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• Ewings Sarcoma Rearrangement Screen

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000389

• Batches 4-6 prostatectomy analysis

  Whole Genome Sequencing Illumina HiSeq data from 111 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). This data is from batches 4 to 6.

  Dataset EGAD00001003225

• KNS42 and SF188 H3K36me3 chipSeq

  Chromatin immunoprecipitation (ChIP) was carried out employing antibodies against H3K36me3 and RNA polymerase II using the HistonePath and TranscriptionPath assays by ActiveMotif. Whole genome sequencing was carried out using an Illumina HiSeq2000 and data is provided as 6 BAM files. H3K36me3 chipseq RNA polymerase II chipseq and input coverage for each cell line.

  Dataset EGAD00001004119

• RNAseq of patients with Ewings sarcoma

  Cancer is driven my mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000444

• Monomorphic sarcomas RNAseq dataset

  Dataset is composed of FASTQ files from 165 samples of small round cell sarcomas which were RNA-sequenced (whole transcriptome) with either Illumina HiSeq 2500 (120 million reads per sample, paired-end 100 pb) or Illumina NextSeq 500 (110 million reads per sample, paired-end 150)

  Dataset EGAD00001003121

• Characterization of iPSC derived macrophages - cardiovascular pilot (2017-05-24)

  This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-05-24.

  Dataset EGAD00001003347

• V2 panel bait design test

  This study comprises of three different datasets. 1) 57 samples from the 1243 canapps cell line study,2) 91 FFPE normal samples and 3) 87 samples from the SCORT WS2 dataset. The aim is to sequence these 235 samples in order to test the new V2 Colorectal bait design.

  Dataset EGAD00001003242

• Genome-Wide Association Study of Patients with Coccidioidomycosis

  BackgroundValley Fever is typically an infection of the lungs caused by the fungi Coccidioides immitis and Coccidioides posadasii. The incidence of Coccidioidomycosis (CM), or infection with Coccidioides, has dramatically increased over the last 20 years. This is particularly true in the Southwest of the United States, where people often breathe fungal spores that arise from the soil. Reasons for increased infection rates are thought to include population growth and construction in these endemic regions, an increase in the number of people whose immune systems are compromised due to infection or treatment with drugs required for organ transplants, climate change, as well as improved testing practices and greater physician awareness. Mild CM most commonly presents itself with flu-like symptoms and rashes, which can last weeks to months. Individuals with compromised immune systems, specifically-- substantial suppression of the immune cells known as T cells, can develop severe pulmonary and disseminated disease. Infection that remains localized to the lungs is referred to as pulmonary disease, but when the infection spreads out of the lungs into other parts of the body it represents a more serious condition referred to as a disseminated disease, or disseminated CM. In nature, Coccidioides spp. exists as mold and lives in dust and soil. When the contaminated soil or dust is disturbed by human activity, animals, or weather, the Coccidiodies spores are released into the air. Airborne spores are taken up by breathing and settle in the lungs. Once in the moist and warm environment of the lung, spores transform into spherules, which divide and become filled with smaller spores, called endospores. When the spherules get large enough, they rupture and release these endospores, which can spread and disseminate to surrounding tissue. The cycle then repeats itself as these endospores develop into new spherules3. Different ethnic groups have been described to vary in their susceptibility to developing disseminated CM after initial infection with Coccidioides. For example, evidence suggests that African-American and Filipino patients suffer the disseminated disease at a greater rate than other ethnicities. The suggestion that race plays a role in the clinical expression of the disease is still a source of debate amongst the scientific community and any genetic mechanisms responsible for these differences have yet to be fully elucidated. If our genetic makeup influences our ability to limit the spread of infection, finding which DNA differences cause these variances could provide clues to how the body successfully fights infection, and provide opportunities to boost the body’s ability to do this. Further, if we are able to identify the specific genetic risk factors that correlate with the development of disseminated infection, physicians could perform genetic screenings to identify high-risk patients and provide them with preemptive antifungal therapy prior to developing disseminated disease.The genome, made up of DNA, contains all of the information needed for humans to develop and grow. Genome-wide association studies (GWAS) allow us to look for inherited differences that are more common between people who share a particular trait, for example, height or susceptibility to certain diseases, compared to those who do not share the trait. Although some traits and diseases are controlled by a single gene, the majority are influenced by contribution from several, or even many, different genes. To find evidence of genes that contribute to specific traits, GWAS typically compares genome information from large numbers of people who have a particular disease (referred to as “cases”) looking for DNA sequences that are common among these samples, and are different from DNA sequences seen in large numbers of people who lack the trait, but are as much like the cases as possible (referred to as “controls”). The DNA sequence data from each group, cases versus controls, are analyzed to see if there are specific genomic differences that tend to be associated with the disease. MethodsTwo separate GWAS approaches were taken to look for genetic differences that could be responsible for the observed differences between the different patient populations we are studying. The first method, known as genotyping, scans for differences at a set of positions across the genome, which includes both the genes that encode our proteins and the larger amount of DNA that does not. The second method, known as exome sequencing, allows us to compare the entire sequence of the portion of the genome that codes for proteins.  For this study, DNA from patients with either pulmonary or disseminated CM were genotyped and exome sequenced to look for DNA differences that are associated with one condition or the other. All patients were at least 18 years old, had no evidence of immunosuppression, and had proven or probable pulmonary coccidioidomycosis according to established diagnostic criteria. Of these patients, a subset demonstrated disseminated disease, i.e., they showed evidence of coccidioidal infection outside of the thorax by biopsy/aspiration, had radiographic imaging, and show positive coccidioidal serology. Our criteria for including patients with the pulmonary disease were that they must not require ongoing antifungal treatment or show evidence of active CM (in skin test positive patients), show no evidence of extrapulmonary dissemination, and have no evidence of ongoing pulmonary infection (pulmonary nodules are accepted) beyond six months from diagnosis.Patient DNA was purified from blood or from sputum samples by the labs of our collaborators, Drs. George Thompson (UC Davis School of Medicine) and John Galgiani (University of Arizona Health Sciences). Genome-wide association (GWAS) analysis was carried out to look for candidate loci associated with pulmonary versus disseminated disease, taking into account the population structure of the samples. Single nucleotide or insertion/deletion variants were identified from whole-exome sequences (WES) using the Picard/BWA/GATK pipeline. ResultsTable 1. Pulmonary versus Disseminated Cases of Coccidiomycosis for GWAS, Sorted by EthnicityEthnicityPulmonary CasesDisseminated CasesAsian85Black/African American1664Caucasian/White4015Filipino03Hispanic/Latino3414Indian21Mexican American1039Pacific Islander01Samoan03Vietnamese10Unknown16917More than one race02Total373134Table 1 shows the number of samples analyzed from patients with pulmonary versus disseminated disease, and patient ethnicity, where known. In all, we worked with 507 samples, including 134 samples from patients with disseminated disease and 373 samples from patients with pulmonary disease. Of these, 505 samples were genotyped using the Multi-Ethnic Global Array from Illumina Inc. In addition, we were able to generate whole-exome sequence from 498 patient samples. No significant associations were detected that differed between samples from patients with pulmonary versus disseminated disease; that is, no particular DNA sequences were found to be significantly enriched in patients with disseminated disease compared to patients with pulmonary disease. The ability to detect genetic association between specific sequences and genetically determined traits is influenced by several factors, including how many patient samples are available to compare, how many different genes contribute to the trait and how strong their contributions are. When the number of genes is small and the contribution of each gene is great, smaller numbers of patient samples are needed to detect an association. When more genes are involved, or the contribution from each gene is more modest, larger numbers of patient samples must be examined. While we were not able to detect any associated within this study, it does not mean that subsequent studies would not find this connection. Our study suggests significantly more samples should be analyzed in further studies.Whole-exome sequences were generated from 498 samples and were aligned to reference sequences to identify positions where the sequences differed from the reference. These data are being analyzed to determine if any variants are associated with pulmonary, versus disseminated, disease. 

  Study phs002170

• Cross-Sectional Characterization of Idiopathic Bronchiectasis

  This GDMCC protocol will study adult patients with non-CF, idiopathic bronchiectasis, whose genetic etiologies are not known. Idiopathic bronchiectasis is reportedly more common in females with certain tall, thin body types and associated with environmental organisms, such as nontuberculous mycobacterium (NTM). The other susceptibility factors predisposing to bronchiectasis or acquisition of NTM are unclear. The study will attempt to broaden the understanding of this disease by comparing gender-associated factors and NTM status. A relatively equal number of both females/males and NTM/non-NTM infected subjects will be enrolled. Approximately 300 people may be screened to find 260 eligible subjects, since a small number (e.g., 40 patients) may be diagnosed with PCD, vCF, or other known etiology as an explanation for the bronchiectasis. This single-visit protocol will use a systematic approach to characterize the physical features, radiographic patterns, and associated lower airway microbial flora. There is no natural history of disease course follow-up component to this protocol. Participants will have one outpatient clinic visit for evaluation with a physical examination including detailed body size measurements, medical history, collection of blood samples for routine lab tests and genetic analyses, and a chest X-ray if no recent one is available. Participants will also have tests of lung function, and measurement of a gas called nitric oxide in the nose. Participants whose initial tests show abnormal results may also be asked to have a nasal scrape to collect cell samples and/or a skin sweat test to measure salt concentrations. Participants will also have a sputum specimen collected during the visit and will be asked to collect two additional early morning sputum samples and a mouth rinse at home within 2 weeks of the clinic visit, and mail the sample collection materials to the research team. Careful evaluation and characterization of the physical and clinical characteristics will guide the genetic characterization of idiopathic bronchiectasis, and likely lead to an improved diagnostic approach. Identification of disease causing genes may provide new therapeutic targets.

  Study phs001279

• Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Strong Heart Study (SHS) and Strong Heart Family Study (SHFS)

  The SHS is a study of cardiovascular disease and its risk factors among American Indian men and women. Using standardized methodology, it was designed to estimate cardiovascular disease mortality and morbidity and the prevalence of known and suspected cardiovascular disease risk factors and to assess the significance of these risk factors in a longitudinal analysis. The study included 13 American Indian tribes and communities in three geographic areas: an area near Phoenix, Arizona, the southwestern area of Oklahoma, and western and central North and South Dakota. The SHS included three components: The first was a survey to determine cardiovascular disease mortality rates from 1984 to 1994 among tribal members aged 35-74 years of age residing in the 3 study areas (the community mortality study). The second was the clinical examination of 4,500 tribal members aged 45-74. The SHS has completed three clinical examinations of the original Cohort (Phase I: 1989-1991; Phase II: 1993-1995; Phase III: 1998- 1999, respectively). The third component is the morbidity and mortality (M&M) surveillance of these 4,500 participants. Yearly SHS surveillance has only 0.2% loss to follow-up. All deaths and all nonfatal CVD events are classified by standardized criteria, including details of stroke and HF. The Strong Heart Family Study (SHFS) is a genetic epidemiological study designed to investigate the heritability of CVD and its risk factors and to localize genes that contribute to CVD risk in American Indians. SHFS participants include 3,838 family members that were >/=15 years old, and ascertained through sibships of the original SHS, from 94 extended (large, multigenerational) families. Exams have occurred in a pilot Phase III (1998-1999, 900 SHFS participants), in Phase IV (2001-2003), and Phase V (2006-2009). SHFS morbidity and mortality surveillance has occurred throughout the study phases, with 0.3% lost to follow-up. Genetic data includes complete pedigree information, DNA samples from all family members, a 10cM-spaced microsatellite map used for IBD estimation and to perform linkage analysis, genotypes for more than 12,000 SNPs in candidate regions, and genotypes from commercially available SNP assays.

  Study phs000580