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• WTCCC case-control study for Coronary Artery Disease

  WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000003

• Collagen XVII Promotes Pancreatic Cancer Through Regulation of PIK3R5

  Pancreatic ductal adenocarcinoma (PDAC) contains a desmoplastic stroma that promotes the aggressive biology of this disease. While the varied mechanisms by which fibrillar collagens contribute to PDAC have been defined, little is known about the contribution of transmembrane collagens. Among this class of collagens, Collagen XVII uniquely contains an extensive intracellular domain that connects intracellular cytoplasmic components with the extracellular matrix. Collagen XVII is best characterized as the defining component of the type I hemidesmosome, an anchoring complex that attaches epithelial cells to the underlying basement membrane. In this study, we characterize the expression of collagen XVII in PDAC and the mechanisms by which it contributes to PDAC biology. We demonstrate that crosstalk between PDAC cells and cancer associated fibroblasts drive collagen XVII expression in vitro and xenograft tumor models in vivo. Genetic depletion of collagen XVII in low-passage patient derived cell lines diminishes their metastatic potential and ability to form tumors in mice. Whole transcriptome sequencing of tumors formed by cells with diminished collagen XVII levels revealed dramatically lower levels of PIK3R5, a regulatory subunit of class IB phosphatidylinositol-3-kinase (PI3K) that interacts with G protein-coupled receptors. Consistent with this, collagen XVII-deficient tumors exhibited lower levels of phosphorylated AKT, a downstream effector of PI3K. The studies highlight the importance of collagen XVII signaling in PDAC and define a novel mechanism by which collagen XVII mediates activation of PI3K.

  Study phs003641

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Genome-Wide Association Study of HIV-1 Host Genetics Among Injection Drug Users

  The overarching goal of this project is to identify and characterize genetic determinants of HIV 1 susceptibility and resistance in samples of African American (AA) and European American (EA) injection drug users (IDUs) by conducting (1) a case/control genome-wide association (GWA) study of HIV 1 infection (positive/negative); (2) a case-only GWA study of viral load among HIV+ IDUs. The study uses existing samples and data from Urban Health Study (UHS) (PI: Alex Kral), which was the longest-running study of street-recruited IDUs in North America, from 1986-2005. UHS was a serial, cross-sectional sero-epidemiological study. Data were collected every 6 months in communities with a high prevalence of injection drug use in the San Francisco Bay Area. It used targeted sampling in neighborhoods at easily accessible community field sites, such as churches, single room occupancy hotels, and community centers. Eligibility criteria for initial entry to the study were (1) injection drug use in past 30 days; (2) ability to provide informed consent; and (3) age 18 or older. The UHS cohort includes over 9,000 African American and European American IDUs whose serum samples have been stored and data are available on HIV antibody status, HIV risk behaviors, drug abuse and demographics. The current study includes 985 HIV+ cases and 5,222 HIV- controls. Approximately six HIV- controls per case were frequency matched on: (1) self-reported ancestry; (2) sex; (3) age; (4) year of ascertainment; and (5) HIV risk class. This GWAS (DA026141) was funded by the National Institute on Drug Abuse (NIDA; PI: Eric O. Johnson). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by NIDA and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C).

  Study phs000454

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• WTCCC2 case-control study for Ulcerative Colitis

  WTCCC2 project genome-wide case-control association study for Ulcerative Colitis (UC) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000084

• 10x Genomics raw data of intestinal plasma cells

  The dataset contains raw fastq files (fastq.gz) for Chromium Single Cell 5’ gene expression (GEX), human B cell VDJ and feature barcode (CSP) sequencing from transglutaminase 2-specific and other small intestinal plasma cells isolated from four untreated celiac disease patients. Single cell 5’ gene expression, V(D)J-enriched and cell surface protein libraries were generated using Chromium single cell kits, and barcoded cDNA from a total of 5,000-10,000 cells per sample was generated using the 10x Genomics Chromium Controller. The libraries were pooled prior to sequencing on a NovaSeq 6000 instrument (Illumina) using the following configuration: read 1: 26 cycles, read 2: 89 cycles, index read 1: 8 cycles.

  Dataset EGAD50000000342

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• Genomewide Association Study of Inflammatory Bowel Disease

  WTCCC genome-wide case-control association study for Inflammatory Bowel Disease (IBD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000006