

• Tenk10k Phase 1: Whole Genome Sequencing

  TenK10K Phase 1 is a dataset of matched human whole-genome sequencing (WGS) from 1,925 individuals, and single-cell RNA sequencing (scRNA-seq) from over 5 million peripheral blood mononuclear cells across 28 immune cell types. Single-cell ATAC sequencing was additionally performed on a subset of 922 individuals. This EGA study consists of the WGS data from 1,925 individuals while a separate EGA study comprises the scRNA-seq and scATAC-seq data.

  Study EGAS50000001654

• Genomic Signatures of Intestinal Metaplasia in Six Countries with Varying Incidence of Stomach Cancer

  Intestinal metaplasia (IM) is a pre-cancerous condition associated with gastric cancer (GC), a deadly malignancy with varying geographic incidence. Performing a genomic analysis of over 1,500 IM samples from six countries, we identified 46 significantly mutated genes. We observed IM driver genes associated with high-risk populations and worse prognosis (ARID1A), members of the KRAS/MAPK signalling pathway (KRAS, BRAF, MAP2K1, MAP3K1, MAP2K4, NF1), and altered mucosal immunity (PIGR).

  Study EGAS50000001056

• An isogenic human iPSC model unravels neurodevelopmental abnormalities in SMA

  Whether neurodevelopmental defects underlie the selective neuronal death that characterizes neurodegenerative diseases is becoming an intriguing question. To address it, we focused on the motor neuron (MN) disease Spinal Muscular Atrophy (SMA), caused by reduced levels of the ubiquitous protein SMN. Taking advantage of the first isogenic human induced pluripotent stem cell-derived SMA model that we have generated and a spinal cord organoid system, here we report that the relative and temporal expression of early neural progenitor and MN markers is altered in SMA. Furthermore, the corrected isogenic controls only partially reverse these abnormalities. These findings raise the relevant clinical implication that SMN-increasing treatments might not fully amend SMA pathological phenotypes. The approach we have taken demonstrates that the discovery of new disease mechanisms is greatly improved by using human isogenic models. Moreover, our study implies that SMA has a developmental component that might trigger the MN degeneration.

  Study EGAS00001007259

• APOBEC mutagenesis is a common process in normal human small intestine

  The single base substitution mutational signatures SBS2 and SBS13, likely caused by APOBEC cytosine deaminases, are common in many human cancer types. However, the stimulus activating APOBEC mutagenesis is unknown and understanding of when it occurs in the progression from normal to cancer cell is limited. Here, as part of a wider survey of human tissues, we whole genome sequenced 342 microdissected normal epithelial crypts from the small intestines of 39 individuals. SBS2/13 mutations were present in 17% normal small intestine crypts and were likely due to APOBEC3A activity. Localised clusters of SBS2/13 mutations (kataegis) were also commonly found. APOBEC mutation burdens were variable between individuals and between crypts from the same individual. Crypts with SBS2/13 often had immediate crypt neighbours without SBS2/13, suggesting that the underlying cause of SBS2/13 is cell-intrinsic rather than a widely distributed microenvironmental exposure, or needs to be permitted by cell-intrinsic conditions. APOBEC mutagenesis occurred throughout the human lifespan, including in young children, and was episodic with a small number of episodes occurring during the life history of a single cell. The results indicate that APOBEC mutagenesis is more common in the small intestine epithelium than in many other cell types, and is an episodic process in vivo initiated or permitted by cell intrinsic factors.

  Dataset EGAD00001008764

• Reconstruction of complex rearrangement patterns causing the initiation of clear cell renal cell carcinoma.

  The genomic hallmark of clear cell renal cell carcinoma is the loss of the short arm of chromosome three. This appears to be the earliest genomic event in the formation of these cancers. Often chromosome 3 is lost at the same time as part of chromosome 5 is duplicated via an unbalanced translocation, often with features consistent with focal chromothripsis. In this study, we sought to reconstruct the chromothriptic event that underlies the initiation of kidney cancer. We used long read sequencing (promethION, Oxford Nanopore Technologies) of patient tumour-derived DNA to elucidate how a single cell division error can generate cancer genome complexity.

  Study EGAS00001004015

• Whole genome and transcriptome sequencing of cancer of unknown primary tumours

  Whole genome and transcriptome sequencing of cancer of unknown primary tumours was used to determine yield of clinical biomarkers for a molecular guided trial or for resolving cancer type of origin. This study includes profiling of germline DNA and tumour DNA and RNA by whole genome and transcriptome sequencing. All samples are in BAM format aligned with GRCh38 reference genome. This dataset includes: 1. Whole genome sequencing (WGS) of 78 cancer of unknown primary tumour samples and 73 matched germline DNA. 2. Whole transcriptome sequencing (WTS) of 69 cancer of unknown primary tumour samples (matched to WGS cases) 3. Whole genome sequencing of 22 cell-free DNA samples from cancer of unknown primary patients and matched Germaine DNA(8 samples matched to tumour WGS)

  Dataset EGAD50000000656

• Dataset for study Genome-wide gene expression analysis following CRISPRi of transposable elements

  Transposable elements (TEs), once regarded as parasitic genomic remnants, are now recognized as key regulators of gene expression and genome evolution, yet the functional specificity of individual TE subfamilies remains largely unexplored. This dataset investigates the transcriptional consequences of targeted repression of MER57E3 and LTR10B2 elements using CRISPR interference (CRISPRi) in human induced pluripotent stem cells (hiPSCs). hiPSCs expressing CRISPRi machinery (n = 2 biological replicates) were transduced with guide RNAs targeting individual or grouped copies of MER57E3 and LTR10B2, as well as the ZNF678 promoter or a lacZ non-targeting control. Transduced cells were subsequently differentiated into neural progenitor cells (NPCs), and total RNA was extracted for mRNA library preparation and sequencing. The dataset comprises 24 single-end mRNA-seq FASTQ files generated from these NPCs and wild-type controls.

  Dataset EGAD00001015689

• Circulating Tumor DNA Analysis Profiles of Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

  The dataset contains circulating tumor DNA (ctDNA) profiles from frozen plasma samples of 593 patients from the TRIDENT-1 clinical trial. Plasma was processed with centrifugation and automated liquid handling systems, and cell-free DNA was extracted using the Qiagen QIAsymphony platform. ctDNA libraries were constructed with the Guardant360 2.11 assay, which used targeted, hybridization-based capture and barcoding of cfDNA fragments for digital analysis, followed by high-throughput sequencing on the Illumina NextSeq 550 instrument. Sequencing data were processed and interpreted using the Bioinformatics Pipeline (BIP v3.5.2 or later) for variant calling and quantification and managed within LabVantage LIMS (v3.7 or later) to support sample tracking and workflow integration. Aligned read files are provided in bam and bai formats.

  Dataset EGAD50000002249

• Genome wide association study on coronary heart disease in patients with familial hypercholesterolemia

  Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17 000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap 550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (p<1×10-4). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an ‘extreme genetics’ approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may therefore not lead to significant gains in statistical power. (NB submitten and conditionally accepted at European Journal of Human Genetics-please use abstract only for internal review until submission complete)

  Study EGAS00001000734

• Million Veteran Program (MVP) Summary Results from Non-Sensitive Omics Studies

  MVP is an ongoing prospective cohort study and mega‐biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans. This is the accession to hold publicly available results. Results from sensitive phenotypes or MVP population subsets can be found at accession phs001672 and will require an application for access.

  Study phs002453

• Diverse modes of genomic alterations in hepatocellular carcinoma

  Hepatocellular carcinoma is the most prevalent type of liver cancer. We intended to study the genomic landscape of this disease. We conducted whole-genome, exome and transcriptome sequencing for 42 patients. We show diverse modes in which the HCC genome is affected in these patients, including well-known and novel mutations, structural variations, and Hepatitis B-virus integration into the genome.

  Study EGAS00001000824

• Amplicon_based_sequencing_of_drug_resistant_organoids

  A BRAF V600E colorectal organoid which is sensitive to MAP kinase inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a combination of Trametinib, Dabrafenib and Cetuximab. Single cell derived organoids were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors from a screen in 2 2D BRAF V600E colorectal cell lines. Pools of resistant clones were also sequenced.

  Study EGAS00001001639