19385 results for "Cheap fc 26 coins Buyfc26coins.com is official EA Sports partner for FC 26 coins That was the fastest delivery ever..fxB4"

in 32.23 milliseconds.

• Jeju Genome Project DAC

  This Data Access Committee (DAC) evaluates and manages access requests for large-scale genomic and phenotypic datasets generated as part of the Jeju Genome Project (JGP). The committee's mission is to facilitate responsible data sharing to advance precision medicine and population genetics. The DAC ensures that data access is granted only to bona fide researchers who agree to the terms of the Data Access Agreement (DAA) and whose proposed research is strictly consistent with the informed consent provided by the participants and the ethical guidelines of the project.

  Dac EGAC50000000938

• Pediatric Non-Down Syndrome Acute Megakaryoblastic Leukemia is Characterized by Distinct Genomic Subsets with Varying Outcomes

  Acute Megakaryoblastic Leukemia (AMKL) is a subtype of acute myeloid leukemia (AML) in which cells morphologically resemble abnormal megakaryoblasts.  While extremely rare in adults, AMKL accounts for 4-15% of newly diagnosed childhood AML1-3.  A significant proportion of pediatric AMKL cases occur in children with Down syndrome (DS).  These patients have excellent outcomes and are characterized at the genomic level by a founding GATA1 mutation4-6.  In contrast, AMKL in patients without DS (non-DS-AMKL) is frequently associated with poor outcomes.  Previous efforts have identified chimeric oncogenes in a significant number of cases, including RBM15-MKL1, CBFA2T3-GLIS2, KMT2A gene rearrangements and NUP98-KDM5A7-9.  The etiology of 30-40% of cases, however, remains unknown.  To better understand the genomic landscape of non-DS-AMKL, we performed RNA and exome sequencing on specimens from 99 patients (75 pediatric and 24 adult).  We demonstrate that pediatric non-DS-AMKL is a heterogeneous malignancy that can be divided into seven subgroups with varying outcomes.  These subgroups are characterized by chimeric oncogenes with cooperating mutations in epigenetic and kinase signaling genes.  Overall, these data shed light on the etiology of AMKL and provide useful information for treatment tailoring. 

  Study EGAS00001002183

• Efficacy of a Therapeutic Treatment Trial in Angelman Syndrome

  This study has been designed to evaluate the possible therapeutic benefits of L-5-methyltetrahydrofolate (Metafolin), vitamin B12, creatine and betaine in children with Angelman Syndrome (AS). This study is based on the hypotheses 1) that dietary manipulation may increase global DNA methylation; 2) that increased methylation of the paternal chromosome in AS participants may increase expression of the Angelman gene causing clinical benefit; and 3) that dietary interventions with Metafolin in conjunction with creatine, betaine, and vitamin B12 would represent little risk, but some chance for benefit. The dietary regimen is felt to be quite benign and safe. The clinical response will be measured by recording: changes in seizure activity, changes in communication skills, changes in developmental skills and changes in behavioral patterns as indicated by formal developmental assessments and clinical evaluations. We will assess the progress of the participants by monitoring their changes from baseline throughout their participation in the study and measure their improvement in particular in the developmental parameters. As a secondary aim, we plan to measure the biochemical response to these compounds by obtaining levels of homocysteine, methionine, S-adenosyl-methionine (SAM), and S-adenosyl-homocysteine (SAH). The molecular response will be measured by global DNA methylation analysis. As an exploratory aim, we hope to use control data we have previously obtained from a double blind placebo-controlled trial done in the past using betaine and folic acid to compare the development of those children who have and those who have not received medications. More specifically, we wish to compare differences in the rate of development for those children who have never received study medications (from the first trial) with those who have received medications from the present trial. Developmental parameters used in the previous trial will be consistent with those used in the present trial in order to permit these comparisons. The previous trial was conducted at Baylor College of Medicine, Rady San Diego Children's Hospital and Boston Children's Hospital whereas a group of AS participants received folic acid and betaine or placebo in a randomized double-blind basis. All the participants for the study will include patients who have a documented molecular diagnosis of AS. The participants will be seen at Baylor College of Medicine, Rady Children's Hospital of San Diego, Boston Children's Hospital and the Greenwood Genetics Center at 0 months and at 12 months for follow-up. Clinical and relevant historical data will be collected during the clinical visit and examination and also by reviewing medical and laboratory records. This information will then be entered into a HIPAA compliant clinical research database.

  Study phs000701

• How to use EGA Webin?

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

  Documentation submission/metadata/submission/EGA_webin

• Identification_of_the_underlying_causal_variant_in_a_multi_generational_family_with_autosomal_dominant_common_variable_immunodeficiency

  Common variable immunodeficiency (CVID) is the most common form of primary immunodeficiency with an estimated incidence of 1:10,000. It has been apparent for many years that CVID has a genetic component, occurs frequently in families and can have both a recessive or dominant mode of inheritance. In recent years, 4 genes underlying CVID have been identified; however, mutations within in them are estimated to account for no more than 10% of all cases of CVID.We have identified a multi-generational family with autosomal dominant CVID. Genome-wide linkage analysis has mapped the locus underlying CVID in this family to an approximately 9.2 Mb interval on chromosome 3q27.3-q29, between the markers D3S3570 and D3S1265. This locus is distinct from any of the previously mapped susceptibility loci suggesting a novel genetic variant is responsible for disease in this family. The aim of this study is to use exome sequencing of affected (n = 4) and unaffected (n = 4) individuals, in tandem with the available genetic mapping data, to identify the causal variant underlying CVID in this family.

  Study EGAS00001000269

• Epigenome-wide methylation analysis of colorectal carcinoma, adenoma and normal tissue reveals novel biomarkers addressing unmet clinical needs

  Studies about CRC biomarker discovery have focused on methylation patterns in normal and colorectal tumor tissue, leading to a lack of knowledge of methylation in adenomas. Therefore, we performed the first epigenome-wide study to compare the epigenomes of all three tissue types combined, and to identify discriminatory biomarkers. Public Illumina MethylEPIC® data was collected from 552 normal, 118 carcinoma and 116 adenoma samples. Pairwise analyses were performed for discovery of differentially methylated probes (DMPs). We identified 693 813, 620 643 and 558 897 DMPs when comparing normal vs carcinoma, normal vs adenoma and adenoma vs carcinoma respectively. To double evidence (DE) these DMPs, analysis of Illumina 450K data from public datasets was performed. Through this analysis, 13 DE DMPs with │Δβ│≥0.3 were identified for adenoma vs carcinoma. A binary logistic regression model was generated to evaluate the discriminatory potential of these DE DMPS. The model was validated in an in-house experimental methylation dataset of 13 adenoma and 9 carcinoma samples. Our classifier reached a cross-validated AUC of 0.996 and 0.855 in the discovery and validation datasets respectively. A sensitivity and specificity of 96% and 95% were reached, with an overall accuracy of 96%. Our analysis show that methylation biomarkers have the potential to discriminate between normal, precursor and carcinoma tissues of the colorectum. More importantly, we highlight the power of the methylome, showing that DMPs can be used as biomarkers in the clinic to identify colorectal adenoma and carcinoma. 

  Study EGAS00001007017

• Data Access Committee for Maurice Lab - UMC Utrecht

  The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

  Dac EGAC50000000876

• ScRNA-seq of human kidney immune cells of patients with ANCA-associated glomerulonephritis, Lupus Nephritis against a "healthy" nephrectomy control

  ANCA-associated glomerulonephritis (AGN) associates with a high risk of end-stage kidney disease. The role of kidney immune cells in local inflammation remains unclear. Here, we investigate kidney immune cell diversity and function. Kidney tissue from AGN patients (n=5) and a lupus nephritis (LN) patient (n=1) were aquired during a biopsy procedure for a clinical indication. Needle-core biopsies were obtained for histopathological examination, and an additional pass was performed to retrieve kidney tissue for scRNA-seq. Healthy kidney tissue (n=1) was obtained from a kidney that was surgically removed do tue due to a (non-invasive) papillary urothelial carcinoma. Immediately after collection, kidney tissue was processed into a single-cell suspension and sorted using a 4-color flow cytometry panel to isolate living, CD45+ immune cells. To aid in the multi-omic characterization, surface markers and T and B cell repertoires were sequenced in 2 samples (1 AGN patient and the nephrectomy control). These samples were incubated with an oligo-antibody TotalSeq-C cocktail containing 130 unique cell surface antigens.

  Study EGAS50000000159

• NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in GLAUGEN Samples

  This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the GLAUGEN (Glaucoma Gene Environment) initiative have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the GLAUGEN description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the GLAUGEN study. From the MEEI, 50 patients were selected from POAG pedigrees, to include all the probands genotyped by CIDR and are currently undergoing exome sequencing, and to include additional genotyped probands who belong to pedigrees of sufficient size and structure that parent of origin effects could be evaluated. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000308 (Geneva - Glaugen GWAS Study).

  Study phs000461

• A PROSTATE TUMORGRAFT PANEL TO ACCELERATE PRECISION MEDICINE

  The management of advanced prostate cancer (PCa) has strongly evolved in the last decade with the introduction of the next generation of androgen receptor pathway inhibitors which have considerably improved patient outcomes. Most recently, the investigation of genomic landscape has provided targetable molecular alterations such as homologous gene DNA repair defects correlated with response to PARP inhibitors. Despite these significant advances, while localized PCa is generally associated with favorable outcome, metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

  Study EGAS00001007033

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Novel Factors for Unexplained Phenotypes of Subclinical Carotid Atherosclerosis

  The overall goal for this study was to determine the genetic factors associated with extreme phenotypes of subclinical atherosclerosis (protective and deleterious). Study participants were selected from the Northern Manhattan Study (NOMAS), a population based cohort study investigating stroke and stroke risk factors in Northern Manhattan. Cases and controls were individuals at the extreme ends of the distribution for carotid intima-media thickness and carotid plaque, with cases defined as individuals with subclinical atherosclerosis that could not be explained by traditional vascular risk factors (USAth) and controls defined as individuals with unexplained protection against atherosclerosis (UPAth).

  Study phs001560

• The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis.

  In the present study, we identified differentially expressed protein-coding genes from RNA transcriptional profiling performed on 11 paired cancer tissues and adjacent non-cancerous tissues. Then, we conducted GO, KEGG, PPI network and centralities analyses to study and identify changes in pathways and hub genes. The aim of this study was to improve understanding of HCC carcinogenesis by providing information concerning the genetic changes that occur during disease progression and to uncover the expression of biomarkers with potential use for clinical diagnosis, treatment, and monitoring of disease progression.

  Study EGAS00001002526

• Ensemble learning for classifying single-cell data and projection across reference atlases

  Single-cell data are being generated at an accelerating pace.How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types.

  Study EGAS00001004283

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study

  This is a case-control study of primary open angle glaucoma (POAG). POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. For this study we have formed a collaborative consortium contributing 2170 POAG cases and 2347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition has also been harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The NEIGHBOR consortium has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). The consortium includes eleven different centers where data collection and analysis take place. The eleven sites and investigators are: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman, D. Zack); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Eye Institute (X01HG005259).

  Study phs000238

• WGS of liver cancer in the Japanese population

  Hepatocellular carcinoma (HCC) is the third leading cancer-related cause of death and the seventh most common form of cancer worldwide, with an estimate of more than 700,000 new cases each year. The most established risk factors of HCC are chronic HBV and HCV infection. HBV infection is responsible for over 50% of the worldwide attributable risk of HCC, especially in East Asia and Africa, while in Japan and several Western countries HCV infection is the most common risk factor for HCC. To gain insights into the molecular alterations of virus-associated HCC, we performed whole genome sequencing (WGS) of 321 HCC tumors from 159 patients. This work was performed as a part of the ICGC (International Cancer Genome Consortium) project.

  Study EGAS00001000678

• GEenetic landscape of hypodiploid acute lymphoblastic leukemia

  Hypodiploid acute lymphoblastic leukemia (ALL) is an aggressive leukemia characterized by aneuploidy and poor outcome. The genetic basis of hypodiploid ALL is unknown. Here, using complementary genome-wide profiling approaches, we show that hypodiploid ALL comprises two subtypes that differ in the severity of aneuploidy, transcriptional profile and submicroscopic genetic alterations. Near haploid cases with 24-31 chromosomes frequently harbor alterations targeting receptor tyrosine kinase- and Ras signaling (71%) and IKZF3 (AIOLOS; 13%). In contrast, low hypodiploid ALL cases with 32-39 chromosomes are characterized by TP53 alterations, almost half of which are present in non-tumor cells, and have alterations of IKZF2 (HELIOS; 53%) and RB1 (41%). Both near haploid and low hypodiploid tumors exhibit activation of Ras and PI3K signaling pathways, and are sensitive to PI3K inhibition, indicating that these drugs should be explored as a new therapeutic strategy for this frequently lethal form of leukemia.

  Study EGAS00001000380

• DONSON encodes a novel replication fork protection factor mutated in microcephalic dwarfism.

  To ensure efficient genome duplication, cells have evolved a multitude of factors that promote unperturbed DNA replication, and protect, repair and restart damaged forks. Here we identify DONSON as a novel fork protection factor, and report biallelic DONSON mutations in 29 individuals with microcephalic dwarfism. We demonstrate that DONSON is a component of the replisome that stabilises forks during normal genome replication. Loss of DONSON leads to severe replication-associated DNA damage arising from nucleolytic cleavage of stalled replication forks. Furthermore, ATR-dependent signalling in response to replication stress is impaired in DONSON-deficient cells, resulting in decreased checkpoint activity, and potentiating chromosomal instability. Hypomorphic mutations substantially reduce DONSON protein levels and impair fork stability in patient cells, consistent with defective DNA replication underlying the disease phenotype. In summary, we identify mutations in DONSON as a common cause of microcephalic dwarfism, and establish DONSON as a critical replication fork protein required for mammalian DNA replication and genome stability.

  Study EGAS00001002224

• Esophageal Squamous Cell Carcinoma Precursor Study

  Esophageal cancer is the sixth most common cause of cancer death in the world. High-risk areas occur across central Asia and from eastern to southern Africa, and in these populations, nearly all of the cases are esophageal squamous cell carcinoma (ESCC). ESCC has a dismal prognosis, largely because symptoms usually appear late in the course of the disease, when the tumors are incurable. Early detection and treatment of curable precursor lesions and early invasive ESCC in asymptomatic high-risk adults offers the potential for long-term survival and reduced mortality from this disease. Previous studies have shown that routine cytology of non-endoscopically collected esophageal cell samples is not sensitive and specific enough to be clinically useful, so we are now looking for molecular markers of high-grade esophageal squamous dysplasia (HGD), the proven clinically important precursor lesion of ESCC, that can be used to increase the accuracy and utility of this initial screening exam. National Cancer Institute (NCI) and Cancer Institute and Hospital, Chinese Academy of Medical Sciences (CAMS) began collaborative studies of ESCC since the mid-1980s in China. The present proposal is designed to characterize the type and prevalence of DNA mutations in tissue samples of HGD and to establish biologic and questionnaire resources for further study. The proposed study has two components, a field study to obtain questionnaire data and biological samples, and a genomic analysis to perform sequencing of the biological samples and bioinformatics analysis of the sequencing. 

  Study phs002814

• Single-cell targeted DNA-sequencing and protein sequencing

  We performed single-cell targeted DNA sequencing (MissionBio) on 13 high hyperdiploid B-ALL patients at diagnosis to study the genetic heterogeneity. For a number of patients single-cell surface protein antibody sequencing was added (DAB-seq) to better characterize the different cell types. Furthermore, additional samples during treatment were collected and analysed for some patients. In this way we want to study the clonal heterogeneity of these B-ALL samples, based both on mutations and CNVs, and identify resistant clones that could be targeted after relapse.

  Study EGAS50000000580

• Human PMS1-dependent non-canonical mismatch repair converges with MBD4 to repair 5-methylcytosine deamination

  CpG dinucleotides are mutational hotspots due to spontaneous deamination of 5-methylcytosine (5mC), resulting in T:G mismatches that can lead to CpG>TpG transitions. These mutations are a hallmark of aging and cancer and play a central role in the evolution of vertebrate genomes. We have previously uncovered MBD4 as the primary Base Excision Repair (BER) glycosylase responsible for 5mC deamination repair. Here, we employ an APOBEC1 deaminase fused to a catalytically dead Cas9 to induce targeted 5mC deamination independently of DNA replication, and track its repair in human cells. This approach reveals that MBD4 elicits a coordinated repair response with a non-canonical branch of Mismatch Repair (MMR) involving complexes MutLβ (MLH1-PMS1) and MutSα (MSH2-MSH6). We demonstrate that human PMS1 loss phenocopies the CpG>TpG hypermutation associated with MBD4 deficiency, revealing 5mC deamination repair as one of its main functions. Structural predictions with functional validation reveal that MBD4 activity is dependent on its physical interaction with MutLβ. In alignment with our experimental data, we show that the CpG>TpG mutational burden of MMR-deficient tumors is partly explained by replication-independent processes. Altogether, we uncover a novel function of non-canonical MMR that underscores its interplay with BER in safeguarding genomic integrity against damage to methylated DNA.

  Study EGAS50000001662

• Tetralogy of fallot whole-exome sequencing

  829 adult and child probands of Northern European ancestry presenting with TOF were recruited from nine centres: seven in the UK, Leuven (Belgium), and Sydney (Australia). Patients sequenced exhibited no clinical features of recognised syndromes, extra-cardiac abnormalities or learning difficulties. All samples were screened for the 22q11.2 deletion associated with TOF prior to sequencing to ensure that this was not present. Samples were sequenced on HiSeq2000 and reads aligned using BWA.

  Study EGAS00001003302

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• GENOMIC MUTATION LANDSCAPE OF SKIN CANCERS FROM DNA REPAIR-DEFICIENT XERODERMA PIGMENTOSUM PATIENTS

  Xeroderma pigmentosum (XP) is a genetic disorder caused by mutations in genes of the Nucleotide Excision Repair (NER) pathway (groups A-G) or in Translesion Synthesis (TLS) DNA polymerase η (group V). XP is associated with an increased skin cancer risk, reaching, for some groups, several thousand-fold compared to the general population. Here, we analyzed 38 skin cancer genomes from five XP groups. We found that the activity of NER determines heterogeneity of the mutation rates across skin cancer genomes and that transcription-coupled NER extends beyond the gene boundaries reducing the intergenic mutation rate. Mutational profile in XP-V tumors revealed the role of polymerase η in the error-free bypass of (i) rare TpG and TpA DNA lesions, (ii) 3’ nucleotides in pyrimidine dimers, and (iii) TpT photodimers. Our study unravels the genetic basis of skin cancer risk in XP and provides insights into the mechanisms reducing UV-induced mutagenesis in the general population.

  Study EGAS00001006732

• Comparison of the performance of two commercial genome-wide association study genotyping platforms in Han Chinese Samples

  Affymetrix 6.0, Illumina OMNIExpress, and llumina Immunochip genotype data for Han Chinese population including rheumatoid arthritis cases and controls. Data is in PLINK binary format. Illumina genotype clustering was performed using Illumina’s BeadStudio software. SNPs were reclustered using the study samples, low quality subjects were removed, and a subset of clustering results were manually inspected and verified. All SNPs with GenCall scores less than 0.15 were excluded. For Affymetrix chips, clustering was performed using the program Birdseed version 2, as implemented using Affymetrix Genotyper Console v4.0, using the default quality control (QC) thresholds.

  Study EGAS00000000131