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• Hyperdiploid Acute Lymphoblastic Leukemia RNA-Seq

  Few genetic drivers of children with hyperdiploid precursor B-cell acute lymphoblastic leukemia (ALL) have been identified to date. In an effort to detect novel genomic rearrangements that could be promoting leukemogenesis in this subset of patients, we sequenced ribosomal RNA-depleted transcriptomes isolated from 5 hyperdiploid acute lymphoblastic leukemia samples. In addition to looking for novel genomic rearrangements, we also sought to identify transcripts that could be created as a result of a novel posttranscriptional process. Surprisingly, we identified transcripts created as the result of exon circularization. The results of our studies are present in the paper "Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types" published in PLoS ONE (PMID: 22319583).

  Study phs000522

• Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

  The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

  Study phs002295

• Transcription Factor Analysis of SLE

  Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets. Results: We examined 20 patients with SLE and 8 controls and found the TNF, IL-2/STAT5, and KRAS pathways were identified across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Conclusions: NFkB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.

  Study phs003713

• Mutated H3 Histones Drive Human Pre-Leukemic Hematopoietic Stem Cell Expansion And Promote Leukemic Aggressiveness

  Leukemogenesis is a stepwise progression from mutated, pre-neoplastic hematopoietic stem cells (HSCs) to full-blown leukemia. Our ability to prevent or treat acute myeloid leukemia (AML) is limited by our incomplete understanding of the epigenetic disruption that is central to this process, including improper histone methylation. Comprehensive analysis of 16 histone H3 genes in 434 primary AML samples identified Q69H, A26P, R2Q, R8H and K27M/I mutations (1.6%), and a higher incidence in secondary AML (s-AML) (9%). We establish that these mutations are important early events in leukemogenesis. They occur in pre-leukemic HSCs, increase the frequency of functional human HSCs, and alter differentiation. The mutations are present in the major leukemic clones in primary samples, and the mutant histones amplify leukemic aggressiveness with increased proliferation, expansion of leukemic progenitor and blast cells, and superior competitiveness in vivo. These effects are dependent on the specific mutation. Genome-wide analysis of K27 mutants revealed increased expression of genes involved in erythrocyte and myeloid differentiation with a corresponding decrease in histone H3 K27 tri-methylation and increase in K27 acetylation. The functional impact of histone mutations is independent of RUNX1 mutations, although they can co-occur. These data establish the involvement of H3 mutations as initial drivers of pre-cancerous stem cell expansion and leukemogenesis.

  Study EGAS00001003288

• Whole Exome Sequencing of a Chinese Cataract Girl

  Whole exome sequencing of a Chinese girl with congenital cataract. The dataset contains one sample with two fastq files. The novel PAX6 mutation (c.221G>A) is associated with congenital cataract, and the WFS1 mutation (c.2070_2079del) interactively aggravates this process.

  Dataset EGAD00001008267

• Influence of the Microbiome on Epigenetic Mechanisms in IBD

  Live CD4 T cells were sorted from inflamed and non-inflamed tissue samples of IBD patients or from healthy and IBD blood samples. ATAC-Seq libraries were generated from live CD4 T cells sorted from i) inflamed and non-inflamed tissue samples, ii) healthy and IBD blood samples, or from iii) CD4 T cell subsets polarised from healthy blood samples. After isolating crude nuclei, live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry. On the other hand, single cell RNA-Seq libraries were generated exclusively from inflamed and non-inflamed tissue samples of Crohn’s disease patients. Briefly, live CD4 T cells were captured and encapsulated before cDNA amplification using the 10X Genomics Chromium Platform. Samples were prepared as outlined by 10x genomics Single Cell 3’ Reagent Kits v2 user guide. Samples were sequenced on a HiSeq 2500 with the following run parameters: Read 1 – 26 cycles, read 2 – 98 cycles, index 1 – 8 cycles.

  Dataset EGAD00001011066

• A Genome Wide Scan of Lung Cancer and Smoking

  The majority of cases of lung cancer are the culmination of a dynamic process that begins with smoking initiation, proceeds through dependency and smoking persistence, continues with lung cancer development and ends with progression to disseminated disease or response to therapy and survival. We are conducting a whole genome study of lung cancer and smoking to examine critical steps in lung cancer progression. This study is a genome-wide association study (GWAS) to investigate the genetic determinants of lung cancer risk. The study design efficiently allows identification of genes that also contribute to smoking persistence and outcome from lung cancer using a single GWAS of 5,900 subjects using the primary GENEVA dataset, derived from two studies. The first is the Environment and Genetics in Lung Cancer Etiology Study (EAGLE), a population-based, biologically intensive, case-control study from the Lombardy region of Italy including ~2000 newly diagnosed lung cancer cases and ~2000 age-, gender- and region- matched controls. The second is the Prostate, Lung, Colon and Ovary Study (PLCO) Cancer Screening Trial from which we have selected ~850 lung cancer cases and ~850 controls, also matched on age and gender. Understanding the basis for the well-established hereditary component of lung cancer and smoking persistence could provide new insights into etiology, prevention, and treatment, and have an enormous impact on public health. The same GWAS genotyping data in the two studies will be used to investigate the genetic determinants of smoking persistence. Specifically, we will analyze current smokers and former smokers from EAGLE and PLCO for diverse smoking phenotypes, including persistence of smoking as well as ever/never smoking comparisons, quitting attempts, and the Fagerström index of tobacco addiction. PLCO participants are all European-Americans and EAGLE involves subjects from Italy. EAGLE is a case-control study and contains 3937 phenotyped subjects. PLCO is a screening trial with a cohort design and contains 1651 phenotyped subjects. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to lung cancer and smoking through large-scale genome-wide association studies of population-based samples of lung cancer cases and controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000093

• Single-cell multidimensional profiling of tumor cell heterogeneity in supratentorial ependymomas

  Supratentorial ependymomas (ST-EPNs) are aggressive and treatment-resistant pediatric brain tumors that form along the human cortex, with suspected origin from radial glia cells. Although histologically similar, ST-EPNs are molecularly classified into six distinct subgroups, many of them remaining understudied. Here, we integrated molecular cell states and spatial architecture to resolve the cellular origins and aberrant differentiation trajectories of ST-EPNs at single-cell resolution. We show that, while all ST-EPNs display a unified origin from neuroepithelial cells, different subgroups harbor highly diverse cell states and differentiation potential associated with neural or ependymal differentiation. Spatial mapping uncovered a higher-order structural tumor organization driven by presence of the mesenchymal state, and refines classical histological features based on detailed molecular resolution. By benchmarking a morpho-molecular cell-state classification system in different disease models and human tumors, we identified four cellular subtypes defined by the architecture of neurite-like extensions that mediate either self-renewal or fast, saltatory invasive phenotypes reminiscent of neurons during neurodevelopment. Collectively, our study provides a comprehensive framework for the study of ST-EPN cellular states, and reveals biologically relevant tumor compartmentalization with potential clinical implication.

  Study EGAS50000001513

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. One possibility for this inefficiency is an incomplete understanding of the molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to develop a foundational dataset for identifying candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Study EGAS00001003667

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin