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• Genetic vulnerability of knockout cancer lines (2019-04-01)

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004881

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• Chip_seq_oesophageal_adenocarcinoma_

  There is complex interplay between underlying genetic sequence and epigenetic factors, however this interplay is still illusive. Massively reconstructed cancer genomes can be used in order to better understand this relationship. Six oesophageal adenocarcinoma organoids will be sequenced using long read sequencing technologies and will be profiled for a range of epigenetic marks. Combination of genetic and epigenetic data will allow the thorough characterisation of reference cancer genomes and will provide novel insights into mechanisms of gene regulation. Description: Chip-seq Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger.

  Study EGAS00001007180

• All you need to know about our new DAC Portal v2

  An updated version to boost the management of DACs (Data Access Committees), policies, and data access requests. In September of 2023, we launched new services for all EGA users, including a DAC Portal. Since then, our team has been working to refine it and improve the user experience. The version 2 of our DAC Portal is now ready, with a range of new features aimed at streamlining your workflow and boosting productivity. If you are interested in learning more about the latest version of our DAC Portal, then you are in the right place! In this post, you will find information about the implemented features and more. The full documentation is available on our website. Moreover, we highly recommend exploring the DAC Portal through the Take the Tour. This said, let's get cracking! Customise your data access requests table This table offers the possibility to tailor information about the data access requests by making visible or hiding different columns regarding the Dataset Persistent Identifier, the Organisation or the requestor's name s, among others. You can choose which columns to see, depending on your needs and interests. Additionally, we have implemented two new features columns with two new functionalities, DAC Comment and Expiration Date. You can find more details in the following sections! In this table, all data access requests are displayed by default. With the latest version of the Portal, you can now apply filters, combine them, and save them for future use. Leave internal comments on pending requests and visible to all the DAC Members We understand that many Data Access Committees (DACs) cannot instantly approve or deny data access requests. Often, there's an intermediary phase where discussions and the signing of legal documents are necessary. To facilitate this process, we've introduced the DAC comment feature! When you navigate to the DAC column, you'll find two tabs: "User" and "DAC". Under "User", you'll see the message provided by the requester at the time of requesting access to the data. As a DAC member/admin, you can then add an internal comment in the "DAC" tab. These comments are visible only to DAC members/admins, ensuring confidentiality. Requesters won't have access to DAC comments. By adding a DAC comment to a pending request, we'll know that you've begun reviewing it. This allows you to filter pending requests without DAC comments to focus on genuinely new requests, and it prevents you from receiving email notifications about ongoing data requests. Set expiration dates for permissions and revoke them automatically The latest update to the DAC Portal introduces a new feature allowing you to set expiration dates for new access requests. For instance, if you anticipate approving a data access request but only wish to grant access for a limited time, you can now specify an expiration date for the granted permissions. Once this date is reached, the permissions will automatically be revoked. By default, permissions are granted indefinitely without an expiration date. However, if you ever need to revoke permissions, you can easily do so from the History page. Audit your metadata objects Managing and auditing your metadata objects will be easier from now on as the new DAC Portal enhances and facilitates your role as a Data Controller. This is possible thanks to the tables available in each of the primary tabs visible on the homepage: DACs, Policies and Datasets. Starting with DACs, this section allows to check the policies linked to a specific DAC. In Policies, you can obtain a list of the datasets connected to a particular policy. In the Dataset tab, it is possible to group datasets by either DAC or Policy, as well as the release status. Now you have the option of deprecating metadata objects that you don’t want to use anymore, or that were created by mistake. You will find the deprecate button on the EDIT page of the DAC, as well as for registered policies. You can find more information here. What's neat about this feature is that once a DAC or policy is deprecated, it becomes hidden within the DAC Portal. This ensures that you only see information that is consistently up to date! Define your preferences regarding email notifications For pending requests, you will be able to decide how often you want to get the notifications: daily, weekly or fortnightly. Remember, you will not receive email notifications for pending requests with a DAC comment! Furthermore, you have the flexibility to decide which notifications you wish to receive, such as invitations to join a new DAC or notifications regarding DAC acceptance by the Helpdesk, among other options. Check the User preference to see the complete list of available notification settings! What’s next: incoming DAC Portal API In addition to the new DAC Portal, we are excited to announce the release of the DAC API! This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can consult the DAC API specification. This post was written by Aina Jené and Ana T. Alonso.

  Blog new-dac-portal-v2

• Platelets contain a repertoire of DNA fragments that map over the human nuclear genome, including tumour-derived DNA in patients with active malignancy.

  This dataset consists of WGS from six patients with a recent diagnosis of gastrointestinal adenocarcinoma. DNA-Seq libraries were prepared from platelet DNA (pDNA) and plasma cfDNA obtained from the same peripheral blood sample. pDNA was size selected into 2 groups (small, s-pDNA: less than 600 bp and long, b-pDNA: greater than 600 bp). The short fragments were further cleaned to remove <100 bp fragments and large platelet fragments were fragmented via sonication. Libraries were then prepared using the NEBNext Ultra II DNA Sample Preparation Kit for Illumina according to the manufacturer’s protocol and sequenced on an Illumina NextSeq 500 (300 cycle PE) at low-pass (0.1X) for all samples, and 10X for the cfDNA and s-pDNA, using four lanes in each sample.

  Dataset EGAD00001009856

• Mutational signatures of environmental carcinogens in human tissue organoids

  Whole genome sequencing of human tumours has revealed distinct patterns (signatures) of mutations that provide clues to the causative origins of cancer. Some signatures have been attributed to endogenous processes, some to exogenous agents, while a substantial proportion are of unknown origin. Generation of mutational signatures induced in experimental systems can verify the signature assignments and shed light on their origins and mechanisms. We have investigated mutational signatures of environmental carcinogens in human tissue organoid cultures. These 3-dimensional systems retain some of the architecture and functions of the organs from which they are derived, affording the opportunity to observe the effects of carcinogens in both target and non-target organs. There was a lesser requirement for an exogenous metabolizing system, as the cultures were, in most cases, capable of activating test agents. Duplex sequencing eliminated PCR amplification errors from mutational profiles and removed the need to clone carcinogen-treated cultures. Gastric, colon, liver, pancreas and kidney organoids were exposed to benzo[a]pyrene (BaP), aflatoxin B1 (AFB1), aristolochic acid (AAI) and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP). All four agents induced single-base substitution (SBS) signatures, BaP and AAI induced double-base substitution (DBS) signatures and indel (ID) signatures, and PhIP also induced an ID signature. These signatures were the same in all five organoid types, although there were quantitative differences. A further 13 environmental carcinogens were investigated in human gastric organoids, and signatures were obtained for seven of them: ethylnitrosourea (ENU), methylazoxymethanol acetate (MAM), N-methyl-N′-nitro-N-nitrosoguanidine (MMNG), potassium bromate, glycidamide, styrene oxide and propylene oxide, providing additional insights into processes underlying the causes of human cancer.

  Dataset EGAD00001015616

• Mutational signatures of environmental carcinogens in human tissue organoids – WGS Bulk Normals

  Whole genome sequencing of human tumours has revealed distinct patterns (signatures) of mutations that provide clues to the causative origins of cancer. Some signatures have been attributed to endogenous processes, some to exogenous agents, while a substantial proportion are of unknown origin. Generation of mutational signatures induced in experimental systems can verify the signature assignments and shed light on their origins and mechanisms. We have investigated mutational signatures of environmental carcinogens in human tissue organoid cultures. These 3-dimensional systems retain some of the architecture and functions of the organs from which they are derived, affording the opportunity to observe the effects of carcinogens in both target and non-target organs. There was a lesser requirement for an exogenous metabolizing system, as the cultures were, in most cases, capable of activating test agents. Duplex sequencing eliminated PCR amplification errors from mutational profiles and removed the need to clone carcinogen-treated cultures. Gastric, colon, liver, pancreas and kidney organoids were exposed to benzo[a]pyrene (BaP), aflatoxin B1 (AFB1), aristolochic acid (AAI) and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP). All four agents induced single-base substitution (SBS) signatures, BaP and AAI induced double-base substitution (DBS) signatures and indel (ID) signatures, and PhIP also induced an ID signature. These signatures were the same in all five organoid types, although there were quantitative differences. A further 13 environmental carcinogens were investigated in human gastric organoids, and signatures were obtained for seven of them: ethylnitrosourea (ENU), methylazoxymethanol acetate (MAM), N-methyl-N′-nitro-N-nitrosoguanidine (MMNG), potassium bromate, glycidamide, styrene oxide and propylene oxide, providing additional insights into processes underlying the causes of human cancer.

  Dataset EGAD00001015630

• GenomeDenmark Phase 2 - MHC haplotypes

  The MHC vcf call set was generated using a modified AsmVar and BayesTyper pipeline. In contrast to the original pipeline, where variant calling is performed using alignment of collapsed assemblies to a reference genome, the MHC call set was produced using alignment of phased MHC haplotypes. Two iterations of BayesTyper was run, a first iteration for each haplotype seperately and a second iteration performing joint variant calling on all haplotypes. 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 EGAD00001003455

• Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

  Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

  Study phs000629

• Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

  While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE [Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics] project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis.

  Study phs001703