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• Sequencing data for oesophageal and related samples - Mourikis et al (RNA)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. RNAseq (BAM files) 137 samples

  Dataset EGAD00001004776

• Sequencing data for oesophageal and related samples - Ng, Contino et al (RNA)

  Data supporting: "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. RNAseq (BAM files) 214 oesophageal adenocarcinoma samples

  Dataset EGAD00001007809

• Sequencing data for oesophageal and related samples - Alex Frankell et al (RNA)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. RNAseq (BAM files) 116 tumours

  Dataset EGAD00001004423

• Exome trios in patients with gastroschisis (2019-04-08)

  Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. 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 2019-04-08.

  Dataset EGAD00001004942

• Whole genome and transcriptome sequencing of lung cancer patients and cell lines at Genentech

  Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

  Study phs000299

• Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary with Neuroendocrine Differentiation

  PURPOSE: Cancer of unknown primary (CUP) is a group of metastatic tumors in which the standard diagnostic work-up fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large since their tumors might have actionable driver mutations that can provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomics analyses could inform on the origin of the tumor. PATIENT AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a PDX mouse model and bioinformatics was used to identify an actionable mutation, predict resistance development to the targeted therapy, and to correctly diagnose the origin of the tumor. The Cancer Genome Atlas was used to benchmark the bioinformatics workflow. RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatics workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from The Cancer Genome Atlas. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomics analyses could inform on the origin of tumors in patients suffering from CUP.

  Study EGAS00001003026

• Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

  We profiled the transcriptomes of individual cells obtained from bone marrow aspirates of 7 treatment-naïve newly diagnosed JAK2-mutant myeloproliferative neoplasm (MPN) patients (3 polycythemia vera and 4 essential thrombocythemia patients), and 2 healthy controls. The submitted data corresponds to sequencing reads mapped to the human reference genome GhRC38 build using CellRanger for a total of 9 samples (one per patient). In addition, to reconstruct the lineage histories of single cells in MPN patients, we performed whole-genome sequencing of single-cell-derived colonies of hematopoietic stem and progenitor cells from 2 essential thrombocythemia (ET) patients: 22 JAK2-mutant colonies and 20 WT colonies for patient ET 1; and 13 JAK2-mutant colonies and 21 WT colonies for patient ET 2. The submitted data consists of sequencing reads aligned to the human reference genome GhRC38 build using bwa-mem. Each file corresponds to the whole-genome sequencing data for one colony.

  Study phs002308

• Sci Trans Med - Mouliere et al. 2019

  Dac EGAC00001001570

• NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

  This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

  Study phs000988

• Virginia PrIMeD Study

  The goal of this study was to determine whether screening children (2-16 yrs) in pediatric waiting rooms for genetic risk of type 1 diabetes (T1D) could be applied to diverse (by geography, genetic ancestry) communities, and for those at "high genetic risk," if barriers prevent subsequent screening for presence of islet autoantibodies. A total of 3,818 children were recruited from eight general pediatric and specialty clinics across Virginia. Clinical Research Coordinators were stationed at each clinic and obtained informed consent/assent, a brief medical history, and a saliva sample for DNA extraction and determination of their genetic risk using a T1D Genetic Risk Score (T1D GRS). Children were present in the clinic for a "healthy" visit, although children with and without a history of T1D were recruited into the study. Age, sex, self-reported ancestry/race, T1D history, and other medical history information was obtained. DNA was extracted from the saliva samples and genotyping with a T1D-focused array using 74 SNPs (including 26 SNPs in the HLA region) provided data to generate a T1D GRS for each individual. Of the 3,818 children recruited, there was a slight excess of males (1,959, 51.3%), a majority of white and Hispanic/Latino ancestry (82.8%), and 91 (2.4%) with prevalent T1D. A total of 542 (14.2%) had "high T1D genetic risk" (T1D GRS > 5). Although the T1D GRS included non-HLA genetic variants, 80% of those with "high genetic risk" would have been classified using only those SNPs in the HLA region alone. Of children with "high genetic risk" and without pre-existing T1D (n=494), 7.0% (34/494) consented for islet autoantibody screening. Among children with pre-existing T1D (n=91), 52% (n=48) also had a "high genetic risk." The HLA-focused T1D GRS was not significantly associated with age at onset of T1D. Of those at high genetic risk that consented for autoantibody testing (n=34) and completed the blood collection (n=28), two (2/28, 7.1%) tested positive for multiple autoantibodies and were at significant risk of developing T1D. Follow up of 55% of parents/guardians identified 2 (of 2,096, 0.095%) participants who developed T1D, one at "high genetic risk" and one with a first-degree relative with T1D. A major factor in obtaining islet autoantibody testing was concern over SARS-Cov-2 exposure and an independent non-scheduled blood collection.Individual-level data at each SNP (genotyped and imputed) for T1D genetic risk and affiliated data are provided in dbGaP.

  Study phs003609