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• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002697

• FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

  The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

  Blog fega-faqs-elixir-ahm-2024

• CRU-Ukrainian National Research Center for Radiation Medicine Trio Study

  Data on transgenerational effects following nuclear accidents are important for understanding fully the consequences of parental exposure to ionizing radiation. Few studies to date have had adequate statistical power to detect effects of the magnitude expected based on animal data, and most have not been of low-dose, protracted exposures associated with nuclear accidents and their aftermath. Although, to date, scant use has been made of the new genomic technologies, in Chernobyl-exposed areas of Ukraine and Belarus, excess minisatellite mutations have been seen in children born after the accident. We propose a study of parent-child trios in which at least one parent was exposed to Chernobyl radiation as a clean-up worker (mean dose>=100 mGy) and/or evacuee from a contaminated area (mean >=50 mGy). The specific aims are to investigate the transgenerational and de novo mutation rates of the spectrum of genetic variants in trios, in particular looking at effects in children and mapping them to possible parental origin of the chromsoome. Together with long-term collaborators at the Research Center for Radiation Medicine (RCRM) in Kiev, epidemiologic data will be collected for up to 450 trios of parents with preconceptional doses and their unexposed offspring. We will use state-of-the-art genomic technologies to characterize the landscape of the genomes of the trios to determine whether parental radiation exposure is associated with genetic mutations transmitted to the offspring, by examining de novo mutation rates, minisatellite mutations, copy number alterations, and variations in telomere length. The analysis will be conducted in peripheral blood and/or buccal samples (when blood is not available) from complete father-mother-child trios. Doses to the gonads from the time of the accident to the time of conception will be reconstructed for all parents using existing records supplemented by interview data. Trio subjects will be selected from representative populations exposed to radiation from Chernobyl who are under active follow-up in the Clinico-Epidemiologic Registry at RCRM. To help identify specific effects of paternal and maternal radiation exposure, we will initially select sets of trio subjects in five categories: (1) exposed father, unexposed mother; (2) unexposed father, exposed mother; (3) both parents exposed; (4) both parents unexposed; and (5) a group of high dose "emergency workers" with acute radiation syndrome. All trio members will be invited to the RCRM outpatient clinic for collection of a 20 ml blood sample (or buccal cells for those who refuse phlebotomy). Both parents will be asked to complete a general questionnaire to obtain demographic and lifestyle data. Then one or both will complete detailed dosimetry questionnaires, based on forms used in previous collaborations with RCRM and administered by specially trained interviewers. Once 50 trios have been recruited (10 from each of the 5 exposure categories), we will conduct an interim evaluation of participation rates, sample collection and quality, and dose reconstruction in order to modify the protocol as needed. The analytical approach will be to correlate the extent, especially for de novo events of genetic alterations in the offspring with parental pre-conceptional radiation dose overall and by parental origin. The statistical power in relation to de novo mutations is very high, in excess of 90%, but somewhat lower for trends in minisatellite mutations. Study findings will contribute importantly to knowledge of the heritable effects of moderate- and low-dose radiation exposure in humans and to radiation risk projection. Eventually data from the Trio Study may be shared with the international community through dbGap.

  Study phs001163

• The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension

  Study Design: The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension contains N=797 participants. At the time of recruitment individuals ranged from 15-84 years of age and had varying ethnic backgrounds (Whites, African-Americans and Hispanics). The cohort was developed to study the genetic basis of autonomic dysfunction in human essential hypertension (reviewed in Zhang et al. Curr Hypertens Rep. 2011 13: 36-45. PMID: 21104344) and contains cross-sectionally collected phenotypes related to blood pressure regulation.  Phenotypes: Phenotype data specifically focuses on the sympathetic branch of the autonomic system, which is a key regulator of blood pressure. Data includes circulating concentrations of the secretory "quantum" (catecholamines, neuropeptides, chromogranins) which influence vascular responses to sympatho-adrenal activation resulting in blood pressure. Other measures on the twins and a subset of family members include a standard urine panel with absolute concentrations of potassium, sodium, uric acid, phosphorous; DynaPulse acquired heart rate and blood pressure measures including systolic and diastolic blood pressure, mean arterial pressure, heart rate, Left Ventricular (LV) ejection time, LV contractility, cardiac output, stroke volume data including; and absolute concentrations of plasma aldosterone, endothelin, leptin, and insulin. Phenotype data is included for the 697 individuals sequenced here and 100 family members.  Whole Genome Sequence Data Generation: Whole genome sequencing (20X coverage) was conducted on plasma-derived DNA. The WGS was generated using the Illumina HiSeq X Ten sequencing platform with variants called by Human Longevity, Inc (HLI; Ref 1). Preparation of sample libraries was conducted by mechanical shearing of gDNA (100-800 bp), isolation of DNA fragments 300-500bp in size, followed by library PCR amplification employing high-fidelity, low-bias PCR to amplify library fragments consisting of appropriate adapter sequences on both ends. BAM files were created by alignment of sequence reads to the reference genome (GRCh38) using iSAAC-01.14.02.06 (Python2.7). Note: The user may want to realign the sequence data and recall variants. In total, the WGS dataset contains 30 monozygotic twin pairs represented by one member of the twin pair, 133 monozygotic twin pairs with both individuals sequenced, 7 dizygotic twin pairs represented by one member of the twin pair, 67 dizygotic twin pairs with both individuals sequenced, 8 twin pairs with undetermined zygosity (both individuals sequenced) and 1 triplet with mother (all individuals sequenced). The dataset also contains sequences of 260 family members of twins including their mother, father, non-twin sibling, and offspring. Table 1 describes the composition of families ("sibling" refers to a non-twin sibling in the cohort). Note: We suggest users check gender and family relatedness. Table 1: Description of the families with sequence data                                                                                                               Units with:Twin PairsTwin (no pairs)No twinSibshipsMother and Father511Mother only1222Father only113One or more siblings22133Mother and siblings132Father and siblings(s)211Offspring of twins11Non twin siblings2Sib with unknown relative1Only one member of8The UCSD/O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension is now being managed at the UCSD School of Medicine's Institute for Genomic Medicine (IGM). The TSP Resource has collected a wide range of information (phenotypic, genotypic, demographic, metabolomic) and reagents (blood, plasma, urine, DNA, human induced pluripotent stem cells). For additional information about the resource, including other data types available as well as references and links to data from studies with previous collaborators, please go to the resource website at IGM [http://igm.ucsd.edu/research/twins-resource.shtml] or contact Dr. Brinda Rana at UCSD [bkrana@ucsd.edu]. 

  Study phs002230

• The Collaborative Study on the Genetics of Alcoholism (COGA)

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results, are included for a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative families was selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Human OmniExpress array 12.VI to genotype 2,282 subjects selected from 118 densely affected families. Genotyping was performed at the Genome Technology Access Center at Washington University School of Medicine in St. Louis. In addition, we also included genotypes for subjects (n=275 subjects) from these 118 families who were genotyped in a previous case-control GWAS using the Illumina 1M array. For quality control purposes, 51 of the 275 subjects were genotyped again on the Illumina Human OmniExpress array at the Washington University School of Medicine core facility.In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2 (v2). For v2, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings. Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance use variables are made available in v2. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125]. GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976]. GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS [phs001208]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000763

• Cancer Genome Project Exome Sequencing

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.

  Dataset EGAD00001000289

• InterPregGen-GWAS-UZB-1

  GWAS genotype data for maternal and fetal (baby) cases of preeclampsia and controls from Uzbekistan. This dataset is a component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium members in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Dataset EGAD00010001918

• CITE-seq AdaptNK

  CITEseq was performed as outlined in Biolegend ‘TotalSeqTM-A Antibodies and Cell Hashing with 10x Single Cell 3' Reagent Kit v3 3.1 Protocol’ with minor modifications, using Biolegend oligo-conjugated antibodies and streptavidin TotalSeq reagents. Briefly, ADAPT-NK cells were stained with CD56-biotin mAb (Miltenyi, clone REA196), followed by TotalSeq antibodies and streptavidin-PE and Live/Dead Aqua (Invitrogen). Cells were subsequently sorted for viable CD56+ cells by flow cytometry.

  Dataset EGAD50000000329

• PBMC scRNA-seq data using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data and single-cell CITE-seq data collected from 16 patients enrolled in GO30103 trial, and the cell level annotation. Specifically, PBMCs at C1D1, C1D15 (2 weeks after treatment), C2D1 (3 weeks after treatment) and C4D1 (9 weeks after treatment) were collected and subject to 10x Genomics protocol. Associated metadata also included.

  Dataset EGAD50000000370

• RNAseq of preneoplasia lung adenocarcinoma

  RNA sequencing of 168 pulmonary samples including lung preneoplasia atypical adenomatous hyperplasia (AAH, N=38), adenocarcinoma in situ (AIS, N=22), minimally invasive adenocarcinoma (MIA, N=19) and invasive lung adenocarcinoma (ADC, N=38) and adjacent lung tissues (Normal, N=62).

  Study EGAS50000000271

• Ultrasensitive Profiling of UV Mutations in Facial Tumors in TSC

  In this study we searched for mutations in the TSC2 and TP53 genes in sample sets from individuals with Tuberous Sclerosis Complex (TSC) and from subjects without TSC. The study was focused on the analysis of TSC facial angiofibroma.

  Study phs002914

• An Omics View of Asthma through Monozygotic Twins

  The etiology of asthma involves both genetic and non-genetic factors. We performed whole transcriptome sequencing on monozygotic twins discordant or concordant for asthma (with concordant healthy twins as controls), and identified multiple potential transcriptomic profiles associated with the asthma phenotype.

  Study phs000886

• Single Cell ATAC-Seq of MELAS

  This dataset includes combined single Assay for Transposase-Accessible Chromatin, using sequencing (ATAC-seq), and mitochondrial DNA sequencing of peripheral blood mononuclear cells from three individuals with m.3243A>G associated MELAS (Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like episodes).

  Study phs002217

• Characterization of Clonal Evolution in Microsatellite Unstable Metastatic Cancers through Multi-Regional Tumor Sequencing

  Whole exome sequencing was performed on blood and multiple tumor samples from six patients with known microsatellite unstable tumors. Subclones within each tumor site were identified and within each subclone, differing microsatellite instability was characterized.

  Study phs001925

• Eosinophil Activation and Function in Parasitic Infections and Other Conditions with Increased Tissue or Peripheral Blood Eosinophilia in Humans

  Whole-genome sequencing of tumors and matched normal samples from 11 patients with PDGFR-rearranged hypereosinophilic syndrome reveals simple genomic alterations in this disease without recurrent somatic changes besides the known rearrangement.

  Study phs003180

• Low-coverage whole-sequencing of metastasised colorectal cancer samples treated with bevazicumab

  Low-coverage whole-genome sequencing (LC-WGS) was performed on tumor tissue, normal tissue and plasma samples collected from mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444) and the University Medical Center Mannheim (UMM).

  Study EGAS50000000131

• Profiling of gene expression and epigenomics in the fetal brain

  scRNA-seq and Cut&Tag from a sample of the human fetal brain. To compare neurogenesis in the primary human brain with that in organoids, we profiled transcriptome and chromatin accessibility (10X multiome) as well as bulk Cut&Tag of histone modifications H3K27me3, H3K27ac and H3K4me3. We used a human brain sample from GW 19 for all experiments.

  Dataset EGAD50000000225

• Non-KMT2Ar infant Acute Lymphoblastic Leukemia Sequencing

  Integrated genomic analysis of non-KMT2A rearranged infant ALL reveals clinically relevant alterations and common disease origins with childhood ALL. Whole genome and whole transcriptome sequencing from 21 infant ALL patients with no matched normal DNA sequencing.

  Study EGAS50000000405

• IMPRESS_all

  Dataset containing tumor, normal and blood sample data, for various tissue and tumor types. Data is targeted methylation data, using smMIP probes to target informative CpG sites in the genome. Sample type can be inferred from the name, with 'W' being normal samples and 'TC' tumor samples. Dataset contains 259 samples in duplicate, with one half of the runs being cut by MSRE's, and the other not. For every sample paired fastq files are present.

  Dataset EGAD50000000882

• Colorectal cancer functional annotation - MPRA

  We performed a Massively Parallel Reporter Assay (MPRA) in colorectal cancer (CRC) cell lines HT29 and SW403 and normal colon cell line HCEC-1CT. We specifically targeted the regions around the CRC GWAS loci to identify which variants alter transcription.

  Study EGAS50000000406

• Dataset for WGS and RNA samples of acute myeloid leukemia with MNX1 expression (non-hipo)

  This dataset contains 115 samples of WGS, ATAC, 4C and RNAseq samples of patients with acute myeloid leukemia. The sequencing was performed on Illumina HiSeq 4000, 2000 and HiSeq X using Illumina TruSeq Nano DNA and Agilent Strand Specific RNA Kits. The sequencing was always paired.

  Dataset EGAD50000001097

• Anti-MPO BCR sequences described in 'Anti-myeloperoxidase IgM B cells in anti-neutrophil cytoplasmic antibody-associated vasculitis'

  FASTA files from quality-checked Sanger Sequencing results from BCR-specific PCR products. B cells from 4 different MPO+ AAV patients were single cell sorted and processed to sequence the specific BCR, resulting in 51, 175, 12 and 3 heavy chain BCR sequences for AAV1, 2, 3, and 5 respectively. Sequence names indicate patient ID and isotype (IgG, IgM or IgA).

  Dataset EGAD50000001112

• WES of head and neck cancer patients refractory to anti-PD-1 therapy

  Whole exome sequencing (WES) was performed on baseline (before low-dose 5-aza treatment) blood and tumor paired samples from 12 participants with head and neck cancer who were refractory to anti-PD-1 therapy. DNA extractions were performed by the Broad Institute of MIT and Harvard using Qiagen AllPrep DNA/RNA kits (Cat. 80204). In total, 24 150-bp pair-end WES data were generated by Illumina.

  Dataset EGAD50000001011

• Cohort B tumor exome sequencing

  Cohort B includes IDH-wild type, EGFR amplified, surgically derived glioblastoma tissue samples from male and female individuals. Tumor DNA was isolated from FFPE tissue. Both tumor and germline DNA are present for each sample in the overall dataset.

  Study EGAS50000000955

• Single-cell RNA seq-derived signatures define response patterns to atezolizumab + bevacizumab in advanced hepatocellular carcinoma

  FASTq files and normalised gene expression counts from bulk RNA-sequencing of pre-treatment tumour (n=39) and adjacent non-tumour tissue samples (n=13) from advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab.

  Study EGAS50000000838