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• A GWAS for cutaneous leishmaniasis in Brazil

  Our goal was to identify genetic risk factors for cutaneous leishmaniasis (CL) caused by Leishmania braziliensis. Genotyping 2066 CL cases and 2046 controls using Illumina HumanCoreExomeBeadChips provided data for 4,498,586 imputed single nucleotide variants (SNVs). Genome-wide association testing using linear mixed models took account of genetic diversity/ethnicity/admixture. Post-GWAS positional, expression quantitative trait locus (eQTL), and chromatin interaction mapping was performed in FUMA. Transcriptional data were compared between lesions and normal skin, and cytokines measured using flow cytometry and Bioplex assay.

  Study EGAS00001004596

• Molecular analysis of circulating tumour cells identifies distinct profiles in chemosensitive and chemorefractory patients with small cell lung cancer

  In a search for profiles that distinguish chemosensitive versus chemorefractory SCLC disease, we examined copy number aberrations (CNA) in circulating tumour cells (CTCs) from pre-treatment SCLC blood samples. A CNA classifier was generated from 88 CTCs isolated from 13 patients (training set) then verified in 18 additional patients (112 CTC samples) (testing set) and in six SCLC patient-derived CTC explants explant tumours. These data highlight the potential utility of CTCs for molecular profiling and stratification of SCLC patients in future clinical trials.

  Study EGAS00001001951

• Rapid Whole Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units

  Monogenic diseases are frequent causes of neonatal morbidity and mortality, and disease presentations are often undifferentiated at birth. More than 3,500 monogenic diseases have been characterized, but clinical testing is available for only some of them and many feature clinical and genetic heterogeneity. As such, an immense unmet need exists for improved molecular diagnosis in infants. Because disease progression is extremely rapid, albeit heterogeneous, in newborns, molecular diagnoses must occur quickly to be relevant for clinical decision-making. We describe 50-hour differential diagnosis of genetic disorders by whole-genome sequencing (WGS) that features automated bioinformatic analysis and is intended to be a prototype for use in neonatal intensive care units. Retrospective 50-hour WGS identified known molecular diagnoses in two children. Prospective WGS disclosed potential molecular diagnosis of a severe GJB2-related skin disease in one neonate; BRAT1-related lethal neonatal rigidity and multifocal seizure syndrome in another infant, identified BCL9L as a novel, recessive visceral heterotaxy gene (HTX6) in a pedigree, and ruled out known candidate genes in one infants. Sequencing of parents or affected siblings expedited the identification of disease gene in prospective cases. Thus, rapid WGS can potentially broaden and foreshorten differential diagnosis, resulting in fewer empirical treatments and faster progression to genetic and prognostic counseling. Reprinted from Saunders et. al, Rapid Whole-Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units. Sci. Transl. Med. 4, 154ra135 (2012; PMID: 23035047) with permission from AAAS.

  Study phs000564

• ATAC-SEQ MAIN - PHASE 1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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/

  Dataset EGAD00001001320

• Genetic Study of Vascular Anomalies

  Vascular anomalies are malformations or tumors of the vasculature that can result in significant morbidity and mortality. Vascular anomalies are caused by germline or post-zygotic pathogenic variants in genes that regulate cell growth and vascular development. Complex or extensive vascular anomalies are often intractable despite interventions such as sclerotherapy, embolization, or surgery. In recent years, targeted therapy has played an increasingly crucial role in the management of these diseases. Identification of the molecular causes of vascular anomalies is essential to provide efficacious therapy; however, genetic profiling is often limited by difficulty obtaining affected tissues and limited sequencing depth. The lack of this information limits treatment options and the precision of targeted therapy, especially for primary complex lymphatic anomalies. To address these limitations, we have applied novel techniques, including analysis of unconventional samples such as endothelial cells isolated from lymphatic fluid and cell-free DNA, deep coverage exome sequencing, and unique molecular identifier ultra-deep targeted sequencing, in the molecular profiling of these diseases.

  Study phs003197

• Microvascular Permeability, Inflammation, and Lesion Physiology in Endometriosis: A Microphysiological Systems Approach

  The goal of the study is to identify novel molecular pathways involved in the etiology of endometriosis and to develop in vitro model systems to enable the study of the mechanisms regulating reproductive function. Using a physiomimetic modeling approach, primary tissue samples of the human endometrium derived from patients diagnosed with and without endometriosis and/or endometriotic diseases (e.g. adenomyosis) were used for secondary analysis using multi-omic systems biology analysis and to build tissue engineered models. We performed single cell RNA sequencing (scRNA-Seq, N=6)) to study the cellular and transcriptomic composition of the endometrial tissue microenvironment and proteomics (LC-MS/MS) to study protein-level signaling pathways and the matrisome of the native endometrium. Systems biology analysis of these datasets helped identified a putative dysregulated inflammatory signaling pathway in endometriosis patients compared to controls. Moreover, subsets from these scRNA-Seq and proteomic datasets were used to aid the design of a synthetic extracellular matrix hydrogel as an in vitro platform for the culture of endometrial cells. Tissue-engineered synthetic PEG hydrogel enables the simultaneous co-culture of endometrial epithelial organoids and stromal fibroblasts in a fully defined, 3D, and tunable environment. We demonstrated that the in vitro co-culture model recapitulates key phenotypic processes observed across the human menstrual cycle in response to sex hormone stimulation through both biochemical and transcriptomic (bulk RNA-sequencing) analysis. This model will enable future mechanistic studies that examine origins of endometriotic disease phenotypes. The transcriptomic data generated for this study including the scRNA-Seq data from primary human endometrial tissues and the bulk RNA-Seq datasets from the experimental co-culture models is available through dbGAP.

  Study phs003326

• The Genomic Analysis of Medulloblastoma

  Medulloblastoma is a heterogenous disease made up of at least four distinct subtypes of disease which appear to exploit and disrupt naturally occurring developmental pathways of cellular growth and hindbrain development. To better understand the driver mutations of this disease, we performed whole genome sequencing of 37 medulloblastomas and the corresponding normal DNA of the 37 affected children treated at St. Jude Children's Research Hospital. We have found several novel mutations which appear subtype specific. These mutations were checked for frequency in a separate tumor cohort of 56 children with medulloblastoma, also treated on the St. Jude Medulloblastoma 2003 trial, and were tested in several animal models of medulloblastoma for proof of oncogenic potential.

  Study phs000409

• RNA_expression_profiling_of_melanoma_patient_derived_xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growthThis 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/

  Study EGAS00001001537

• ATAC-Seq of inflamed and non-inflamed biopsies

  Inflamed and non-inflamed biopsies were digested for 45 minutes at 37ºC with collagenase from Clostridium histolyticum (Sigma). Suspension cells were then stained with an antibody cocktail to sort live CD8-CD4+ T cells. After isolating crude nuclei of two thousand live CD4+ T cells, they were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007344

• single cell sequencing of resting and Influenza-stimulated mononcluear phagocytes of African and Europeans with varying degree of ex-vivo susceptibility to Influenza

  There is considerable inter-individual immunological and clinical variability upon influenza A virus (IAV) infection in humans; yet, the factors underlying such heterogeneity remain elusive. Here, using an ex vivo cellular model that captures natural variation in the transcriptional responses of monocytes to IAV, we find significant differences in viral mRNA levels between individuals of African and European ancestry. Using single cell analyses, we show that the overall number of cells that will ultimately become infected, rather than the amount of viral transcript expression per cell, is the main driver of the surprisingly higher IAV mRNA levels detected in European cells. Finally, we identify 135 genes, including the interferon-stimulated genes IFITM3, MX1, and OAS3, for which basal mRNA expression levels associate with IAV mRNA levels post infection. Our findings reveal that basal differences in activation of IRF/STAT-induced antiviral mechanisms may contribute to individual and population disparities in susceptibility to IAV infection.

  Study EGAS00001005000

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Dataset EGAD00001007872

• A somatic reference standard for cancer genome sequencing.

  Paired PCR-free whole genome sequencing data of a matched metastatic melanoma cell line (COLO829) and normal across three lineages and across separate institutions, with independent library preparations, sequencing, and analysis. The data was generated with mean mapped coverages of 99X for COLO829 and 103X for the paired normal across three institutions. Overall, common events include >35,000 point mutations, 446 small insertion/deletions, and >6,000 genes affected by copy number changes. We present this reference to the community as an initial standard for enabling quantitative evaluation of somatic mutation pipelines across institutions.

  Dataset EGAD00001002142

• Genotyping of GM samples

  This dataset contains a vcf file for 99 GM individuals genotyped on the Illumina HumanOmni2.5 array . The vcf file is originated after imputation (IMPUTE2) and filtering for minor allele frequency MAF≥0.05, imputation confidence score INFO of >0.4 and Hardy-Weinberg Equilibrium (HWE) p>1e-06, yielding ~6.3 million variants.

  Dataset EGAD00001010255

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Moroccan Genome Project: Sequencing Data from 109 Whole Genomes of Moroccan Individuals

  This study is the first phase of the Moroccan Genome Project, which included the complete sequencing of 109 genomes from the Kingdom of Morocco. The sequencing was performing using the Illumina NovaSeq6000 platform, with a mean coverage of 30X.

  Dataset EGAD50000000750

• Investigation of Brain Nitrogen Metabolism in Partial Ornithine Transcarbamylase Deficiency (OTCD) Using 1H MRS, DTI, and fMRI

  This is a case controlled, observational study. This project studies cognitive and motor dysfunction in adult and pediatric patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation (outside of the newborn period) 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 ranged from ages 7-60 years and were 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 phs001296

• Dataset for transcriptomic sequencing of Merkel cell carcinoma(MCC) samples

  This dataset contains transcriptome sequencing for 5 samples of MCC tumors . The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

  Dataset EGAD00001015702

• cfDNAme allows early prediction of PE

  Preeclampsia (PE) is a leading cause for peripartal morbidity, especially if developing early in gestation. To enable prophylaxis to prevent PE, it is essential that pregnancies at risk of PE are identified early, in the first trimester. To identify patients at risk, we profiled methylomes of plasma-derived cell-free DNA (cfDNA) from pregnant women. We detected DNA methylation differences between control and PE pregnancies that enable risk stratification of patients, at PE diagnosis but also presymptomatically, around 12 weeks of gestation.

  Study EGAS00001007071

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Validation data for the SV analysis package: GRIDSS, PURPLE, LINX

  Validation data containing sequencing data of 13 samples. An hybrid capture approach was used to validate findings of both Manta and GRIDSS for the samples in the validation set. The dataset also contains the reference sequences used.

  Dataset EGAD00001005525

• Exome_sequencing_of_a_cohort_of_Rett_syndromelike_patients

  The aim of the project is the definition of the molecular defect in a cohort of Rett-like patients negative for mutations in known disease genes. To this aim, a number of unrelated trios (patients plus parents) will be analysed by exome sequencing. 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/

  Study EGAS00001002059

• Research for drug discovery and elucidation of pathophysiology using disease-specific iPS cells

  We investigated roles of KRAS on stemness maintenance and differentiation propensity in the context of induced pluripotent stem cells (iPSCs) using isogenic KRAS mutant (G13C/WT) and wild-type (WT/WT) iPSCs from the same RAS-associated autoimmune lymphoproliferative syndrome-like disease (RALD) patients. Exome-seq analysis was conducted to compare gene profiles of WT/WT and G13C/WT iPS cells. We have not found any differences of gene mutation in the two genotypes.

  Study JGAS000136

• Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

  Study EGAS00001007877

• Transcriptome analysis of Williams syndrome

  Williams syndrome (WS) is a neurodevelopmental disorder caused by microdeletion on chromosome 7q11.23, and has attracted much attention for its distinctive features, such as hypersociability. However, it remains unclear which genes are involved in the complex phenotypes of their condition. Here, we performed transcriptome analysis of peripheral blood to identify genes associated with WS.

  Study JGAS000132

• ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity

  Chronic inflammation in autoimmunity is driven by hyperactive T cells with dysregulated metabolism. ABHD11 is a mitochondrial hydrolase that supports alpha-ketoglutarate dehydrogenase function and has been associated with remission in rheumatoid arthritis. To explore its role in T cell function, we used CRISPR/Cas9 to knock down ABHD11 in Jurkat T cells and performed RNA-Seq analysis. Differential gene expression revealed widespread transcriptional changes, with sterol-related pathways among the most significantly enriched. These findings highlight ABHD11 as a potential regulator of metabolic programming in T cells with implications for autoimmunity.

  Study EGAS50000001297