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• Pilot_experiment_on_functional_genomics_in_osteoarthritis

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will generate genotype data on the HumanCoreExome array and will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of methylation (Illumina 450k array), transcription (RNASeq) and expression (quantitative proteomics). The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data. If successful, it is envisaged that we will proceed with expanding the work to 500 patients in the first year, with a target total sample size of 3,000 in the longer term. The key collaborators in this work are Mark Wilkinson (Sheffield) and Jyoti Choudhary

  Study EGAS00001001212

• Pilot_experiment_on_functional_genomics_in_osteoarthritis

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will generate genotype data on the HumanCoreExome array and will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of methylation (Illumina 450k array), transcription (RNASeq) and expression (quantitative proteomics). The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data. If successful, it is envisaged that we will proceed with expanding the work to 500 patients in the first year, with a target total sample size of 3,000 in the longer term. The key collaborators in this work are Mark Wilkinson (Sheffield) and Jyoti Choudhary

  Study EGAS00001001213

• Somatic Mutation Profile by Next Generation Sequencing in HER2+ Breast Cancer

  The HER pathway is the driving force behind 30% of human breast cancers. It is important to understand how targeted therapies block different cellular pathways, and mechanisms of escape from this blockage. Therapies directed at HER2 establish a successful treatment paradigm, but de novo and acquired resistance exist. The HER signaling system is a complex network with four receptors and eleven ligands, a phosphorylation signaling cascade, and many transcription factors, all complicated by both positive and negative feedback circuits. Analysis of genomes, exomes and transcriptomes by next generation sequencing is aimed at uncovering the genetic factors responsible for patient responses to HER2-directed therapies. We are sequencing HER2-overexpressing cancers, in order to identify potential somatic changes that may better select patients who will benefit from therapy, to determine new targets that may overcome resistance, and to improve outcomes with known current HER2-targeted therapies. Whole exome capture sequencing will determine somatic mutation profiles in HER2-overexpressing tumors, to comprehensively characterize the somatic alterations, with the goal of identifying those patients most likely to respond, as well as discovering new targets that may overcome resistance to HER2-directed therapy. We augment the whole exome data with RNA-seq data to determine expression levels of somatic mutations we discover.

  Study phs000770

• EGA file encryption types

  EGA file encryption The European Genome-Phenome Archive (EGA) stands as a significant initiative in the field of genomics, facilitating the secure storage and sharing of vast amounts of genomic data. Jointly hosted by the Centre for Genomic Regulation (CRG) and the European Bioinformatics Institute (EMBL-EBI), the EGA offers a robust infrastructure for managing encrypted data, ensuring the privacy and integrity of sensitive genomic information. Both CRG and EMBL-EBI play pivotal roles in the EGA, each institution bringing unique expertise in managing different types of encryptions. EMBL-EBI EGACryptor encryption system, while CRG utilises Crypt4GH, resulting in two distinct encryption file types: cip and c4gh, respectively. How can I check the file encryption? To access your dataset of interest on the European Genome-Phenome Archive (EGA) and determine the corresponding encryption file extension, please follow these step-by-step instructions: Utilise the search or navigation features provided on the EGA website to locate the dataset you are interested in. Once you find the dataset webpage, click on the "Files" tab, typically located on the dataset's webpage. Upon reaching the "Files" tab, you will be presented with a table containing comprehensive information about the files associated with the dataset. This table will include various columns, such as "File Name," "Size," and "Location." The "Location" column is particularly relevant for determining the encryption file extension. Figure 1: File table showing all the information available for the files in a dataset. This table is specific for each dataset. To identify the encryption file extension corresponding to a specific file, locate the "Location" column in the table. If the file is archived in Spain, the file will have the .c4gh extension, indicating that it is encrypted using Crypt4gh. Conversely, if the file is archived in the UK, the encrypted file extension will be .cip, indicating the usage of EGACryptor for encryption. It is worth noting that a file can be available in both locations, meaning it will be accessible with both file extensions (.c4gh and .cip). This allows users to choose the encryption method that aligns with their preferred platform or analysis tools.

  Documentation check-encryption-type

• Precision High Intensity Training Through Epigenetics (PHITE)

  Exercising regularly promotes health, but these benefits are complicated by acute inflammation induced by exercise. A potential source of exercise-induced inflammation is cell-free DNA (cfDNA), yet the cellular origins, molecular causes, and immune system interactions of exercise-induced cfDNA are unclear. To study these, 10 healthy individuals were randomized to a 12-week exercise program of either high-intensity tactical training (HITT) or traditional moderate-intensity training (TRAD). Blood plasma was collected pre- and post exercise at weeks 0 and 12 and after 4 week of detraining upon program completion. Whole-genome enzymatic methylation sequencing (EM-seq) with cell-type proportion deconvolution was applied to cfDNA obtained from the 50 plasma samples and paired to concentration measurements for 90 circulating cytokines. Acute exercise increased the release of cfDNA from neutrophils, dendritic cells (DCs), and macrophages proportional to exercise intensity (HITT > TRAD). Exercise training reduced cfDNA released in HITT participants but not TRAD and from DCs and macrophages but not neutrophils. For most participants, training lowered mitochondrial cfDNA at rest, even after detraining. Using a sequencing analysis approach we developed, we concluded that rapid extracellular traps (ETosis) was the likely source of cfDNA, demonstrated by enrichment of nuclear DNA. Further, several cytokines were induced by acute exercise, such as IL-6, IL-10, and IL-16, and training attenuated the induction of only IL-6 and IL-17F. Cytokine levels were not associated with cfDNA induction, suggesting that these cytokines are not the main cause of exercise-induced cfDNA. Overall, exercise intensity and training modulated cfDNA release and cytokine responses, contributing to the anti-inflammatory effects of regular exercise. One additional subject was also used in the methyl-seq data as a control for comparing bisulfite-sequencing to enzymatic methyl sequencing. DNA methylation for MPO gene was found to be significantly different as well, in line with interpretation that neutrophils are primarily undergoing ETosis.

  Study phs003873

• Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations

  It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes-so-called sporadic or simplex families-we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 617 individual exomes from 209 families deposited in dbGaP. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected beta-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.

  Study phs000482

• UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

  Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

  Study phs002504

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__Botseq

  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. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. 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 EGAS00001004330

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__alkylating_agents

  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. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. 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 EGAS00001003637