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• METABRIC: Data from Batra et al (2021); DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation

  DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, RRBS-based profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, the study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

  Study EGAS00001004327

• Genetic Epidemiology of Ovarian Cancer Histotypes

  Epithelial ovarian cancer is a highly fatal malignancy with known genetic etiology; however, it is estimated that a substantial portion of narrow sense heritability remains to be discovered. The goal of this research was to use genetic information from distantly related ovarian cancer cases to identify regions of the genome that may harbor rare risk variants for epithelial ovarian cancer. The study was conducted in the setting of the Utah Population Database, a statewide data resource in which extensive ancestry data are linked to Utah Cancer Registry records. Focusing on families with a statistically significant excess risk of epithelial ovarian cancer, we used the Infinium Global Screening Array v.3.0 to generate germline genotyping data for distantly related cases. We then applied Shared Genomic Segment Analysis to each set of related cases to identify genomic regions that may harbor ovarian cancer risk variants. Eleven regions were identified. Genotype data are available through dbGaP for one case from each pedigree. Genotype data from other ovarian cancer cases within the high-risk pedigrees as well as the pedigrees' corresponding structures can be requested and made available with approval from the Utah Resource for Genetic and Epidemiologic Research (RGE).

  Study phs003140

• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• Family Genomics of Congenital Heart Defects

  The study identified the causal mutation in a five-generation pedigree harboring a cardiac septal defect. The inheritance pattern is consistent with an autosomal dominant mutation with high penetrance. We performed whole-genome sequencing (Complete Genomics) on 21 individuals in the pedigree, of which 11 individuals are affected. We identified a single gene, GATA4, as primarily responsible for this cardiac phenotype in this pedigree.

  Study phs000758

• Human Microbiome Project Demonstration Study of Cutaneous Microbiome in Psoriasis

  Psoriasis, a highly prevalent disease of humans of unknown cause, is a chronic inflammatory disorder primarily involving skin, with distinctive clinical characteristics. With the newly developed tools that facilitate microbiome research, it now is possible to assess whether the cutaneous microbiome plays a role in the pathogenesis of this disorder. Preliminary data from our studies suggest that the cutaneous microbiome in psoriasis is complex and possibly different from normal. To deal with this complexity, we propose to examine the cutaneous microbiome in relation to psoriasis with explorations at several taxonomic and informatic levels. Our overall objective is to examine how changes in the normal cutaneous microbiome contribute to the pathogenesis of psoriasis. Since causality is complex and often difficult to prove, and beyond the scope of this RFP, our overall hypothesis is that there are alterations in the cutaneous microbiome in areas of skin affected by psoriasis in comparison with the range observed in clinically unaffected areas, or in healthy persons. We also hypothesize that the characteristics of the microbiome may affect clinical responses to the immunomodulatory agents used to treat psoriasis. An alternative hypothesis is that effective treatment of psoriasis with systemic immunomodulatory agents will not substantially affect the disordered microbial ecosystem. Such observations would provide evidence for the roles of the microbiota in this disorder. Since an important consideration in microbiome research is the optimal level (e.g. phylum, genus, species, strain, gene) at which to examine a scientific question, and we are not yet certain what are the optimal levels for psoriasis, this also will be examined. Our studies of psoriasis should allow development of both approaches and tools that will have general utility for Microbiome research. To test our hypothesis, we propose the following specific aims: 1) To understand the cutaneous microbiome species composition overlaying psoriatic lesions; 2)To investigate differences in metagenome content for psoriatic lesions compared to normal skin; 3) To identify differences in the transcriptional profiles of the microbiome and the host between normal skin and psoriatic lesions using high-throughput sequencing; and 4) To estimate the effects of systemic immunomodulatory therapy for psoriasis on microbiome composition. In total, these studies should help us understand the role of the microbiome in psoriasis pathogenesis. We sought to characterize and compare the cutaneous microbiota of psoriatic lesions (lesion), unaffected contralateral skin from psoriatic patients (normal), and similar skin loci in matched healthy controls (control) in order to discern patterns that govern skin colonization and their relationship to clinical diagnosis. Using high-throughput 16S rRNA sequencing, we assayed the cutaneous bacterial communities of 51 matched triplets and characterized these samples using community data analysis techniques.

  Study phs000251

• RNA sequencing of NK cells in human lung

  Human lung tissue-resident NK cells (trNK cells) are likely to play important roles in viral infections, inflammation and cancer. However, knowledge about lung trNK cells is lacking but is fundamental for exploiting these cells in therapeutic approaches. Here we analysed the transcriptome of CD69+CD49a+CD103+CD16-CD56bright, CD69+CD49a+CD103-CD16-CD56bright, CD69+CD49a-CD103-CD16-CD56bright, CD69-CD49a-CD103-CD16-CD56bright, and CD56dimCD16+NKG2A+CD57- NK cells isolated from human lung.

  Study EGAS00001003544

• Detecting and Subtyping Lung Cancer Through Analysis of Circulating Tumor DNA

  Small cell lung cancer (SCLC) is among the most aggressive tumors with poor clinical outcomes. Tumors are rarely resected, which is a major barrier to molecular profiling of tumor tissue; therefore, non-invasive approaches using circulating tumor DNA (ctDNA) from liquid biopsies are needed to help advance research and clinical care for patients with SCLC. We developed a targeted capture panel that profiles SCLC genes and transcriptional regulation sites, including transcription start sites (TSS) and transcription factor binding sites (TFBS). This is a single assay that detects genomic mutations and transcriptional regulation activity based on ctDNA fragment patterns reflecting epigenetic nucleosomal positions. We applied this assay to sequence patient-derived xenograft (PDX) and patient plasma samples. We also performed whole genome sequencing (WGS) for a subset of the PDX plasma samples to validate the capture data. We developed new algorithms to quantify activity of key SCLC marker genes of ASCL1, NEUROD1, POU2F3, and ATOH1 and to classify SCLC subtypes based on activity of these markers. Furthermore, we developed a model to classify SCLC from non-small cell lung cancer (NSCLC), which has potential important applications for monitoring transdifferentiation and tumor plasticity.

  Study phs003570

• Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

  The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

  Study phs000220

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• GenomeDenmark Phase 2 - whole genome variants called using BayesTyper

  Variants and genotypes called in 50 danish parent-offspring trios from 80x Illumina sequencing data using BayesTyper. Data was produced using different insert size libraries of the sizes 180, 500, 800, 2000, 5000, 10000 and 20000 bp. The sample IDs for the fathers and mothers are TrioID-01 and TrioID-02, respectively, and the IDs for the children are TrioID-0x, where x is a number between 3 and 7

  Dataset EGAD00001003188