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• Whole-exome sequencing of additional thyroid disease cases (2017-05-11)

  Whole-exome sequencing of a cohort of families (probands and affected/unaffected relatives) suffering from one of two rare thyroid disorders: congenital hypothyroidism (CH) and resistance to thyroid hormone (RTH). This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003331

• Breast Cancer Sequential Sampling Targeted Capture

  This study aims to target capture sequence regions of interest from DNA derived from breast cancer patients who received neo-adjuvant chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved.

  Dataset EGAD00001000784

• Microinjection of hIPSC-derived intestinal organoids with Salmonella Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are 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 EGAD00001001363

• BCG-Flu Challenge Study Human RNA-seq

  Whole blood RNA sequencing data generated from human samples collected as part of the BCG-Flu Challenge study. The dataset includes 746 samples. Paired-end sequencing was performed on an Illumina NovaSeq 6000 platform with a 150 bp paired-end configuration. Raw FASTQ files are provided.

  Dataset EGAD50000002407

• 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

• SardiNIA Medical Sequencing Discovery Project

  The SardiNIA Medical Sequencing Discovery Project studies the genetics of blood lipid levels and personality in a Sardinian population cohort. The project has generated draft genome sequences for approximately 2,000 individuals using whole genome shotgun sequencing. The draft sequences will allow investigators to evaluate the contribution of common and rare single nucleotide polymorphisms, short insertions and deletions, large copy number polymorphisms and other structural variants to blood levels of low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c) and triglycerides (TG), all of which are key risk factors for cardiovascular disease, and to the 5 domains of personality as assessed by the NEO-PI-R questionnaire. The two traits represent different ends of the spectrum of medically interesting complex traits. Blood lipid levels are a risk factor for cardiovascular disease for which genetic studies have been very successful. In contrast, personality traits and other behavioral phenotypes represent a set of phenotypes that have proven more challenging to dissect using standard genetic tools. In both cases, we expect whole genome sequencing to improve our understanding of the underlying biology. The isolated Sardinian population is ideal for this type of study for several reasons, in particular because: (i) the bottleneck that occurred after colonization of the island attenuated natural selection against alleles with phenotypic consequences, increasing the odds that functional alleles will reach modest frequencies (0.5 - 5.0%) and will be detected in the present study and (ii) sharing of long haplotype stretches surrounding rare variants will facilitate imputation based analyses of shotgun sequence data, which improve the accuracy of individual genotype calls and thus increase power. This research helps advance NIH's mission by furthering our understanding of the genetic factors contributing to blood lipid levels and coronary heart disease and to personality, behavior and mental health. In addition, these data should facilitate development of analysis tools and strategies that can be used to study the genomes of hundreds to thousands of individuals and further our understanding of the genetics and biology of many different traits and conditions.

  Study phs000313

• Molecular defects in pseudohypoparathyroidism or related disorders

  Maintaining calcium levels within a narrow normal range is of critical importance for numerous different cellular functions. One of the most important regulators of blood calcium levels is parathyroid hormone (PTH), which mediates its actions through the PTH/PTHrP receptor, a Gαs-coupled receptor. Few inherited disorders are characterized by diminished blood calcium levels and elevated blood phosphate levels; some of these disorders are caused by too little PTH synthesis and/or secretion (hypoparathyroidism, HP), while others are caused by resistance towards PTH (pseudohypoparathyroidism, PHP). Only few of the inherited forms of HP (<10%) have been defined at the molecular level. In contrast, genetic mutations have been identified for several inherited forms of PHP. For example, PHP type Ia (PHP-Ia) is caused by maternally inherited mutations in those GNAS exons that encode Gαs, while autosomal dominant PHP type Ib (AD-PHP-Ib) is caused by maternal inherited deletions within or up-stream of GNAS, which are associated with abnormal GNAS methylation. However, a large number of patients with PTH-resistance and thus hypocalcemia show GNAS methylation changes, but their underlying genetic defects have not yet been defined at the DNA level. These "sporadic" patients may be affected by an autosomal recessive form of PHP-Ib (AR-PHP-Ib), which is most likely not linked to the GNAS locus. In our studies, we propose to search through exome sequence analyses for novel genetic mutations responsible for novel autosomal dominant forms of HP that are not caused by mutations in the known disease-causing genes; some of these families are large enough to perform genetic linkage studies. We furthermore propose to search for the genetic mutation(s) responsible for the autosomal recessive variant of PHP-Ib through the analysis of whole exome sequences; for these studies we focus particularly on patients, whose parents are likely to be consanguineous. The proposed efforts are expected to lead to the identification of novel genes that are involved in parathyroid development and function (HP) and genes that are involved in the establishment or maintenance of GNAS methylation (AR-PHP-Ib).

  Study phs000476

• Effect of Breast Feeding on Immunologic Priming in Young Infants

  The mechanisms generating immunoglobulin heavy chain (IgH) biodiversity result in over potentially unique immunoglobulin sequences within an individual. However, over the course of B cell development, B cell receptor (BCR) selection constrains the repertoire significantly. In newborn infants compared to adults, developmental regulation of terminal deoxynucleotidyl transferase (TdT) activity in the bone marrow, selective use of V, D and J gene segments in the IgH locus during fetal life, and immaturity of somatic hypermutation (SHM) and class switch recombination (CSR) mechanisms are likely to contribute to a less diverse IgH repertoire, although the extent of repertoire biodiversity in newborns has not been extensively examined. Furthermore, the fetal IgH repertoire is tightly controlled and for the most part independent of environmental antigenic influences. As a result, the neonatal repertoire, in contrast to older children and adults, is less impacted by the selective pressures of the microbiome, pathogen exposure, and environmental antigens. Evidence for developmental differences in TdT activity is seen in shorter CDR3 lengths and decreased junctional diversity in BCR in both term and preterm newborns. Next Generation Sequencing (NGS) is a sensitive approach to evaluate the neonatal IgH repertoire and assess the relative contribution of each aspect of IgH rearrangement and affinity maturation to overall IgH biodiversity prior to and following isotype class switch. NGS and bioinformatics accurately assess biodiversity by determining the number of unique sequences within the IgH repertoire. Combined with novel analytic tools, NGS provides an approach to compare the extent of somatic hypermutation (SHM), N insertions, V/D/J gene segment usage, and CDR3 length between newborns and adults. Taken together, these measures can be used to assess the earliest events in B cell development using the newborn Ig transcriptome to evaluate the IgM, IgG, and IgA IgH repertoires. The goal of this study was to define the extent of IgH biodiversity in newborns and examine the factors that contribute to the generation of biodiversity during early life. Establishment of the bioinformatics pipeline can be applied to examine the immune deficiency, response to vaccine and infection at molecular population level.

  Study phs002073

• NIDDK IBD Genetics Consortium Crohn's Disease Genome-Wide Association Study

  This dataset contains data from a genome-wide association study performed with 968 Inflammatory Bowel Disease (IBD) affected cases and 995 unrelated controls using the Illumina HumanHap300 Genotyping BeadChip. Cases were selected to have Crohn's disease with ileal involvement, and controls were matched to cases based on sex and year of birth. Subjects were drawn from two cohorts: (1) persons with non-Jewish, European ancestry (561 cases and 563 controls), and (2) persons with Jewish ancestry (407 cases and 432 controls). Genotyping was performed at the Feinstein Institute for Medical Research. Seven-hundred fifty-four of the samples (468 cases and 286 controls) were taken from the NIDDK IBD Genetics Consortium cell line repository. These samples are identified in the IBD_Sample file. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are available, together with the Consortium's phenotyping manual and the forms used to collect the data. The remaining 1,209 samples were obtained from pre-existing collections ascertained through Cedars-Sinai Medical Center, Johns Hopkins University, University of Chicago, University of Montreal, University of Pittsburgh, University of Toronto, and the New York Health project (controls only). For these samples, only sex, cohort (Jewish vs. non-Jewish), and age at diagnosis (cases only) are available. Two-hundred three individuals from among the pre-existing samples did not provide consent to release their genotype data (designated as consent group 2 in the file IBD_Subject). Thus, individual genotype data are only provided for 1,760 samples. To compensate for this, we have provided summary results for each SNP. These are based on a stratified analysis testing case/control association. Fifty-one samples had a call rate less than 93% and were therefore excluded from this analysis, leaving an overall sample size of 1,963 - 51 = 1,912. X Chromosome Heterozygosity Nine samples have X chromosome heterozygosity that is neither consistent nor inconsistent with their phenotypic sex. One of these samples was found to have Turner Syndrome. The remaining 8 samples have heterozygosity ranging from 35-76%.

  Study phs000130

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178