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• How to upload Crypt4GH files

  Uploading files Users who hold an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files, please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention, such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. To manage the available resources, we enforce a limit of 10TB per submission account at any one time. If you exceed this limit, a “permission denied” message will be displayed. This will prevent you from uploading more files, but connecting to your inbox.For submissions larger than 10TB, please perform uploads in 10TB batches: register all the metadata and then finalise the submission. Upload the next batch of files and repeat the same metadata registration and finalisation process until you have completed the file upload. Further information can be found in the SP documentation. INBOX FTP The INBOX is only compatible with files encrypted using the Crypt4gh tool Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated, you will be able to request a submitter role. [Optional] Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g., ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. To upload files to your account, you can use the graphical user interface (GUI) or the command line. Graphical User Interface (GUI)We recommend using FileZilla, a free, open-source FTP client. However, you can use any other GUI that allows connecting over the SFTP protocol. For FileZilla as your GUI, follow these steps to upload files: Create a new connection in Site Manager (File > Site Manager) and select the following options (Figure 1): Protocol: SFTP - SSH File Transfer ProtocolHost: __EGA_INBOX_DOMAIN__Logon Type: Key fileUser: your EGA usernameKey file: Path/to/your/private_keyFigure 1: Process of establishing a new connection to __EGA_INBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers.Click Connect, and you will log in remotely to your home directory. You can think of this folder as a storage "in the EGA cloud" in which you will add your files for the EGA. The uploading area has three folders:To-encrypt: Files uploaded in this folder will be encrypted automatically on the fly.Encrypted: Files uploaded in this folder must already be encrypted with Crypt4gh. Upload your files here if your connection is unstable or you have problems completing the upload into-encrypt.Etc: This folder contains two files that allow the server to show you your username and group instead of some internal numbers. Please do not upload files here; otherwise, you will obtain a permission denied error. Find the files you want to upload by browsing your local storage (left side of your screen in FileZilla). Select all the files you want to upload, then right-click on them and select Upload (Figure 2). Figure 2: Step-by-step process of manually uploading files to __EGA_INBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can transfer data from their local storage to the "EGA cloud" by following the depicted steps Please note that regardless of which folder you upload your files in, both folders (to-encrypt, encrypted) will point to the same path (/) (Figure 3). Therefore, you will see your files in both folders. Figure 3: Both folders, to-encrypt and encrypted, point to the same path (/)" If your connection is unstable, please encrypt your files first using Crypt4gh. Then upload them to the ‘encrypted’ folder. The example above shows how to connect to __EGA_INBOX_DOMAIN__ using the private key. However, if you prefer to log in using your credentials, you can do so. Please go to the Frequently Asked Questions (FAQs)  for more information. SFTP command line To upload files securely to your private area of the EGA, you can use SFTP(Secure File Transfer Protocol) with your favorite FTP client. Here's what you need to know to get started: Connect to the target host __EGA_INBOX_DOMAIN__. This is the new hostname for the EGA SFTP service. Log in with your EGA username and key files (or password). Upload files to your private EGA inbox to ensure that only you can access the files. By following these steps, you can securely upload your files to the EGA for safe storage and sharing. Using the SFTP command line client in Linux/Unix Open a terminal and type sftp username@hostnameEnter your EGA passwordTo see a list of available SFTP commands, type helpsftp> put – Upload filesftp> get – Download filesftp> cd path – Change remote directory to ‘path’sftp> pwd – Display remote working directorysftp> lcd path – Change the local directory to ‘path’sftp> lpwd – Display local working directorysftp> ls – Display the contents of the remote working directorysftp> lls – Display the contents of the local working directoryType the "put" command to upload files. For example: put *.bamUse the bye command to close the connection (SFTP session). After uploading- Once you have uploaded files to the inbox, please bear in mind that the checksum needs to be calculated, which can take up to two days. You will only be able to link your files to a run/analysis once the encrypted checksum has been calculated.- When linking your files to the 'Run' or 'Analysis', ensure that the file name matches the file path '/name' in the INBOX folder.- Please delete the files from your SFTP INBOX after all the runs/analyses have been registered and files are ingested (SP > Files > Files ingested). This will clear your inbox space an allow you to upload more files. This will also prevent the files from reappearing in your Submitter Portal inbox. Frequently Asked Questions Specific to the inbox What username should I use to log in to my inbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username.  If you have forgotten your registered username, please contact our Helpdesk team for assistance. How are checksums calculated in your inbox? If you encrypt the file beforehand and upload it to the "encrypted" folder, the unencrypted checksum will not be calculated until the file is ingested (i.e., until it is used in a run/analysis). If the file is uploaded to the "to-encrypt" folder, then both checksums are calculated.Please bear in mind that after files have been uploaded to the inbox, the checksum must be calculated, which can take from a few hours to two days.  Specific to using keys to authenticate Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_INBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

  Documentation submission/data/uploading-files/inbox

• Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

  Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step towards clinical application of patient-tailored treatment regimens. Toward this goal, we have established a library of 139 gynecologic tumors including cervical, endometrial, and epithelial ovarian cancers (EOCs) and uterine sarcomas that were genomically and/or pharmacologically annotated and explored dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discovered lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identified TP53 mutation as a molecular determinant that elicit therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identified transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Together, our results demonstrate potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers.

  Study EGAS00001003556

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• National Eye Institute (NEI) Genetic Epidemiology of Age-Related Macular Degeneration in the Old Order Amish

  Identifying genetic risk loci for Age-Related Macular Degeneration is important. Most of the loci identified to date have been found through the interrogation of common variants. This study initiates the identification of rare variants in a founder population, the Amish, and will use genotyping of known risk loci and ultimately use the whole exome chip to assess the association of Age-related Macular Degeneration with coding variants. We will further refine the Age-Related Macular Degeneration phenotype through the use of modern imaging, the OCT, to visualize the early anatomic signs of Age-Related Macular Degeneration. We hypothesize there are endophenotypes associated with specific genotypes that can be used to determine Age-related Macular Degeneration progression. These endophenotypes are hypothesized to be influenced by a combination of common and rare variants. We will relate these endophenotypes to genotypes to define the role of genetics in the progression of Age-Related Macular Degeneration and a new risk profile incorporating genotypic information.

  Study phs001361

• Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Study EGAS00001007650

• EGA account management

  How to manage your EGA account Welcome to the documentation page for creating an EGA user. The European Genome-Phenome Archive (EGA) is a platform for archiving, managing, and sharing human genomic and phenotypic data. To submit, access, and manage requests for the data hosted on the EGA platform, users are required to register for an account. This documentation page provides step-by-step instructions for creating an EGA user account, as well as information on the different types of EGA user accounts and their associated privileges. You can check the EGA data flow for a better understanding. Manage EGA account step-by-step guide Contact Information Public Keys Password Authenticator Federated Identity Sessions Request an EGA account step-by-step guide Fill in this form.You cannot use a generic email account (e.g., Gmail). Make sure you use your institutional email account.Your email is by default your username.The criteria for a strong password is: It should contain between 8 and 32 charactersIt should contain at least one uppercase letterIt should contain at least one numberIt should contain at least one special characterYou will need to wait for the Helpdesk team to check your identity. Please allow two business days for this step.After the Helpdesk validation step, you will receive an email with a link to validate your institutional email.Click the link to verify your email. It will redirect you to the EGA website.As soon as your account has been validated, you will be able to start adding more information to your EGA profile. For that, you first need to log in using your credentials from step 1. Manage EGA account step-by-step guide As a logged-in user, go to your profile by clicking on Welcome > My Profile. To modify it, click the Edit button.You will see the following options: Contact Information In this section, you can modify the personal information of your EGA account. Public Keys Adding a public key is necessary for downloading data via Live Outbox distribution. If you don’t know how to generate your key, you can follow the instructions available on How do I create a key? Password In the Password tab, you can change your password anytime to ensure the security of your account. However, if you receive an email notifying you that your password was modified and you did not initiate the change, it could be a sign that your account has been compromised. In this case, you should immediately contact our Helpdesk team to report the issue and receive assistance in restoring your account security. Authenticator You can set your two-factor authentication (2FA) system for your EGA account as an identity and access management security method that requires two forms of identification to access resources and data. To obtain your code, please follow the instructions below, also available in the Authenticator tab in your profile. Sessions The Sessions tab displays a list of all devices where you are currently logged in as an EGA user. This includes any open sessions you have on your computer, phone, or other devices. By reviewing the list of active sessions, you can monitor the devices that have access to your account and ensure that there are no unauthorised logins. If you notice any suspicious activity, you can close the sessions from this page to immediately terminate access to your account from the unauthorised device.

  Documentation how-to-manage-your-account

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_squamous_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002725

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002726

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003702

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Identification and characterisation of pathogenic and non-pathogenic FGF14 repeat expansions

  Repeat expansions in FGF14 cause autosomal dominant late-onset cerebellar ataxia (SCA27B) with estimated pathogenic thresholds of 250 (incomplete penetrance) and 300 AAG repeats (full penetrance), but the sequence of pathogenic and non-pathogenic expansions remains unexplored. Here, we demonstrate that STRling and ExpansionHunter accurately detect FGF14 expansions from short-read genomic data using outlier approaches. By combining long-range PCR and nanopore sequencing in 169 patients with cerebellar ataxia and 802 controls, we compare FGF14 expansion alleles, including interruptions and flanking regions. Uninterrupted AAG expansions are significantly enriched in patients with ataxia from a lower threshold (180-200 repeats) than previously reported based on expansion size alone. Conversely, AAGGAG hexameric expansions are equally frequent in patients and controls. Distinct 5' flanking regions, interruptions and pre-repeat sequences correlate with repeat size. Furthermore, pure AAG (pathogenic) and AAGGAG (non-pathogenic) repeats form different secondary structures. Regardless of expansion size, SCA27B is a recognizable clinical entity characterized by frequent episodic ataxia and downbeat nystagmus, similar to the presentation observed in a family with a previously unreported nonsense variant (SCA27A). Overall, this study suggests that SCA27B is a major overlooked cause of adult-onset ataxia, accounting for 23-31% of unsolved patients. We strongly recommend re-evaluating pathogenic thresholds and integrating expansion sequencing into the molecular diagnostic process.

  Study EGAS50000000481

• Rare occurrence of Aristolochic Acid Mutational Signatures in Oro-Gastrointestinal Tract Cancers

  Aristolochic Acids (AAs) are a family of carcinogenic phytochemical compounds commonly found in plants of Aristolochia and Asarum genus. Comprehensive genomic profiling of genitourinary and hepatobiliary cancers has highlighted the widespread prevalence of Aristolochic Acid (AA) signatures in cancer patients across parts of Asia, particularly in Taiwan. The aim of our study was to determine in Oro-Gastrointestinal Tract (OGITC) cancers, the prevalence, role and significance that AA plays as a driver of tumorigenesis as AA containing products are commonly administered orally. This would suggest a possible etiological relationship between cancers of OGITC. However, in this study the rarity of AA mutational signatures in OGITC suggests that AA is unlikely to drive carcinogenesis in OGITC through direct exposure. Our study is valuable to show that AA exposure is not an equal driver of tumorigenesis in different organs and represents an important piece of information in the field.

  Study EGAS00001005909

• Kids First: Whole Genome Sequencing of Nonsyndromic Craniosynostosis

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Nonsyndromic craniosynostosis (NCS) is a common, major structural birth defect - due to the premature fusion of one or more cranial sutures - that requires extensive surgical correction and is associated with considerable ongoing medical problems and health care costs. Because little is known about the causes of NCS, whole genome sequencing will help advance knowledge of genetic factors contributing to the etiology of NCS. Data from this project will lead to a better understanding of biological processes involved in the etiology of NCS and provide critical insights for development of early diagnostic tools and therapeutic strategies.

  Study phs001806

• Lenalidomide Resistance in del(5q) Myelodysplastic Syndrome Follows Loss of RUNX1/TP53-mediated Megakaryocytic Differentiation

  Interstitial deletion of the long arm of chromosome 5 (del(5q)) is the commonest structural genomic variant in myelodysplastic syndromes (MDS). Lenalidomide (LEN) is the treatment of choice for patients with del(5q) MDS, but half of the responding patients become resistant within two years. TP53 mutations are detected in ~20% of patients who become resistant to LEN. Our data show that patients who become resistant to LEN harbor either TP53 or RUNX1 mutations or loss of RUNX1 expression. Here we show that LEN-induced degradation of IKZF1 permits a RUNX1/GATA2 complex to drive megakaryocytic differentiation and consequent del(5q) MDS progenitor cell death via CRBN-mediated CSNK1A1 degradation. Overexpression of GATA2 is able to restore LEN sensitivity in the context of RUNX1 or TP53 mutations by enhancing LEN-induced megakaryocytic differentiation. Screening for TP53 and RUNX1 mutations or downregulation should identify patients resistant to LEN, and strategies to activate GATA2 may resensitize del(5q) MDS cells to LEN

  Study EGAS00001004113

• Human tumour ChIP-seq.

  We profiled 16 patient tumour samples by ChIP-seq. H3K27ac and Input are provided for 16 samples and H3K27me3 is provided for 14 samples. Among the 16 samples, 9 are G34WT and 7 are G34R/V. The raw fastq or bam files are provided.

  Dataset EGAD00001006100

• Paediatric Hepatic International Tumour Trial (JPLT2: PHITT)

  Hepatoblastoma (HBL) is the most common primary liver tumor in children. Despite their diversity in histopathological phenotype and clinical outcome, the underlying molecular aberrations have not been fully understood. Here we describe a comprehensive landscape of genomic, epigenomic, and transcriptomic heterogeneity among the 163 cases of HBLs and transitional liver cell tumors (TLCTs) collected in the multicenter clinical trial JPLT-2. The total numbers of mutational events in HBLs are very few (0.52 SNVs/Mb on exonic regions) but show a positive correlation with the age of onset. While dysregulation of Wnt-pathway related genes was observed (somatic deletion or mutations of CTNNB1 and germline or somatic mutations of APC) in 83.6% of the HBL cases, TERT promoter mutations are mainly in the elderly HBLs (> 8 years old), meeting with the proposed criteria of TLCT. These TLCT cases are clustered in the hypermethylated epigenotype in promoter and enhancer regions. Copy number analyses also revealed recurrent 11p15.5 UPD/LOHs including the IGF2/H19 region (31.6%), focal deletions in 4q35 (15.8%) and focal amplifications in 2q24.3 (7.0%) predominantly in the child and infant HBLs. Motif enrichment analysis of the specific hypomethylated enhancers in these HBL subtypes suggests specific binding of ASCL2, the regulatory transcription factor for definitive endoderm and digestive systems. Transcriptome and histochemical analysis revealed that ASCL2 is upregulated not in HCC and TLCT but in child and infant HBL, suggesting their ?cell of origin? derived from the premature hepatoblast with high proliferative potential such as intestinal epithelial cells. Systematic molecular profiling of HBL will provide a fundamental understanding of hepatoblast carcinogenesis and clues for risk stratification.

  Study JGAS000236

• Recursive splicing in long vertebrate genes

  Recent studies have shown that expression of many genes with exceptionally long introns in the mammalian brain can be perturbed by regulatory factors linked to neurodevelopmental or neurodegenerative disorders1-3, suggesting unique regulatory mechanisms. Here we identify functional recursive splice sites (RSS) in long introns of genes expressed in the brain. These RSS are highly conserved in genes with extreme length across diverse vertebrate species and permit step-wise removal of long introns via recursive splicing. Recursive splicing requires initial definition of a “recursive exon” that is located downstream of RSS, and most often contains premature stop codons. Moreover, we show that RSS create a splicing switch driven by splice site competition in order to distinguish primary mRNA isoforms from alternative isoforms that are prevalent in long genes. The recursive exon is not detectable in the dominant mRNA isoform due to recursive splicing, but is completely included when cryptic promoters or other cryptic exons are used. Thus, by coupling inclusion of recursive exons with the use of cryptic elements, RSS act to distinguish new mRNA isoforms emerging from long genes.

  Study EGAS00001001170

• Molecular subtypes of pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX explain biological variability

  Pancreatic Neuroendocrine Tumors (PanNETs) most probably arise from the islets of Langerhans, although direct evidence is still lacking. About 40% of non-functioning (NF) PanNETs harbour mutations in MEN1, often in conjunction with alterations in DAXX/ATRX. Despite the homogeneous genetic background, the ADM (mutation in DAXX/ATRX and MEN1) group is heterogeneous regarding molecular features and response to treatment. To explore the molecular and clinical heterogeneity within this group, we integrated transcriptomic and DNA methylation data from 36 and 93 samples, respectively. Using a multi-omic approach we described a two-level hierarchy separating PanNET subtypes mutated in MEN1, DAXX and ATRX. First, DNA methylation discriminates ADM-PanNET from PanNET mutated in MEN1 only (α-like). Compared to α-like, all ADM tumors exhibit DNA methylation changes at enhancer and lowly methylated regions as well as at peri-centromeric and telomeric regions, associated with alternative lengthening of telomeres, increased chromosomal instability, and enhanced proliferative capacity. At a second level, transcriptomic analysis revealed three distinct ADM subtypes: ADM hypoxic, ADM NST (No Special Type), and ADM immunosuppressive. The ADM hypoxic subtype is characterized by strong hypoxia signature, likely regulated epigenetically. The ADM NST subtype appears to be primarily driven by epigenetic changes that promote proliferation. The ADM immunosuppressive is highly enriched in immune component and strong metastasis-like signature. While all the three subtypes are highly associated with liver metastasis formation and invasion, the ADM immunosuppressive are significantly smaller (&lt;2.5 cm p.value=0.023) despite displaying aggressive molecular features. By defining these three novel ADM subtypes, our study provides a refined framework for understanding PanNET heterogeneity. This classification underscores potential diagnostic markers and highlights distinct biological vulnerabilities that may inform the development of subtype-tailored therapeutic strategies.

  Study EGAS00001008272

• Network-based systems pharmacology identifies heterogeneity in LCK and BCL2 signaling and differential vulnerability of T-cell acute lymphoblastic leukemia to targeted therapy

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and novel therapeutics are much needed. Profiling patient leukemia’ drug sensitivities ex vivo, we discovered striking inter-patient variability in T-ALL response to a panel of targeted agents. Applying network-based systems pharmacology analyses, by integrating ex vivo pharmacotyping, bulk and single-cell RNA-seq, genomics, phospho-proteomics, and genome-wide CRISPR screening data, to examine signal circuitry, we identified the pharmacogenomic basis of T-ALL drug response and revealed a therapeutic vulnerability that is directly related to the developmental stage of leukemia cells. In conclusion, our results indicate that heterogeneity in the differentiation of T-ALL drives activation of key signaling pathways in this leukemia, providing unique opportunities for targeted therapy.

  Study EGAS00001004700

• Endothelium-derived stromal cells contribute to bone marrow niche formation

  Comprehensive transcriptional characterization of bone marrow stromal cells by RNA sequencing was performed to determine the molecular properties/signatures of endothelium during niche formation.Here, we identify a rare subset of cells in the human fetal BM that co-express endothelial and stromal markers, including low-affinity nerve growth factor receptor (LNGFR/CD271). They display transcriptional reprogramming consistent with endothelial-to-mesenchymal transition (EndoMT), reflected in their potential to generate stromal cells with in vivo BM niche forming capacity.

  Study EGAS00001004946

• CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

  The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

  Study EGAS50000000170

• CSER: Evaluating Utility and Improving Implementation of Genomic Sequencing for Pediatric Cancer Patients in the Diverse Population and Healthcare Settings of Texas: The KidsCanSeq Study

  Through this Clinical Sequencing Evidence-Generating Research (CSER) with Enhanced Diversity project we are completing a clinical study (The Texas KidsCanSeq Study) comparing the results of targeted cancer panel sequencing versus genome-scale testing in pediatric cancer patients across diverse clinical settings. We will compare the targeted pediatric cancer panel to germline whole exome sequencing (WES) of unselected childhood cancer patients. We will also compare an RNA/DNA targeted pediatric cancer panel versus WES, transcriptome sequencing and copy number array of FFPE tumor samples for the subset of patients with high-risk tumors. Exome sequencing is performed from a blood or saliva sample of the pediatric age (0-18) patient. We are building on our success completing the CSER program BASIC3 exome sequencing trial (which included 60% Hispanic and African-American patients from a single large academic center) in this large multi-institutional study of an even more diverse patient population from six pediatric oncology healthcare settings across Texas. Data from the Texas KidsCanSeq study will be submitted through the CSER Data Coordinating Center for access in NIH-supported databases.

  Study phs002378

• The Southern African Human Genome Programme

  The Southern African Human Genome Programme (SAHGP) is a national and regional initiative that aims to unlock the unique genetic character of southern African populations. Its vision is to improve quality of life through understanding human genetic diversity. It is timely to advance the SAHGP initiative since global genomic initiatives are increasingly pointing to populations in Africa, more specifically the San and Khoe from southern Africa, as harbouring the most ancient genetic signatures among the living populations of the world. Studies on African populations have already generated a wealth of information upon which the SAHGP can build. This information will be used to promote and support genomic research programmes both nationally and regionally to address critical questions that would benefit the people of our region. The SAHGP aims to make a significant contribution to the understanding of DNA variation among southern Africans and how this impacts on the health of the people of this region. Aims of the SAHGP: To develop capacity for genomic research in southern Africa; To establish sustainable resources for genomic research in the region; and To translate knowledge and information into improvements in human health in the region. The objective is to derive the maximum benefit from the SAHGP, and that the data should be widely shared with the scientific community for the benefit of the people of the sub-continent and beyond.

  Study EGAS00001002639

• Subtype specific progression from DCIS to invasive breast cancer

  Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.

  Study EGAS00001001866

• Integrated Clinical and Transcriptomic Profiling to Characterize Disease Phenotype

  Personalized medicine requires that we first address the challenge of genetic heterogeneity, prominent in rare cancers to common disease. While current clinical DNA sequence data successfully identify novel genetic variants, the genomic data alone are insufficient biomarkers of clinical phenotype. There is an unmet need for systematic integration of specific functional genomic data with patient genetic data, in order to bridge the knowledge gap between genetic variation and clinical phenotype. This specific study is focused on functional genomic data from platelets as disease-specific cells that are also ideal for proof-of-principle transcriptomic investigation (being anucleate), and highly-relevant to multiple disease processes.

  Study phs002121

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• RNA sequencing of multiple myeloma identifies genes dysregulated by structural variants.

  Multiple myeloma is a disease of structural changes brought about by copy number abnormalities and translocations. Many of these changes result in super-enhancers being placed next to key oncogenes. Here, we have investigated which genes are commonly dysregulated by these changes.

  Study EGAS00001003411

• WES on tumor DNA and germline DNA in pediatric cancer

  This dataset contains whole exome sequencing (WES) data from tumor DNA samples of various pediatric cancer entities. Files are provided in fastq format. Samples were sequenced on a Novaseq6000 or Hiseq2500 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Study EGAS00001005429

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer

  Background Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. Methods We combined immunohistochemistry (IHC) with RNA-sequencing and whole genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Further, we explored transcriptional features of immune archetypes, T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions, and assessed common adult biomarkers such as neoantigen load and TMB. Results A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. Conclusions Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

  Study EGAS00001007029

• The 3D evolution of glioma cell populations

  Study description: A detailed understanding of heterogeneity in solid tumors has been limited due to insufficient sampling and a lack of knowledge from where within the tumor the sample was taken from. We present here a novel resource - the 3D Glioma Atlas - in which we record the precise, three-dimensional (3D) coordinate for each of 8-20 spatially-distinct samples obtained from each patient tumor.By revealing how genetic alterations and tumor cell states are patterned in glioma in 3D space, our Atlas shows that genetic diversity is more regionally confined in indolent as compared to aggressive tumors, that recurrent tumors have a greater density of genetic diversity, and that more aggressive tumors have greater tumor-wide transcriptomic heterogeneity.

  Study EGAS00001003710

• Transcriptomics-driven classification of ALAL

  Acute leukemia of ambiguous lineage (ALAL) is a rare, poor-prognosis subtype of acute leukemia that cannot be assigned to a single hematopoietic lineage. Although ALAL patients are typically treated with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) regimens, optimal treatment choice is hindered by their lineage ambiguity. Therefore, we investigated the added value of transcriptomics for improving lineage assignment, currently based mainly on surface markers. First, we used an in-house pipeline to comprehensively detect genetic lesions in RNA-sequencing data (n=23) with a sensitivity &gt;90%, as confirmed by targeted DNA sequencing. Second, we compared ALAL gene expression profiles (GEPs) with representative AML (n=145), B-ALL (n=223) and T-ALL (n=85) cases. In a principal component analysis, ALALs did not form a separate group, but clustered with AML, B-ALL or T-ALL. Accordingly, a machine learning classifier trained with GEPs of acute leukemias segregated 20/23 ALALs into myeloid-, B- or T-lymphoid leukemia. These 20 cases harbored genetic abnormalities consistent with the classifier-assigned leukemia. Furthermore, ALAL GEPs were deconvoluted with single-cell transcriptional profiles of normal hematopoietic cells using CIBERSORTx, revealing enrichment for signatures of lineages corresponding to the leukemic type predicted by our algorithm. The classifier was validated on an external ALAL cohort (n=24), assigning 75% of the patients to a lineage matching their immunophenotypic and methylation profiles. In conclusion, integrative analysis of RNA-sequencing data can accurately classify most ALAL cases. The pipeline and classifier developed in our study are valuable tools to improve ALAL diagnosis and guide therapeutic decisions.

  Study EGAS00001007967

• Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

  Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

  Study EGAS00001006059

• Liquid Biopsy Detection of Tumor-specific Structural Variants in High Grade Serous Ovarian Cancer

  WGS Liquid Biopsy. Recurrence is frequent for most patients with high grade serous ovarian cancer (HGSOC), even after effective chemotherapy induced remission. However, after achievement of complete clinical response, the minimal residual disease is often insufficient for genomic analysis. Therefore, methods to interrogate the clonal composition and molecular properties of minimal residual disease are needed to better understand the mechanisms of HGSOC relapse. To address this unmet need, we developed and validated a novel cfDNA-based approach for tracking disease burden using NGS-informed tumor specific structural variants (SVs). Methods: The optimization of the methodology was first performed using synthetic cfDNA generated by ultrasonication of gDNA from ovarian cancer cell lines. Following the optimized workflow, whole genome sequencing of multisite biopsies from pre-treatment HGSOC patients were performed and high confidence SVs were called by consensus of multiple published SV callers. Real-time PCR and digital droplet PCR (ddPCR) were used for assays development.

  Study EGAS50000001044

• International Consortium to Identify Genes and Interactions Controlling Oral Clefts

  Oral clefts represent the most common group of craniofacial birth defects in humans, and include cleft lip with or without cleft palate (CL/P) and cleft palate (CP). Oral clefts have a complex and heterogeneous etiology, with strong evidence for both genetic and environmental causal factors. Candidate gene studies and genome wide linkage studies have yielded compelling but inconsistent evidence that multiple genes control risk, and several studies have shown evidence for interaction between genes and environmental exposures, especially maternal smoking and nutrient intake. This consortium pulls together a very large collection of cases and their parents from multiple populations, and offers a unique opportunity to expand the search for genes controlling risk to the genome wide level. The specific aims are: To conduct a genome wide analysis on 2000+ case-parent trios ascertained through a case with isolated, non-syndromic CL/P or CP to test for linkage and disequilibrium. Initial analysis will consist of individual tests for gene effects while simultaneously testing for GxE interaction with common maternal exposures including vitamin supplementation, cigarette smoking and alcohol consumption (which have all been implicated as environmental risk factors for oral clefts). To use haplotypes in tests for GxE interaction incorporating population specific estimates. Since haplotype frequencies vary among populations, trios will be assigned haplotypes in a stratified estimation and then a pooled test statistic will be constructed. To test for interaction between SNPs in different genes showing evidence of influencing risk in a test for GxG interaction. To test for interaction between genes and maternal biomarkers using trios from Utah where measures of plasma folate, vitamin B-6, homocysteine and zinc in mothers are available. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to oral clefts through large-scale genome-wide association studies of well-characterized cases and their parents from multiple populations. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000094

• BIONi010-C-8 / SAMEA4454011 WGS data

  The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001028

• BIONi010-C-3 / SAMEA4342740 WGS data

  The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001034

• BIONi010-C-7 / SAMEA4454010 WGS data

  The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001035

• BIONi010-C-6 / SAMEA4454009 WGS data

  The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001037

• BIONi010-C-9 / SAMEA4454012 WGS data

  The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001040

• BIONi010-C-4 / SAMEA4452060 WGS data

  The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001043

• EDi014-B / SAMEA4459371 WGS data

  The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001053

• BIONi010-C-5 / SAMEA4452061 WGS data

  The iPSC line BIONi010-C-5 / SAMEA4452061 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001062

• BIONi010-C-2 / SAMEA4342705 WGS data

  The iPSC line BIONi010-C-2 / SAMEA4342705 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001068

• Assessing Neural Mechanisms of Injury in Inborn Errors of Urea Metabolism Using Structural MRI, Functional MRI, and Magnetic Resonance Spectroscopy

  Urea cycle disorders represent a group of rare inborn errors of metabolism that lead to accumulation of ammonia, a toxic product of protein metabolism. Individuals with urea cycle disorders cannot metabolize the ammonia that accumulates due to enzyme deficiency. The symptoms of these disorders may present at birth, childhood or adulthood (milder deficiencies). There are currently eight enzyme deficiencies that constitute the range of inborn errors of ureagenesis. This project will focus on the most common enzyme disorder of the urea cycle, ornithine transcarbamylase deficiency, inherited as an X-linked trait. This project will study cognitive and motor dysfunction in patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non -invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies will range from ages 18-60 years and will be compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001108

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

  Study EGAS00001007573

• Genomic Factors Involved in Chromosome Rearrangements

  Approximately 15-20% of children referred for chromosomal microarray analysis (CMA) testing have a clinically relevant CNV that in many cases explains their phenotype. The goal of this study is to discover the genomic factors that mediate chromosome rearrangements and the phenotypic effects of chromosome rearrangements. We hypothesize that particular DNA sequences are susceptible to breakage and rearrangement. To this end, we fine-map chromosome breakage sites and analyze the DNA motifs that underlie double-strand breaks (DSBs). Our studies will also capture the genomic structure of breakpoint junctions, which will allow us to determine the mechanisms of DNA repair that shape different types of chromosome rearrangements. We also correlate chromosome rearrangements with clinical features to establish genotype-phenotype correlations. Defining critical regions of deletion or duplication is the first step to identifying candidate genes responsible for particular phenotypes.

  Study phs000845

• Effects of busulfan, fludarabine and clofarabine treatment on human small intestinal organoids generated from healthy donors

  The intestine is vulnerable to chemotherapy-induced toxicity due to its high epithelial proliferative rate, making gut toxicity an off-target effect in several cancer treatments, including conditioning regimens for allogeneic hematopoietic cell transplantation (HSCT). In HSCT, intestinal damage is an important factor in the development of Graft-versus-Host Disease (GVHD), an immune complication in which donor immune cells attack the recipient's tissues. Here, we developed a novel human intestinal organoid-based 3D model system to study the effects of chemotherapy-induced intestinal epithelial damage at the RNA level. We show that chemotherapy conditioning specifically reprograms the intestinal epithelial transcriptome after treatment with either busulfan (3.5μM), fludarabine (15μM) or clofarabine (0.5μM) for 24h. This knowledge can potentially enable us to understand which changes undergo in healthy tissues upon conditioning and how those are related with immune activation typical in GVHD.

  Study EGAS00001007550

• Addictions: Genotypes, Polymorphisms, and Function/Human Genetic Correlates of Addictive Diseases

  Drug addiction continues to be a major medical and social problem. It is estimated that one million or more persons in the United States are currently addicted to heroin or prescription opioids, with millions more worldwide. Cocaine addiction and alcohol dependence are frequent comorbid conditions in persons with heroin/opioid dependence in addition to being major primary addictions. Many studies over the past thirty years have shown that these drugs disrupt physiologic systems, and that these disruptions may contribute to drug addiction and alcohol dependence and to relapse to drug or alcohol abuse following withdrawal and abstinence. Clinical observations suggest that individuals differ in their response to heroin, cocaine, and alcohol; however, little is known about specific underlying hereditary genetic factors which might influence individual susceptibility to the addictive properties of these substances. Studies also suggest that both common and distinct heritable factors account for the genetic variance in the susceptibility to the separate addictive diseases. We hypothesize that there is a heritable as well as environmental basis for the acquisition and persistence of, and relapse to, specific addictive diseases. Using samples from individuals without and with opioid and other specific drug dependence diagnoses and psychiatric comorbidities, genetic analyses will be used to determine association and linkage. All study subjects will be extensively characterized with respect to the addictive diseases, medical history, family medical addictive disease history; psychiatric comorbidity, and psychological profile, as well as ethnic/cultural background. A better understanding of the consequences of genetic contributions with respect to protection from, or susceptibility to, heroin/opioid addiction and related codependencies and comorbid conditions, could have enormous importance in both prevention and treatment of this problem.

  Study phs001109